基于WRF模式的无定河流域极端气候特征分析

doi:10.12118/j.issn.1000-6060.2023.597

Abstract

Abstract:

There are still many uncertainties to be solved about extreme climate events in the semi-arid region of the Loess Plateau under climate change. In this study, the weather research and forecasting (WRF) model driven by the static geographical data and the final operational global analysis (FNL) global reanalysis data was used to simulate the climate of the Wuding River Basin of Shaanxi Province, China from 2011 to 2022, and the simulated results were verified using the observed data from four meteorological stations in the basin to analyze the applicability of the model. On this basis, 11 extreme weather indicators were selected, combined with Sen’s slope estimator and the Mann-Kendall (M-K) test to analyze the spatial distribution characteristics and spatiotemporal trend changes of extreme precipitation and extreme temperature at the annual and seasonal scales in the Wuding River Basin. The conclusions are as follows: (1) Extreme precipitation events in the basin are more frequent in the east than in the west, and the interannual and seasonal spatial distribution characteristics of the maximum daily precipitation (RX1day) and precipitation total (PRCPTOT) are high in the east and low in the west. (2) Extreme precipitation events in the basin will further increase, precipitation amount and intensity will further increase, but the duration of precipitation and the degree of drought will decrease, specifically reflected in increased precipitation in all seasons but decreased precipitation in autumn in the east. (3) Extreme temperature events in the basin are more frequent in the east than in the west, and the interannual and seasonal spatial distribution characteristics of the minimum temperature (TNn) and maximum temperature (TXx) are high in the east and low in the west. (4) Extreme temperature events in the basin will further increase, and the frequency of high and low temperatures and their intensity show opposite changes in the east and west directions, specifically manifested as decreased temperature in summer and increased temperature in spring.

Key words: WRF, extreme precipitation, extreme temperature, spatiotemporal variation characteristics, Wuding River Basin

ZHANG Shunwei, ZHOU Zixiang, XIONG Xuanchen, ZHOU Jie. Extreme climate characteristics in the Wuding River Basin based on WRF model[J].Arid Land Geography, 2024, 47(9): 1482-1495.

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数据名称	数据描述	数据来源
地理基础信息数据	行政区划、水系等	http://www.ngcc.cn/ngcc/
高程数据	空间分辨率（30 m×30 m）	http://www.gscloud.cn/
静态地理数据	空间分辨率（1 km×1 km）	https://www2.mmm.ucar.edu/
FNL全球再分析数据	空间分辨率（1°×1°）	https://rda.ucar.edu/
气象数据	逐日降水、气温	https://data.cma.cn/

分类	指数名称	指数代码	定义	单位	时间尺度
强度指数	单日最大降水量	RX1day	最大1日降水量	mm	月或年
	雨日降水总量	PRCPTOT	雨日（日降水量≥1 mm）降水总量	mm	月或年
	雨日降水强度	SDII	年内日降水量≥1 mm的总量与总日数之比	mm·d^-1	年
持续指数	持续干燥日数	CDD	日降水量<1 mm的最长连续日数	d	月或年
	持续湿润日数	CWD	日降水量≥1 mm的最长连续日数	d	月或年

分类	指数名称	指数代码	定义	单位	时间尺度
强度指数	极端最低气温	TNn	日最低气温的最小值	℃	月或年
	极端最高气温	TXx	日最高气温的最大值	℃	月或年
	气温日较差	DTR	日最高气温与最低气温的差值	℃	月或年
持续指数	暖持续日数	WSDI	连续6 d日最高气温>90%分位值日	d	年
	霜冻日数	FD	日最低气温低于0 ℃的日数	d	月或年
	夏日日数	SU	日最高气温大于25 ℃的日数	d	月或年

两层嵌套方案	参数设置	物理方案	方案名称
初始边界条件	FNL Data	长波辐射方案	RRTM
投影坐标系	Lat-Lon	短波辐射方案	Dudhia
区域中心点	38.2°N，109.5°E	地表参数化方案	MYJ Monin-Obukhov
时间步长	150 s	云微物理方案	CAM 5.1
嵌套格点	d01：30×30；d02：61×66	陆面过程方案	Noah LSM
空间分辨率	d01：0.25°；d02：0.05°	大气边界层方案	MYJ
输出的时间步长	d01：24 h；d02：1 h	浅积云方案	Kain-Fritsch

气象要素	站点	RMSE	MAE	r	IA
最高气温/℃	榆林	3.98	2.08	0.96	0.96
	绥德	3.92	2.11	0.96	0.97
	横山	1.90	1.70	1.00	0.99
	靖边	1.74	1.56	1.00	0.99
最低气温/℃	榆林	3.39	1.69	0.97	0.97
	绥德	0.85	0.74	1.00	1.00
	横山	0.79	0.67	1.00	1.00
	靖边	1.24	1.02	1.00	1.00
降水量/mm	榆林	0.25	0.17	1.00	0.99
	绥德	0.53	0.31	0.93	0.97
	横山	0.13	0.09	0.99	1.00
	靖边	0.18	0.12	0.99	0.99

Extreme climate characteristics in the Wuding River Basin based on WRF model

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