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Title:
MONTHLY-SCALE RAINFALL FORECAST CORRECTION METHOD COUPLED WITH GAMMA AND GAUSSIAN DISTRIBUTION
Document Type and Number:
WIPO Patent Application WO/2022/104709
Kind Code:
A1
Abstract:
A monthly-scale rainfall forecast correction method coupled with gamma and Gaussian distribution, comprising the following steps: acquiring forecast data of basin surface mean monthly-scale rainfall and observation values of basin surface mean rainfall corresponding to the forecast data as input data; performing fitting on the input data by means of a gamma distribution function; calculating a cumulative distribution function value of each piece of input data in the corresponding gamma distribution; converting the cumulative distribution function values into variables obeying a standard normal distribution; constructing a joint normal distribution according to the variables obeying the standard normal distribution to characterize a correlation between the forecast data and the observation values in the input data; and performing random sampling on the observation values according to the correlation, and performing inverse conversion on acquired samples to obtain a corrected forecast result. The monthly-scale rainfall forecast correction method can effectively quantify random errors, solves the problem of influence of complexity of a system and the random errors on rainfall forecast precision, and effectively improves the forecast precision.

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Inventors:
ZHAO TONGTIEGANG (CN)
HUANG ZEQING (CN)
Application Number:
PCT/CN2020/130457
Publication Date:
May 27, 2022
Filing Date:
November 20, 2020
Export Citation:
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Assignee:
UNIV SUN YAT SEN (CN)
International Classes:
G01W1/10; G06F17/18
Foreign References:
CN108830419A2018-11-16
CN109814178A2019-05-28
CN110110339A2019-08-09
CN111898831A2020-11-06
CN111831966A2020-10-27
JP2020134300A2020-08-31
JP2017003416A2017-01-05
KR101672810B12016-11-04
US20170351963A12017-12-07
Attorney, Agent or Firm:
YOGO PATENT AND TRADEMARK AGENCY LIMITED COMPANY (CN)
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