Development of a New Precipitation Dataset for Model Downscaling and Bias Correction

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Monday, 18 January 2010: 5:00 PM
B304 (GWCC)
Michael Charles, EMC, Camp Springs, MD; and Z. Toth, D. Hou, and R. Krzysztofowicz

Bias correction and downscaling of forecast products, such as temperature and wind, of the NCEP Global Ensemble Forecasting System (GEFS) and the North America Ensemble Forecasting System (NAEFS) have demonstrated benefit in improving the forecast. The application of the same procedure to precipitation is hindered by the lack of a satisfying precipitation dataset. The required dataset should be our best estimate for truth on a 5x5km (NDFD) grid for each 6-hour period, and it should be accurate and quality controlled.

The two widely used precipitation datasets are the CPC Unified Precipitation Analysis and the RFC Quantitative Precipitation Estimate. The Former is based on gauge records with a uniform quality control across the entire domain and thus bears more confidence, but it provides only 24 hour accumulation at one eighth degree resolution. The RFC dataset, on the other hand, has a spatial resolution nearly equal to NDFD grid and temporal resolution of 6 hours, but it is subject to different methods of quality control and adjustments by different River Forecasting Centers.

This paper describe the development of a new data set by combining the two dataset to take advantage of the higher climatological reliability of the CPC dataset and the higher temporal and spatial resolution of the RFC dataset. The methodology employed is basically statistical adjustment. The RFC dataset is first aggregated to CPC resolution. As the next step, a statistical relationship is established between the two datesets at CPC resolution and used to adjust the aggregated RFC data to make its climatology look like the CPC dataset. Finally, the adjusted RFC data is downscaled back to its original resolution to recover its original variability in time and space.