A Vision of Future Observations for Western U.S. Extreme Precipitation Events and Flooding: Monitoring, Prediction and Climate

M. Ralph1, M. Dettinger2, A. White1, D. Reynolds3, D. Cayan2, T. Schneider4, R. Cifelli5, K. Redmond6, M.

Anderson7, F. Gherke7, K. Mahoney8, L. Johnson1, S. Gutman9, V. Chandrasekar10, A. Rost11, J. Lundquist12, N. Molotch13, L. Brekke14, R. Pulwarty15, J. Horel16, L. Schick17, A. Edman18, P. Mote19, J. Abatzoglou20, R. Pierce21,

G. Wick1, S. Matrosov8

1NOAA/Earth System Research Laboratory/Physical Sciences Division, Boulder, Colorado

2U.S. Geological Survey, Scripps Institution of Oceanography, La Jolla, California

3NOAA/National Weather Service/Monterey Weather Forecast Office, Monterey, CA

4NOAA/NWS/Office of Hydrologic Development, Boulder, Colorado

5Cooperative Institute for Research in the Atmosphere, Fort Collins, Colorado

6NOAA/Western Region Climate Center, Reno Nevada

7California Department of Water Resources, Sacramento, California

8Cooperative Institute for Research in Environmental Sciences, Boulder, Colorado

9NOAA/Earth System Research Laboratory/Global Systems Division, Boulder, Colorado

10Colorado State University, Department of Electrical and Computer Engineering, Fort Collins, Colorado

11NOAA/NWS/�National Operational Hydrologic Remote Sensing Center, Chanhassen, Minnesota

12University of Washington/Dept. of Civil and Environmental Engineering, Seattle, Washington

13University of Colorado at Boulder, Geography Department, Boulder, Colorado

14U.S. Bureau of Reclamation, Technical Services Center, Denver, Colorado

15NOAA/OAR/Climate Program Office, Physical Sciences Division, Boulder, Colorado

16University of Utah, Department of Meteorology, Salt Lake City, Utah

17.S. Army Corps of Engineers, Seattle, Washington

18NOAA/NWS Western Region Headquarters, Salt Lake City, Utah

19Oregon State University, Oregon Climate Change Research Institute, Corvallis, Oregon

20University of Idaho, Department of Geography, Moscow, Idaho

21NOAA/NWS/San Diego Weather Forecast Office, San Diego, California

Contact: F. Martin (Marty) Ralph at marty.ralph@noaa.gov, 303-497-7099 (office)

Provided to the Western States Water Council on October 5th, 2011 in Idaho Falls, Idaho

2��

Capsule Summary

This document provides a vision of 21st Century observations for tracking, predicting and ultimately managing the occurrence and impacts of major storms in the west. The vision recommends innovations and enhancements to existing monitoring networks for rain, snow, snowmelt, flood and their hydrometeorological precursor conditions over land and ocean. These include new radars to monitor winds aloft and precipitation, streamgages, Snotel enhancements, and more, as well as entirely new and only recently-possible observational tools. The document presents the scientific and management motivations and contexts for this vision, describes its key components and an implementation strategy, along with expected benefits. This document supports a Resolution of the Western States Water Council and an MOU between NOAA and the Western Governors Association, both addressing extreme events.

Fig. E1. Four broad conceptual elements of the vision for 21st Century monitoring in the Western US. Each of the

frames will appear again later in the document at full scale and will be explained and motivated in detail.

Monitoring Atmospheric Conditions That Fuel Extreme Precipitation & Flood

New Snow and Streamflow Monitoringfor Better Snow Melt Forecasts

Atmospheric River Observatories to Fill Largest Single Monitoring Gap

Offshore Monitoring to Extend Forecast Lead Times for Extreme Precipitation

3��

1. The Challenge

This document was requested for inclusion in a report from the March 2011 workshop on extreme events sponsored by California’s Department of Water Resources, Western States Water Council (WSWC), and the Western Governors’ Association (WGA).

Key elements of this plan were presented at the July 2011 WSWC meeting in Bend Oregon. The following day, July 29, 2011, a Resolution was approved by the WSWC as an official “position” for consideration by the WGA. Key elements of this Resolution are directly related to this Vision document, and provides the following overarching guidance quoted from the Resolution titled

“RESOLUTION of the WESTERN STATES WATER COUNCIL supporting FEDERAL RESEARCH AND DEVELOPMENT OF UPDATED HYDROCLIMATE GUIDANCE FOR

EXTREME METEROLOGICAL EVENTS”

“WHEREAS, advances in weather forecasting research, such as that of NOAA’s Hydrometeorological testbed program on West Coast atmospheric rivers, demonstrate the potential for improving extreme event forecasting at the operational time scale; and”

“WHEREAS, WGA and NOAA signed a memorandum of understanding on June 30, 2011, regarding state adaptation to climate variability and change that focuses on climate extremes, variability and future trends as they relate to disaster risk reduction and improved science for coastal and marine resources management”

“BE IT FURTHER RESOLVED, that the Western States Water Council supports development of an improved observing system for Western extreme precipitation events, to aid in monitoring, prediction, and climate trend analysis associated with extreme weather events; and

BE IT FURTHER RESOLVED, that the Western States Water Council urges the federal government to support and place a priority on research related to extreme events, including research on better understanding of hydroclimate processes, paleoflood analysis, design of monitoring and change detection networks, and probabilistic outlooks for climate extremes.”

A copy of the full Resolution is provided at the end of this document. The purpose of this White Paper is to provide a vision of next generation observations that could aid in monitoring, prediction and climate understanding associated with extreme weather events that affect either water supply or flooding in the semi-arid Western United States. The Vision expressed in this document represents a next step toward implementation of the guidance contained within the WSWC Resolution noted above. At the request of the WSWC, a half-day tutorial will be provided to WSWC members and staff in Idaho Falls, Idaho on 5 October 2011 on the uses of, and needs for, current and future observations in weather and hydrology prediction, as well as for climate monitoring, along with a synopsis of the Observing System Vision described here. The presenters are Dave Reynolds (NWS-Weather), Harold Optiz (NWS-Hydrology), Jessica Lundquist (Univ. of Washington), and Marty Ralph (NOAA-Research).

4��

Key societal imperatives related to extreme precipitation, flooding and water supply:

- Provide the necessary flood protection while ensuring adequate water supply in an environment characterized by extreme events

- Provide enough warning lead time with quantified forecast uncertainty to enable preemptive actions by emergency preparedness officials, including out to 10 days where feasible

- Address risks due to aging flood control infrastructure (e.g., the Howard Hanson Dam crisis is an example as are levees across the west)

- Avoid a “Katrina-of-the-West” scenario in which an extreme event disrupts or overwhelms existing operations or aging infrastructures catastrophically, which studies such as ARkStorm have identified as a significant risk (with projected damages that could exceed $500 Billion)

- Address risks associated with the effects of warming on the water cycle and atmospheric processes, which may include:

o decreasing overall snowpack (i.e., the summer water supply) o shortening the snow season and thus extending the flood season earlier into spring o possible expansion of flood season on west coast to earlier in the fall or later into spring o increasing flood risk with warmer, and possibly more intense, storms

- Mitigate potential impacts of climate change by providing a better information base for developing adaptation strategies such as forecast-based reservoir operations that can enable greater water supply while maintaining maximum flood control using existing structures (Fig. 1)

- Provide low-cost alternatives for consideration in planning major new flood control and water supply infrastructure

- Protect endangered species, such as salmon, aided by potential benefits to water supply - Improve next-generation meteorological and hydrologic models using revolutionary observations - Address increase wild fire activity, which can lead to flash flooding and debris flows

During a 17-year period studied by Pielke et al. (2002), the Western States of WA, OR, CA, ID, NV, UT, AZ, MT, WY, CO, NM, ND, SD, NE, KS, OK, and TX experienced $24.7 Billion in flood damages, an average of $1.5 Billion annually. California, Washington and Oregon combined to account for $10.6 B (46%) of this regional total (see Appendix A).

A key challenge for the next decade is "lead time -- lead time -- lead time". The bar has been raised. It used to be adequate to provide a few hours of lead time. Today, however, community leaders not only have to be prepared from a safety standpoint, but they need to be able to minimize the costs of taking preparedness actions, e.g. by shifting work schedules so that preparatory work can be done on regular time versus overtime. Increasingly community leaders need lead times out to 7, 10- even 14 days.

To address these major challenges will require innovative solutions that, in turn, will require a strong scientific enterprise of monitoring, observations and science. Solutions will depend upon better understanding, tracking and prediction of the causes of extreme events and how they might change in the future. Solutions will also depend on innovative engineering efforts to develop capabilities that can cost-effectively fill gaps in observations, forecasts and related services that to support vibrant economies, healthy ecosystems and reliable water and living resources.

5��

Fig. 1. Schematic illustration of possible outcomes associated with early spring runoff depending upon whether the decision is made to release water to preserve flood control space for use in a potential late season flooding storm or to store water in expectation of summertime water-supply demands.

2. The Context

a) Lessons learned from recent projects

The main drivers for a future observing network are needs related to real-time monitoring, predictions (from minutes to days for flooding, and to seasons for water supply), and climate trend analysis. The network described here draws upon many existing documents describing needs and requirements, including

- NRC reports (Flooding on Complex Terrain; Network of Networks; GPM Satellite system), - Interagency needs assessments, e.g., Workshop on non-stationarity…(2010), USBR Science and

Technology Program (2011), USWRP Workshop on QPF (2005) - Planning for Integrated Water Resources Science and Services (IWRSS) - Planning for a National Water Center, - Experience from NOAA’s Hydrometeorological Testbed (HMT; hmt.noaa.gov), - Understanding of the joint roles of atmospheric rivers in extreme events and water supplies in the

west (Ralph and Dettinger 2011; Dettinger et al. 2011) - The ARkStorm emergency preparedness exercise in California - Ongoing NOAA Regional Integrated Science and Assessment studies - Experience from State Climatologists

6��

- Observing system gap analysis for atmospheric rivers (ARs) by NOAA’s Unmanned Aircraft Systems program, and

- NOAA’s radar network planning.

This paper takes advantage of a series of significant recent advances in observing system technology, research findings, experience gained by testing prototype observing systems in NOAA’s HMT, the National Integrated Drought Information System (NIDIS) and the North American Monsoon Experiment (NAME; Higgins et al. 2006), as well as advances in numerical weather prediction, hydrologic forecasting and real-time communications. Interagency needs assessments have also been produced relating to these issues, including a report focused on extreme precipitation forecasting (Ralph et al. 2005), and more recently a major report on dealing with issues related to quantifying extreme event probabilities (Workshop on Nonstationarity, Hydrologic Frequency Analysis, and Water Management; Olsen et al. 2011, http://www.cwi.colostate.edu/publications/is/109.pdf).

One broad conclusion of observing system research has been that monitoring of the atmospheric column, and not just the surface meteorology, and monitoring the atmosphere over the Pacific (where key weather features take shape before moving ashore) is vital to understanding/predicting precipitation intensity and form (rain/.snow) in the western states.

Another vital requirement is that data from key elements of this network, especially those that provide observations aloft and/or offshore, need to be assimilated into numerical weather prediction models to reap maximum rewards. Existing models either already are able to assimilate key observations, e.g., wind profiler, GPS-met and dropsondes data, or methods to assimilate other data can be developed. Many direct uses of these same data exist, even without this data assimilation but maximum benefits will accrue from the combination of both the direct uses and model assimilation. These several findings are at the root of the vision presented here.

This vision was developed by a team of experts from federal, state, and local agencies, the academic community in hydrometeorology, hydrology, and climate, and representatives of some of the western water-related systems that require information on extreme precipitation, flooding and water supply. Lessons learned from the recent flood control crisis in Washington State, where the flood protection from Howard Hanson Dam above Seattle was seriously compromised by seepage that developed after a record storm, are incorporated (White et al. 2011; Appendix D). Similarly, experience from an emergency preparedness scenario, named ARkStorm (Appendix M), that explored the potential impacts of a devastating series of atmospheric rivers hitting California, also informed this report. The ARkStorm exercise concluded that over $500 billion in economic impacts could occur from a single major storm sequence in California through damages, business disruption, and other dimensions, and that significant loss of life could occur (Porter et al. 2010). Historical flood damages provide much the same perspective.

The vision presented here was developed within, and recognizing, the context of several recent and ongoing efforts to enhance observing capacities and networks related to extreme precipitation events in the West:

7��

Enhanced Flood Response and Emergency Preparedness (EFREP; led by CA Dept. of Water Resources, NOAA and Scripps Institution of Oceanography; Appendix E): Development and deployment of statewide monitoring, modeling and decision-support programs drawing from, and making operational, key findings from HMT-West, for better detection, monitoring and prediction of ARs and their impacts. A key component is a “picket fence” of four coastal atmospheric river observatories, a statewide soil-moisture network, snow-level radars, and land-based monitoring of vertically integrated water vapor (IWV), with associated decision support capabilities. Out of a total of four “tiers” (i.e., levels of complexity, investment and protection), the ongoing implementation covers tiers 1 and 2 for California (93 field sites in all), and will be complete in 2013. A brochure from CA DWR is available online at�http://www.esrl.noaa.gov/psd/atmrivers/projects/pdf/Advanced%20Monitoring%20Network%20FloodER%20Prgrm.pdf. The lessons there apply directly to Washington and Oregon. The top two tiers, 3 and 4, are broader in scope and cost, with benefits stretching across much of the Western U.S., and are included in this white paper.

Deployment of a NEXRAD on the Washington Coast (led by NOAA/NWS): The Next-Generation Radar (NEXRAD) network consists of over 150 radars across the continental U.S. and territories. Recently a major gap in NEXRAD radar coverage off of the Washington coast has been identified. This has led to the installation of a NEXRAD radar on the Washington coast. The site will be operational late in 2011.

The Winter Storm Reconnaissance Program (led by NOAA/NWS): Using NOAA’s G-IV and military C-130s, for the last few years an annual monitoring effort has been conducted for several weeks over the Pacific Ocean to improve forecasts across the US. These efforts have demonstrated techniques that could be refined and extended to provide early characterizations of many more extreme events affecting the Western U.S.

Enhancements of the SNOTEL high altitude network (led by NRCS): This includes the addition of soil moisture at a number of SNOTEL sites, as well as selected other instrument upgrades.

Enhancement of the Climate Reference Network (USCRN) to include soil and humidity measurements (led by NOAA): Supported by the National Integrated Drought Information System (NIDIS), by September 2011, all 114 CRN locations had soil probes and associated data loggers and relative humidity instruments installed. By the end of FY 2011, subject to funding, all 114 USCRN stations in the conterminous United States will have received soil moisture probes and RH sensors. (See FY 2010 USCRN Annual Report at�http://www.ncdc.noaa.gov/crn/annual-reports.html, including its Fig. 6)

Deployment of Regional Climate Reference Network (RCRN; led by NOAA): The USRCRN consists of about 430 new stations nationally that meet siting and instrumentation standards of CRN. (These sites do not include soil moisture or relative humidity sensors.) A pilot project involving 71 grid points in the Four Corner states is wrapping up, and another 76 grid points are now being surveyed by WRCC in the five westernmost continental Pacific states. Initial emphasis is on western states to serve NIDIS needs. See http:www.ncdc.noaa.gov/crn/usrcrn/.

