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Development of APCC multi-model probabilistic forecast system

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Frame of Image forecasts, APCC has developed the multi-model ensemble categorical probabilistic forecast method and implemented it in operational practice in the version based on Gaussian PDF (Probability Density Function). Since June 2006, APCC has provided the seasonal categorical probabilistic forecasts of precipitation, temperature at 850hPa surface, and geopotential height of 500hPa surface and disseminated it through the APCC web site. Along with Gaussian fitting, the methods based on empirical and gamma distributions were developed, the methods focusing mainly on precipitation which probability distribution asymptotically converges to the gamma on and may not fit Gaussian approximation in statistical sense. The tests show the difference between forecasts based on different PDFs, particularly, Gaussian approximation results in overestimating of “below normal” category probability and in underestimating of “above normal” one. There is a need for comparison of different methods in terms of skill score to understand which method is the most skillful for the forecast. Thus, we plan to verify the performance of probability forecast to select the mostly appropriate method out of three developed for each of the variables for different regions.
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1. Introduction
It is well known that all environmental forecasts are associated with uncertainty and the amount of uncertainty can be situation dependent. The utility of a single forecast of an atmospheric quantity is limited because the populatio


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Title Development of APCC multi-model probabilistic forecast system
Similar Titles
Material Type Reports
Author(English)

APEC Climate Center

Publisher

[Busan]:APEC Climate Center

Date 2006
Series Title; No APCC annual report; APCC technical report
Pages 151
Language English
File Type Documents
Original Format pdf
Subject Territorial Development < Environment
Holding APEC Climate Center

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