Construction of Temperature Climate Data Records in the Upper Troposphere and Lower Stratosphere Using Multiple RO Missions from 2006 to 2023 at NESDIS/STAR

The atmospheric temperature in the upper troposphere and lower stratosphere (UTLS) provide a clear fingerprint of global warming signals. An accurate UTLS temperature trend estimate is vital to understand climate variation and its causes. In the past 40 years, spaceborne microwave (MW) radiometers and radiosonde observations (RAOBs) have been primary data sources for upper-air temperature trend detection. However, evaluating long-term temperature changes from these platforms is challenging owing to the trend uncertainties caused by the instrument changes over time, changes in the observational network, and inconsistent calibration and correction approaches of the inter-satellite offsets among missions.

Complementing with MW sounders and RAOBS, Global Navigation Satellite System (GNSS) Radio Occultation (RO) data are useful for weather forecasting, atmospheric studies, and climate monitoring. Because the raw RO data are time delay measurements between GNSS emitters and receivers whose clocks are traceable to the atomic clocks on the ground (SI traceability), the RO data are of exceptionally high stability where the inter-mission differences are almost equal to zero.

NOAA Center for Satellite Applications and Research (STAR) has developed capabilities as a GNSS RO science and data center (STAR RO DSC). Like other NOAA’s infrared and microwave satellite missions, we aim to establish enterprise RO processing algorithms for all RO missions. In this study, we will demonstrate how we used the STAR-reconfigured Radio Occultation Processing Package (ROPP) to produce the RO bending angle, refractivity, and dry temperature profiles from multiple RO missions, including Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC-1, launched in 2006), Constellation Observing System for Meteorology, Ionosphere, and Climate-2 (COSMIC-2, launched in 2019), Spire (data available since 2020), Meteorological Operational Satellite-A (Metop-A), -B, and -C. In addition, we also demonstrate how we construct consistent temperature climate data records (CDRs) in the UTLS from 2006 to 2023. Because RO measurements from those missions are of different temporal and spatial coverages, we must first remove the sampling errors to generate consistent monthly mean climatology (MMC). Here we use three reanalysis datasets (i.e., fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5), Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and Japanese 55-year Reanalysis (JRA-55)) to estimate the related sampling errors and the uncertainty of sampling errors. Then we compare the STAR UTLS temperature MMCs with the MMC produced by EUMETSAT RO Meteorology Satellite Application Facility (ROM SAF) and the ERA5 reanalysis dataset. Results show that STAR temperature MMCs are consistent with ERA5 reanalysis and ROM SAF MMCs from 2006 to 2023. The results show STAR temperature MMC has a robust cooling trend within the lower stratosphere (20-30 km) at a rate of -0.24 ± 0.04 K/Decade, coupled with a warming trend within the upper troposphere (8-12 km) at a rate of 0.32 ± 0.08 K/Decade.

Disclaimer: The scientific results and conclusions, as well as any views or opinions expressed herein, are those of the author(s) and do not necessarily reflect those of NOAA or the Department of Commerce.