8��

Addition of dual-polarimetric capability to NEXRAD (led by NOAA): Beginning in 2011, NEXRAD radars will be upgraded to include dual polarization capability. Dual polarization offers several advantages compared to current NEXRAD single-polarization radar systems, providing additional information about the size, shape, and orientation of precipitation particles. This information can be used to more accurately identify the type of precipitation (e.g., hail vs. rain), correct for signal loss (attenuation) in heavy precipitation, and more easily identify and remove non-meteorological radar echoes. Dual polarization phase measurements allow for rainfall estimation that is much less affected by problems related to absolute calibration of the radar system, to signal attenuation effects, as well as to partial beam blocking.

Testing of Unmanned Aircraft Systems (UAS) for offshore weather data collection (led by NOAA, in close partnership with NASA): The “Winter Storms and Pacific Atmospheric Rivers” (WISPAR) experiment was conducted in early 2011 over the eastern Pacific Ocean. The ability of the unmanned NASA Global Hawk aircraft to carry a NOAA dropsonde system that directly measured atmospheric profiles within atmospheric rivers over the ocean was demonstrated. Flights were up to 25 hours long, and were coordinated with NOAA’s G-IV reconnaissance aircraft, which also sampled an AR near Hawaii (Appendix H).

b) Meteorological context

Extreme precipitation is the primary cause of flooding in the region, and when these events occur in winter they can substantially increase snowpack and thus water supply. Another major cause of extreme runoff and flooding in some regions is snow melt in the spring and summer, which can be triggered by unusually warm and sunny conditions, and/or warm, heavy rainfall.

The meteorological phenomena responsible for extreme precipitation varies across the region, as illustrated in Fig. 2. Four primary precipitation-causing phenomena are highlighted here:

Ͳ Atmospheric rivers (cool-season storms that come ashore from the Pacific; Appendix C) Ͳ Southwest monsoon (involving summer thunderstorms and remnant tropical storms) Ͳ Great Plains convective storms, i.e., thunderstorms (in spring and summer) Ͳ Upslope storms along the “front Range” of the Rocky Mountains (in spring)

9��

Fig. 2. Schematic illustration of regional variations in the primary weather phenomena that lead to extreme precipitation and flooding and contribute to water supply in the Western U.S. This has been developed with input from experts on these phenomena who contributed directly to this document.

Although there is some overlap in the seasonality of these phenomena, they are relatively distinct, with hydrometeorologically significant atmospheric rivers (ARs) occurring primarily from October through March, spring upslope storms occurring from April to June, the southwest monsoon being almost exclusively in July-October, and Great Plains deep convection from April to August.

The availability of COOP daily precipitation data from thousands of sites in the region going back 30 years or more, helps to clarify the geographic domains for each of these phenomena. For each COOP site, the 10 historical days with the largest daily precipitation totals were identified (i.e., the top 10 out of roughly 10,000 dates or more days in a site’s period of record). The season that had the largest number of these “top-10” extreme precipitation events at each COOP site was then plotted on a map (Fig. 3a). While the seasonal and geographic boundaries can blur or overlap to a degree (as in the Colorado Front Range), the overall patterns are clear enough to illustrate the regionally and seasonally varying causes of extreme precipitation across the West. Peak-streamflow dates (Fig. 3b) help to corroborate these patterns.

�

��

�

�

Atmospheric�Rivers��

(fall�and�winter)

Southwest�Monsoon�

(summer�&�fall)

Great�Plains�Deep�Convection

(spring�and�summer)

Spring��Front�Range�Upslope�(rain/snow)

10��

Fig. 3. (a) Seasonality of extreme precipitation events across the Western U.S. based on daily precipitation totals from thousands of COOP observations (dots) covering at least 30 years each. The color of each site corresponds to the season of the year when more of the top-10 daily precipitation events occurred than any other season. (b) Seasonality of annual peak daily stream flows highlighting the geographic distributions of AR-, snowmelt and monsoon dominated regions.

c) Challenges associated with the regional geography

The geography of the west severely complicates both the monitoring and prediction of these extreme events, including weather and climate time scales for the following reasons.

Ͳ Many storms originate over the Pacific Ocean where there are major limitations in weather observations, e.g., severely limited measurements of vertical profiles of winds, temperature and moisture in ARs and the larger-scale weather systems within which they are embedded.

Ͳ The presence of large and complex mountain ranges creates large differences in important weather conditions over short distances, making adequate monitoring and forecasting much more challenging.

Ͳ Large areas of the mountainous west are uniquely vulnerable to future increases in flooding during extreme events because over half of the largest (historical) daily precipitation totals occurred when daily mean temperatures were between -3 and 0 deg C, meaning that a warming of 3 deg C would greatly exacerbate flooding (Fig. 4; Bales et al. 2006)

Ͳ Much of the weather observing infrastructure in place today is simply too sparse, outdated (e.g., most vertical profiling today depends on infrequent in-situ balloon measurements when higher observation frequencies are needed), or is not deployed in an optimal manner for western US

11��

applications (see Fig. F1 in Appendix F for an example of NEXRAD coverage gaps in the western U.S.).

d) Selected requirements

- Accurate hydrometeorological forcings for the next generation flood-forecasting and streamflow models, including those being developed as part of IWRSS and the National Water Center, including soil moisture conditions, snow pack, existing stream flow, base flow, precipitation inputs, temperature, evapotraspiration, etc.

- Accurate Quantitative Precipitation Estimates (QPE) in complex terrain - Accurate Quantitative Precipitation Forecasts (QPF) for extreme events - Nowcasts and shortShort-term high-resolution QPF over urban areas for water, stormwater, and

sewage management - 6-h forecasts of the end of heavy rain over key watersheds for reservoir operations - 1-5 day guidance/forecasts of the location and intensity of extreme events to support future forecast-

based reservoir operations to optimize flood control and water supply - Improved situational awareness that provides enough lead time with quantified forecast uncertainty to

enable preemptive actions by emergency preparedness officials, including out to 10 days where feasible

- Seasonal guidance of the potential for both flood risk and water supply that can enable decision makers to select optimal policy options

- Accurate QPE and QPF for fire risk management and fire fighting - short term (minutes to a few hours) forecasts of rain rates that initiate debris flows over recent burn

scars - Increase in the use of GIS to pinpoint areas of concern to help local forecasters keep track of multiple

impact related events - Guidance on the potential risk of extreme events in a changing climate so as to inform major

infrastructure planning (e.g., Fig. 4 shows those areas for which warming of 3 degrees C would transform snow accumulation in extreme events into liquid, and thus change the stream flow in ways that could lead to great cool-season peak flows and possibly flooding at times of year currently not as vulnerable at those times)

These requirements correspond closely with the information needs as outlined in the U.S. Bureau Reclamation Science and Technology Program’s in the climate change and variability priority area, specifically addressing the following needs related to Shorter Term Climate Variability (USBR 2011, section 5.A.2) on time scales of days to years:

• Improved use of existing-quality weather, climate and/or hydrologic predictions in the development of operations outlooks (e.g., improved use of forecast uncertainty through novel methods or tool development)

• Development of superior-quality weather and climate and predictions relative to current information products from Reclamation's forecast providers

12��

• Enhanced communication of uncertainties and risks associated with weather, climate predictions in the development of Reclamation's operations outlook.

Fig. 4. Areas for which an increase in cool-season extreme precipitation and flooding would most likely occur in the case of a 3 deg C warming of the regional climate during storms. From Bales et al. 2006.

13��

3. The Vision

a) Overview

This section outlines a strategy that would lead, over a 6-yr period, to a fully functional modern monitoring system optimized for the west over a 6-year period. It would utilize existing organizations with the suitable expertise, infrastructure and missions to perform the implementation and then to carry on long-term operation, maintenance and ongoing improvements. While many details remain to be worked out, in principle, capabilities (i.e., knowledge, skills, tools) currently exist to execute this strategy if adequate funding becomes available. The vision is an expert opinion on what can be done to address these major societal challenges based on existing and emerging technologies and techniques, but does not identify funding sources.

The observational tools and related efforts are based on

Ͳ A set of requirements (often overlapping or complementary to one another) associated with detecting the phenomena that cause extreme precipitation as well predicting them hours to days beforehand and monitoring signatures of climate change

Ͳ Progress in numerical modeling of both the atmosphere and of hydrologic conditions, and the need for high resolution observations and predictions of key hydrometeorological conditions that drive them

Ͳ Several years of testing and prototyping new tools and methods in the NOAA HMT-West project and in other experimental settings and campaigns, such as CalWater and the Yosemite High-Altitude Hydroclimate Network, have provided many lessons about what works and does not work, and how much effort is involved

Ͳ Emergence of new observational technologies (summarized below), information systems (e.g., GIS), real-time and reliable communication from remote sites, and better understanding of the physical phenomena themselves.

Our vision consists of

Ͳ A broad land-based network (Fig. 5) customized to monitor conditions in the extreme precipitation regimes identified in Fig. 2, with observations focused on water vapor content and its transport, QPE, snow level, soil moisture and dust- and rain-on-snow effects. A key strategy is monitoring conditions aloft, below roughly 3 km altitude. This is the layer most difficult to observe using satellite or scanning radars, and yet is where some of the most important meteorological conditions, in terms of extreme precipitation, reside. It is where most of the water vapor and clouds are concentrated exists, where airflows interact with terrain, and where the atmospheric “boundary layer” conditions set the stage for heavy precipitation.

Ͳ An enhanced mountain array (Fig. 6), also land based, focused on snow conditions on the ground for tracking melt (Appendix K & L)

Ͳ Offshore monitoring (Fig. 7), with an emphasis on AR conditions and assimilation of data into weather models from the critical upwind region over the eastern Pacific from which so many

14��

western storms approach. States and communities need time to prepare, to minimize the cost impact of preparations/recovery from major storms in any ways they can. Offshore monitoring can help to provide such lead time before storms and flooding in many parts of the west. This need not be a perfect forecast...but a heads up that a big storm is coming and an initial statement of the characteristics of storm, e.g., cold, wet, windy, a once in 10 year event, or a typical big winter storm.

Fig. 5. Schematic network of new sensors (land-based) to improve monitoring, prediction and climate trend detection for hydrometeorological conditions that create extreme precipitation and flooding.

The land-based network (Figs. 5 and 6) described here would ideally include

Ͳ 100 new low-mid altitude soil moisture observing sites (Fig. 5, Appendix J) Ͳ 125 existing high-altitude sites with new snow-related data (Fig. 6, Appendix K) Ͳ 100 new GPS-met observing sites (Appendix I) Ͳ 25 snow-level radars Ͳ 25 wind profiling/ARO sites (section 3c and Appendix E) Ͳ 14 C-band scanning radars (Appendix F) Ͳ 10 X-band scanning radars or mini CASA networks (Appendix F)

15��

Fig. 6. Existing SNOTEL sites color coded to their altitude range. Red ovals highlight regions where a subset of the existing SNOTEL sites would have additional sensors emplaced to support better spring snow melt monitoring and prediction, or where new sites would be needed to broaden the altitude range of coverage. For more information, see Appendix K.

Fig. 7. Conceptual elements of an offshore observing network to improve monitoring, prediction and climate trend detection for hydrometeorological conditions that create extreme precipitation and flooding.

16��

b) Overarching gap: Monitoring water vapor transport – fuel for extreme precipitation

An overarching gap in observations associated with extreme precipitation events is monitoring of water transport, i.e., the “fuel” for the precipitation. Existing observations typically do not measure winds and water vapor aloft except in a handful of locations twice per day, and yet these are the key variables that determine the water vapor transports that fuels precipitation. The observing system that is proposed here is based on filling this gap, and designed in many settings on the specific characteristics of ARs that are most important to severe storms and that have now been well documented, including their width, depth, snow level, water vapor transport and orientation. Studies have shown that half of the hour-to-hour variance on coastal mountain rainfall is due to variance in the upslope wind speed, direction and water vapor transport at about 1 km above sea level, both within AR and beyond as well. In addition, it has been shown that the direction of the low-altitude wind in ARs has a major controlling effect on exactly which watersheds will receive the greatest rainfall in a given event (Ralph et al. 2003, Neiman et al. 2011), as is illustrated in Fig. 8.

When atmospheric rivers strike coastal mountains (Ralph et al. 2003)¾Air ascends coastal mountains, water vapor condenses, heavy rainfall occurs¾Details of the atmospheric river determine which watersheds flood

Fig. 8. Illustration of the role of coastal mountains in controlling the spatial distribution of heavy rainfall when an atmospheric river strikes the coast. The orientation of the winds in the AR creates rain shadows that can shelter some regions from the heaviest rainfall. In the case, where the “dividing streamline” crossed the Santa Cruz Mountains, it separated flood-producing rain to its west from moderate rain to its east that did not create flooding.

17��

Fig. 9. Schematic of atmospheric river conditions and an associated observing strategy (known as an ARO) combining wind profiler, GPS met, snow-level radar, and surface data. Because an average AR is about 400 km wide, the optimal horizontal spacing of AROs is 200 km.

Based on a decade of development at NOAA and in HMT, a method has been invented that deploys unattended sensors coupled with numerical weather model output to fill this gap (Fig. 9). Four atmospheric river observatories (AROs) are now being deployed along the California coast as part of its EFREP program and the technique was part of NOAA’s rapid response to the Howard Hanson Dam crisis.

The present vision involves completing a west coast array of AROs to capture water vapor transport from over the Pacific Ocean in ARs, along with a few more AROs farther inland to monitor water vapor transports through preferred pathways into the intermountain west. Similar instrumental arrays (called TARS) already exist along the border with Mexico, to support drug interdiction efforts by providing wind profile information aloft for operation of tethered balloons carrying surveillance radars to detect low-flying aircraft. The present plan would develop tools to take advantage of this border array to help monitor water vapor influx into the Southwest from the South, especially as part of the summer monsoon which derives its moisture through transport from either Mexico or the Gulf of Mexico. The plan also applies this technology along a line roughly 100 km east of the Front Range of the Rockies to monitor water vapor influxes from the Great Plains towards the Rockies in upslope storms, and would be coupled with snow-level radars in the foothills to monitor, in realtime, the fraction of vulnerable watersheds that would be exposed to rain versus snow. This fraction a critical factor determining the mix of flooding versus snowpack water storage from any given storm. Because water vapor transport from north to south across the Canadian border tends to be very weak (due to the prevalence of dry cold continental air there), no such array is proposed for that area.

18��

c) Phenomenological and regional requirements and relevant observations

This section summarizes specific observational enhancements addressing gaps related to the phenomena primarily responsible for extreme precipitation and streamflow.

