| NSF Org: |
AGS Division of Atmospheric and Geospace Sciences |
| Recipient: |
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| Initial Amendment Date: | October 20, 2006 |
| Latest Amendment Date: | January 11, 2011 |
| Award Number: | 0646401 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Eric DeWeaver
edeweave@nsf.gov (703)292-8527 AGS Division of Atmospheric and Geospace Sciences GEO Directorate for Geosciences |
| Start Date: | March 1, 2007 |
| End Date: | February 28, 2013 (Estimated) |
| Total Intended Award Amount: | $457,420.00 |
| Total Awarded Amount to Date: | $457,420.00 |
| Funds Obligated to Date: |
FY 2008 = $93,569.00 FY 2009 = $90,199.00 FY 2010 = $92,912.00 FY 2011 = $95,716.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
3100 MARINE ST Boulder CO US 80309-0001 (303)492-6221 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
3100 MARINE ST Boulder CO US 80309-0001 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | Climate & Large-Scale Dynamics |
| Primary Program Source: |
01000809DB NSF RESEARCH & RELATED ACTIVIT 01000910DB NSF RESEARCH & RELATED ACTIVIT 01001011DB NSF RESEARCH & RELATED ACTIVIT 01001112DB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.050 |
ABSTRACT
Using an atmospheric observation to initialize a numerical weather forecast requires that the statistics of the observation error be known. Among the sources of error is the "error of representativeness," which arises because an observation of a variable at, say, a single point, is used to initialize that variable throughout a grid cell, and the value of the variable at that point includes a component due to turbulent motions, the properties of which vary over space and time. The PI will apply improved local estimates of observation error to the assimilation of atmospheric data from realistic observing systems under realistic atmospheric conditions. This will lead to full use being made of data from high quality observations, such as from Doppler radar, and it will permit an accurate evaluation of the utility of next-generation observing systems. Accurate estimates of observation error will also be applied to generating realistic ensembles of perturbed initial conditions for ensemble forecasts. Because these applications depend on accurate measurements of turbulent statistics, the PI will investigate the statistical description of turbulence from research aircraft and from radiosonde data.
Broader impacts of this research arise from its application to improving weather forecasts.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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