Abstract 258

Abstract ID: 258

Progress Towards for better Understanding of the Sources of Global S2S Precipitation Prediction using Land Temperatures Anomaly over high mountains: A brief overview from the GEWEX/LS4P Initiative

Lead Author: Yongkang Xue
University of California, Los Angeles (UCLA), United States of America


Keywords: GEWEX/LS4P, S2S prediction, Land surface/subsurface temperature (LST/SUBT), Tibetan Plateau, Tibetan Plateau-Rocky Mountains Circumglobal (TRC) wave train

Abstract: 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) and Rocky Mountains (RM) 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 Initiative (Impact of initialized Land Surface temperature and Snowpack on Sub-seasonal to Seasonal Prediction). The LS4P Phase I (LS4P-I) experiment 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. The cause of the 2003 drought had never been identified. More than forty institutions worldwide have participated in this effort, many of which are the major climate/weather centers in the world.

As a newly developed approach, observational evidence of land memory and statistically significant lag relationship between spring TP LST and summer precipitation were assessed. An out-of-phase oscillation between the TP and RM surface temperatures and a TP-RM Circumglobal (TRC) wave train have been identified. Meanwhile, the large bias in simulating the TP LST and regional wet/dry conditions by the LS4P-I Earth System Models were also noticed. With the newly developed LS4P initialization method for TP land temperature, 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 TRC wave train. For comparison, the global Sea surface temperature (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.

A. Bonne (CNRM, Université de Toulouse, Météo-France, CNRS, ,France)
T. Yao ( Institute of Tibetan Plateau Research, Chinese Academy of Sciences, China
I. Diallo (he Pennsylvania State University, USA)
X. Zeng (University of Arizona; Tucson, USA)
W. K.-M. Lau (ESSIC, University of Maryland, College Park, USA)
F. Vitart (European Centre for Medium-Range Weather Forecasts, UK)
D. Neelin (University of California, Los Angeles, USA)