s4d workshopparis, france polar meteorology group, byrd polar research center, the ohio state...
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S4D Workshop Paris, France
Polar Meteorology Group, Byrd Polar Research Center, The Ohio State University, Columbus, Ohio
A High-ResolutionA High-Resolution
David H. Bromwich1,2 and Keith M. Hines1
1Polar Meteorology GroupByrd Polar Research CenterThe Ohio State University
Columbus, Ohio, USA
2Atmospheric Sciences ProgramDepartment of GeographyThe Ohio State University
Columbus, Ohio, USA
Arctic System ReanalysisArctic System Reanalysis
Arctic System Reanalysis Arctic System Reanalysis (ASR)(ASR)
1. Rapid climate change appears to be happening in the Arctic. A more comprehensive picture of the coupled atmosphere/land surface/ ocean interactions is needed.
2. Global reanalyses encounter many problems at high latitudes. The ASR would use the best available description for Arctic processes and would enhance the existing database of Arctic observations. The ASR will be produced at improved temporal resolution and much higher spatial resolution.
3. The ASR would provide fields for which direct observation are sparse or problematic (precipitation, radiation, cloud, ...) at higher resolution than from existing reanalyses.
4. The system-oriented approach would provide a community focus including the atmosphere, land surface and sea ice communities.
5. The ASR would provide a convenient synthesis of Arctic field programs (SHEBA, LAII/ATLAS, ARM, ...)
S4D Workshop Paris, France
Polar Meteorology Group, Byrd Polar Research Center, The Ohio State University, Columbus, Ohio
ASR OutlineA physically-consistent integration of Arctic data
enhanced observations of the Sustained Arctic Observing Network (SAON)
Participants:Ohio State University - Byrd Polar Research Center (BPRC)
- and Ohio Supercomputer Center (OSC)National Center Atmospheric Research (NCAR)University of ColoradoUniversity of IllinoisUniversity of Alaska Fairbanks
High resolution in space (20 km) and time (3 hours)
Begin with years 2000-2010 (EOS coverage)
Supported by NSF as an IPY project
Issues with Observations and Reanalyses
The storm of 19 October 2004 as depicted by the NCEP/NCAR global reanalysis. Contours represent isobars of sea level pressure at increments of 3 hPa. [from visualization package of NOAA Climate Diagnostics Center]
The Figure shows an intense storm depicted in the NCEP/NCAR reanalysis for 19 October 2004. This storm, which led to flooding of downtown Nome, Alaska, has a central pressure of 949 hPa in the reanalysis. The actual central pressure deduced by the National Weather Service was as low as 941 hPa.
Arctic Clouds / Radiation
solar and cloud fraction at Barrow (June 2001): ERA40 (red) vs ARM/NSA (black)
Radiation and Cloud Differences in the Arctic
longwave and cloud fraction at Barrow (June 2001): ERA40 (red) vs ARM/NSA (black)
Radiation and Cloud Differences in the Arctic
New data sources:
Important developments in Data Assimilation
WRF is well represented• MODIS winds
– Tests underway
• AIRS
• COSMIC– Radio occultation soundings from GPS
satellites
• ATOVS
Typical distribution of COSMIC GPS radio occultation soundings (green dots) over a 24-hour period over the Arctic.
Mesoscale Modeling
High Resolution Depictions
Observed annual mean precipitation (mm) derived from station data, contour interval = 200 mm
Annual mean precipitation, 1991-2000 derived from polar MM5 V3.5 (cm). Contour interval = 20 cm. MM5 is driven at the boundaries by ECMWF operational analyses.
Precipitation over Iceland from Polar MM5
Importance of high-resolution simulations and skill of numerical models in high latitudes
WRF – Weather Research and Forecasting model
• Base model for ASR
• Polar WRF – Polar-optimized version has been developed (Ohio State)– Tested for Greenland– Tested for Antarctica– Testing for Sheba– Testing for Arctic land
• Data Assimilation (NCAR)
• Land surface processes (NCAR)
On the Impact of MODIS Winds on AMPS WRF Forecasts
Jordan G. Powers, Syed R.H. Rizvi, and Michael G. Duda
Mesoscale and Microscale Meteorology DivisionNational Center for Atmospheric Research
Boulder, Colorado, USA
MODIS Wind Retrieval Filtering
Unfiltered— ALL Filtered— MOD1
0000 UTC 15 May 2004 Init
• WRF Experiments Init: 0000 UTC 15 May 2004
– First-guess and BCs: 1 GFS
– Standard AMPS data: Sfc repts, AWS, upper-air, ships, buoys, cloud-track winds
CTRL No data assimilation
ALL 3DVAR w/std AMPS data + all MODIS
MODQC 3DVAR w/std AMPS data + MODIS FILTER/QC subset
EXMOD 3DVAR w/std AMPS data only
• MM5 Simulation
AMPS MM5 3DVAR w/std AMPS data only
III. Simulations and Results
Experiment Results— WRF Sfc Winds 2300 UTC 15 May (Hr 23)
MOD1
25 25
ms-1ms-1
L
•
STD
ALLCTRL
34
Sfc
Win
ds
(ms-1
)S
LP
(hP
a)34
LL
L
ASR High Resolution Domain
Outer Grid: ~45 km resolution
Inner Grid: ~15 km resolution
Vertical Grid: ~60 levels
Inner Grid includes Arctic river basins