Attributing the Decline of Evapotranspiration over the Asian Monsoon Region during the Period 1950–2014 in CMIP6 Models

Author:

Zhu Xiaowei1,Kong Zhiyong2ORCID,Cao Jian23,Gao Ruina1,Gao Na1

Affiliation:

1. Key Laboratory for Meteorological Disaster Monitoring and Early Warning and Risk Management of Characteristic Agriculture in Arid Regions, Yinchuan 750002, China

2. School of Atmospheric Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China

3. Earth System Modeling Center, Nanjing University of Information Science and Technology, Nanjing 210044, China

Abstract

Evapotranspiration (ET) accounts for over half of the moisture source of Asian monsoon rainfall, which has been significantly altered by anthropogenic forcings. However, how individual anthropogenic forcing affects the ET over monsoonal Asia is still elusive. In this study, we found a significant decline in ET over the Asian monsoon region during the period of 1950–2014 in Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The attribution analysis suggests that anthropogenic aerosol forcing is the primary cause of the weakening in ET in the historical simulation, while it is only partially compensated by the strengthening effect from GHGs, although GHGs are the dominant forcings for surface temperature increase. The physical mechanisms responsible for ET changes are different between aerosol and GHG forcings. The increase in aerosol emissions enhances the reflection and scattering of the downward solar radiation, which decreases the net surface irradiance for ET. GHGs, on the one hand, increase the moisture capability of the atmosphere and, thus, the ensuing rainfall; on the other hand, they increase the ascending motion over the Indian subcontinent, leading to an increase in rainfall. Both processes are beneficial for an ET increase. The results from this study suggest that future changes in the land–water cycle may mainly rely on the aerosol emission policy rather than the carbon reduction policy.

Funder

National Key R&D Program of China

Natural Science Foundation of China of Jiangsu Province

Ningxia Science and Technology Innovation Team: Research and Application of Ningxia Intelligent Digital Forecasting

Key R&D Program of Ningxia

Publisher

MDPI AG

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