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Validation and Error Characterization of the GPCP-1DD Precipitation Product over the Contiguous United States
Author(s) -
James McPhee,
S. A. Margulis
Publication year - 2005
Publication title -
journal of hydrometeorology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.733
H-Index - 123
eISSN - 1525-755X
pISSN - 1525-7541
DOI - 10.1175/jhm429.1
Subject(s) - precipitation , environmental science , climatology , categorical variable , rain gauge , meteorology , forcing (mathematics) , statistics , mathematics , geography , geology
A validation and error characterization study of the Global Precipitation Climatology Project, 1 degree daily (GPCP-1DD) precipitation product over the contiguous United States is presented. Daily precipitation estimates over a 1° grid are compared against aggregated precipitation values obtained from the forcing field of the North American Land Data Assimilation System (LDAS). LDAS daily values are consistent with the National Centers for Environmental Prediction Climate Prediction Center (CPC) gauge-based daily precipitation product and hence are regarded as realistic ground-truth values with full coverage of the United States. Continuous and categorical measures of skill are presented, so that both the ability of GPCP-1DD to identify a precipitation event and its accuracy in determining cumulative precipitation amounts are evaluated. Daily values are aggregated into seasonal averages, and spatial averages are computed for five arbitrarily defined zones that cover most of the study area. Results show that in general there is good agreement between GPCP-1DD and LDAS values, except for areas where GPCP-1DD is unable to identify high-intensity events, particularly the Pacific coast north of parallel 40°N. Computation of continuous statistics shows that average bias is negligible in most areas of the United States except for humid regions north of parallel 40°N. However, the rmse statistics shows that differences in estimated precipitation for individual 1° cells can be significant, exceeding in most cases the magnitude of the average precipitation. Beyond the validation, the error characterization presented here can significantly enhance the utility of the GPCP-1DD product by providing necessary inputs for ensemble hydrologic modeling and forecasting.

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