报告题目：Atmosphere-(land, ocean, ice) surface interactions: modeling and dataset development

　　报 告 人：Prof. Xubin Zeng（曾旭斌）

　　单 位：University of Arizona

　　报告时间：2017年7月4日（星期二）上午9:30

　　地 点：303会议室

　　报告摘要

　　Atmosphere-land-ocean-ice interface processes strongly affect weather and climate prediction and the energy/water/carbon cycles. Here I will overview some of our recent work in these areas: First, we have developed a new and innovative method to obtain daily 4 km snow water equivalent and snow depth data from 1981 to present over continental U.S. The robustness of our method and our product has been demonstrated using three approaches. Using this dataset, we have found large snow water equivalent and snow depth errors from analysis, reanalysis, land data assimilation systems, and satellite remote sensing, and identified the primary reasons. Second, we have developed 0.5 deg hourly surface air temperature datasets over global land. A new finding on the diurnal temperature range over high latitudes will be discussed. Furthermore, 1,400 station years of in situ measurements of surface air temperature over Greenland have been used to comprehensively assess existing observation-based gridded datasets, reanalyses, and CMIP5 models. One finding is that observation-based gridded datasets and reanalyses differ in mean values and trends. Finally, we have developed an observational data-driven model for decadal and long-term global warming projections. This model combines natural multi-decadal variability with anthropogenic warming that depends on the history of annual emissions. It shows good skill in decadal hindcasts with the recent warming slowdown well captured. We have also compared our decadal and long-term projections (including the uncertainty range) with those from CMIP5 models.