环境科学
辐射压力
水循环
气候模式
温室气体
强迫(数学)
耦合模型比对项目
植被(病理学)
水资源
蒸散量
归一化差异植被指数
自然地理学
大气科学
土地覆盖
降水
气候学
气候变化
绿化
水文学(农业)
气象学
地理
生态学
地质学
病理
生物
医学
作者
Jiao Lu,Guojie Wang,Shijie Li,Aiqing Feng,Mingyue Zhan,Tong Jiang,Buda Su,Yanjun Wang
摘要
Land evaporation (ET) is of great significance in climate change research, water resource management, and numerical weather forecasting. In this study, Ridge Regression Method and Sensitivity Analysis Methods have been used to study the projected land evaporation changes over China, and its response to vegetation greening under low (Shared Socioeconomic Pathway [SSP]1-2.6), medium (SSP2-4.5), and high (SSP5-8.5) forcing scenarios during 2020–2099, based on 16 of the latest generation of Earth System Models (ESMs) taking part in the Coupled Models Intercomparison Project Phase 6. Land evaporation is projected to significantly increase under all climate change scenarios, especially in the southern China where there is a humid climate. The influencing factors, including precipitation, air temperature, solar radiation, and leaf area index (LAI), are analyzed; LAI is indicated to dominate the interannual variations of land ET, contributing over 40% of the interannual variance in the warming climates. However, the sensitivity of land ET to vegetation greening is found to generally reduce along with the increasing radiation forcing levels. Such a reduced sensitivity is particularly true when making intermodel comparisons, possibly due to the uncertainties of vegetation parameterizations in different models. This study reveals the response of land ET to vegetation greening under multiple climate change scenarios, which may help to understand the essential role of vegetation in water cycle and provide support for future water resource management.
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