• Broad area coverage components (addressing all four meteorological phenomena that cause extreme precipitation, plus spring/summer rapid snowmelt) These observations represent low-cost sensors that would be of benefit across the entire Western U.S. - Soil moisture (Appendix J) - GPS met for IWV (Appendix I) - “Bulk” snow measurements (depth, SWE, precipitation; Appendix K) - Air-snow interface (snow albedo, wind, dew point temperature, solar radiation) - Snowpack internal conditions (e.g., chemistry of dust, snow densities, Appendix L) - Additional stream gages

• Atmospheric River-focused components Another element of the network emphasizes horizontal water vapor transport in ARs, along with snow level monitoring and enhanced QPE through gap-filling scanning radars over major urban areas. The design also requires offshore monitoring to extend the range of predictions out to several days. - Atmospheric river observatories (ARO) in the AR-impacted regions - Snow level radars - Scanning polarimetric radars over major cities (e.g., Seattle, Bay Area, Phoenix,Vegas) - Offshore monitoring (coastal scanning radars - C-band, aircraft, buoy-mounted wind profilers, all taking advantage of satellites)

• Monsoon-focused components As indicated in Fig. 2, the southwestern U.S., including Arizona, Nevada, Utah, Colorado, and New Mexico, are impacted by the precipitation associated with the North American Monsoon (NAM). In particular, parts of southern Arizona and New Mexico receive over 50% of their annual precipitation during the NAM season (Douglas et al. 1993; Adams and Comrie 1997). The key gaps for monsoon monitoring include both water vapor transport from Mexico or the Gulf of Mexico, plus scanning radars to fill very large gaps in current radar coverage. - ARO-like installations, but focused on Monsoon-related water vapor transport and taking advantage of the existing TARS profiler network - Gap-filling scanning radars with polarimetric capability over major urban areas

• Great Plains convection components The Great Plains have one of the best existing radar networks for monitoring broad area storms (although gaps for monitoring tornadoes and severe thunderstorms remain). The present network vision emphasizes water vapor distribution and transport, as well as soil moisture.

19��

- Gap filling polarimetric radars in flood-prone front-range watersheds - Enhanced lightning network

• Front Range upslope storms Upslope storms primarily occur along the east slopes of the Rocky Mountains, extending from Montana to New Mexico (Fig. 2). These storms usually consist of a 200-300 km wide area of easterly or northeasterly winds north of a cold front and surface low pressure system. The passage of the cold front is often complicated by local terrain, and uncertainties regarding the specific location of the low pressure center development typically confounds forecasts. The monitoring system thus emphasizes monitoring these features and the conditions that modulate them, with

Ͳ A network of 449 MHz wind profilers 100 km east of the base of the foothills to monitor cold fronts and upslope winds, plus another array of 915 MHz wind profilers 10 km east of the base of the foothills to monitor both barrier jet winds and snow level (449 HMz profilers are more expensive, but can see much higher into the atmosphere than 915 MHz systems)

Ͳ Snow level radars at the base of the foothills as an alternative to the 915 MHz wind profilers

• Snow melt As highlighted in Fig. 3b, spring melt creates most of the highest flows seen on many rivers, especially in the intermountain region. For this reason special emphasis is given here to snowmelt conditions. Most of the proposed actions for this purpose require new sensors at high altitudes, but could also include sensors at altitudes where cold storms deposit snow that can contribute to flooding in somewhat rare events. The most effective approach would leverage the existing SNOTEL network, which already targets regions of significant snowpack, and has infrastructure that could facilitate implementation of new tools. In fact, some of this is already happening within the NRCS, and with California’s EFREP, in terms of adding soil moisture measurements to some sites. Figure 6 highlights the locations where system enhancements are recommended, and lists the key sensors that would be used, while Appendix K describes novel needs and methods recommended here.

d) Some excluded elements

While additional NEXRAD systems have potential uses here (such as illustrated by the planned deployment of a new NEXRAD radar on the Washington coast) the NEXRAD network is optimized more for Great Plains convection and detection of tornadoes and hail. For example, the NEXRADs do not scan at elevations angles below 0.5q above the horizon. In the west, where radars are commonly sited in areas of high terrain to reduce blockage, the ability of the radar to observe at or below the horizon is critical for accurate QPE. Moreover, the NEXRAD network is already far more dense in the Great Plains than over the mountainous part of the west (see Fig. F1 in Appendix F) and individual new NEXRAD radars are prohibitively expensive relative to the scope of the present vision.

Also, although new satellite techniques (i.e., new sensors or next generation satellites) hold potential to support the objectives of this white paper, their costs are beyond the scope of what is being considered

20��

here for regional applications. Nonetheless, the proposed network will integrate with existing and future radar and satellite observations, e.g., by using existing satellite sensors and NEXRAD data in new ways. For example, a) passive microwave and GPS occultation satellite observations are crucial over the ocean for AR monitoring; however, the passive microwave method does not work over land. A land-based GPS-met land-based network is proposed here specifically to help fill this gap. Also, no satellite methods currently monitor AR winds and water vapor transports aloft over the oceans or land, so airborne reconnaissance is proposed here to fill this gap. Finally, some key satellite footprints/spatial resolutions are simply too coarse to resolve conditions associated with the especially complex terrain of the west.

e) Additional actions related to achieving the objectives of this modernization:

- Measure the performance of precipitation forecasts that use measures of accuracy focused specifically on extreme precipitation events

- Measure snow-level and soil moisture forecast performance - Create a scale for assessing the strength of ARs offshore (e.g., compare water vapor transport in an

AR to the average flow of the Mississippi river; as in “this AR transports in one day a amount of water as vapor similar to what 7 to 15 Mississippis transport in one day as liquid)

- Create a simple scale for communicating and comparing magnitudes of extreme precipitation and stream flow over land

- Develop predictive modeling and decision support tools/systems to optimize use of the data - Use of new GIS-based tools for information management, display and dissemination - Ensure that data from key elements of this network, especially those that provide observations aloft

and/or offshore, are assimilated into operational weather prediction models. Note that models either are already able to assimilate many of the observations (e.g., wind profiler, GPS-met and dropsondes data) proposed here when and if they are made, and that methods to assimilate other data types could be developed.

- Sustaining an improved western observing network requires a stronger collaboration across several agencies

4. Transition to Operations

This new observational network would be established in the midst of significant new capabilities in the nation’s water resources science and services, which would facilitate the operational transition and increase the operational impacts of these new information streams. This section discusses this operational framework as well as related existing infrastructure.

IWRSS

The Integrated Water Resources Science and Services (IWRSS) is a new multi-agency framework to meet the nation’s growing water resource challenges. In May 2011, the National Oceanic and Atmospheric Administration, the US Army Corps of Engineers, and the US Geological Survey signed a memorandum of understanding establishing IWRSS. In the future, additional federal agencies (24 in all) that have water resource responsibilities will join the consortium. Through IWRSS, these agencies will engage in

21��

collaborative science and develop services and tools to support integrated and adaptive water resources management. IWRSS consortium members will operate within a common operating picture, employing shared modeling and information services frameworks, allowing their individual decision support systems to work in concert towards meeting the water challenges faced by our Nation.

IWRSS considers a broad range of time scales – from historical “analyses of record” through forecasts and projections spanning weather and climate. Three crosscutting themes on (i) Human Dimensions (including stakeholder interactions and communications), (ii) Information Technology (agency-spanning, service oriented architecture), and (iii) Operational Science (a summit to sea modeling and prediction framework) inform IWRSS efforts. The IWRSS common operating picture will provide decision support system interoperability and data synchronization services in which these new information streams can be shared enhancing their value and impact, across multiple federal agencies.

Another key element of the IWRSS strategy, are a series of regional watershed demonstrations (or pilots). A number of candidate pilot studies have been identified in the Western US, but the first to be explored will be a regional demonstration centered on Northern California, leveraging ongoing and developing efforts by HMT, NIDIS and other key programs. A series of IWRSS-led workshops is anticipated beginning in the fall of 2011, that will identify gaps and stakeholder requirements, explore technical and scientific solutions and approaches and produce recommendations to inform a regional pilot plan.

More information on IWRSS is available at: http://www.nohrsc.noaa.gov/~cline/IWRSS/IWRSS_ROADMAP_v1.0.pdf

The NOAA NWC

An important development within IWRSS is the establishment of the National Water Center (NWC). The NWC will be housed in a new NOAA facility being constructed in Tuscaloosa, Alabama and will serve as a focal point for IWRSS developments and NOAA’s water resource information services. The NWC is expected to be operational by the Winter of 2014. The NWC will provide an end-to-end, summit-to-sea data and modeling framework for all water related processes at and near the Earth’s surface. As noted earlier, these information services will cover a historical period, an analysis of current conditions, and forecasts and projections on weather and climate time scales. As such they will span too much and too little water conditions. Within NOAA, the NWC will support the NWS River Forecast Centers with end-to-end, high-resolution gridded water resource information, much like NCEP provides for the NWS Weather Forecast Offices.

The NWC will provide capabilities to integrate the new observations discussed herein, through assimilation into the IWRSS forcing data engine and operational modeling framework, and by integrating them into a data model that supports both NWS operations, as well as those of the IWRSS consortium. The NWC then becomes a vehicle for widespread dissemination and application to operational centers and stakeholders and customers of water resource information.

22��

NCEP/WFOs

IWRSS/NWC will complement and enhance the NWS’s long-established and highly efficient framework for disseminating weather and water information, forecasts and warnings. The NOAA National Centers for Environmental Prediction (NCEP) provide 24x7x365 large scale modeling forecasts and guidance. This information supports a network of 122 Weather Forecast Offices (WFOs) and 13 River Forecast Centers (RFCs), which serve as focal points of local expertise and knowledge, as well as for engagement with local communities and stakeholders. These data will feed into WFOs, supporting their role in issuance of locall watches and warnings.

NCEP leads NOAA’s efforts in assimilating observations into operational numerical models, including wind profiler and dropsondes data from aircraft. GSD innovates on assimilating observations from many sources in high resolution models. The existing capabilities in these arenas will be utilized, including use of current assimilation methods and development of new ones.

5. Implementation, costs and timelines

A tiered approach to implementation was used to develop the 21st Century vision for monitoring being implemented by California’s EFREP program. A similar approach could be used to organize, schedule and prioritize the westwide vision presented here (Fig. 10).

IV: Off-

shorerecon.

Tier III:Newer technology

Ex: Gap-filling radars,Buoy-mounted WPs

Tier I: Address well-defined needs with proven technology

Ex: Soil moisture sensors at CIMIS sites, GPS receivers of opportunity, snow-level radars

Tier II: Expand on well-defined needs with proven technology

Ex: Wind profilers, Coastal Atmospheric river observatory

A tiered approach for new obs to help address CA’s water resource issues

Fig. 10. A tiered approach to implementation could be used. Lower tiers are the least costly and most readily implemented. The upper tiers are more expensive and require greater effort to deploy. (From the California-DWR sponsored HMT-West Legacy/Enhanced Flood response and Emergency Preparedness project; Appendix E).

23��

The costs to operate, maintain and optimize the network can be reduced considerably by deploying automated monitoring systems and methods for monitoring performance, diagnosing faults, emphasizing reliability during critical meteorological conditions, training local “hosts” who can perform less technical tasks (e.g., restarting a computer), depending upon existing sensor network communications and quality control tools (such as MADIS - http://madis.noaa.gov/ and MESOWEST - http://mesowest.utah.edu/index.html), maintaining a small, technical and engineering staff that can be on call to perform repairs, and using methods developed partly in HMT for maintaining regional networks in a cost-effective manner. The proposed network is also structured to also take advantage of existing, underutilized networks, such as the TARS profiler network along the southern border with Mexico, pre-existing GPS sensors currently deployed for seismic monitoring, and extensive existing SNOTEL and streamgage networks, and provides resources to ensure key stream gauges are supported long-term.

Approximate cost for elements of this major improvement in western U.S. infrastructure are presented below but are very rough, order of magnitude (VROM) estimates, assuming optimal use of existing network facilities and co-location with pre-existing power supplies and telemetry streams where possible. The following list summarizes the VROM cost estimates for key components of this modern system:

Land-based network Ͳ Acquire and deploy land-based in situ and small remote sensors: $30 M ($10 M for in-situ sensors

and GPS-met; $20 M for profiling wind and precipitation radars) Ͳ Acquire and deploy land-based scanning radars: $35 M (14 C-band radars + 10 X-band radars) Ͳ Operate, maintain and optimize use of the land-based network (including one central group of

technical experts, three regional support hubs and one optimization R&D program); this would include a “Rapid Response” capability that would be on call for deployment of a scanning polarimetric radar, 2 mobile atmospheric river observatories and supporting surface meteorological data – consider the Howard Hanson Dam issue as an example; Operate a snow and rain sample collection network (and diagnostic systems) for isotope, chemistry and aerosol monitoring, including for “dust on snow” and Asian dust: $13 M/year

Ͳ Ensure long-term support for key existing stream gauges in the region: $5 M/year

Offshore network and tool development Ͳ Develop an optimized offshore monitoring system and concept of operations using aircraft, buoy

and island-mounted systems, integrated with existing and planned satellite observations and numerical modeling tools: $15 M (includes $5 M for buoy-mounted ARO development)

Ͳ Acquire and outfit necessary aircraft (likely including the no-cost transfer of outdated military aircraft, such as Unmanned Aircaft Systems -UAS, to either NOAA or NASA): $25 M

Ͳ Operate, maintain and optimize use of offshore network (1 aircraft including expendables such as dropsondes, 4 buoy-mounted AROs, 8 island observing sites, optimization R&D): $17 M/year

Total integrated network (land-based + offshore) Ͳ Develop, acquire and deploy: $105 M (one-time costs) Ͳ Operate, maintain and optimize: $35 M (annually)

24��

Timeline

Initially, emphasis could be placed on targeted development tasks, acquisition of existing technologies and deployment of systems. As time progresses, the need to operate, maintain and optimize uses increases, as does the opportunity to develop new applications and tools. The fully implemented system can be in place within 6 years, including $105 M of one-time costs. The final ongoing costs are $33 M/year, and could be carried out by a core facility plus three regional hubs.

Year Develop, Acquire, Deploy ($M)

Operate, Maintain, Optimize ($M)

Total for the year ($M) Highlights/notes

1 27 8 35 Expand EFREP network to OR, WA, ID, NV; develop offshore tools; Order long-lead equipment

2 24 11 35�Start Front range and snow networks; deploy soil moisture and GPS-met to intermountain area;

3 21 14 35�First gap-filling radars deployed; continue snow network deployment; Expanded EFREP network done

4 18 17 35�Front-range network complete; Airborne assets in place; core OMO staff and facilities established

5 15 20 35�Gap-filling radar network complete; snow network complete; offshore system completed

6 0 35 35�Full network in place; full OMO system in place; ongoing service improvement system in place

Total $105 M $105 M $210 M Ongoing costs $35 M/year Note: These estimates represent rough order of magnitude costs based on a concept of operations that highly leverages existing facilities, organizations and applies cost-saving strategies tested in HMT. Table 1. Strawman implementation strategy to establish long-term capability for the Western U.S. We would also seek to coordinate the development of the enhanced observation system with the information systems and administrative mandates of the primary federal, state and related water data and management agencies, and to leverage existing data wherever possible.

6. Expected Outcomes

Based on past experience with implementing major new observational infrastructure (e.g., NEXRAD, satellites, EFREP, and HMT-West), the time frame for implementation is roughly 5-10 years. During this time the methods and tools to use the new data would also be being enhanced, and benefits would begin to accrue. This is not a “quick fix” strategy. It is a thorough, scientifically based, strategy to modernize the region’s observational infrastructure for dealing with the extremes of too much, or too little water.

