北京师范大学全球变化与地球系统科学研究院
北京师范大学全球变化与地球系统科学研究院
   
当前位置: 首页»科研成果» 2013 A New Weighting Function for Estimating Microwave Sounding Unit Channel 4 Temperature Trends Simulated by CMIP5 Climate Models 张选泽、郑小谷、杨赤、骆三

 A New Weighting Function for Estimating Microwave Sounding Unit Channel 4 Temperature Trends Simulated by CMIP5 Climate Models

 

ZHANG Xuanze1,2, ZHENG Xiaogu1*, YANG Chi1, and LUO San1

 

1College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875;

2College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000.

 

ABSTRACT

A new static microwave sounding unit (MSU) channel 4 weighting function is obtained from using Coupled Model Inter-comparison Project, Phase 5 (CMIP5) historical multimodel simulations as inputs into the fast Radiative Transfer Model for TOVS (RTTOV v10). For the same CMIP5 model simulations, it is demonstrated that the computed MSU channel 4 brightness temperature (T4) trends in the lower stratosphere over both the globe and the tropics using the proposed weighting function are equivalent to those calculated by RTTOV, but show more cooling than those computed using the traditional UAH (University of Alabama at Huntsville) or RSS (Remote Sensing Systems in Santa Rosa, California) static weighting functions. The new static weighting function not only reduces the computational cost, but also reveals reasons why trends using a radiative transfer model are different from those using a traditional static weighting function. This study also shows that CMIP5 model simulated T4 trends using the traditional UAH or RSS static weighting functions show less cooling than satellite observations over the globe and the tropics. Although not completely removed, this difference can be reduced using the proposed weighting function to some extent, especially over the tropics. This work aims to explore the reasons for the trend differences and to see to what extent they are related to the inaccurate weighting functions. This would also help distinguish other sources for trend errors and thus better understand the climate change in the lower stratosphere.

 

KEY WORDS: CMIP5, RTTOV, MSU weighting function, lower stratospheric temperature variability

 

PUBLISHED IN: ADVANCES IN ATMOSPHERIC SCIENCES, 2013, 30 (3): 779-789.

 

DOWNLOAD PDF: http://link.springer.com/content/pdf/10.1007%2Fs00376-013-2152-x.pdf