20th Conference on Probability and Statistics in the Atmospheric Sciences


Linkage between pseudo-precipitation and precipitation distribution

Huiling Yuan, CIRES and NOAA/ESRL, Boulder, CO; and P. Schultz, Z. Toth, and J. C. Schaake

Precipitation forecast biases are very common in numerical weather prediction models, especially over complex terrain. The discontinuous nature of precipitation distribution poses even more challenges for mitigating such biases. The concept of pseudo-precipitation is introduced to reveal the linkage between water vapor deficit and precipitation biases. Unlike precipitation alone, pseudo-precipitation is continuous in space, which generates continuous variables in the statistics and facilitates bias correction. Reforecasts from Golobal Forecast System (GFS) fixed version at T62 resolution with 15 ensemble members have been examined for water vapor deficit. The NCAR/NCEP reanalysis data is used to produce the referenced pseudo-precipitation (dryness) and gauge precipitation data is used to compare with GFS precipitation forecasts. The relationship between water vapor deficit and precipitation distribution is analyzed in details for regions of interest such as California's cool season over several years. We then use historical relationships between the predictors and observations to calibrate real-time forecasts.

Poster Session , 20th Conference on Probability and Statistics Poster Session
Wednesday, 20 January 2010, 2:30 PM-4:00 PM, Exhibit Hall B2

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