25��

This 21st century observing system for the West will meet many of the 21st Century needs for solid, real-time information based on the most up-to-date science, to support decision making affecting millions of people, businesses and the environment of the west. Benefits will include:

Ͳ Mitigating risks of >$100 B Katrina-like disasters on the U.S. West coast (see NRC reports from before Katrina and ARkStorm activities since then)

Ͳ Reducing flood risks and damages through development of modern decision support tools that allow for pre-storm releases from flood control reservoirs that are refilled by the storm, thereby enhancing also water supply for the summer

Ͳ Enabling forecast-based reservoir operations for combined benefits of improved flood control and enhanced water supplies, possibly offseting some requirements for new reservoir space being considered in the west ($Billions in savings)

Ͳ Improving drought monitoring and associated benefits in support of NIDIS Ͳ Improving the capacity for early detection of climate change impacts on water supply and flooding

in the west and to inform adaptation and mitigation strategies optimized for regional impacts and needs

Ͳ Tighter collaborations across federal, state, local agencies to assure effective implementation into existing water information and management systems

Ͳ Strengthening of science and technology job sectors in the region

From a policy perspective, it is perhaps most notable that improved water-year-type forecasts in California alone have estimated values that could exceed $100 M in a single year (Simpson et al. 2004). In terms of flood risks, enhanced preparedness for flooding events that mitigates loss of life and property for flooding – the phenomena that is responsible for the greatest impacts as defined through Presidential disaster declarations (e.g., average flood losses in the region are $1.5 Billion per year-Appendix A) – is a primary strategy for controlling and reducing those risks. With improved monitoring, improved forecasts and longer lead times, community leaders will be better able to prepare for extreme events not only from a safety standpoint, but can minimize the costs of taking preparedness actions, e.g. by shifting work schedules so that preparatory work can be done on regular time versus overtime. Thus we believe that prudence dictates a proactive approach to monitoring for extreme precipitation events and flooding across the western states, and we hope that the vision presented here can be implemented as a proactive strategy.

26��

7. Full text of the Resolution of the Western States Water Council passed on July 29, 2011

Position No. 332 RESOLUTION

of the WESTERN STATES WATER COUNCIL

supporting FEDERAL RESEARCH AND DEVELOPMENT OF UPDATED HYDROCLIMATE

GUIDANCE FOR EXTREME METEOROLOGICAL EVENTS

Bend, Oregon July 29, 2011

WHEREAS, Western states have recently been experiencing near-record flooding, droughts, or wildfires that threaten public safety, tax aging water infrastructure, and/or have significant economic consequences; and

WHEREAS, before the first half of 2011 was over, the year had already set records for extreme weather events, with the nation having experienced eight $1 billion-plus disasters, according to the National Oceanic and Atmospheric Administration (NOAA); and

WHEREAS, extreme weather events have grown more frequent in the U.S. since 1980, according to NOAA, and are believed to be caused by a changing climate; and

WHEREAS, the top twelve warmest years on record globally all have occurred since 1997, and climate change is expected to result in future increases in the frequency, extent, and/or severity of floods, coastal inundation, and droughts.

WHEREAS, some of NOAA’s probable maximum precipitation estimates used by water agencies for dam safety analyses have not been updated since the 1960s and the federal Guidelines for Determining Flood Flow Frequency Analysis (published as Bulletin 17B) have not been revised since 1981, and neither of these guidance documents address hydroclimate non-stationarity; and

WHEREAS, flood frequency analyses are used by public agencies at all levels of government to design and manage flood control and stormwater infrastructure, with Bulletin 17B still representing a default standard of engineering practice; and

WHEREAS, federal funding for hydrology research has waned since the 1970s-1980s, and alternative statisticalmethodologies for flood frequency analyses or deterministic analytical procedures are not being supported and transitioned to common engineering practice; and

WHEREAS, the Federal Emergency Management Agency has adopted a process for local communities to explicitly incorporate “future conditions hydrology” in the national flood insurance program’s flood hazards mapping; and

WHEREAS, a federal agency committee composed of the U.S. Army Corps of Engineers, U.S. Bureau of Reclamation, NOAA, U.S. Geological Survey, and U.S. Environmental Protection Agency held a 2010 national science workshop on non-stationarity, hydrologic frequency analysis, and water management, to identify information gaps and the state of the science for handling hydroclimate uncertainty; and

27��

Position No. 332

WHEREAS, the Council co-sponsored a 2011 workshop on hydroclimate non-stationarity and

extreme events, to identify actions that could be taken at planning to operational time scales to improve readiness for extreme events; and

WHEREAS, the federal and the Council workshops identified multiple approaches that could be employed at the planning time scale, including ensembles of global circulation models, paleoclimate analyses, and alternative techniques for flood frequency analysis; and

WHEREAS, advances in weather forecasting research, such as that of NOAA’s Hydrometeorological testbed program onWest Coast atmospheric rivers, demonstrate the potential for improving extreme event forecasting at the operational time scale; and

WHEREAS, the 2006Western Governors’ Association (WGA) report on Water Needs and Strategies for a Sustainable Future and the follow-up 2008WGA Next Steps report identify addressing climate change impacts as a priority for moving forward, and make specific recommendations for actions that the federal government and the states should take to support adaptation, including detailing research and planning needs.

WHEREAS, WGA and NOAA signed a memorandum of understanding on June 30, 2011, regarding state adaptation to climate variability and change that focuses on climate extremes, variability and future trends as they relate to disaster risk reduction and improved science for coastal and marine resource management; and

WHEREAS, the Draft Vision and Strategic Framework for a Climate Service in NOAA includes changes in extremes of weather and climate as one of the four key societal challenges that will initially be a focus of the climate service.

NOW, THEREFORE, BE IT RESOLVED, that the federal government should update and revise its guidance documents for hydrologic data and methodologies – among them precipitationfrequency estimates, flood frequency analyses, and probable maximum precipitation – to include subsequently observed data and new analytical approaches; and

BE IT FURTHER RESOLVED, that theWestern States Water Council supports development of an improved observing system forWestern extreme precipitation events, to aid in monitoring, prediction, and climate trend analysis associated with extreme weather events; and

BE IT FURTHER RESOLVED, that theWestern States Water Council urges the federal government to support and place a priority on research related to extreme events, including research on better understanding of hydroclimate processes, paleoflood analysis, design of monitoring and change detection networks, and probabilistic outlooks of climate extremes.

BE IT FURTHER RESOLVED, that theWestern States Water Councilwill work with NOAA in supporting efforts on climate extremes, variability, and future trends as called for in theWGA-NOAA memorandum of understanding.

F:\POSITION\2011\Bend, OR\-#332 WSWC Position on Extreme Meteorological Events 2011July 29.doc

28��

Appendices

A: Flood damages in the western U.S.

B: Comparison of extreme precipitation in the western US with other regions

C: Storms, floods, and the science of atmospheric rivers

D: Howard Hanson Dam crisis Rapid Response

E: California’s Enhanced Flood Response and Emergency Preparedness (EFREP) project

F: Scanning radar options

G: A possible scaling for extreme 3-day precipitation

H: WISPAR experiment with the Global Hawk Unmanned Aircraft System (UAS)

I: Global Positioning System – Meteorology (GPS-Met)

J: Soil moisture observing network design and instrumentation

K: An Approach to Enhancement of the Western SNOTEL and Streamgage Networks

L: Dust-on-snow sampling

M: ARkStorm: Emergency Preparedness Scenario for An Extreme Atmospheric River Event

N: Gap-filling radar example for Colorado Front Range flood from a burn area

References

Adams, D. K., A. C. Comrie, 1997: The North American Monsoon. Bull. Amer. Meteor. Soc., 78, 2197–2213. Bales, R., Molotch, N., Painter, T., Dettinger, M., Rice, R., and Dozier, J., 2006, Mountain hydrology of the western US: Water Resources Research, 42, W08432, doi:10.1029/2005WR004387, 13 p. Douglas, M.W., R. Maddox, K. Howard, and S. Reyes, 1993: The Mexican monsoon. J. Climate, 6, 1665–1667. Dettinger, M.D., Ralph, F.M., Das, T., Neiman, P.J., and Cayan, D., 2011: Atmospheric rivers, floods, and the water resources of California. Water, 3 (Special Issue on Managing Water Resources and Development in a Changing Climate), 455-478. Higgins, W., D. Ahijevych, J. Amador, A. Barros, E.H. Berbery, E. Caetano, R. Carbone, P. Ciesielski, R. Cifelli, M.C. Vazquez, A. Douglas, M. Douglas, G. Emmanuel, C. Fairall, D. Gochis, D. Gutzler, T. Jackson, R. Johnson, C. King, T. Lang, M.I. Lee, D. Lettenmaier, R. Lobato, V. Magana, J. Meiten, K.

29��

Mo, S. Nesbitt, F.O. Torres, E. Pytlak, P. Rogers, S. Rutledge, J. Schemm, S. Schubert, A. White, C. Williams, A. Wood, R. Zamora, and C. Zhang. 2006: The NAME 2004 field campaign and modeling strategy. Bull. Amer. Meteor. Soc., 87, 79-94. IWRSS Roadmap: http://www.nohrsc.noaa.gov/~cline/IWRSS/IWRSS_ROADMAP_v1.0.pdf Neiman, P. J., L. J. Schick. F. M. Ralph, Mi. Hughes, and G. Wick, 2011: Flooding in Western Washington: The connection to atmospheric rivers. J. Hydrometeor., (In press).

Olsen, J. Rolf, Julie Kiang and Reagan Waskom, (editors). 2010. Workshop on Nonstationarity, Hydrologic Frequency Analysis, and Water Management. Colorado Water Institute Information Series No. 109. www.cwi.colostate.edu.

Porter, Keith, Wein, Anne, Alpers, Charles, Baez, Allan, Barnard, Patrick, Carter, James, Corsi, Alessandra, Costner, James, Cox, Dale, Das, Tapash, Dettinger, Michael, Done, James, Eadie, Charles, Eymann, Marcia, Ferris, Justin, Gunturi, Prasad, Hughes, Mimi, Jarrett, Robert, Johnson, Laurie, Dam Le-Griffin, Hanh, Mitchell, David, Morman, Suzette, Neiman, Paul, Olsen, Anna, Perry, Suzanne, Plumlee, Geoffrey, Ralph, Martin, Reynolds, David, Rose, Adam, Schaefer, Kathleen, Serakos, Julie, Siembieda, William, Stock, Jonathon, Strong, David, Sue Wing, Ian, Tang, Alex, Thomas, Pete, Topping, Ken, and Wills, Chris; Jones, Lucile, Chief Scientist, Cox, Dale, Project Manager, 2010: Overview of the ARkStorm scenario: U.S. Geological Survey Open-File Report 2010-1312, 183 p. and appendixes.

Ralph, F. M., Neiman, P. J., D. E. Kingsmill, P. O. G. Persson, A. B. White, E. T. Strem, E. D. Andrews, and R. C. Antweiler, 2003: The impact of a prominent rain shadow on flooding in California’s Santa Cruz mountains: A CALJET case study and sensitivity to the ENSO cycle. J. Hydrometeor., 4, 1243-1264.

Ralph, F. M., R. M. Rauber, B. F. Jewett, D. E. Kingsmill, P. Pisano, P. Pugner, R. M. Rassmussen, D. W. Reynolds, T. W. Schlatter, R. E. Stewart and J. S. Waldstreicher, 2005: Improving short-term (0-48 hour) Cool-season quantitative precipitation forecasting: Recommendations from a USWRP Workshop. Bull. Amer. Meteor. Soc., 86, 1619-1632.

Ralph, F.M., and M.D. Dettinger, 2011: Storms, Floods and the Science of Atmospheric Rivers. EOS, Transactions, Amer. Geophys. Union., 92, 265-266.

Simpson, J. J., M. D. Dettinger, F. Gehrke, T. J. McIntire, G. L. Hufford, 2004: Hydrologic Scales, Cloud Variability, Remote Sensing, and Models: Implications for Forecasting Snowmelt and Streamflow. Wea. Forecast., 19, 251-276.

U.S. Bureau of Reclamation (USBR) 2011: FY 2011 Science and Technology Program, Research and Development Office, Denver, CO. www.usbr.gov/research/docs/S&T_2011_research_abstracts.pdf

White, A. B., B. Colman, G. M. Carter, F. M. Ralph, R. S. Webb, D. G. Brandon, C. W. King, P. J. Neiman, D. J. Gottas, I. Jankov, K. F. Brill, Y. Zhu, K. Cook, H. E. Buehner, H. Opitz, D. W. Reynolds, L. J. Schick, 2011: NOAA's Rapid Response to the Howard A. Hanson Dam Flood Risk Management Crisis. Bull. Amer. Meteorol. Soc. (in press July 2011), doi: 10.1175/BAMS-D-11-00103.1.

��

1��

A Vision of Future Observations for Western U.S. Extreme Precipitation Events and Flooding: Monitoring, Prediction and Climate

Appendices

Marty Ralph (NOAA), Mike Dettinger (USGS), et al.

(See author list in main text, and authors listed for each Appendix)

A: Flood damages in the western U.S.

B: Comparison of extreme precipitation in the western US with other regions

C: Storms, floods, and the science of atmospheric rivers

D: Howard Hanson Dam crisis Rapid Response

E: California’s Enhanced Flood Response and Emergency Preparedness (EFREP) project

F: Scanning radar options

G: A possible scaling for extreme 3-day precipitation

H: WISPAR experiment with the Global Hawk Unmanned Aircraft System (UAS)

I: Global Positioning System – Meteorology (GPS-Met)

J: Soil moisture observing network design and instrumentation

K: An Approach to Enhancement of the Western SNOTEL and Streamgage Networks

L: Dust-on-snow sampling

M: ARkStorm: Emergency Preparedness Scenario for An Extreme Atmospheric River

N: Gap-filling radar example for Colorado Front Range flood from a burn area

Provided to the Western States Water Council on October 5, 2011

��

2��

Appendix A: Historical flood damages in the Western U.S.

M. D. Detttinger (USGS) and F.M. Ralph (NOAA)

The following figure was published by Pielke et al. in 2002 and used an analysis of NWS data for the period 1983-1999. During these 17 years, the Western States of WA, OR, CA, ID, NV, UT, AZ, MT, WY, CO, NM, ND, SD, NE, KS, OK, and TX experienced $24.7 Billion in flood damages, an average of $1.5 Billion annually. California, Washington and Oregon combined to account for $10.6 B of this (i.e., 43% of the regional total), with California alone accounting for 25% of the western total.

Fig. A1. Flood damages nationally, and for the 17 states in the contiguous western US (red).

��

3��

For comparison, if the strawman modernization of Western US observations for extreme precipitation and flooding, achieved even a 2% reduction in flood damages, i.e., $30 M/year in savings, then it would be cost effective even without considering the benefits to water supply that would also accrue. A general idea of how large the water-supply benefits might be is provided by an estimate from Simpson et al. (2006) that a better water-year status forecast for California, in a single year, could save the State (not including businesses in the State) about $150 million.

Still other benefits would include reduced loss of life. For example, in 1998, experimental offshore reconnaissance enabled NWS forecasters in coastal California to issue a warning with enough lead time so that emergency responders were able to be pre-position equipment and supplies, and thus affected hundreds of rescues with only 1 fatality. A similar storm 15 years earlier caused many flood fatalities (Ralph. et al. 2003).

Finally, the vulnerability of the region is highlighted by recent conditions at Howard Hanson Dam in Washington that put $4 B in infrastructure at risk, and where the most effective management response proved to be installation and operation of many of the observational assets described in this vision in order to provide highest quality forecast capabilities to the reservoir managers who had to managed those risks (White et al. 2011; Appendix D).

