P1.70 The Impact of Cloud Microphysics on Precipitation using an Integration of Observation and WRF Simulation: A Squall Line Case Study

Monday, 28 June 2010
Exhibit Hall (DoubleTree by Hilton Portland)
Di Wu, University of North Dakota, Grand Forks, ND; and X. Dong, B. Xi, Z. Feng, and G. Mullendore

A key uncertainty for climate models is the representation of sub-grid scale cumulus convection; in particular, the cumulus cloud parameterization of GCMs is perhaps the parameterization with greatest uncertainty in how to represent it. To investigate the impact of cloud microphysics on precipitation, we use WRF simulations, Oklahoma Mesonet and NEXRAD observations over the SGP region on May 24, 2007. In particular, we have implemented a robust NEXRAD classification algorithm near the SGP that separates various parts of convective systems, such as convective cores (heavy precipitation), stratiform region (light precipitation) and anvil clouds (no precipitation). This classification and Oklahoma Mesonet surface rain observations can provide a ground truth to validate model simulations. We use two WRF microphysical schemes for this case study: WSM5 (vapor, cloud ice, cloud water, rain, snow) and WSM6 (same categories as WSM5, plus graupel/hail). Preliminary results show an appreciable increase with WSM6 in both 10 min precipitation rate and area coverage in convective region compared to WSM3 and WSM5. The increased precipitation rate is about 79% and the area coverage is about 30% more with WSM6. However, the precipitation rate in WSM6 is 56% more than observations. The related dynamics/microphysics fields will be investigated to show how graupel/hail can impact precipitation as well as storm structure/development. This study provides a good example of evaluating the model's microphysics scheme and using the observations as constraints. Conversely, the model simulations can provide the detailed cloud microphysical information that is usually difficult to obtain from observations.
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