Applicability of China’s First Generation of Global Land Surface Reanalysis Monthly Precipitation Products in the Yangtze River Basin

doi:10.11988/ckyyb.20231363

Abstract

Abstract:

China’s first-generation global land surface reanalysis CRA monthly precipitation products offer a new boundary information source for basin hydrological analysis. Taking station observations in the Yangtze River Basin as a reference, we assessed the applicability of CRA products from aspects of temporal evolution, spatial distribution, and drought identification ability. The results reveal that CRA data can effectively capture the interannual variations and monthly distribution of areal precipitation in the Yangtze River Basin. The multi-year average precipitation derived from CRA data is only 1.2% lower than the observed data. The correlation coefficients of monthly data all exceed 0.9. Nevertheless, the efficiency coefficients during the main flood season (July and August) are below 0.9, slightly lower than those in other months. The applicability of CRA products shows significant spatial heterogeneity. The mainstream of the Yangtze River from Yibin to Hukou has the best applicability with minimal spatial variation within this region, while the Minjiang and Tuojiang Rivers has the lowest applicability with remarkable spatial variability. CRA data tend to underestimate the precipitation in high-value areas and overestimate the precipitation in low-value areas. Nonetheless, CRA products display strong capabilities in identifying various levels of drought events on an intra-annual scale. These findings provide a reference for analyzing and enhancing the accuracy of CRA products, facilitating their application in basin hydrology.

Key words: CRA, reanalysis data, applicability assessment, precipitation, drought, Yangtze River Basin

CLC Number:

TV125降水

WANG Wen-peng, ZHANG Xin-yue, CUI Jun-hao, WU Guang-dong, ZHANG Tian-yu, LIU Bo. Applicability of China’s First Generation of Global Land Surface Reanalysis Monthly Precipitation Products in the Yangtze River Basin[J]. Journal of Changjiang River Scientific Research Institute, 2025, 42(4): 52-60.

Figures/Tables 12

Fig.1 Water resources zoning and locations of meteoro-logical observation stations in the Yangtze River Basin

Table 1 Ranges and optimums of evaluation indicators for the applicability of reanalysis precipitation products

评估指标	取值范围	最优值	评估指标	取值范围	最优值
PBIAS	$- ∞, + ∞$	0	PCOR	$- 1,1$	1
RV	$0, + ∞$	1	KGE	$- ∞, 1$	1

Table 1 Ranges and optimums of evaluation indicators for the applicability of reanalysis precipitation products

评估指标	取值范围	最优值	评估指标	取值范围	最优值
PBIAS	$- ∞, + ∞$	0	PCOR	$- 1,1$	1
RV	$0, + ∞$	1	KGE	$- ∞, 1$	1

Table 2 Drought classification based on SPI values

干旱等级	SPI	干旱等级	SPI
无旱	>-0.5	重旱	(-2.0, -1.5]
轻旱	(-1.0, -0.5]	特旱	≤-2.0
中旱	(-1.5, -1.0]

Table 3 Ranges and optimums of evaluation indicators for drought event identification

评估指标	取值范围	最优值	评估指标	取值范围	最优值
POD	$0,100 %$	100%	ETS	(-33.3%,100%]	100%
FAR	$0,100 %$	0

Table 3 Ranges and optimums of evaluation indicators for drought event identification

评估指标	取值范围	最优值	评估指标	取值范围	最优值
POD	$0,100 %$	100%	ETS	(-33.3%,100%]	100%
FAR	$0,100 %$	0

Fig.2 Annual precipitation changes obtained from CRA reanalysis and observations over the Yangtze River Basin during

Fig.3 Multiyear averaged monthly precipitation distribution over the Yangtze River Basin

Table 4 Evaluation results of applicability of CRA reanalysis data in each month

月份	PBIAS/%	PCOR	RV	KGE
1	-3.28	0.92	0.98	0.91
2	8.94	0.98	1.12	0.85
3	-1.42	0.94	1.01	0.93
4	2.22	0.95	1.02	0.94
5	-0.90	0.92	1.02	0.92
6	2.72	0.92	1.03	0.91
7	-5.98	0.91	0.92	0.86
8	-3.86	0.91	1.05	0.89
9	-0.48	0.94	1.07	0.91
10	-3.83	0.96	1.00	0.94
11	-0.81	0.96	1.00	0.96
12	-3.94	0.99	0.95	0.93

Fig.4 Spatial distribution of the applicability of CRA reanalysis data

Table 5 Classification of the mean and standard deviation of KGE for each water resources region

水资源分区	KGE均值	综合适用性	KGE标准差	空间差异
金沙江石鼓以下	[0.7, 0.8)	良	[0.1, +∞)	较大
岷沱江	(-∞, 0.7)	一般	[0.1, +∞)	较大
金沙江石鼓以上、汉江、洞庭湖水系、鄱阳湖水系	[0.8, 1.0]	优	[0.05, 0.1)	中等
嘉陵江、乌江	[0.7, 0.8)	良	[0.05, 0.1)	中等
两宜区间、湖口以下干流、宜昌至湖口、太湖水系	[0.8, 1.0]	优	[0, 0.05)	较小

Table 6 Classification of the mean and the corresponding confidence interval of KGE for each water resources region

水资源分区	KGE均值	综合适用性	置信区间	置信区间特点
金沙江石鼓以上、太湖水系	[0.8, 1.0]	优	[0.1, +∞)	区间宽,不确定性较大
岷沱江	(-∞, 0.7)	一般	[0.1, +∞)	区间宽,不确定性较大
洞庭湖水系、鄱阳湖水系、湖口以下干流	[0.8, 1.0]	优	[0.05, 0.1)	区间适中,不确定性中等
嘉陵江、金沙江石鼓以下、乌江	[0.7, 0.8)	良	[0.05, 0.1)	区间适中,不确定性中等
两宜区间、宜昌至湖口、汉江	[0.8, 1.0]	优	[0, 0.05)	区间窄,不确定性较小

Fig.5 SPI time series calculated based on CRA reanalysis and observed precipitation data

Table 7 Assessment of the ability to identify drought events in the Yangtze River Basin based on CRA reanalysis precipitation data

干旱等级	SPI3			SPI12
干旱等级	POD/%	FAR/%	ETS/%	POD/%	FAR/%	ETS/%
轻旱	83	15	68	10	87	-2
中旱	82	23	62	19	82	4
重旱	82	11	72	8	95	1
特旱	100	0	100	11	88	5

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