------------------

Pielke RA Jr., Downton MW, Barnard Miller JZ (2002) Flood damage in the United States, 1926-2000--A reanalysis of National Weather Service Estimates: UCAR, Boulder, CO, 86 p.

Ralph FM, Neiman PJ, Kingsmill DE, Persson POG, White AB, Strem ET, Andrews ED and Antweiler RC, 2003, The impact of a prominent rain shadow on flooding in California’s Santa Cruz Mountains—A CALJET case study and sensitivity to the ENSO cycle: J. Hydrometeorology, 4, 1243-1264.

Simpson, J.J., Dettinger, M.D., Gerhke, F., McIntyre, T.J., and Hufford, G.I., 2004, Hydrologic scales, cloud variability, remote sensing and models—Implications for forecasting snowmelt and streamflow: Weather and Forecasting, 19, 251-276.

��

4��

Extreme Precipitation and Atmospheric Rivers on the U. S. West Coast

BY F. M. RALPH1 AND M. D. DETTINGER2

1NOAA/ESRL, Physical Sciences Division, Boulder, Colorado 2U.S. Geological Survey, Scripps Institution of Oceanography, La Jolla, California

Submitted on 22 Aug 2011 to Bull. Amer. Meteor. Soc. as a contribution to “Map Room”

INTRODUCTION. Strong winter storms battered the U.S. West Coast from western Washington to southern California in December 2010, producing from 250 to over 670 mm (10 to 26 inches of rain) in preferred areas (Fig. 1). A common denominator among these events is that the synoptic weather patterns produced a series of strong atmospheric rivers (AR) that transported large amounts of water vapor from over the Pacific Ocean to the U.S. West Coast (Fig. 2), which fueled the heavy rain and flooding, and provided beneficial increases in snowpack. For example, by December 22 – the first full day of winter, the southern Sierra had already received 75% of its annual average snowpack and was well on its way to one the deepest annual snowpacks recorded.

Just how “extreme” were these events relative to other atmospheric river cases in the region? More generally, how does West Coast AR-fed precipitation compare with extreme precipitation in other parts of the U.S., such as from landfalling hurricanes and tropical storms? This report uses decades of Cooperative Observer (COOP) daily precipitation reports from over 5800 stations across the U.S. to address these questions, and then summarizes the West Coast events and forecasts of December 2010.

A BRIEF BACKGROUND ON ATMOSPHERIC RIVERS. Atmospheric rivers (AR) are long, narrow zones within extratropical cyclones that contain large water vapor contents and strong winds and that are responsible for > 90% of all atmospheric water vapor transport in midlatitudes (Zhu and

Newell, 1998). They are 1000s of km long and, on average, only 400 km wide (Ralph et al. 2004); 75% of the water vapor transport occurs below 2.25 km altitude (Ralph et al. 2005). ARs regularly produce extreme precipitation in coastal regions because they transport large quantities of water vapor and comprise almost ideal conditions for producing heavy orographic rains and flooding when they encounter mountains (Ralph et al. 2005, 2006, 2011; Neiman et al. 2008, 2011). The west coast of North America is particularly vulnerable to ARs, as are the west coasts of other midlatitude continents, such as

Fig. 1. 14-day observed precipitation in the Western U.S. (Courtesy, NWS Advanced Hydrologic Prediction Service).

��

5��

Fig. 2. Polar orbiting satellite observations of vertically integrated water vapor from SSM/I and SSM/IS showing atmospheric river conditions associated with two of the extreme precipitation events in December 2010 on the U.S. West Coast. These images represent two separate and independent ARs. (Courtesy of G. Wick and D. Jackson.) Europe (Stohl et al. 2008). Although they are linked to extreme precipitation and flooding, ARs also produce 25-50% of the annual precipitation on the U.S. West Coast (Guan et al. 2010, Dettinger et al. 2011), and thus are important in generating water resources in the region. as well as cloud liquid water and rain rate (e.g., Wick et al. 2008).

For more information on ARs, including a list of publications, see http://www.esrl.noaa.gov/psd/atmrivers/.

ANALYSIS OF EXTREME PRECI-PITATION USING COOP DATA. Although much is now known about key geophysical characteristics of ARs, a systematic comparison of extreme AR rainfall on the U.S. West Coast with extreme precipitation elsewhere has not been made. To provide such a comparison, long-term (>30 yr) COOP precipitation records of 3-day precipitation totals were used to determine where and how often storms in each of several simple rainfall categories (R-Cats) have been reported across the contiguous U.S. The categories used are listed in Table 1.

a) Methodology The categories developed and used here were based on daily accumulated precipitation totals reported in the Summary of the Day observations from cooperative weather stations across the United States [National Weather Service (NWS), (1989)]. Missing data were excluded, as were accumulations from multiple days reported only as multi-day totals. While daily totals are a common measure of precipitation, multiple-day precipitation totals can be of more practical importance with respect to progressive hazards, like floods on main-stem rivers and some landslides.

A “station event” is defined here as an occasion when a single COOP station reports a precipitation total within one of the R-Cats. An “episode” is defined as a 3-day period during which at least one COOP station reports precipitation within one of the R-Cats. A single episode can, and usually does, include multiple station events. Multiple-day precipitation totals are considered because multi-day totals are commonly most relevant for landslides, flooding and other hydrological impacts on main-stem rivers. Although 2- and 4-day totals were also considered, 3-day windows were used because: (a) when 2-day windows were considered, roughly half of the

12�Dec�2010

18�Dec�2010

��

6��

Table 1. Rainfall categories used in this study, and national frequencies of occurrence. Note that an “episode” is defined as a single 3-day period for which one or more stations observed at least 200 mm of precipitation in the same general area.

Fig. 3. Maximum 3-day precipitation totals at 5877 COOP stations in the conterminous US.

major storms (by 3-day standards) were missed, and (b) when 4-day periods were used, one of the four days typically contributed little to the multiple-day totals (on average, nationally, the driest day of 4-day site-events contributed only 4% of the 4-day totals, whereas, on average across all events, the driest day in a 3-day window still accounts for 10% of the total).

b) Results Historical patterns of extreme precipitation, labeled by R-Cats, are shown in Fig. 3, which reveals that, although R-Cat 1–2 events are reported in most states, nearly all R-Cat 3–4 events occurred in California, Texas, or the southeastern states. Thus, extreme-precipitation events in the mountains of California are found to be comparable with those in the southeastern U.S. (including Texas) and are only equaled by storms in that

�

�

75�W

��

7��

�

Fig. 4. Seasonality of extreme precipitation events in the Eastern U.S. versus the Western U.S. Number of 3-day episodes achieving the highest rainfall categories, east (pink) and west (blue) of 105ºW, by month of year, normalized to the number of COOP sites in each region. Two thresholds are used, light shading for R-Cat 2 (i.e., >300 mm), and dark shading for R-Cat 3-4 (i.e., >400 mm).

region. Extreme precipitation events in California are further notable because, unlike those in Texas and the Southeast, it is not uncommon for California stations to have experienced multiple R-Cat 3-4 episodes during their periods of record.

By defining R-Cat “episodes,” i.e., 3-day periods during which at least some stations exceeded a given R-Cat threshold, we verified that the more extreme the episode - the larger its areal extent (Table 1). Episodes were then binned by month of year for stations east and west of 105°W. The resulting episode counts (Fig. 4) reveal that most eastern episodes occurred during the spring, summer, and fall seasons, whereas the western episodes occurred almost exclusively during the cool season (Nov-Apr) when strong ARs typically impact the region (Neiman et al. 2008). Despite the timing difference, for a wide range of 3-day precipitation totals the fraction of wet days exceeding those totals are nearly the same for the cool-season (Nov-Apr) in the western U.S. as for the warm season (May-Oct) in the eastern U.S. (Fig. 5).

Evaluation of all R-Cat episodes from 1997-2005 in terms of meteorological conditions showed that in all 17 episodes west of 115°W that met or exceeded the R-Cat 2 threshold, satellite data showed that an AR

had struck the west coast during the 3-day episode (Neiman et al. 2008). During the same period, roughly half of the major eastern events were associated with tropical storms and hurricanes. Also, by using daily NCEP-NCAR Reanalysis estimates of vertically integrated water vapor transports from 1950-2008, it was found that 44 of 48 R-Cat 3-4 episodes in the western US coincided with landfalling ARs there. Upon normalizing long-term eastern and western counts by number of stations in each region, the annual-averaged frequencies of extreme R-Cat episodes east and west of 105°W are identical, i.e., with 44 R-Cat 1-4 episodes per year. Similarly, the normalized annual-averaged frequencies of R-Cat 3-4 episodes are 2.1 - 2.2 per year in both areas. Thus, 3-day precipitation extremes associated with landfalling ARs on the U.S. West Coast are heavier than extreme storms anywhere else in the country outside the southeast U.S. (including those related to landfalling tropical storms and hurricanes). Also, they yield comparable precipitation totals with the southeastern storms, and occur station-by-station just as frequently as the extreme-precipitation episodes there.

�

�

�

��

� 8

Fig. 5. Frequency of occurrence of extreme precipitation east and west of 105 deg W (normalized to number of COOP stations in each region). EXTREME PRECIPITATION STRIKES THE U.S. WEST COAST IN DECEMBER 2010. As an example, the extreme nature of the precipitation associated with the ARs of December 2010 is described below, along with a synopsis of the associated forecasts. The first major storm in the series produced 292 mm (11.5 inches) of rain at Quinault on the western side of Washington’s Olympic Mountains and localized flooding from 10-12 December. Thus, this was an R-Cat 1 event, although it nearly achieved an R-Cat 2 rating. The second set of storms struck California from 17 – 22 December 2010, producing more than 670 mm (26 inches) of rain in the San Bernardino Mountains of southern California over those 6 days, and upwards of 10-15 feet of snow in the southern Sierra Nevada Mountains. Within this period of heavy rain the 3-day total at Lytle Creek in southern California was 440 mm (17.32 in) from 19-21 December. Thus it was an R-Cat 3 event. In addition to flooding in Washington and California, these storms produced 432 mm (17 inches) of rainfall in the mountains of southern Utah over 5 days between 18-23 December at the “Little Grassy” SNOTEL site. The 3-day maximum accumulation at that site was 351 mm (13.8 in) from 20-22 December, and thus was an R-Cat 2 event. Flooding in southern Utah caused serious property damage and damage to the

earthen Trees Branch Dam along the Virgin River near Springdale, Utah. In the case of the southern California and Utah areas, a strong AR stalled in the region for several days, providing a persistent supply of tropical water vapor from near Hawaii (which also experienced flooding).

As part of NOAA's standard procedures for issuing precipitation and stream flow forecasts, quantitative precipitation forecasts (QPF) were produced in a collaborative effort between the Hydrometeorological Prediction Center (HPC), the Northwest River Forecast Center (NWRFC), the California-Nevada River Forecast Center (CNRFC), and the local NWS Weather Forecast Offices (WFOs) in the region. These QPFs were then transformed into quantitative stream flow forecasts for key watersheds by the CNRFC and NWRFC.

By the time the first storms hit the Washington Coast from 1200 UTC 10 Dec-

Fig. 6. HPC 3-day precipitation forecasts (in inches). These forecasts were issued a) 9 Dec 2010 at 1350 PST, b) 17 Dec 2010 at 0151 PST, and c) 20 Dec 2010 at 0202 PST.

��

� 9

ember to 1200 UTC 13 December 2010, QPFs produced by HPC (Fig 6a) provided valuable guidance that heavy rain was on its way, and the river hydrographs forecasted by NWRFC gave ample warning for the flooding that ensued. HPC, NOAA's Environmental Modeling Center (EMC), NWRFC, and the Seattle WFO produced specialized precipitation and hydrologic forecasts for many western Washington river basins including the Green River Basin near Seattle because of the limited flood prevention capability provided by the damaged Howard A. Hanson Dam (White et al. 2011). On December 17, when the next series of powerful storms began to make landfall in central and southern California, weather forecasters were armed with a similar set of forecasts from HPC, EMC and CNRFC, including remarkable precipitation forecasts (Figs. 6b and 6c) of more than 250 mm (10 inches) in 72 hours for both December 17-20 (1200 UTC to 1200 UTC) and December 20-23 (1200 UTC to 1200 UTC).

IMPLICATIONS. Dave Reynolds, meteorologist-in-charge of the National Weather Service's (NWS) San Francisco WFO, said NWS operational forecasters were well prepared for the storms in December 2010 in part because of enhanced awareness and improved understanding of the role of ARs. Reynolds recently presented an online briefing to NWS Western Region staff on the AR phenomenon and related scientific advances. These advances, led by NOAA's Physical Sciences Division (PSD) in Boulder, Colorado, were conducted under NOAA’s Hydrometeorology Testbed (HMT), and used modern satellite and other observational tools to reveal the importance of ARs to both flooding and water supply in the region. Evaluations of QPF products by HMT during the cool season of 2005/06 (Ralph et al. 2010) also revealed that 18 of the 20 most extreme precipitation events that season were associated with ARs, and that QPF was biased low by roughly 50% in the events with greater than 127 mm (5 in) of precipitation in one day. Ongoing research and prototyping is underway to further assess QPF and to explore potential new tools to assist in prediction of extreme

precipitation from ARs, such as the water vapor “AR flux tool” (Neiman et al. 2009).

In practical terms, the R-Cat categorization applied here is simple enough to facilitate communication in both technical and public arenas, could be used to standardize research analyses and forecasts, and could improve reporting of climate-change projections regarding extreme precipitation. The categorization complements standard return-period methods, straightforwardly accommodating the nonstationarities of climate change (Milly et al. 2008) and short record lengths that can make estimation of return-periods very difficult. Such categorizations will be all the more important as research into the potential impacts of a changing climate on ARs and extreme precipitation begins (e.g., Dettinger 2011). The extent to which the R-Cat episodes (from all mechanisms) are identifying truly extreme precipitation episodes may be judged either economically or physically. For example, nationally, six of the R-Cat 3–4 episodes from 1997-2005 were associated with damages exceeding $1 billion each. Meanwhile, R-Cat 2–4 episodes (combined) occur historically roughly just as frequently as do hurricanes (Atlantic and Eastern Pacific combined, measured by the Safir-Simpson scale) and as do violent tornadoes (measured by the Fujita scale), indicating that the simple R-Cat scale used here is identifying extreme precipitation that is just as rare and extreme, nationally, as are standard categorizations of these other mechanisms of extreme weather. Thus the R-Cat description of the nation’s most extreme precipitation episodes could be an exceptionally useful communications and research tool, and in the present analysis provided a clear, objective perspective on the severity of AR storms in the western US. FOR FURTHER READING Dettinger, M.D., F. M. Ralph, T. Das, P.J.

Neiman, and D. Cayan, 2011: Atmospheric rivers, floods, and the water resources of California: Water, 3, 455-478.

-----, 2011: Climate change, atmospheric rivers and floods in California—A multimodel analysis of storm frequency and magnitude

��

� 10

changes: J. Amer. Water Resour. Assoc., 47, 514-523.

Guan, B., N. P. Molotch, D. E. Waliser, E. J. Fetzer, and P. J. Neiman, 2010: Extreme snowfall events linked to atmospheric rivers and surface air temperature via satellite measurements. Geophys. Res. Lett., 37, L20401, doi:10.1029/2010GL044696.

Milly, P.C.D., J. Betancourt, M. Falkenmark, R.M. Hirsch, Z.W Kundzewicz, D.P. Lettenmaier, and R.J. Stouffer, 2008: Stationarity is dead: Whither Water Management?, Science, 139, 573-574.

