讲座简介

In this study, a simplified semi-physical retrieval algorithm for latent heat (LH) released from precipitation over the Tibetan Plateau (TP) is derived and analyzed. The physical basis of this algorithm is that the vertical gradient of rain rate (-dR/dZ or Γ) represents the temporal rate of rain formation based on the steady-state assumption, and the precipitation formation rate is closely related to the cloud formation rate, which is directly proportional to the latent heating rate. In this algorithm, the LH rate is represented as a linear function of Γ with fixed slope and intercept term determined by 3-month Weather Research and Forecasting Model simulations over the TP. Comparison to model results shows that the retrieval scheme can correctly capture the main features of LH horizontally and vertically. Comparison with results from other two widely accepted LH algorithms using Global Precipitation Measurement Dual Precipitation Radar real observations shows that this retrieval scheme generally agrees with them over low-altitudeareasbut yields more convective-type LH over the highlands witha relativelylower heating center. This algorithm is specially designed for application to high altitudes. With this algorithm and the associated coefficients provided, researchers can readily do LH retrieval in their cases of interest by themselves. The only required input is the vertical profile of rain rate, which is available from current satellite precipitation radar observations.

主讲人简介

？李锐，教授，博士生导师，2005年毕业于中国科学技术大学，2006-2013年在纽约州立大学从事博士后、Research Scientist工作，2013年受中国科学院百人计划“引进国外杰出人才”项目资助回国，现任中国科学技术大学地球与行星科学系副主任、大气科学学科点长。目前主要研究方向为卫星定量遥感大气，及其在地球气候系统水循环和能量平衡中的应用。特别关注云-气溶胶相互作用、降水潜热以及全天候条件下的植被-大气相互作用过程研究。在以上领域发表论文40多篇，近5年来领导了自然科学基金重点、贝尔蒙托论坛国际合作、重大研发计划课题等多个国家级重点项目。