current and future data requirements chandra kondragunta hydrometeorology group hydrology laboratory...

Current and Future Data RequirementsCurrent and Future Data Requirements

Chandra KondraguntaChandra Kondragunta

Hydrometeorology GroupHydrometeorology Group

Hydrology LaboratoryHydrology Laboratory

Office of Hydrologic DevelopmentOffice of Hydrologic Development

NOAA/National Weather ServiceNOAA/National Weather Service

Contributors: Contributors: Mike Smith, Victor Koren, David Kitzmiller, Mary Mike Smith, Victor Koren, David Kitzmiller, Mary Mullusky, John Bradley, Stephen Francis, and Tom GrazianoMullusky, John Bradley, Stephen Francis, and Tom Graziano

OutlineOutline

. Purpose. Purpose

. Requirement process. Requirement process

. Accomplishments – OHD. Accomplishments – OHD

. Precipitation. Precipitation

. Temperature. Temperature

. Soil moisture. Soil moisture

. Skin temperature. Skin temperature

. Potential Evapotranspiration. Potential Evapotranspiration

. Accomplishments – NWS. Accomplishments – NWS

. AOR, AFWS, NERON. AOR, AFWS, NERON

. Future Plans – NWS. Future Plans – NWS

. NERON, High resolution grids, Dual polarimetric radar. NERON, High resolution grids, Dual polarimetric radar

PurposePurpose

. To update on the hydrologic data requirements and . To update on the hydrologic data requirements and requirement processrequirement process

. Work accomplished to meet the requirements. Work accomplished to meet the requirements

. Work in progress to meet the requirements. Work in progress to meet the requirements

. Future plans to meet the requirements. Future plans to meet the requirements

Requirement processRequirement process

Two levels of observational requirements:Two levels of observational requirements:

. Threshold (T): The minimum requirement below . Threshold (T): The minimum requirement below which the utility of the system becomes which the utility of the system becomes questionablequestionable

. Objective (O): An optimal specification that, if met, . Objective (O): An optimal specification that, if met, would significantly enhance meeting the missionwould significantly enhance meeting the mission

Requirement process (Contd.)Requirement process (Contd.)

Priority categories associated with a user:Priority categories associated with a user:

“ “1” > Mission Critical : Cannot meet operational 1” > Mission Critical : Cannot meet operational mission objectives without this datamission objectives without this data

“ “2” > Mission Optimal : Data not critical but would 2” > Mission Optimal : Data not critical but would provide significant improvement to operational provide significant improvement to operational capabilitycapability

“ “3” > Mission Enhancing : Needed to enhance 3” > Mission Enhancing : Needed to enhance state of knowledge / assess potential for state of knowledge / assess potential for operational capabilityoperational capability

Requirement Process (Contd.)Requirement Process (Contd.)

Hydrology Program Requirements TeamHydrology Program Requirements Team

Larry Cedrone (Lead)Larry Cedrone (Lead)

Donna PageDonna Page

Pedro RestrepoPedro Restrepo

Chandra KondraguntaChandra Kondragunta

Tom CarrolTom Carrol

(Feedback from scientists in the Hydrology Laboratory)(Feedback from scientists in the Hydrology Laboratory)

Requirement Process (contd.)Requirement Process (contd.)

Data Attributes:Data Attributes:

1. Priority1. Priority

2. Geo-cover2. Geo-cover

3. Spatial Resolution - vertical resolution, range, units3. Spatial Resolution - vertical resolution, range, units

- horizontal resolution, range, units- horizontal resolution, range, units

4. Temporal Resolution - Sampling interval4. Temporal Resolution - Sampling interval

- data latency- data latency

5. Measurements – range, accuracy, precision, units5. Measurements – range, accuracy, precision, units

6. Long Term stability6. Long Term stability

7. Weight for each attribute7. Weight for each attribute

Sample of Requirements Table

Requirement Process (contd.)Requirement Process (contd.)

NOSA Website:NOSA Website:

http://www.nosa.noaa.gov/requirements/WW_Hydro.htmlhttp://www.nosa.noaa.gov/requirements/WW_Hydro.html

http://www.nosa.noaa.gov/requirements/WW_Hydro.xlshttp://www.nosa.noaa.gov/requirements/WW_Hydro.xls

Some Data Requirements Some Data Requirements

VariableVariable Hor. ResolutionHor. Resolution AccuracyAccuracy Sampling Sampling IntervalInterval

Precip. RatePrecip. Rate 1 km1 km 1mm/hr1mm/hr 6 min6 min

Air TemperatureAir Temperature 10 km10 km 1 deg k1 deg k 1hr1hr

Surf. Temp.Surf. Temp. 10 km10 km 1 deg k1 deg k 1 hr1 hr

Soil MoistureSoil Moisture 1 km1 km 5%5% 1 hr1 hr

Accomplishments - OHDAccomplishments - OHD

Precipitation:Precipitation:

. HADS: On Aug 1, 2003, HADS crossed the . HADS: On Aug 1, 2003, HADS crossed the 10,000 DCP milestone10,000 DCP milestone

. Between May 2005 and January 2006, HADS . Between May 2005 and January 2006, HADS added 1480 new DCPs to the system.added 1480 new DCPs to the system.

