Global mean surface temperature(GMST)is one of the most important large-scale indicators for characterizing climate change on Earth,and Surface Temperature(ST)is also the most accurate key climate element currently understood by scientists and the public.Even so,there have been extensive discussions about the accuracy of global(regional)surface temperature(air temperature)changes[lj.From the perspective of climatic data acquisition and data reliability,the current GMST series and the evaluation of global warming rates are all based on several observation-based datasets produced by combining anomalies of Land Surface Air Temperatures(LSAT)and Sea Surface Temperatures(SST).
Qjngxiang LiWenbin SunBoyin HuangWenjie DongXiaolan WangPanmao ZhaiPhil Jones
The relationship between vegetation greening and climate change remains unclear due to its complexity, especially in drylands. Against the background of global warming, arid and semi-arid areas, including mid-latitude deserts, are most sensitive to climate change. In recent decades, the mechanisms underlying the relationship between vegetation greening and climate change have been widely discussed in the literature. However, the influence of vegetation greening in high latitudes on regional climate has not been fully studied. In this paper, a two-dimensional energy balance model was used to study the influence of greening in high latitudes on mid-latitude deserts. The authors found that when greening occurs in high latitudes, the mid-latitude desert recedes at the south boundary, while the polar ice belt and low-latitude vegetation belt both expand. Simultaneously, greening in high latitudes can induce a negative temperature anomaly in northern latitudes and a positive temperature anomaly in southern latitudes. The mid-latitude desert expands at its north and south boundaries until the CO2 concentration reaches 600 ppm(saturated state). The greening in high latitudes could result in a lower global-mean temperature in the ‘saturated’ state, due to the stronger cooling in high latitudes.
BI LuHE YongliHUANG JianpingLI YaokunGUAN XiaodanLIU Xiaoyue
