What Does the Model Tell Us about the Seeding Effect: Results of WRF Simulations of WWMPP Seeding Cases in 3 Seasons

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Wednesday, 7 January 2015: 9:45 AM
211B West Building (Phoenix Convention Center - West and North Buildings)
Lulin Xue, NCAR, Boulder, CO; and R. M. Rasmussen, S. A. Tessendorf, D. Breed, C. Weeks, K. Ikeda, and C. Liu

During the full course (2008-2014) of Wyoming Weather Modification Pilot Program (WWMPP), the observations in 2009-2010 season showed the highest Root Regression Ratio (RRR, a derived value indicating the seeding impact on precipitation) than other seasons while RRRs of 2011-2012 and 2013-2014 seasons were significantly lower than others. To help understand what environmental parameters and physical processes led to these very different RRRs, all seeding cases in these three seasons have been simulated by the recently developed AgI cloud seeding microphysics scheme (Xue et al., 2013a, b) in the Weather Research and Forecasting (WRF) model.

The simulations were driven by the analysis data of the Real Time - Four Dimensional Data Assimilation (RT-FDDA) WRF forecast model deployed for WWMPP operational forecast. The single model domain covers both mountain ranges (Sierra Madre and Medicine Bow) with a grid spacing of 900-m. For each 4-hour long seeding case, about 2 hours spinup time and 2 more hours after seeding stopped were simulated. The comparisons of sounding parameters, liquid water path, precipitation and statistics between observations and model results showed that the model captured the essential environmental and microphysical conditions and reproduced the statics reasonably well.

The in-depth analysis of the model results that helps to explain physical meanings behind the statics of the observations and the implications of the simulated seeding effects will be presented in detail on the conference.