Session 2 Precipitation Processes and Observations for Atmospheric, Land Surface, and Hydrological Modeling Part II

Monday, 7 January 2013: 4:00 PM-5:30 PM
Ballroom E (Austin Convention Center)
Host: 27th Conference on Hydrology
Thomas Adams, NOAA/NWS, Ohio River Forecast Center, Wilmington, OH

The session will focus on precipitation measurement/estimation with a eye on historical, high resolution, gridded, hourly, daily and subdaily precipitation (re-)analysis. Recently, significant research interest has focused on multi-sensor (gauge-radar-satellite-model) fusion procedures for hi-resolution regional precipitation We are hoping to continue discussions on: (1) the current status of precipitation data set development; (2) the current and future requirements for the data sets; (3) how to produce precipitation products that serve the research community while benefiting operations and service activities; (4) demonstrate successful uses of these products; and (5) describe multi-sensor data fusion processes. Contacts: Pingping Xie (, Thomas Adams (

4:00 PM
A High-Resolution Analysis of Daily Precipitation Climatology Reflecting the Impact of Topography across China
Anyuan Xiong, CMA National Meteorological Information Center, Beijing, China; and B. Xu, P. Xie, and Z. Chen
4:15 PM
Status of Dual Pol QPE in the WSR-88D Network
Daniel S. Berkowitz, NOAA/NWS, Norman, OK; and J. A. Schultz, S. Vasiloff, K. L. Elmore, C. D. Payne, and J. B. Boettcher
4:45 PM
Improving analysis of heavy to extreme precipitation with conditional bias-penalized optimal estimation
Ridwan Siddique, University of Texas at Arlington, Arlington, TX; and D. J. Seo, Y. Zhang, and D. Kim
5:00 PM
Building a climatology of precipitation system organization in the Carolinas using the NOAA radar-based Multi-Sensor Precipitation Estimation (MPE) product
Thomas M. Rickenbach, East Carolina University, Greenville, NC; and R. Nieto-Ferreira, S. E. Stevens, B. R. Nelson, and B. Blanton

5:15 PM
Depth-area-duration characteristics of storm rainfall in Texas using Multi-Sensor Precipitation Estimates
John A. McEnery, University of Texas at Arlington, Arlington, TX; and K. Jitkajornwanich
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