National Weather Service (NWS), (1989), National Weather Service Observing Handbook Number 2. Cooperative Station Observations: Observing Systems Branch, Office of Systems Operations, 94 pp.

Neiman, P. J., F. M. Ralph, G. A. Wick, J. D. Lundquist and M. D. Dettinger, 2008: Meteorological characteristics and overland precipitation impacts of atmospheric rivers affecting the West Coast of North America based on eight years of SSM/I satellite observations. J. Hydrometeor., 9, 22-47.

-----, A.B. White, F.M. Ralph, D.J. Gottas, and S.I. Gutman, 2009: A Water Vapor Flux Tool for Precipitation Forecasting. U.K. Journal of Water Management, 162, 83-94.

-----, L. J. Schick, F. M. Ralph, M. Hughes, G. A. Wick, 2011: Flooding in Western Washington: The Connection to Atmospheric Rivers. J. Hydrometeor. (In Press), doi: 10.1175/2011JHM1358.1.

Ralph, F.M., P.J. Neiman, and G.A. Wick, 2004: Satellite and CALJET aircraft observations of atmospheric rivers over the eastern North-Pacific Ocean during the El Niño winter of 1997/98. Mon. Wea. Rev., 132, 1721-1745.

-----, -----, and R. Rotunno, 2005: Dropsonde observations in low-level jets over the Northeastern Pacific Ocean from CALJET-1998 and PACJET-2001: Mean vertical-

profile and atmospheric-river characteristics. Mon. Wea. Rev., 133, 889-910.

-----, ----- G. A. Wick, S. I. Gutman, M. D. Dettinger, D. R. Cayan, and A. B. White, 2006: Flooding on California’s Russian River: Role of atmospheric rivers. Geophys. Res. Lett., 33, L13801, doi:10.1029/2006GL026689.

-----, E. Sukovich, D. Reynolds, M. Dettinger, S. Weagle, W. Clark, P.J. Neiman, 2010: Assessment of extreme quantitative precipitation forecasts and development of regional extreme event thresholds using data from HMT-2006 and COOP observers. J. Hydrometeor., 11, 1288-1306.

-----, and M.D. Dettinger, 2011: Storms, Floods and the Science of Atmospheric Rivers. EOS, Transactions, Amer. Geophys. Union., 92, 265-266.

Stohl, A., C. Forster, and H. Sodemann, 2008: Remote sources of water vapor forming precipitation on the Norwegian west coast at 60º N - A tale of hurricanes and an atmospheric river. J. Geophys. Res.113, D05102, doi:10.1029/2007JD009006.

White, A. B., B. Colman, G. M. Carter, F. M. Ralph, R. S. Webb, D. G. Brandon, C. W. King, P. J. Neiman, D. J. Gottas, I. Jankov, K. F. Brill, Y. Zhu, K. Cook, H. E. Buehner, H. Opitz, D. W. Reynolds, and L. J. Schick, 2011: NOAA's Rapid Response to the Howard A. Hanson Dam Flood Risk Management Crisis. Bull. Amer. Meteorol. Soc. (In Press), doi: 10.1175/BAMS-D-11-00103.1.

Wick, G. A., Y. Kuo, F. M. Ralph, T. Wee, and P. J. Neiman, 2008: Intercomparison of integrated water vapor retrievals from SSM/I and COSMIC, Geophys. Res. Lett., 35, L21805, doi:10.1029/2008GL035126.

Zhu, Y, and R. E. Newell, 1998: A proposed algorithm for moisture fluxes from atmospheric rivers. Mon. Wea. Rev., 126, 725-735.

��

� 11

Appendix C: Storms, Floods and the Science of Atmospheric Rivers

Published as the Cover Story in EOS, a weekly, peer reviewed journal of the American Geophysical Union. August 2011. (Ralph, F.M., and M.D. Dettinger, 2011: Storms, Floods and the Science of Atmospheric Rivers. EOS, Transactions, Amer. Geophys. Union., 92, 265-266.)

��

� 12

��

� 13

��

� 14

��

� 15

Appendix D: NOAA’s Rapid Response to the Howard A. Hanson Dam Flood Risk Management Crisis

ALLEN B. WHITE1, BRAD COLMAN2, GARY M. CARTER3, F. MARTIN RALPH1,

ROBERT S. WEBB1, DAVID G. BRANDON4, CLARK W. KING1, PAUL J. NEIMAN1, DANIEL J. GOTTAS1, ISIDORA JANKOV5, KEITH F. BRILL6, YUEJIAN ZHU7, KIRBY COOK2, HENRY E.

BUEHNER2, HAROLD OPITZ8, DAVID W. REYNOLDS9, and LAWRENCE J. SCHICK10

1NOAA/Earth System Research Laboratory/Physical Sciences Division, Boulder, CO

2NOAA/National Weather Service/WFO Seattle, Seattle, WA 3NOAA/National Weather Service/Office of Hydrologic Development, Silver Spring, MD

4NOAA/National Weather Service/Western Region Hydrology and Climate Services, Salt Lake City, UT

5Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, and NOAA/Earth System Research Laboratory/Global Systems Division,

Boulder, CO 6NOAA/National Weather Service/Hydrometeorological Prediction Center, Suitland, MD

7NOAA/NWS/National Centers for Environmental Prediction/Environmental Modeling Center, Camp Springs, MD

8NOAA/National Weather Service/Pacific Northwest RFC, Portland, OR 9NOAA/National Weather Service/WFO San Francisco Bay Area, Monterey, CA

10U.S. Army Corps of Engineers, Seattle, WA

In Press at Bulletin of the American Meteorological Society (July 2011)

Capsule Summary: NOAA Operations and Research join forces to implement recent scientific and technical advances to better predict a possible flood in western Washington and help calm public fears regarding reduced flood protection from Howard A. Hanson Dam.

ABSTRACT The Howard A. Hanson Dam (HHD) has brought flood protection to Washington’s Green River Valley for more than 40 years and opened the way for increased valley development near Seattle. However, following a record high level of water behind the dam in January 2009 and the discovery of elevated seepage through the dam’s abutment, the U.S. Army Corps of Engineers declared the dam “unsafe.” NOAA’s Office of Oceanic and Atmospheric Research (OAR) and National Weather Service (NWS) worked together to respond rapidly to this crisis for the 2009/10 winter season, drawing from innovations developed in NWS offices and in NOAA’s Hydrometeorology Testbed (HMT).

��

� 16

New data telemetry was added to 14 existing surface raingages allowing the gauge data to be ingested into the NWS rainfall database. The NWS Seattle Weather Forecast Office produced customized daily forecasts, including longer lead-time hydrologic outlooks and new decision support services tailored for emergency managers and the public – new capabilities enabled by specialized products from NOAA’s National Centers for Environmental Prediction (NCEP) and from HMT. The NOAA Physical Sciences Division (PSD) deployed a group of specialized instruments on the Washington Coast and near the HHD that constituted two atmospheric river observatories (AROs) and conducted special HMT numerical model forecast runs. Atmospheric rivers (ARs) are narrow corridors of enhanced water vapor transport in extratropical oceanic storms that can produce heavy orographic precipitation and anomalously high snow levels, and thus can trigger flooding. The AROs gave forecasters detailed vertical profile observations of AR conditions aloft, including monitoring of real-time water vapor transport and comparison with model runs.

Fig. D1. Base map indicating the locations of the newly telemetered raingages provided by the NWS (open black diamonds), the atmospheric river observatory equipment deployed by PSD (three bull’s eyes), and a few additional observing system assets in the region (see key). The wedge depicting the prime range of low-level wind directions in ARs for Green River flooding is based on a recent study by Neiman et al. (2011).

��

� 17

Appendix E: HMT-West Legacy Network supporting California Department of Water Resources’ Enhanced Flood Response and Emergency Preparedness

Effort within the Flood Safe Program

Allen B. White1, F. M. Ralph1, Mike Dettinger2, Dan Cayan2, Mike Anderson3, Art Hinojosa3

1NOAA/Earth System Research Laboratory/Physical Sciences Division, Boulder, CO 2USGS/Scripps Institution of Oceanography, La Jolla, CA

3California Department of Water resources, Sacramento, CA

A partnership between California’s DWR, NOAA HMT and USGS/Scripps Institution of Oceanography has been established to implement a 21st Century Observing System for California. It includes over 90 field sites, 43 of which are for soil moisture (and rainfall), 36 for water vapor aloft (using GPS-Met technology), 10 for newly designed snow-level-radars, and 4 atmospheric river observatories. Tools are being developed to combine these observations with high-resolution modeling techniques into decision support tools for use in monitoring and predicting extreme precipitation and flooding. The network is optimized for monitoring atmospheric river conditions as storms strike the coast and move inland. It complements existing observations, including NEXRAD and satellite systems. Implementation is over 5 years, and is supported primarily through $10.5 M of Bond funding from California DWR. Expertise from NOAA, USGS, DWR, and Scripps is being used to develop and deploy the systems. A brochure from CA DWR is available online at http://www.esrl.noaa.gov/psd/atmrivers/projects/pdf/Advanced%20Monitoring%20Network%20FloodER%20Prgrm.pdf.

Fig. E1. Basemap showing new observations being deployed as part of the HMT-West Legacy/EFREP project between 2009-2013.

��

� 18

Appendix F: Scanning Radar Requirements and Alternatives for QPE in the Western U.S.

Rob Cifelli1, V. Chandrasekar2, Marty Ralph1

1NOAA/Earth System Research Laboratory, Boulder, Colorado 2Colorado State University, Fort Collins, Colorado

Providing accurate quantitative precipitation estimation (QPE) in the western U.S. is difficult due to the combined challenges of low density of observations, sharp, topographically-forced precipitation gradients, complex microphysical processes resulting from the interaction of precipitation producing processes with orography, and limitations in the existing operational NEXRAD radar network design (including areal coverage – see Fig. X). Moreover, the operational NEXRAD network radars are not able to scan below 0.5q elevation angle. The result is that, due to earth’s curvature and the increasing size of the radar beam with range, the useful range of NEXRAD for QPE is limited to < 150 km (see Fig. Y).

Figure F1. NEXRAD coverage at (a) 3 km AGL and (b) 1 km AGL using 0.5 deg beam elevation angle (from McLaughlin et al. 2009)

��

� 19

Figure F2. Schematic diagram showing the Seattle NEXRAD (KATX) radar beam view in the Green River Basin (south east of Seattle, WA).

Given regional and localized variability in terrain and precipitation processes, it is likely that there is no “one size fits all” solution for monitoring extreme precipitation and QPE in complex terrain. What is needed is an adaptive strategy to optimize the coverage (through a combination of gauges and radar) for a given location.

The strategy for HMT’s QPE activities is called AdaPtive Precipitation Estimation Network Design (APPEND). The APPEND approach is to evaluate the QPE systems in different topographic/regional settings so that improved understanding of advantages, disadvantages and uncertainty of the various sensor networks, data assimilation and modeling tools incorporated into the current QPE systems can be obtained. The APPEND approach will include a design platform for developing next generation QPE systems that builds upon the best aspects of the current systems and take advantage of future sensor technologies and data processing algorithms.

Although much remains to be determined regarding optimal mix of observations, Fig. Z summarizes characteristics and costs of 4 types of radar that could be considered. Based on the points made above regarding QPE, and on the costs of the largest radar type, the strawman network in this white paper focuses on C-band and X-band radar systems, both of which have been tested in the complex terrain of the western U.S. in HMT. An additional radar system, called CASA (Collaborative Adaptive Scanning of the Atmosphere - a sophisticated networking approach to scanning with X-band radars), could be an option in the future, although its design has primarily targeted severe weather (i.e., tornadoes, and severe thunderstorm detection in the Great Plains) that is less prevalent in much of the mountainous west. CASA has demonstrated very promising QPE results in the Oklahoma region and is therefore listed in the table below; however, its potential for QPE in mountainous terrain remains untested.

��

� 20

Fig. F3. Comparison of four types of scanning radar systems, including three that have been tested in HMT-West. Based on the complex terrain of the west, the importance of low altitude conditions, and costs, this white paper focuses on C-band and X-band type radars, both including polarimetric capability.

�

�

��

� 21

Appendix G: Categories for Comparison and Communication of Extreme-Precipitation Storm Totals across the US: Potential Application to NWS

Hydrologic Operations

David Reynolds (NWS Monterey), F. Martin Ralph (NOAA/ESRL/PSD),

and Michael Dettinger (US Geological Survey)

The magnitude and frequency of occurrence of extreme precipitation events1 are documented geographically and seasonally across the contiguous U.S using a simple categorization scheme [1] with potential for use in technical and public arenas (Fig. 1).

Fig. G1. Three-day accumulations of precipitation (P) from 59 years of Cooperative Observer (COOP) precipitation measurements [2] at 5877 sites were used to construct the categorization scheme for extreme precipitation used in the figures and table, according to:

������������������������������������������������������������1��Extreme�rainfall�in�this�context�refers�to�large�areaͲwide�rainfall�events,�most�often�associated�with�landͲfalling�tropical�cyclones�or�extratropical�winter�cyclones,�with�the�potential�to�cause�mainͲstem�river�flooding�as�opposed�to�smaller�scale�convectively�driven�events�associated�with�flash�floods�or�urban�flooding.��The�categories�here�are�determined�by�maximum�3Ͳday�point�rainfall.�

��

� 22

x Rainfall Category 1 (R-CAT 1) storms totaling 200<P<300 mm (~8-12 in) x Rainfall Category 2 (R-CAT 2) storms totaling 300<P<400 mm (~12-16 in) x Rainfall Category 3 (R-CAT 3) storms totaling 400<P<500 mm (~16-20 in) x Rainfall Category 4 (R-CAT 4) storms totaling P>500 mm (~>20 in)

Storms in these categories are of similar magnitude and frequency east and west of 105ºW, where a natural dividing line between western extreme precipitation events (predominately cool season events associated with land-falling atmospheric rivers [3, 4]) and eastern events (predominately warm season and mostly associated with land-falling tropical cyclones) was identified. This is shown in the insert to Fig. 1, and in Fig. 2.

Fig. G2 Illustration of the comparability of frequency of occurrence of extreme precipitation west of 105ºW from Nov-Apr relative to east of 105ºW from May-Oct.

To put the extremity and frequency of these new storm categories into perspective, consider that the combined frequency of Category 2, 3 and 4 extreme precipitation episodes, averaging 12/yr, is nearly the same as the number of hurricanes in the Atlantic and Eastern Pacific ocean basins, 15/yr, and as the number of violent tornadoes (F4-F5) annually, 10-20/yr. The more extreme storms, Category 3 and 4 storms occur 3 times per year whereas “major” hurricanes (Saffir-Simpson CAT 3, 4 or 5) occur 6 times per year somewhere in the Atlantic Basin [5], and F5 tornadoes occur 1-2 times per year [6]. Thus the extreme-precipitation scaling system above plays much the same role in 1) focusing and standardizing research analyses and forecasted rainfall intensities, 2) in evaluating climate change projections of extreme precipitation, and 3) in communicating storm risks to non-specialists, as do the Saffir-Simpson

��

� 23

scale of hurricane intensities and modified Fujita scale for tornadoes (both based primarily on wind speeds rather than precipitation). The lack of a similarly recognized and simple categorization scale for extreme-precipitation events has made communicating and comparing storm magnitudes complicated. This scaling helps address gaps in current quantitative precipitation information identified in scientific, forecast and forecast-user community planning efforts in the past [7], and is an outcome of NOAA’s Hydrometeorology Testbed [7; hmt.noaa.gov].

