A gcm correction method considering the fluctuation characteristics of daily data
A correction method and a technology of fluctuation characteristics, applied in the field of GCM correction, can solve the problems of lack of daily data accuracy analysis and judgment, and achieve accurate results
Active Publication Date: 2019-08-06
HOHAI UNIV
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However, the traditional downscaling or bias correction methods only correct the climate model data from the perspective of the monthly average, without analyzing and judging the accuracy of the daily data
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[0066] The BCC-CSM1.1(m) radiation data in Kunshan in 2030 was corrected for bias. Specific steps are as follows:
[0067] (1) Extract the daily measured and GCM radiation data in Kunshan from 1961 to 2000 and the daily radiation data in 2030 to be corrected for bias. Based on this data, the monthly mean values of the historically measured and GCM historical radiation data are calculated respectively, and the arithmetic mean method is used to calculate the multi-year monthly mean of the measured radiation data. The calculation method is as follows:
[0068]
[0069] Among them, M o,i is the multi-year mean of the i-th month of historical observations, i=1, 2, 3...12; R o,i,k,j The measured radiation value of the ith month, the kth year, and the jth day of the year in the historical period, k=1, 2, 3...40, j=1, 2, 3...28 / 29 / 30 / 31.
[0070] The formula for calculating the multi-year monthly mean of radiation data in the historical period of GCM is as follows:
[0071] ...
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The invention discloses a GCM correction method considering the fluctuation characteristics of daily data, which uses the month as a calculation unit to extract the daily measured data of a certain meteorological factor in the historical period, the GCM daily data in the same historical period, and the GCM daily data to be corrected in the future period , calculate the monthly average of historical measured data and historical GCM data for many years, and construct the average correction factor, so as to correct the daily average value of the future meteorological data, and construct the variance correction factor, and carry out variance correction on the future meteorological data after the correction of the average value, and use the corrected Variance is the constraint condition, and a new future GCM meteorological sequence is obtained. The present invention considers the distribution characteristics of the future GCM data and the consistency of the distribution characteristics of the measured data, and corrects the deviation of the future GCM data, so that the model simulation results using the GCM data tend to be more accurate.
Description
technical field [0001] The invention relates to a GCM correction method considering daily data fluctuation characteristics, and belongs to the technical field of climate analysis and statistics. Background technique [0002] The global climate model is an important data basis for assessing the impact of climate change on human society and natural systems. However, general circulation models (GCMs) are generally of low resolution and suffer from regional systematic errors. Therefore, it is necessary to downscale the climate model data according to the measured data of meteorological stations to achieve the scale matching between the atmospheric circulation model data and the meteorological station data. However, traditional downscaling or bias correction methods only correct the climate model data from the perspective of monthly mean values, without analyzing and judging the accuracy of daily data. In fact, in many research fields, such as agricultural growth water consumpt...
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IPC IPC(8): G06F17/18
CPCG16Z99/00Y02A90/10
Inventor 王卫光丁一民鲍金丽邢万秋董青傅健宇
Owner HOHAI UNIV