Accomplishments - OHD (Contd.)Accomplishments - OHD (Contd.)

Precipitation (Contd.):Precipitation (Contd.):

. . High-resolution multi-sensor precipitation analyses for High-resolution multi-sensor precipitation analyses for flash flooding.flash flooding.

Prototype running in HL, implementation supported by Prototype running in HL, implementation supported by AHPS – Targeted for OB8AHPS – Targeted for OB8

. Probabilistic model for radar rainfall estimate errors:. Probabilistic model for radar rainfall estimate errors:

Initial model developed in collaboration with U. Iowa.Initial model developed in collaboration with U. Iowa.

Prototype system for determining probability of rainfall Prototype system for determining probability of rainfall exceeding flash flood guidance is running in HL.exceeding flash flood guidance is running in HL.

Potential implementation in FFMP – supported by Potential implementation in FFMP – supported by AHPS.AHPS.


Precipitation (Contd.):Precipitation (Contd.):. . Ongoing evaluation of NSSL dual-polarization rainfall Ongoing evaluation of NSSL dual-polarization rainfall

estimation and hydrometeor classification algorithms. estimation and hydrometeor classification algorithms. Supported by NWS Radar Operations CenterSupported by NWS Radar Operations Center. Probabilistic 0-3 hour rainfall prediction:. Probabilistic 0-3 hour rainfall prediction: Operational advective-statistical system developed in Operational advective-statistical system developed in

MDL .MDL . Potential refinements to current operational system Potential refinements to current operational system

studied by Czech Institute for Atmospheric Physics and studied by Czech Institute for Atmospheric Physics and OHDOHD

. Multi-sensor nowcaster for 0-1 hour rainfall forecasts.. Multi-sensor nowcaster for 0-1 hour rainfall forecasts. Prototype running in HL. Implementation supported by Prototype running in HL. Implementation supported by

AHPS – Targeted for OB8AHPS – Targeted for OB8


Precipitation (Contd.):Precipitation (Contd.):

. . Range correction and convective/stratiform separation Range correction and convective/stratiform separation algorithms: Demonstration showing the positive algorithms: Demonstration showing the positive impact of range correction on hydrologic simulations of impact of range correction on hydrologic simulations of stream flow carried out in 2005.stream flow carried out in 2005.

Potential implementation in NEXRAD PPS and AWIPS.Potential implementation in NEXRAD PPS and AWIPS.

. MPE Reanalysis: Creation of MPE Reanalysis data in . MPE Reanalysis: Creation of MPE Reanalysis data in ABRFC for the period Oct 1996 – Sep 2003 for the ABRFC for the period Oct 1996 – Sep 2003 for the DMIP2 studies.DMIP2 studies.

. Collaboration with NCDC on the generation of MPE . Collaboration with NCDC on the generation of MPE reanalysis datareanalysis data


Precipitation (Contd.):Precipitation (Contd.):. Rain gauge QC tools: Spatial Consistency Check and . Rain gauge QC tools: Spatial Consistency Check and

Multi Sensor Check implemented in MPE.Multi Sensor Check implemented in MPE.

. Integration of P3 and DailyQC with MPE – in progress. Integration of P3 and DailyQC with MPE – in progress

. Development of a technique to objectively integrate . Development of a technique to objectively integrate Satellite Precipitation Estimates in MPE.Satellite Precipitation Estimates in MPE.

Implementation in progress – Targeted for OB8Implementation in progress – Targeted for OB8

. Collaboration with NSSL and NESDIS on Next . Collaboration with NSSL and NESDIS on Next Generation Multi-sensor QPEGeneration Multi-sensor QPE

. Participation in NASA – NOAA collaboration on future . Participation in NASA – NOAA collaboration on future satellite rainfall missions (GPM) satellite rainfall missions (GPM)


Temperature:Temperature:. March 2005: Implemented revised temporal interpolation . March 2005: Implemented revised temporal interpolation

scheme for estimating forecasted 6-hour average scheme for estimating forecasted 6-hour average temperatures from maximum/minimum values, for temperatures from maximum/minimum values, for NWRFC NWRFC

. Trying to work out a way of applying some work . Trying to work out a way of applying some work previously done by Eric Anderson for the Alaska region previously done by Eric Anderson for the Alaska region – possible use of gridded MOS temperature guidance – possible use of gridded MOS temperature guidance produced by Meteorological Development Laboratory produced by Meteorological Development Laboratory (MDL) (MDL)


Soil Moisture:Soil Moisture:. Oklahoma Mesonet: Started getting soil moisture data . Oklahoma Mesonet: Started getting soil moisture data

into Hydrology Lab’s research effortsinto Hydrology Lab’s research efforts

. Hydromet Testbed: Soil moisture measurements in the . Hydromet Testbed: Soil moisture measurements in the American River Basin for DMIP studyAmerican River Basin for DMIP study

. Collaboration with NASA in using satellite based soil . Collaboration with NASA in using satellite based soil moisture data in NWS operational modelmoisture data in NWS operational model

. Prepared a document on the needs of soil moisture . Prepared a document on the needs of soil moisture


Soil Temperature:Soil Temperature:

. . Enhanced soil temperature observations in the North Enhanced soil temperature observations in the North

Central RFC region from CO-OP networkCentral RFC region from CO-OP network..

