关键词: 降水量, CMIP6模式, SSP情景, Morlet小波分析

Abstract:

Based on daily data from 117 meteorological stations in Henan province (1960-2014) and data from 10 climate models in the Sixth Coupled Model Intercomparison Project (CMIP6), this study evaluated the simulation ability of multi-model ensemble (MME) models for annual precipitation in Henan during the historical period (1960-2014) and analyzed the spatiotemporal changes in precipitation under different SSP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) for the period 2015-2100, in order to provide a basis for agricultural production in Henan province. The results indicated: (1) from 1960 to 2014, the spatial correlation coefficient (R) between the MME models and observations exceeded 0.95, with a standard deviation (RSD) of 1.05mm and root mean square error (RMSE) of 0.31 mm, indicating that the MME models performed better than individual climate model. (2) Compared to the historical reference period (1960-2014), annual precipitation in Henan under all four scenarios for 2015-2100 showed an increasing trend, with July cumulative precipitation ranging between 150-230mm, higher than in other months. (3) In terms of cyclical changes, all four scenarios exhibited multi-timescale features, with different precipitation cycles at various time scales. The primary periods for scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 were 15y, 25y, 49y, and 26y, respectively. (4) Under all four scenarios, compared to the baseline historical period (1960-2014), the annual precipitation in Henan showed an increasing trend in the near term (2021-2040), mid-term (2041-2060), and late term (2080-2100). Moreover, the higher the emission scenario, the greater the increasing trend. All four scenarios exhibited a spatial distribution feature that increased from northwest to southeast. The findings provide theoretical reference for forecasting future regional precipitation and scientific basis for agricultural production in Henan province.

Key words: Precipitation, CMIP6 models, SSP scenarios, Morlet wavelet analysis