Analysis of global vegetation resilience under different future climate scenarios - Zheng Chen; Peiyi Fan; Xintong Hou; Fei Ji; Li Li; Zhonghua Qian; Guolin Feng; Guiquan Sun (Climate Dynamics, 2024)

Effects of CO$$_2$$ vegetation forcing on precipitation and heat extremes in China - Zheng Chen; Xintong Hou; Peiyi Fan; Fei Ji; Li Li; Guiquan Sun; Guolin Feng; Zhonghua Qian (Climate Dynamics, 2024)

Remote effects of Tibetan Plateau spring land temperature on global subseasonal to seasonal precipitation prediction and comparison with effects of sea surface temperature: the GEWEX/LS4P Phase I experiment - Yongkang Xue; Ismaila Diallo; Aaron A. Boone; Yang Zhang; Xubin Zeng; William K. M. Lau; J. David Neelin; Tandong Yao; Qi Tang; Tomonori Sato; Myung-Seo Koo; Frederic Vitart; et al. (Climate Dynamics, 2024)
The prediction skill for precipitation anomalies in late spring and summer months—a significant component of extreme climate events—has remained stubbornly low for years. This paper presents a new idea that utilizes information on boreal spring land surface temperature/subsurface temperature (LST/SUBT) anomalies over the Tibetan Plateau (TP) to improve prediction of subsequent summer droughts/floods over several regions over the world, East Asia and North America in particular. The work was performed in the framework of the GEWEX/LS4P Phase I (LS4P-I) experiment, which focused on whether the TP LST/SUBT provides an additional source for subseasonal-to-seasonal (S2S) predictability. The summer 2003, when there were severe drought/flood over the southern/northern part of the Yangtze River basin, respectively, has been selected as the focus case. With the newly developed LST/SUBT initialization method, the observed surface temperature anomaly over the TP has been partially produced by the LS4P-I model ensemble mean, and 8 hotspot regions in the world were identified where June precipitation is significantly associated with anomalies of May TP land temperature. Consideration of the TP LST/SUBT effect has produced about 25–50% of observed precipitation anomalies in most hotspot regions. The multiple models have shown more consistency in the hotspot regions along the Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train. The mechanisms for the LST/SUBT effect on the 2003 drought over the southern part of the Yangtze River Basin are discussed. For comparison, the global SST effect has also been tested and 6 regions with significant SST effects were identified in the 2003 case, explaining about 25–50% of precipitation anomalies over most of these regions. This study suggests that the TP LST/SUBT effect is a first-order source of S2S precipitation predictability, and hence it is comparable to that of the SST effect. With the completion of the LS4P-I, the LS4P-II has been launched and the LS4P-II protocol is briefly presented.

Summer precipitation prediction in eastern China based on machine learning - Peiyi Fan; Jie Yang; Zengping Zhang; Naihui Zang; Yingfa Li; Guolin Feng (Climate Dynamics, 2023)