The rainfall categorization above differs from many earlier studies that describe rainfall in terms of “return periods”. While return periods are useful in many applications and naturally scale for each locality, they are difficult to compare inter-regionally and are confusing to the public. Return periods also have significant uncertainty when return periods exceed historical record lengths and, under 21st Century conditions, when they are likely to be nonstationary [8] and thus very difficult to estimate from real-world precipitation series.

The fact that the most extreme precipitation events in one region of the country are not as extreme as in others could be considered a disadvantage. However, NWS makes extensive use of categorizations that are invaluable for those regions of the country impacted by these phenomena, e.g., hurricanes, blizzards, and in some respects, tornadoes as well (Fig. 3), yet are rarely, if ever, used in other major parts of the country.

��

� 24

Fig G3. Schematic illustration of the inherently regional nature of several major meteorological hazards across the U.S. The domains are not intended to be exact, but generally highlight areas most often affected by these hazards.

For operational purposes, a “site event” can be defined as an occasion when a given cooperative station reports a precipitation total within the range of one of the new extreme-precipitation categories. In contrast, an “episode” or “Rainfall Category-n storm” (i.e., R-CAT-1, 2, 3 or 4) can be defined as a period during which at least one station reports precipitation within one of these ranges, and the episode or storm is then labeled in terms of the largest 3-day precipitation total reported. A single episode thus can (and usually does) include multiple site events. To avoid double counting, for wet spells longer than 3 days, only one 3-day site event is cataloged (in the figures above), with that event being identified by the 3-day window with the largest precipitation total. Missing data were excluded, as were accumulations from multiple days reported only as a multi-day total. While daily totals are a common measure of precipitation, multiple-day precipitation totals can be more useful with respect to progressive hazards, like floods and some landslides. Three-day periods are used in the present categorization because, although 2- and 4-day windows were also considered, roughly 1/2 of the major storms (by 3-day standards) were missed when 2-day totals were used instead and, when using 4-day periods, one of the four days typically contributed little to the multiple-day totals (e.g., on average, nationally, the driest day of 4-day events

��

�

“Tornado

Tropical Storms

� Blizzard

Approximate Regional Distribution of Major Meteorological Hazards in the U.S.

��

� 25

contributed only 4% of the 4-day totals). These same definitions and standards can be applied, as needed, to gridded QPEs and model outputs.

Fig. 4 provides an example of the application of the R-Cat methodology to the USGS ARkStorm [9]. This multiday event consisting of two major precipitation episodes, one striking southern California and the second impacting northern California about a week later, is a realistic characterization of a very rare but highly probable event similar but not as intense as the 1861-62 California mega-flood.

Fig. G4 R-Cat levels for the USGS ARkStorm flood scenario.

1. Ralph, F.M., and M.D. Dettinger, submitted, How extreme is precipitation in atmospheric rivers?: Science, 4 p.

2. National Weather Service (NWS), 1989, National Weather Service Observing Handbook Number 2—Cooperative Station Observations: Observing Systems Branch, Office of Systems Operations, 94 pp.

3. Zhu, Y., and R.E. Newell, 1998, A proposed algorithm for moisture fluxes from atmospheric rivers: Mon. Wea. Rev. 126, 725-735.

4. Neiman, P.J., F.M. Ralph, G.A. Wick, J. Lundquist, and M.D. Dettinger, 2008, Meteorological characteristics and overland precipitation impacts of atmospheric rivers affecting the West Coast of North America based on eight years of SSM/I satellite observations: J. Hydrometeor. 9, 22-47.

5. Jarvinen,�B.R.,�C.J.�Neumann,�and�M.A.S.�Davis,�1988,�A�tropical�cyclone�data�tape�for�the�North�Atlantic�basin,�1886Ͳ1983ͲͲContents,�limitations,� and� uses:� NOAA� Technical�Memorandum�NWSͲNHC�22,�21�p.,�http://www.nhc.noaa.gov/pdf/NWSͲNHCͲ1988Ͳ22.pdf.�

6. Schaefer,�J.T.�and�R.�Edwards,�1999.�The�SPC�tornado/severe�thunderstorm�database.�Preprints,�11th�Conference�of�Applied�Climatology,�Amer.�Meteor.�Soc.,�215Ͳ220.�

��

� 26

7. Ralph, F. M., R. M. Rauber, B. F. Jewett, D. E. Kingsmill, P. Pisano, P. Pugner, R. M. Rassmussen, D. W. Reynolds, T. W. Schlatter, R. E. Stewart and J. S. Waldstreicher, 2005: Improving short-term (0-48 hour) Cool-season quantitative precipitation forecasting: Recommendations from a USWRP Workshop. Bull. Amer. Meteor. Soc., 86, 1619-1632.

8. Milly,� P.C.D.,� J.� Betancourt,� M.� Falkenmark,� R.M.� Hirsch,� Z.W� Kundzewicz,� D.P.�Lettenmaier,�and�R.J.�Stouffer,�2008,�Stationarity�is�dead:�Whither�Water�Management?:�Science,�139,�573Ͳ574.�

9. Porter�et�al,� �2011:�An�overͲview�of�the�ArKStorm�scenario.� �To�be�released� in�January,�2011.��USGS�MultiͲhazards�Demonstration�Project.���

�� �

��

� 27

�

��

� 28

��

� 29

Appendix I: Global Positioning System-Meteorology networks (GPS-Met) – leveraging solid earth monitoring for hydrometeorology applications

Seth Gutman1

1NOAA/Earth System Research Laboratory, Glbal Systems Division, Boulder, Colorado Dual-use Observations from GPS networks The West Coast of North America is one of the most seismically active areas on Earth. To mitigate the impact of these inevitable and occasionally catastrophic events, several U.S. Government Agencies (notably the National Science Foundation, U.S. Geological Survey and NASA) in collaboration with public and private academic institutions in California and other states, have deployed an extensive network of geophysical monitoring systems and sensors in critical areas along the North American Plate Boundary. The purpose of this network is to improve our understanding of the tectonics of the region, characterize areas susceptible to movements in response to geological forces, and identify regions along the plate boundary where strain is accumulating and fault motions are most likely to occur. One of the most widely deployed instruments is the satellite Global Positioning System receiver, deployed in extensive networks throughout the region. These unattended instruments continuously record the radio signals broadcast by the GPS satellites in Earth orbit, and the information is transmitted to data processing centers where it is used to monitor the positions of the GPS antennas in near real-time with extraordinary (millimeter) accuracy. Figure I1 (courtesy of the California Real-Time Network headquartered at Scripps Institution of Oceanography http://sopac.ucsd.edu/projects/realtime/) shows the locations of many of the continuously operating GPS reference stations in California. Red and blue symbols denote the locations providing data to CRTN in real-time; light blue and pink symbols identify the locations of planned real-time systems. Similar, though less dense, networks also exist across many of the Western States for solid earth monitoring (Fig. I2). One source of error in monitoring the positions of these systems comes from changes in the atmosphere associated with weather events. The scientists and engineers who developed the techniques used to monitor site positions with this level of precision also recognized the impact of the atmosphere on GPS measurement accuracy and they developed clever ways to reduce atmospherically-induced errors by treating the atmosphere as a nuisance parameter and removing its effects. At about the same time this was happening, atmospheric scientists in Boulder, CO were looking for improved (i.e. more accurate, cost effective and all-weather) ways to monitor water vapor in the atmosphere. Why did they want to do this? Water vapor is the source or raw materials of clouds and precipitation, and an ingredient in most major weather events. The problem is that water vapor at that time was very difficult to observe because it varies rapidly on the scale of clouds. So to monitor water vapor effectively, they needed lots of closely spaced measurements made rapidly. The most operational common ways to observe water vapor at that time were to use weather balloons and/or the information provided by Earth orbiting environmental satellites. The problems with these methods were that weather balloons were (are are) expensive and launching them is labor intensive so they are only launched twice daily at sites spaced about 400 km (250 mi) apart. Satellites are incredibly expensive, the moisture

��

� 30

observations over land are not reliable in the presence of clouds, and satellite techniques to monitor water vapor under all weather conditions are effective only over the open oceans. When it was realized that the errors in position caused by weather were extremely useful to meteorologists, new applications rapidly emerged. Dual use of GPS observations for simultaneously monitoring the solid Earth and the Earth’s atmosphere is not only cost effective, it’s almost free. GPS techniques are now used routinely by NOAA for weather forecasting and climate monitoring. One of the most dramatic and successful applications of GPS technology in weather forecasting is the use of CRTN GPS data to monitor land-falling atmospheric rivers and make improvements in heavy precipitation and flash flood predictions for the people of California, as is being done with the implementation of the HMT-West Legacy network through the California DWR-sponsored EFREP project (Appendix E). In key ways it is the best inland version of the very useful SSM/I satellite data offshore (SSM/I cannot derive water vapor content over land due to technical constraints on the remote sensing method it uses). �

�Fig I1. Locations of continuously operating GPS receivers in CA. Red and blue symbols are sites currently delivering real-time data to the California Real-Time Network (CRTN) for use in earthquake monitoring and other applications. Light blue and pink symbols are other potential sites for the network.

��

� 31

Fig. I2. Network of GPS Solid Earth monitoring stations around the Western U.S. that could potentially be modified t include real-time communications and surface meteorology sensors and could thus provide continuous monitoring of vertically integrated water vapor (IWV) that is a key factor in extreme events.

��

� 32

Appendix J: Soil moisture observing network design and instrumentation

R. J. Zamora1, F. M. Ralph1, E. Clark2, and T. Schneider2

1NOAA/Earth System Research Laboratory/Physical Sciences Division, Boulder, CO 2NOAA/National Weather Service

The National Oceanic and Atmospheric Administration (NOAA) Hydrometeorology Testbed (HMT) program has deployed soil moisture observing networks in the watersheds of the Russian River and North Fork (NF) of the American River in Northern California, and the San Pedro River in southeastern Arizona. These networks were designed to serve the combined needs of the hydrological, meteorological, agricultural, and climatological communities for observations of soil moisture on time scales that range from minutes to decades.

The networks are a major component of the HMT program that has been developed to accelerate the development and infusion of new observing technologies, modeling methods and recent scientific research into the National Weather Service (NWS) offices and to help focus research and development efforts on key hydrological and meteorological forecast problems. These forecast problems are not only of interest to the NWS, but they also play a crucial role in providing input to water managers who work at the national, state, and local government levels to provide water for human consumption, agricultural, and other needs.

The HMT soil moisture networks have been specifically designed to capture the changes in soil moisture that are associated with heavy precipitation events and runoff from snowpack during the melt season. This paper describes the strategies used to site the networks and sensors as well as the selection, testing, and calibration of the soil moisture probes. Figure J1 illustrates the design of a soil moisture monitoring site.

In addition two illustrative examples of the data gathered by the networks are shown. The first example (Fig. J2) shows changes in soil moisture observed before and during a flood event on the Babocamari River tributary of the San Pedro River near Sierra Vista, AZ, on 23 July 2008. The second example (Fig. J3) examines a 5-year continuous time series of soil moisture gathered at Healdsburg, CA. The time series illustrates the transition from a multiyear wet period to exceptionally dry conditions (drought) from a soil moisture perspective.

Zamora, R. J., F. M. Ralph, E. Clark and T. S. Schneider, 2011: The NOAA Hydrometeorology Testbed soil moisture observing networks: Design, instrumentation and preliminary results. J. Atmos. Oceanic Technol., 28, 1129-1140.

��

� 33

Fig. J1. Schematic diagram showing the orientation of the soil probes and surface meteorological observations used at a typical soil moisture observing station.

Fig. J2. Evolution of the cumulative precipitation, and soil wetness fractions measured at 10, 20, and 50 cm depth for the period 18-26 July 2008 at Whetstone, AZ that included a flash flood.

��

� 34

�

Fig. J3. Observations from coastal California. Five year soil wetness fraction climatology (black), daily total precipitation (red) and atmospheric rive events (blue). Dashed line indicates a soil wetness fraction of 0.25. Palmer Drought Indices are shown in bold type.

��

� 35

Appendix K: An Approach to Enhancement of the Western SNOTEL and Streamgage Networks for Snowmelt, Rain-on-Snow and other Flood

Mechanisms

Mike Dettinger (USGS, Scripps Inst. Oceanography, La Jolla, California)

The snow fields of the mountains of the western US are important contributors to high flows and flooding in the region, either during especially rapid and voluminous snowmelt seasons (e.g., 2011) or when they melt rapidly or facilitate rapid rainfall runoff during warm storms. McCabe et al. (2007) recently found a wide range of trending rain-on-snow frequencies around the western US. Lower altitudes areas have tended to have fewer such episodes in recent decades, as snowlines have retreated upward with regional warming so that low snowfields have been less available to be rained on; higher altitudes have tended to experience more rain-on-snow episodes as warming has brought rainfall to snowfields at ever higher altitudes. Marks et al (2001) have shown that, during some well monitored and simulated rain-on-snow events in Idaho, the delivery of heat into snowpacks by the rain itself was a small contribution compared to the heat deposited on snow by rapid condensation of vapor onto the surface. The heat released by this condensation was the primary cause of melting. Even when melting snow is a minor contribution (as often happens at middle and higher altitiudes), rain falling onto snowy surfaces can run off quite efficiently and rapidly so that the rain itself can yield significant flooding. In warm storms, very large parts of river basins that normally would receive snowfall and generate little immediate runoff can instead receive rainfall so that the areas contributing rapid runoff to downstream flows and flooding are greatly enhanced (Detinger et al. 2009). For example, White et al. (2002) showed that for each of four watersheds studied in California, there existed an altitude range for which a 2000 ft rise in the snow level of a storm would triple the runoff.

Thus a vision of observations for extreme storms and flooding in the West necessarily includes consideration of the region’s snowfields (Bales et al., 2006) and, in particular for the purposes of this plan for extreme storms and flooding, a focus on surficial and meteorological observations of those snowfields. At present, high-altitude precipitation, snow-water contents, snow depths, and air temperatures are continually monitored at almost 1000 SNOTEL (or equivalent) sites in the western US, by the USDA Natural Resources Conservation Service and by the California Cooperative Snow Surveys. These observations are used to track the seasonal storage and release of water for water-supply forecasts and management purposes across the region.

As these sites are already established and operated, for the purposes of the present vision for storm and flood monitoring in the region, several enhancements at selected SNOTEL sites are proposed. Thus, at about 20 SNOTEL sites in each of the ovals in Fig. K1, enhanced observational regimes would be instituted to track more closely the fate of the snow waters in the soil and on the landscape and to monitor several conditions of flood generation associated with warm storms.

��

� 36

Fig. K1. Locations of existing SNOTEL (or equivalent) stations in the West, with subregions within which enhancements might be undertaken indicated by red ovals.

