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