Abstract
The Heilong-Amur River Basin (HARB) in Northeast Asia has experienced distinct land surface changes during the past 40 years due to extensive ecological restoration programs, agricultural management, and grassland grazing in different ecosystems. However, the regional climate impact caused by the long-term spatially heterogeneous land surface changes in this mid-high latitude region is not well documented. Therefore, this study used multi-source satellite measurements records and a high-resolution land-atmosphere coupled regional climate model (WRF) to investigate the land surface changes and their associated thermal and moisture impacts across three main ecosystems over the Heilong-Amur River basin from 1982 to 2018. Firstly, satellite observations indicated an overall greening in HARB, with variations across ecosystems. The significant summer farmland greening is the most representative, with the farmland green vegetation fraction (GVF) remarkably increasing by 7.78% in summer. The forest greening magnitude is stronger in spring (3.42%) than in summer (2.85%), while the grassland vegetation showed some local browning signals in summer. Secondly, our simulated results showed the summer farmland greening accelerated evapotranspiration (ET) by 0.161 mm/d and significantly cools the surface temperature by 0.508 °C averaged at the ecosystem scale, which was highly correlated with the satellite observations but with lower cooling magnitude. The forest greening brought less surface cooling in spring than summer due to the stronger albedo feedback, despite with greater increase in GVF and ET. While with the opposite process, the local grassland browning leads to consistent warming effects, which can be detected from both satellite observations and our simulation results. Finally, our results also found that rainfall increasing averagely at the ecosystem scale can't fully compensate the water emission from enhanced ET due to the surface greening, contributing to soil moisture decline in both farmland and relative dry forests.
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