The Atmospheric Infrared Sounder Obs4MIPs version 2 data set.

The Atmospheric Infrared Sounder (AIRS) Obs4MIPs (Observations for Model Intercomparison Projects) Version 2 data set includes monthly mean tropospheric air temperature, specific humidity, and relative humidity for each calendar month from September 2002 to September 2016, on a global 1° × 1° latitude‐longitude spatial grid and on the Coupled Model Intercomparison Project eight mandatory vertical pressure levels from 1,000 to 300 hPa. It also includes standard error and number of observations, for an estimate of AIRS data retrieval error and sampling uncertainty. Three new technical notes describe the data set. This data set is designed for Coupled Model Intercomparison Project climate model evaluation and has been published at Earth System Grid Federation data centers since April 2018. It adds new monthly mean tropospheric relative humidity data to Obs4MIPs and updates and extends the monthly mean tropospheric air temperature and specific humidity data in AIRS Obs4MIPs Version 1 data set. The data source for this data set is the AIRS Version 6 Level 3 standard monthly mean air temperature, specific humidity, and relative humidity data products in the “TqJoint” grids from the AIRS and Advanced Microwave Sounding Unit A combined physical retrievals. This paper documents this data set in terms of motivation for this data set, data description, data origin and processing procedures, major improvements from the previous version, and caveats for its use in climate model evaluation. Plain Language Summary We have published a new data set designed for climate model evaluation from the infrared and microwave atmospheric sounding system (Atmospheric Infrared Sounder and Advanced Microwave Sounding Unit A) on the NASA Aqua satellite. In this paper, we briefly describe the reasons for providing this data set, its detailed data structure, the original data and processing procedures used to generate this data set, major improvements in comparison to the previous version, and the issues to be considered for climate model evaluation with it.