The Atmospheric Infrared Sounder (AIRS) Observations for Model Intercomparison Projects (Obs4MIPs) Version 2.0 (V2.0) monthly mean tropospheric air temperature, specific humidity, and relative humidity profile data were designed for climate model evaluation in the context of the Coupled Model Intercomparison Project (CMIP). Due to the limitations of the Aqua satellite orbit and the AIRS retrieval algorithm, the sampling biases of the AIRS Obs4MIPs V2.0 data can be large for certain cases and must be considered when the AIRS Obs4MIPs V2.0 data are used for climate model evaluation. In this study, we estimate the sampling biases of the AIRS Obs4MIPs V2.0 data based on the fifth generation of the European Centre for Medium‐Range Weather Forecasts (ECMWF) (ERA5) reanalysis and cross‐check them using the Modern‐Era Retrospective Analysis for Research and Application, Version 2 (MERRA‐2) reanalysis. We then remove the estimated sampling biases from the AIRS Obs4MIPs V2.0 data and produce the sampling‐bias‐corrected AIRS Obs4MIPs V2.1 data that have been published at the Earth System Grid Federation (ESGF) data centers and should be used in the future for climate model evaluation.

中文翻译：

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估计和消除AIRS Obs4MIPs V2数据的采样偏差

针对模型比较项目（Obs4MIPs）2.0版（V2.0）的对流大气月平均温度，比湿度和相对湿度分布数据，设计了大气红外测深仪（AIRS）观测值，以在耦合模型比较项目的背景下进行气候模型评估（CMIP）。由于Aqua卫星轨道和AIRS检索算法的局限性，在某些情况下，AIRS Obs4MIPs V2.0数据的采样偏差可能很大，在将AIRS Obs4MIPs V2.0数据用于气候模型评估时必须考虑。在这项研究中，我们估计了AIRS Obs4MIP V2的采样偏差。0数据基于第五代欧洲中距离天气预报中心（ECMWF）（ERA5）重新分析，并使用研究和应用的现代时代回顾性分析版本2（MERRA-2）重新分析。然后，我们从AIRS Obs4MIPs V2.0数据中删除估计的采样偏差，并生成已在地球系统网格联合会（ESGF）数据中心发布并应在以下情况中使用的经过采样偏差校正的AIRS Obs4MIPs V2.1数据。气候模型评估的未来。