Assessing Consistency of Microwave Sounding Data from FY-3 and NOAA Satellites for Climate Applications

Since the inaugural launch of China’s Fengyun-3 (FY-3) satellite series in 2008, the on-board Microwave Temperature Sounders (MWTS) have provided critical atmospheric sounding data for numerical weather prediction and extreme weather monitoring. However, their application in climate research remains limited. To establish FY-3 long-term Fundamental Climate Data Records (FCDRs)—a cornerstone of climate studies—a comprehensive assessment of data consistency between the China FY-3 satellites and their counterparts from the U.S. National Oceanic and Atmospheric Administration (NOAA) is essential. This study systematically evaluates the inter-satellite consistency between FY-3 MWTS observations and three datasets of NOAA FCDRs (produced by the Center for Satellite Applications and Research STAR, the Remote Sensing Systems RSS, and the University of Alabama in Huntsville UAH). The analysis focuses on comparing brightness temperatures and their anomalies over an extended period (2009–2024). Aligning with the 2022 Global Climate Observing System (GCOS) Essential Climate Variables (ECVs) requirements (GCOS-245), the present study quantifies the accuracy and stability of both operational and recalibrated FY-3 brightness temperatures on a global grid scale. Multiple statistical metrics are employed, including root mean square error (RMSE), standard deviation (SD), bias, and linear trend. Key findings are as follows. 1) FY-3 MWTS observations effectively capture the characteristic seasonal cycles and vertical atmospheric structures of brightness temperatures, confirming their basic reliability for climate-related analysis. 2) Significant discontinuities in brightness temperatures are observed in the upper troposphere and lower stratosphere for earlier FY-3 satellites (FY-3A/3B/3C), indicating limitations in their long-term climate consistency. In contrast, newer satellites (FY-3D/3E/3F) show substantially improved consistency with NOAA FCDRs. 3) the recalibrated data of FY-3D exhibit a marked quality improvement, with RMSE reduced by 60% compared to FY-3D operational observations. This recalibrated FY-3D dataset is therefore recommended as the preferred choice for climate applications. 4) Even the operational (non-recalibrated) brightness temperature data of FY-3D achieves remarkable consistency with global benchmarks, boasting a global mean accuracy of 0.270 ± 0.039 K—well within the accuracy thresholds specified by GCOS for ECVs. 5) For specific MWTS channels, the global mean brightness temperatures of Channels 4 (over ocean), 6, and 9 generally meet the stability requirements for climate monitoring, further supporting their utility in long-term climate studies. 6) Larger RMSEs of FY-3D operational data are identified in two key regions: the stratosphere over high latitudes, and the mid-troposphere over topographically complex areas (e.g., the Tibetan Plateau, the Andes Mountains, and parts of Africa). These discrepancies are attributed to two technical factors: non-linearity in the MWTS calibration process and orbital drift of the FY-3 satellites. These findings validate the climate monitoring capabilities of FY-3 MWTS observations while identifying key pathways for data quality improvement, thereby constituting a pivotal step from product generation to climate application.