4.6 Design of the Ensemble Seeding Simulations for the Randomized Seeding Experiments of the Wyoming Weather Modification Pilot Project

Tuesday, 9 January 2018: 2:45 PM
Room 16AB (ACC) (Austin, Texas)
Lulin Xue, NCAR, Boulder, CO; and R. M. Rasmussen

During the full course (2008 – 2014) of the Wyoming Weather Modification Pilot Project (WWMPP), quality-controlled 4-hour accumulated precipitation data of 118 Randomized Seeding Experiment (RSE) unites have been collected by high-resolution snow gauges. The analysis of these RSE observations shows that the overall Root Regression Ratio (RRR, a derived value indicating the seeding impact on precipitation) is about 1.03. Large variability has been found in RRR for individual season. Cloud seeding simulations of RSE cases during 2009-2010, 2011-2012 and 2013-2014 seasons have been conducted using an AgI seeding parameterization implemented in WRF to help understand what environmental parameters and physical processes led to these very different RRRs. However, these deterministic simulations could not reproduce the observed RRR features. The model analysis and the failure of reproducing the observed results inspired us to design an ensemble seeding simulation approach to explore the seeding impact for all RSE cases. The ensemble was designed to cover the uncertainties associated with large-scale weather conditions (forcing from reanalysis data), model physics (boundary layer physics and seeding mechanisms), aerosol backgrounds (CCN and IN concentrations), and precipitation spatial and temporal distributions. This design leads to 96 ensemble members for each RSE case with 24 control and 72 seeding simulations. The details of the ensemble design and the brief validation of the ensemble results will be presented at the conference.
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