Immediate enhancements to monitoring of the fate of snowmelt in the soil could be achieved by addition of soil-moisture and temperature monitors at several depths below the ground surface at the selected SNOTEL sites. With new interests in monitoring and forecasting floods from rapid snowmelt and rainfall runoff in the mountain catchments of the West, especially as new areas are exposed to rainfall and snowmelt accelerations in response to warming trends, the region’s streamflow networks need to be preserved and, if possible, enhanced along with the SNOTEL network (e.g., Kenney et al. 2011). Enhanced monitoring of the fate of snowmelt (and flooding) across the western landscape could be accomplished by some combination of insuring the funding sources for selected existing streamgages (thus ensuring their permanent operation), by restarting some long-term gages (where appropriate) that have been discontinued in recent years, and by establishing new gages, particularly in increasingly important high-altitude locations.

Next, with snowmelt- and warm-storm contributions from the snowfields to flooding in the region in mind, a new regime of monitoring of conditions at the surface of the snowpack could also be added to the selected SNOTEL sites. These snow-surface observations would include

��

� 37

monitoring of wet-bulb temperatures to complement the existing dry-air temperature measurements. Wet-bulb temperatures is a measure of humidity and availability/readiness of vapor for condensation, and would reflect the conditions under which large amounts of water vapor are available and likely to condense onto and into snowpacks, which—as noted previously—can result in rapid melting of snow. The mass of vapor that condenses under such conditions also depends on how much moist air is passing over the snow surface, so that winds would also be monitored. Under other conditions (when condensation is notw the immediate cause of snowmelt), the amount of solar radiation absorbed by the snowpack is critical, and thus these sites would also be enhanced to include continual measurements of solar insolation and surface albedo.

The measurements proposed thus far draw on well-established technologies and methods, and would leverage the existing power and communications at SNOTEL sites. For the future, an important direction for new developments in monitoring of snowpacks of the West might focus more on conditions in the interior of the snowpacks (i.e., between the ground surface and the top of the accumulated snow). There is an increasing understanding that dust and soot that falls on snow and that gets incorporated into snowpacks can greatly affect snowmelt timing and runoff amounts (Painter et al. 2011) and that aerosols in the atmosphere can influence the forms and amounts of precipitation, including snowfall, in the first place (Ault et al. 2011). Furthermore it is well established that structures like ice layers inside of snowpacks influence rates, locations, and amounts of snowmelt and release of melt waters into streams (Pfeffer and Humphrey, 1996). It would be useful to know more about what is happening in the interior of snowpacks to improve our understanding and predictions of the consequences of extreme storms and fair-weather melt conditions.

Thus we also envision a future phase of monitoring enhancements at the selected SNOTEL sites to add measurements of aerosols in the near-surface atmosphere or falling onto the snow surfaces and regular (albeit probably only once-per-year once the bulk of the year’s snowpack has been formed) sampling of snow for measurements of dust, black-carbon, and aerosol contents. The strategies and some of the technologies to make these measurements in long-term operational modes have not yet been developed and so implementation will be preceded by some research and development. Monitoring of physical conditions within snowpacks are also somewhat speculative, but could include continual measurements of snow temperatures and densities at various heights above the soil surface in the snowpack and might (with more development) include monitoring of liquid-water contents at the same heights.

Ault A.P., Williams C.R., White A.B., Neiman P.J., Creamean J.C., Gaston C.J., Ralph F.M., Prather K.A., 2011, Detection of Asian dust in California orographic precipitation: Journal of Geophysical Research - Atmospheres.

��

� 38

Bales, R., Molotch, N., Painter, T., Dettinger, M., Rice, R., and Dozier, J., 2006, Mountain hydrology of the western US: Water Resources Research, 42, W08432, doi:10.1029/2005WR004387, 13 p.

Dettinger, M.D., Hidalgo, H., Das, T., Cayan, D., and Knowles, N., 2009, Projections of potential flood regime changes in California: California Energy Commission Report CEC-500-2009-050-D, 68 p.

Kenney, T.A., Buto, S.G., and Susong, D.D., 2011, Analysis of watersheds monitored by the US Geological Survey streamflow-gaging station network in the Upper Colorado River basin: US Geological Survey Scientific Investigations Report 2011-5081, 102 p.

Marks, D.G., Link, T., Winstral, A.H., and Garen, D., 2001, Simulating snowmelt processes during rain-on-snow over a semi-arid mountain basin: Annals of Glaciology, 32, 195-202.

McCabe, G.J., Clark, M.P., and Hay, L.E., 2007, Rain-on-snow events in the western United States: Bull., American Meteorological Society, 88, 319-328.

Painter, T.H., Deems, J.S., Belnap, J., Hamlet, A.F., Landry, C.C., and Udall, B., 2011, Responses of wind erosion to climate-induced vegetation changes on the Colorado Plateau: Proc. Natl. Acad. Sci., 108, 3854-3859.

Pfeffer, W.T., and Humphrey, N.F., 1996, Determination of timing and location of water movement and ice-layer formation by temperature measurements in sub-freezing snow: Journal of Glaciology, 42, 292-304.

White, Allen B., Daniel J. Gottas, Eric T. Strem, F. Martin Ralph, Paul J. Neiman, 2002: An automated brightband height detection algorithm for use with Doppler radar spectral moments. J. Atmos. Oceanic Technol., 19, 687-697.

��

� 39

Appendix L: Dust-on-snow sampling

Jayne Belnap (USGS) and

Mike Dettinger (USGS, Scripps Inst. Oceanography, La Jolla, California)

Dust production is increased by drought, disturbance of the soil surface, the invasion of exotic annual grasses and fire. Droughts reduce soil moisture, reducing plant cover and thus soil surface protection. Disturbance reduces or removes components that naturally stabilize soils and soil-disturbing activities—energy exploration and development, grazing, and recreation—are increasing substantially in the western U.S. Surface disturbance enhances the invasion of exotic annual grasses. Their presence increases fires that, in turn, increase dust production. Also, in drought years, annual grasses do not germinate, leaving soils barren and vulnerable to erosion. Future increases in temperatures will slow the recovery of vegetation and soil from land use disturbance, further increasing the frequency and magnitude of dust storms.

Large dust storms have both local and regional effects on human and natural resources. Small particles can be lodged in the lungs, causing respiratory disease, and dust can carry organisms that cause diseases such as Valley Fever. Fatalities have resulted when visibility has been reduced on highways. Soil fertility is lost with the dust because nutrients are often attached to dust particles.

Much of the dust produced from low-elevation land is deposited on the snowpack of nearby mountains. The dark-colored dust absorbs heat, increasing the melt rate of the underlying snowpack. Earlier or more rapid melt may contribute to, or decrease, flood risks in the melt seasons. Early melting leaves soils exposed longer to solar radiation and gives plants a longer growing season, resulting in more water being lost to the atmosphere and thus less water entering streams and rivers. In addition, late season water supplies are reduced (Painter et al., 2010). Water quality is reduced when windblown material is deposited in ephemeral washes or when less quantity concentrates sediment, pollutants, and results for higher temperatures.

A reduction in water quantity and quality affects most aspects of resource management in the western U.S., as water is needed for wildlife, agriculture, energy production, household consumption, and recreation. Early snowmelt and reduced surface flow will produce additional challenges for those responsible for delivering this water, as climate changes and increasing human populations will increase the demand for water just as supplies are diminishing. Future energy production alternatives, including solar thermal energy, oil shale development, and nuclear power, also use large amounts of water; hence a decline in water availability may limit

��

� 40

their siting and production levels as well. There is a multi-billion dollar recreation and tourism industry in this region is also dependent upon current stream flows and lake levels.

In order to more effectively manage our water resources, we need a better understanding of 1) what factors affect dust production, including vegetation, soils, and the timing, type, and intensity of activities; 2) what areas consistently produce dust and what are the relative total dust contribution of low intensity diffuse sources (e.g., livestock grazing) versus acute point sources; 3) the major dust deposition zones and where are they relative to sources and 4) how does dust impact snow melt under different conditions? Answering these questions will require a monitoring network that continues through time, with dust outputs and inputs measured.

In the present vision, monitoring to better understand and track (from year to year) the role of dust in snowmelt across the region, snow samples will be collected late (approximately May) in the snowpack development season, but prior to the onset of major melting, and the samples will be analyzed for total dust contents. Sample sites will most likely be associated with either snow courses or SNOTEL installations, and snow from the same sites will be sampled each year. These dust determinations will provide a baseline complement to ongoing and developing research efforts to monitor the conditions that encourage dust production and the radiative effects of dust in snow by other groups.

Painter, T. H., J. S. Deems, J. Belnap Jayne, A.F. Hamlet, C. Landry and D. Udall, 2010: Response of Colorado River runoff to dust radiative forcing in snow. Proc. Nat. Academy Sciences U.S.A. Vol. 107, pp 17125-17130, DOI: 10.1073/pnas.0913139107

��

� 41

Appendix M: ARkStorm Emergency Preparedness Scenario

Mike Dettinger (USGS. Scripps Inst. Oceanography), F. M. Ralph (NOAA), M. Hughes (CIRES), T. Das (Scripps Inst. Oceanography), P. J. Neiman (NOAA), D. Cox (USGS), G. Estes (Extreme Precip Symposium), D. Reynolds (NOAA), R. Hartman (NOAA), D. Cayan (USGS.

Scripps Inst. Oceanography), and L. Jones (USGS)

The USGS Multihazards Project is working with numerous agencies to evaluate and plan for hazards and damages that could be caused by extreme winter storms impacting California. Atmospheric and hydrological aspects of a hypothetical storm scenario have been quantified as a basis for estimation of human, infrastructure, economic, and environmental impacts for emergency-preparedness and flood-planning exercises. In order to ensure scientific defensibility and necessary levels of detail in the scenario description, selected historical storm episodes were concatentated to describe a rapid arrival of several major storms over the state, yielding precipitation totals and runoff rates beyond those occurring during the individual historical storms. This concatenation allowed the scenario designers to avoid arbitrary scalings and is based on historical occasions from the 19th and 20th Centuries when storms have stalled over the state and when extreme storms have arrived in rapid succession. Dynamically consistent, hourly precipitation, temperatures, barometric pressures (for consideration of storm surges and coastal erosion), and winds over California were developed for the so-called ARkStorm scenario by downscaling the concatenated global records of the historical storm sequences onto 6-and 2-km grids using a regional weather model of January 1969 and February 1986 storm conditions. The weather model outputs were then used to force a hydrologic model to simulate ARkStorm runoff, to better understand resulting flooding risks. Methods used to build this scenario can be applied to other emergency, nonemergency and non-California applications.

Dettinger, M. D., F. M. Ralph, M. Hughes, T. Das, P. J. Neiman, D. Cox, G. Estes, D. Reynolds, R. Hartman, D. Cayan, and L. Jones, 2011: Design and quantification of an extreme winter storm scenario for emergency preparedness and planning exercises in California., Nat. Hazards, (in press July 2011).

Porter, Keith, Wein, Anne, Alpers, Charles, Baez, Allan, Barnard, Patrick, Carter, James, Corsi, Alessandra, Costner, James, Cox, Dale, Das, Tapash, Dettinger, Michael, Done, James, Eadie, Charles, Eymann, Marcia, Ferris, Justin, Gunturi, Prasad, Hughes, Mimi, Jarrett, Robert, Johnson, Laurie, Dam Le-Griffin, Hanh, Mitchell, David, Morman, Suzette, Neiman, Paul, Olsen, Anna, Perry, Suzanne, Plumlee, Geoffrey, Ralph, Martin, Reynolds, David, Rose, Adam, Schaefer, Kathleen, Serakos, Julie, Siembieda, William, Stock, Jonathon, Strong, David, Sue Wing, Ian, Tang, Alex, Thomas, Pete, Topping, Ken, and Wills, Chris; Jones, Lucile, Chief

��

� 42

Scientist, Cox, Dale, Project Manager, 2011: Overview of the ARkStorm scenario: U.S. Geological Survey Open-File Report 2010-1312, 183 p. and appendixes.

Fig. M1. Summary map of some extreme weather conditions resulting from the ARkStorm scenario associated with two stormy periods impacting the state over 23 days. The conditions are based on real storms from 1986 and 1969, but assuming they occurred back-to-back, and that the 1969 storm stalled for an additional day. Each storm included a strong atmospheric river.

��

� 43

Appendix N: Example of Utility of Gap-Fill Radar in a Colorado Flash Flood Event

Rob Cifelli1, S. Matrosov2

1NOAA/Earth System Research Laboratory, Boulder, Colorado 2Cooperative Institute for Research in Environmental Sciences, Colorado

In late summer 2010, a wildfire burned over 6,000 acres and 160 homes in the Fourmile Canyon area, immediately west of Boulder, Colorado (Fig. N1-top). As a result of the fire, much of the steep terrain within the canyon area became vulnerable to debris flows and flash flooding. The FourMile Canyon is area is ~80 km from the nearest NEXRAD radar (KFTG) and is not well monitored by the operational National Weather Service (NWS) radar network.

As a result of the fire and in response to concerns from the NWS regarding the increased disaster potential, NOAA/Physical Sciences Division (PSD) deployed a X-band polarimetric radar in Erie, CO during the summer of 2011 to supplement the NEXRAD coverage in the area and determine the added value of gap fill radar data in this region. On July 13th 2011, a series of slow moving storms produced heavy rain and hail over parts of FourMile Canyon, resulting in debris flows and flash flooding in FourMile Canyon (Fig. N1-bottom).

Figure N1. (top) Smoke plume from the FourMile Canyon fire in September 2010 (image courtesy of NASA). The locations of Boulder and Denver are indicated. (bottom) Flood waters in FourMile Canyon on July 14, 2011.

An example of the difference in radar coverage between the NOAA-PSD X-band and NEXRAD KFTG for the July 13, 2011 event is shown in Fig. N2. The X-band radar, located only 30 km from the FourMile Canyon region, provides higher resolution and is able to capture the spatial gradients in precipitation much better compared to the NEXRAD. Although the X-band system operates at a higher frequency and is more prone to signal loss in heavy rain than NEXRAD, the polarimetric phase information can be used to correct for the attenuation and allow for improved rainfall estimation compared to NEXRAD.

��

� 44

Table N1 lists the total rainfall accumulation from a rain gauge deployed by the National Center for Atmospheric Research in FourMile Canyon as well as the corresponding NEXRAD and NOAA X-band for an approximate one hour period on July 13. The NEXRAD total is biased high compared to the rain gauge due to the existence of hail mixed with rainfall. The NEXRAD radar cannot discriminate between the hail and rain and overestimates the actual rainfall total. In contrast, the X-band radar shows better agreement with the gauge due to the polarimetric phase information, which is relatively immune to hail and is able to isolate the rainfall contribution.

Figure N2. (top) NEXRAD radar reflectivity at 00:13 UTC on 14 July, 2011 (18:13 MDT 13 July, 2011). (bottom) Corresponding attenuation-corrected image from the NOAA-PSD X-band radar. The FourMile Canyon burn perimeter is indicated by the irregular boundary in each image. The location of the rain gauge in FourMile Canyon used for rainfall comparisons is indicated by the white circle in each image. The X-band radar data shown have not been quality controlled and should be considered preliminary.

��

� 45

The combination of high resolution and polarimetric information demonstrates the utility of gap fill radar for rainfall estimation in watersheds where NEXRAD coverage is poor.

Rain Gauge (inches) NOAA-PSD X-band radar (inches) NEXRAD radar (inches) 0.9 0.7 1.5

Table N1. Rainfall total for the period 23:45 (13 July) - 01:00 (14 July) UTC (17:45-19:00 MDT 13 July). Rainfall totals are based on preliminary data and are approximate.