Skin Temperature: Skin Temperature: . Collaborating with Marshall Space Flight Center in . Collaborating with Marshall Space Flight Center in

deriving surface skin temperature data from the deriving surface skin temperature data from the satellitessatellites


Potential Evapotranspiration:Potential Evapotranspiration:

. . Just finished a collaboration with Univ. of New Just finished a collaboration with Univ. of New Hampshire to study potential use of GOES surface Hampshire to study potential use of GOES surface radiation budget estimates for PE calculations. radiation budget estimates for PE calculations.

Results were promising.Results were promising. . Collaboration with NASA to assimilate MODIS derived . Collaboration with NASA to assimilate MODIS derived

cloud cover and ASOS cloud cover into NWSRFS for cloud cover and ASOS cloud cover into NWSRFS for PE calculationsPE calculations

. Making North American Regional Reanalysis data . Making North American Regional Reanalysis data available to research community available to research community


Data Archival Needs:Data Archival Needs:

. . Formed a team to identify hydrologic data archival needs Formed a team to identify hydrologic data archival needs

. Finalized a list of data that need to be archived at every . Finalized a list of data that need to be archived at every RFC and submitted to HSDRFC and submitted to HSD

Accomplishments - NWSAccomplishments - NWS

Analysis of Record (AOR):Analysis of Record (AOR):

. Stage II targeted for Real Time Meso-scale Analysis.. Stage II targeted for Real Time Meso-scale Analysis.

Daily and long-term products are not decided yet.Daily and long-term products are not decided yet.


Automated Flood Warning System (AFWS):Automated Flood Warning System (AFWS):

. In 2004, NOAA restructured the AFWS grants program . In 2004, NOAA restructured the AFWS grants program to implement AFWS technology throughout the US.to implement AFWS technology throughout the US.

. Beginning in 2005, AFWS grants program awarded 8 . Beginning in 2005, AFWS grants program awarded 8 grants worth approximately $450,000 to states across grants worth approximately $450,000 to states across the country. the country.

. Grant funds used primarily to add/refurbish/enhance . Grant funds used primarily to add/refurbish/enhance radio reporting “ALERT” precipitation and stream radio reporting “ALERT” precipitation and stream sensorssensors


. Also, NWS received. Also, NWS received

320K in FY05 - IOOS320K in FY05 - IOOS

120K in FY06 - NOS120K in FY06 - NOS

. These funds will be given to USGS to upgrade their . These funds will be given to USGS to upgrade their stream sensors in coastal areas to high data rate stream sensors in coastal areas to high data rate transmitters (once per hour)transmitters (once per hour)


NERON – To dateNERON – To date

. 100 Sites Deployed In The New England Area. 100 Sites Deployed In The New England Area

. Sites Measure: . Sites Measure:

TemperatureTemperature

PrecipitationPrecipitation

Wind Speed and DirectionWind Speed and Direction

• Near Real-Time ReportingNear Real-Time Reporting

Future Plans - NWSFuture Plans - NWS

NERON – Near futureNERON – Near future

. NERON supporting NIDIS. NERON supporting NIDIS

. ~60 Site To Be Deployed in Southwest US. ~60 Site To Be Deployed in Southwest US

. Sites Will Measure: . Sites Will Measure: TemperatureTemperaturePrecipitation Precipitation Wind speed and DirectionWind speed and DirectionRelative HumidityRelative HumiditySoil Moisture Soil Moisture Soil TemperatureSoil TemperatureSolar RadiationSolar Radiation

. Near real-time reporting. Near real-time reporting

Future Plans - NWSFuture Plans - NWS

. . Super Resolution – Radar Reflectivity (FY 2008)Super Resolution – Radar Reflectivity (FY 2008)

Smaller grid (1/2 deg. by 1 km) yielding more Smaller grid (1/2 deg. by 1 km) yielding more precise precipitation input for FFMP and other precise precipitation input for FFMP and other decision assistance tooldecision assistance tool

. Dual Polarization (FY 2011). Dual Polarization (FY 2011) Improve WSR-88D radar estimates of Improve WSR-88D radar estimates of

precipitation type and rate leading to improved precipitation type and rate leading to improved estimates of precipitation input for FFMP.estimates of precipitation input for FFMP.

Thanks Thanks

Questions ?Questions ?

current and future data requirements chandra kondragunta hydrometeorology group hydrology laboratory...

Documents

hydrologic data requirements

accomplishments ohd

accomplishments ohd

current operational

data attributes

prototype system

accomplishments nws

radar rainfall