Correction Based on Distribution Scaling for Precipitation Simulated by Climate Model

Zhou Lin; Pan Jie; Zhang Lei; Xu Yinlong

Vol.25, NO.3, 2014

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2014 > 25(3): 302-311

Zhou Lin, Pan Jie, Zhang Lei, et al. Correction based on distribution scaling for precipitation simulated by climate model. J Appl Meteor Sci, 2014, 25(3): 302-311.

Citation:

Zhou Lin, Pan Jie, Zhang Lei, et al. Correction based on distribution scaling for precipitation simulated by climate model. J Appl Meteor Sci, 2014, 25(3): 302-311.

Zhou Lin, Pan Jie, Zhang Lei, et al. Correction based on distribution scaling for precipitation simulated by climate model. J Appl Meteor Sci, 2014, 25(3): 302-311.

Citation:

Zhou Lin, Pan Jie, Zhang Lei, et al. Correction based on distribution scaling for precipitation simulated by climate model. J Appl Meteor Sci, 2014, 25(3): 302-311.

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Correction Based on Distribution Scaling for Precipitation Simulated by Climate Model

Zhou Lin^1,2,
Pan Jie¹,
Zhang Lei²,
Xu Yinlong^{1,2
,
,}

1.
Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081
2.
Key Laboratory or Semi-arid Climate Change of the Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000

Received Date: 2013-10-26
Rev Recd Date: 2014-02-18
Publish Date: 2014-05-31

Abstract

Abstract

A statistical bias correction based on piecewise Γ distribution fitting to construct seasonal transfer function is applied to the precipitation simulated by a regional climate model PRECIS under the SRES-A1B emission scenario over China. The transfer function (TF) is derived from the control period of December 1962—November 1972, fitting the cumulative probability density function of both simulated and observed precipitation with Γ distribution. The 95th percentile precipitation is chosen to be the threshold and precipitation below and upon the threshold are fitted, respectively. When compared with wholesale fitting, this method can better fit the distributions of both small/medium precipitation and extreme precipitation. Then the TF is applied for the validation period of December 1991-November 2001. The correction strategy is based on the assumption that discrepancies between model and observation stay constant with time.Results show that PRECIS can reproduce the spatial distribution of mean and extreme precipitation, while the biases exist. The biases are larger if the topography is more complex. If the region is high or low in altitudes, the bias tends to be positive or negative, while Sichuan Basin is the exception, where large positive biases occur.The correction based on the piecewise Γ distribution fitting can well correct the spatial distribution of the mean precipitation over China, especially over the original large-bias regions, and the grids in which the bias percentages used to be larger than 100% are reduced from 23.5% down to 1.0%. Simulation of region-averaged monthly precipitation is significantly improved, especially over Southwest China and the Tibet Plateau regions. Precipitation in cold seasons is better corrected, while it has relatively larger biases in warm seasons especially in June due to a wide range of precipitation, which may bring difficulties during fitting. So, it's crucial to improve the fitting probability in warm seasons.The piecewise Γ distribution fitting correction also does a quite good job in correcting the extreme precipitation. The spatial distribution, probability density distribution and spatial correlation coefficient of consecutive dry days, the maximum 5-day precipitation amount and the contribution of extreme precipitation are corrected significantly, except for maximum 5-day preciptiation amount in East China, contribution of extreme precipitation in Northwest China and the Tibet Plateau are overcorrected. These show that the technique has the ability to correct the extreme precipitation.In general, the correction results are satisfying, which implies that the piecewise Γ distribution fitting correction is capable of improving the reproduction of both mean and extreme precipitation simulated by regional climate model PRECIS over China, which is useful for assessment research.
- correction;
- piecewise fitting;
- transfer function (TF);
- extreme precipitation index

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References(31)

Figures and Tables

Fig. 1 Classification in this study

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Fig. 2 Spatial distribution of observed, simulated and corrected mean precipitation and the bias percentage over China in correction period (a) spatial distribution of the observed, (b) spatial distribution of the simulated, (c) the bias percentages of the simulated, (d) spatial distribution of the corrected, (e) the bias percentages of the corrected

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Fig. 3 The observed, the simulated and the corrected region-averaged precipitation in correction period

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Fig. 4 Spatial distribution of the observed (a), the simulated (b) and the corrected (c) consecutive dry days over China in correction period

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Fig. 5 The same as in Fig.4, but for the spatial distribution of maximum 5-day precipitation amount

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Fig. 6 The same as in Fig.4, but for the spatial distribution of extreme precipitation contribution

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Fig. 7 The observed, the simulated and the corrected probability density distributions of consecutive dry days, maximum 5-day precipitation amount and contribution of extreme precipitation over China in correction period

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Table 1 Spatial correlation coefficient of region-averaged extreme index derived from the simulated and the corrected to the observed precipitation in correction period

地区	连续干日数		连续5 d最大降水量		极端降水贡献率
地区	模拟值	订正值	模拟值	订正值	模拟值	订正值
东北	0.56	0.67	0.47	0.56	0.39	0.32^*
华北	0.81	0.90	0.74	0.87	0.38	0.40
西北	0.64	0.94	0.76	0.92	0.22	0.28
华东	0.51	0.77	0.52	0.41^*	0.05	0.20
中部	0.23	0.80	0.30	0.64	0.16	0.29
华南	0.62	0.81	0.41	0.83	0.43	0.63
西南	0.50	0.89	0.40	0.84	0.46	0.76
青藏高原	0.54	0.89	0.72	0.93	0.32	0.29^*
注：*表示过订正，即订正值较模拟值更偏离观测值。

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