Open AccessShort‐ to medium‐range superensemble precipitation forecasts using satellite products: 2. Probabilistic forecasting
Author(s) -
Shin D. W.,
Krishnamurti T. N.
Publication year - 2003
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.67
H-Index - 298
eISSN - 2156-2202
pISSN - 0148-0227
DOI - 10.1029/2001jd001511
Subject(s) - probabilistic logic , satellite , precipitation , environmental science , meteorology , quantitative precipitation forecast , range (aeronautics) , forecast skill , climatology , special sensor microwave/imager , probabilistic forecasting , microwave , computer science , geography , geology , physics , artificial intelligence , telecommunications , materials science , astronomy , composite material , brightness temperature
Short‐ to medium‐range probabilistic precipitation forecasts over the global tropics are explored using satellite products, from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Special Sensor Microwave/Imager (SSM/I) instruments. In addition to the conventional probability of precipitation (POP) forecast, superensemble (SE) POP forecasts are introduced and applied to the multianalysis, multicumulus‐scheme, and multimodel ensemble configurations in two different horizontal resolution forecasts. It is shown that an ensemble system using a single model has a more consistent bias, which can at least partially be removed by a simple bias correction. With the aid of properly prepared ensemble members, meaningful POP forecasts have much longer forecast lead times. Results also show that a family of higher‐resolution forecasts has a greater ability in removing model biases. The advantage of the SE approach is found to be evident in making POP forecasts, compared to the conventional method. The skills of SE POP are 10 to 20 percent better than those of the bias‐corrected.