Trends of MSU Brightness Temperature in the Middle Troposphere Simulated by CMIP5 Models and Their Sensitivity to Cloud Liquid Water

Xuanze Zhang College of Global Change and Earth System Science, Beijing Normal University, Beijing, China

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Xiaogu Zheng College of Global Change and Earth System Science, Beijing Normal University, Beijing, China

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Zhian Sun Centre for Australian Weather and Climate Research, Bureau of Meteorology, Victoria, Melbourne, Australia

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San Luo College of Global Change and Earth System Science, Beijing Normal University, Beijing, China

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Abstract

Only a climate model that is able to simulate well the historical atmospheric temperature trend can be used for estimating the future atmospheric temperature trends on different emission scenarios. Satellite-based Microwave Sounding Unit (MSU) brightness temperature in the middle troposphere (T2) is an important analog of midtropospheric atmospheric temperature. So, there is the need to compare the atmospheric temperature trend simulated by the fifth phase of the Coupled Model Intercomparison Project (CMIP5) historical realizations and the observed MSU T2. There are two approaches for estimating modeled MSU T2: apply a global-mean static weighting function to generate the weighted average of the modeled temperature at all atmospheric layers and simulate satellite-view MSU T2 using the model’s output as input into a radiative transfer model (RTM).

In this paper, the two approaches for estimating modeled MSU T2 are evaluated. For each CMIP5, it is shown that there exists a model-simulated static weighting function, such that the MSU T2 trend using the weighting function is equivalent to that calculated by RTM. The effect of modeled cloud liquid water on MSU T2 trends in CMIP5 simulations is investigated by comparing the modeled cloud liquid water vertical profile and the weighting function. Moreover, it is found that warming trends of MSU T2 for CMIP5 simulations calculated by the RTM are about 15% less than those using the two traditional static weighting functions. By comparing the model-derived weighting function with the two traditional weighting functions, the reason for the systematical biases is revealed.

Corresponding author address: Xiaogu Zheng, College of Global Change and Earth System Science, Beijing Normal University, No. 19, XinJieKouWai St., HaiDian District, Beijing 100875, China. E-mail: x.zheng@bnu.edu.cn

Abstract

Only a climate model that is able to simulate well the historical atmospheric temperature trend can be used for estimating the future atmospheric temperature trends on different emission scenarios. Satellite-based Microwave Sounding Unit (MSU) brightness temperature in the middle troposphere (T2) is an important analog of midtropospheric atmospheric temperature. So, there is the need to compare the atmospheric temperature trend simulated by the fifth phase of the Coupled Model Intercomparison Project (CMIP5) historical realizations and the observed MSU T2. There are two approaches for estimating modeled MSU T2: apply a global-mean static weighting function to generate the weighted average of the modeled temperature at all atmospheric layers and simulate satellite-view MSU T2 using the model’s output as input into a radiative transfer model (RTM).

In this paper, the two approaches for estimating modeled MSU T2 are evaluated. For each CMIP5, it is shown that there exists a model-simulated static weighting function, such that the MSU T2 trend using the weighting function is equivalent to that calculated by RTM. The effect of modeled cloud liquid water on MSU T2 trends in CMIP5 simulations is investigated by comparing the modeled cloud liquid water vertical profile and the weighting function. Moreover, it is found that warming trends of MSU T2 for CMIP5 simulations calculated by the RTM are about 15% less than those using the two traditional static weighting functions. By comparing the model-derived weighting function with the two traditional weighting functions, the reason for the systematical biases is revealed.

Corresponding author address: Xiaogu Zheng, College of Global Change and Earth System Science, Beijing Normal University, No. 19, XinJieKouWai St., HaiDian District, Beijing 100875, China. E-mail: x.zheng@bnu.edu.cn
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