5.14
Sensitivity of Surface Analyses to RAWS observations
John D. Horel, University of Utah, Salt Lake City, UT; and D. Myrick
Federal, state, and other wildland resource management agencies contribute to the collection of weather observations from over 1000 Remote Automated Weather Stations (RAWS) located for the most part in remote locations across the western United States. The impact of RAWS observations on surface objective analyses during the 2003/04 winter season was assessed using the ARPS Data Assimilation System (ADAS). A set of control analyses was created each day at 0000 and 1200 UTC by assimilating in ADAS all available observations (approximately 3000 observations). Another set of analyses was generated by withholding all of the RAWS observations available at each time while 10 additional sets of analyses were created by randomly withholding comparable numbers of observations obtained from all sources.
Random withholding of observations from the analyses provides a baseline estimate of the analysis quality. Relative to this baseline, removing the RAWS observations degrades temperature (wind speed) analyses by an additional 0.5C (0.9 m s-1) when evaluated in terms of rmse over the entire season. RAWS temperature observations adjust the Rapid Update Cycle background the most during the early morning hours and during winter season cold pool events in the western United States while wind speed observations have a greater impact during active weather periods. The average analysis area influenced by at least 1.0C (2.5C) by withholding each RAWS observation is on the order of 600 km2 (100 km2). The spatial influence of randomly withheld observations is much less.
Session 5, Data Impact Tests and Observing System Simulation Experiments (OSSE)
Wednesday, 17 January 2007, 8:30 AM-5:00 PM, 212B
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