三套再分析降水资料在安徽省的适用性评估

doi:10.3969/j.issn.1673-503X.2023.04.007

Abstract

Abstract:

In this study, three high resolution reanalysis precipitation datasets (CMA-RA, CMFD, and ERA5) were compared with annual, seasonal and monthly precipitation and the amount of Meiyu precipitation observed at weather station in Anhui province from 1979 to 2018 and their applicability were evaluated The results show that all three datasets can well describe the variation characteristics of seasonal precipitation in Anhui province, with most rainfall concentrated in summer, more rainfall in spring than in autumn, and least in winter.However, all the monthly precipitation is overestimated, with the maximum mean absolute percentage error (MAPE) found in December.In addition, precipitation in mountainous areas is significantly overestimated by the three datasets.Comparatively, the CMA-RA dataset agrees better with the observations than the other two datasets in describing the spatio-temporal distribution characteristics of the annual, summer and winter rainfall across the whole province and the Meiyu precipitation in regions along and south to Yangtze River.In general, the CMFD well captures the interannual variations of the precipitation on all timescales, but is rather poor in depicting their spatial distributions.However, it performs slightly better in describing the spatial-temporal characteristics of precipitation in spring and autumn and the interannual variation characteristics of Meiyu precipitation.As for the ERA5, the precipitation in Anhui province is systematically overestimated, with the bias being the largest among the three datasets, and it performs slightly better than other datasets in the precipitation in January.

Key words: Reanalysis data, CMA-RA, Precipitation

CLC Number:

P468.0⁺24

Jinlan GAO,Huayang WEN,Xiaoyi ZHENG,Ya'nan CAO,Yun WANG. Applicability evaluation of three reanalysis precipitation datasets in Anhui province[J]. Journal of Meteorology and Environment, 2023, 39(4): 47-56.

Figures/Tables 12

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References 24

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评价指标	计算公式	取值范围	最优值
Pearson相关系数(R)	$R=\frac{\sum\limits_{i=1}^n\left(A_i-\bar{A}\right)\left(G_i-\bar{G}\right)}{\sqrt{\sum\limits_{i=1}^n\left(A_i-\bar{A}\right)^2 \sum\limits_{i=1}^n\left(G_i-\bar{G}\right)^2}} $	[-1, 1]	1
平均绝对百分比误差(MAPE)	$\text { MAPE }=\sum\limits_{i=1}^n\left\|\frac{G_i-A_i}{G_i}\right\| \times \frac{100}{n} $	[0, +∞]	0
相对误差(RE)	$ \mathrm{RE}=\frac{G_i-A_i}{G_i} \times 100$	[-∞, +∞]	0
泰勒评分(TSS)	$ \mathrm{TSS}=\frac{4(1+R)^4}{\left(\sigma_{\mathrm{obs}} / \sigma_{\mathrm{sim}}+\sigma_{\mathrm{sim}} / \sigma_{\mathrm{obs}}\right)^2\left(1+R_0\right)^4}$	[0, 1]	1

时段	T-TSS			S-TSS			MAPE/(%)
时段	ERA5	CMA-RA	CMFD	ERA5	CMA-RA	CMFD	ERA5	CMA-RA	CMFD
春季	0.66	0.82	0.96^*	0.94^*	0.94^*	0.83	15.52	6.77	5.12^*
夏季	0.86	0.91	0.98^*	0.96	0.98^*	0.96	19.32	7.14^*	7.29
秋季	0.70	0.87	0.95^*	0.85^*	0.85^*	0.57	14.56	10.02	8.65^*
冬季	0.90	0.91	0.98^*	0.74^*	0.64	0.59	15.16	7.07^*	7.76
年	0.90	0.94	0.97^*	0.97^*	0.96	0.92	14.94	6.41^*	6.63

月份	T-TSS			S-TSS			MAPE/(%)
月份	ERA5	CMA-RA	CMFD	ERA5	CMA-RA	CMFD	ERA5	CMA-RA	CMFD
1月	0.94	0.91	0.97^*	0.96^*	0.96^*	0.88	18.36	13.87	12.19^*
2月	0.92	0.97	0.99^*	0.95	0.97^*	0.94	20.96	9.38	7.87^*
3月	0.91	0.95	0.99^*	0.96	0.98^*	0.98^*	16.67	10.51	6.93^*
4月	0.76	0.92	0.99^*	0.96	0.98^*	0.97	21.61	9.53	5.28^*
5月	0.86	0.90	0.97^*	0.93	0.96^*	0.91	22.67	9.09	6.77^*
6月	0.87	0.92	0.98^*	0.89	0.94^*	0.88	27.09	9.50	7.23^*
7月	0.76	0.88	0.96^*	0.32	0.43^*	0.21	19.14	8.75	7.64^*
8月	0.76	0.90	0.96^*	0.47	0.52^*	0.26	20.38	13.35	11.10^*
9月	0.89	0.88	0.98	0.39^*	0.34	0.34	24.85	19.02	12.12^*
10月	0.91	0.97	0.99^*	0.76^*	0.71	0.65	37.72	15.93^*	25.11
11月	0.91	0.95	0.98^*	0.87^*	0.85	0.83	39.25	18.76	12.18^*
12月	0.96	0.99^*	0.99^*	0.93	0.94^*	0.90	315.50	89.47^*	129.50

区域	T-TSS			S-TSS			MAPE/(%)
区域	ERA5	CMA-RA	CMFD	ERA5	CMA-RA	CMFD	ERA5	CMA-RA	CMFD
江淮地区	0.88	0.95	0.99^*	0.49	0.58	0.71^*	29.23	13.88	6.50^*
沿江江南梅雨区	0.85	0.93	0.95^*	0.52	0.72^*	0.47	25.68	10.74	10.06^*

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Applicability evaluation of three reanalysis precipitation datasets in Anhui province

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