报告题目：
Surface temperature: model improvement, dataset development, and IPCC model evaluation
报告人：Prof. Xubin Zeng
单位： University of Arizona
报告时间：2012年6月4日（星期一）14:30
报告地点：科研楼303会议室
报告摘要：
Surface air and skin temperature is one of the most important variable in
weather and climate research and applications. In this talk, our recent work
on model improvement, dataset development, and IPCC model evaluation of
surface temperature will be discussed.
First, NCEP operational model (GFS) and the NCAR Commmunity Earth System
Model (CESM) both have a significant cold bias of early afternoon surface
skin temperature over global arid regions. In the flux tower measurement
community, there is also difficulty in the measurement and adjustment of
turbulent fluxes under stable conditions. We have developed an improved
treatment of roughness length for momentum and heat to improve both GFS
and CESM. It also improves the assimilation of satellite radiance from
surface-sensitive channels. Furthermore, we offer a new (land-atmosphere
coupled) perspective on the stable turbulence problem. The improvement was
implemented into the GFS operational model in 2011.
Second, there has been much confusion about monthly mean surface air
temperature in the modeling and reanalysis community between the
conventional average of daily maximum and minimum temperature versus the
24-hourly average. We have developed, for the first time, global 0.5 deg
hourly surface air temperature from 1948-2009 to address this issue.
NOAA National Weather Service is already considering our recommendation
of taking 24-hour average as the climate data record.
Finally, a major issue in climate research is the temporal and spatial
scales at which climate model prediction of surface air temperature is
reliable. We have addressed this issue using climate models in both IPCC AR4
and AR5. The progress from AR4 to AR5 models is relatively small.
Surface temperature: model improvement, dataset development, and IPCC model evaluation
报告人：Prof. Xubin Zeng
单位： University of Arizona
报告时间：2012年6月4日（星期一）14:30
报告地点：科研楼303会议室
报告摘要：
Surface air and skin temperature is one of the most important variable in
weather and climate research and applications. In this talk, our recent work
on model improvement, dataset development, and IPCC model evaluation of
surface temperature will be discussed.
First, NCEP operational model (GFS) and the NCAR Commmunity Earth System
Model (CESM) both have a significant cold bias of early afternoon surface
skin temperature over global arid regions. In the flux tower measurement
community, there is also difficulty in the measurement and adjustment of
turbulent fluxes under stable conditions. We have developed an improved
treatment of roughness length for momentum and heat to improve both GFS
and CESM. It also improves the assimilation of satellite radiance from
surface-sensitive channels. Furthermore, we offer a new (land-atmosphere
coupled) perspective on the stable turbulence problem. The improvement was
implemented into the GFS operational model in 2011.
Second, there has been much confusion about monthly mean surface air
temperature in the modeling and reanalysis community between the
conventional average of daily maximum and minimum temperature versus the
24-hourly average. We have developed, for the first time, global 0.5 deg
hourly surface air temperature from 1948-2009 to address this issue.
NOAA National Weather Service is already considering our recommendation
of taking 24-hour average as the climate data record.
Finally, a major issue in climate research is the temporal and spatial
scales at which climate model prediction of surface air temperature is
reliable. We have addressed this issue using climate models in both IPCC AR4
and AR5. The progress from AR4 to AR5 models is relatively small.
