Combining TRMM and Surface Observations of Precipitation: Technique and Validation over South America

摘要: The measure of atmospheric model performance is highly dependent on the quality observations used in evaluation process. In particular case operational forecast centers, large-scale datasets must be made available a timely manner for continuous assessment results. Numerical models and surface usually work at distinct spatial scales (i.e., areal average regular grid versus point measurements), making direct comparison difficult. Alternatively, interpolation methods are employed mapping observational data to grids vice versa. A new technique (hereafter called MERGE) combine Tropical Rainfall Measuring Mission (TRMM) satellite precipitation estimates with over South American continent proposed its evaluated 2007 summer winter seasons. Two different approaches this product against were tested: cross-validation subsampling entire another only areas sparse observations. Results show that high density observations, MERGE technique’s equivalent simply averaging stations within boxes. However, shows superior