Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction Project, Phase I (LS4P-I): organization and experimental design
Authors: Xue Yongkang , Yao Tandong , Boone Aaron A. , Diallo Ismaila , Liu Ye , Zeng Xubin , Lau William K. M. , Sugimoto Shiori , Tang Qi , Pan Xiaoduo , van Oevelen Peter J. , Klocke Daniel , Koo Myung-Seo , Sato Tomonori , Lin Zhaohui , Takaya Yuhei , Ardilouze Constantin , Materia Stefano , Saha Subodh K. , Senan Retish , Nakamura Tetsu , Wang Hailan , Yang Jing , Zhang Hongliang , Zhao Mei , Liang Xin-Zhong , Neelin J. David , Vitart Frederic , Li Xin , Zhao Ping , Shi Chunxiang , Guo Weidong , Tang Jianping , Yu Miao , Qian Yun , Shen Samuel S. P. , Zhang Yang , Yang Kun , Leung Ruby , Qiu Yuan , Peano Daniele , Qi Xin , Zhan Yanling , Brunke Michael A. , Chou Sin Chan , Ek Michael , Fan Tianyi , Guan Hong , Lin Hai , Liang Shunlin , Wei Helin , Xie Shaocheng , Xu Haoran , Li Weiping , Shi Xueli , Nobre Paulo , Pan Yan , Qin Yi , Dozier Jeff , Ferguson Craig R. , Balsamo Gianpaolo , Bao Qing , Feng Jinming , Hong Jinkyu , Hong Songyou , Huang Huilin , Ji Duoying , Ji Zhenming , Kang Shichang , Lin Yanluan , Liu Weiguang , Muncaster Ryan , de Rosnay Patricia , Takahashi Hiroshi G. , Wang Guiling , Wang Shuyu , Wang Weicai , Zhou Xu , Zhu Yuejian 
Published: July 2021

Abstract. Subseasonal-to-seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging, but also has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges
(GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative
called “Impact of Initialized Land Surface Temperature and Snowpack on Subseasonal to Seasonal Prediction” (LS4P) as the first international grass-roots effort to introduce spring land surface temperature
(LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a
crucial factor that can lead to significant improvement in precipitation
prediction through the remote effects of land–atmosphere interactions. LS4P focuses on process understanding and predictability, and hence it is different
from, and complements, other international projects that focus on the
operational S2S prediction. More than 40 groups worldwide have participated in this effort, including 21 Earth system models, 9 regional
climate models, and 7 data groups. This paper provides an overview of the history and objectives of LS4P, provides the first-phase experimental protocol (LS4P-I) which focuses on the remote effect of
the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the
preliminary results. Multi-model ensemble experiments and analyses of
observational data have revealed that the hydroclimatic effect of the spring
LST on the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation beyond East
Asia and its S2S prediction. Preliminary studies and analysis have also
shown that LS4P models are unable to preserve the initialized LST anomalies
in producing the observed anomalies largely for two main reasons: (i) inadequacies in the land models arising from total soil depths which are too
shallow and the use of simplified parameterizations, which both tend to limit the soil memory; (ii) reanalysis data, which are used for initial conditions, have large discrepancies from the observed mean state and
anomalies of LST over the Tibetan Plateau. Innovative approaches have been
developed to largely overcome these problems.