Approximating Long-Term Statistics Early in the Global Precipitation Measurement Era

Long-term precipitation records are vital to many applications, especially the study of extreme events. The Tropical Rainfall Measuring Mission (TRMM) has served this need, but TRMM’s successor mission, Global Precipitation Measurement (GPM), does not yet provide a long-term record. Quantile mapping...

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Bibliographic Details
Published in:Earth interactions 2017-04, Vol.21 (3), p.1-10
Main Authors: Stanley, Thomas, Kirschbaum, Dalia B., Huffman, George J., Adler, Robert F.
Format: Article
Language:English
Subjects:
Approximation
Atmospheric precipitations
Case studies
Climatology
Global precipitation
Hazard assessment
Hydrology
Laboratories
Landslides
Mapping
Mathematical models
Measurement
Precipitation
Rain
Rainfall
Satellites
Statistical methods
Statistics
Tropical climate
Tropical rainfall
Tropical Rainfall Measuring Mission (TRMM)
Weather forecasting
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Summary:Long-term precipitation records are vital to many applications, especially the study of extreme events. The Tropical Rainfall Measuring Mission (TRMM) has served this need, but TRMM’s successor mission, Global Precipitation Measurement (GPM), does not yet provide a long-term record. Quantile mapping, the conversion of values across paired empirical distributions, offers a simple, established means to approximate such long-term statistics but only within appropriately defined domains. This method was applied to a case study in Central America, demonstrating that quantile mapping between TRMM and GPM data maintains the performance of a real-time landslide model. Use of quantile mapping could bring the benefits of the latest satellite-based precipitation dataset to existing user communities, such as those for hazard assessment, crop forecasting, numerical weather prediction, and disease tracking.
ISSN:1087-3562
1087-3562
DOI:10.1175/EI-D-16-0025.1