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              <p>The kicko workshop for the "Impact of initialized land temperature and snowpack on sub-seasonal to seasonal prediction" (LS4P) Initiative and " ird Pole Experiment Multi-Model Intercomparison" (TPEMIP) Project was held just prior to 2018's annual American Geophysical Union meeting. Subsea-sonal to seasonal (S2S) prediction, especially the prediction of extreme climate events such as droughts and floods, is scientifically challenging and has substantial societal impacts and economic consequences. Despite the substantial progress that has been achieved in recent decades, the prediction skill for precipitation anomalies in spring and summer months has remained stubbornly low. e GEWEX/Global Atmospheric System Study (GASS) LS4P initiative put forward a new approach that complements sea surface temperature (SST), snow and soil moisture research by suggesting the effect of land memory in terms of the land surface/subsurface temperature (LST/SUBT) on S2S prediction. Most land-atmosphere interaction studies have focused on the local e ect, while the possible remote effects of large-scale LST/SUBT anomalies in geographical areas upstream on S2S prediction have largely been ignored. e LS4P project intends to address the question of the impact of the initialization of large scale LST/SUBT and snow pack, including aerosols in snow, in climate models on the S2S prediction over different regions. East Asia has been selected as the focus area in the first phase because of the presence of the high elevation Tibetan Plateau (TP) and large-scale snow cover there, in addition to a significant amount of available observational data from the third Pole Experiment (TPE). is provides an ideal geographical location for the rst phase experiment. Regional Earth system (multi-sphere) modelling for the third Pole region and its impact on the adjacent regions at different scales is also one of TPEMIP's main focuses.</p>
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