Comparison of reference upper-air GRUAN and homogenized RHARM data with GNSS-RO

The study of thermodynamical variables, such as temperature and relative humidity in the upper troposphere/lower stratosphere (UT/LS), is one of the key elements for the study of climate change. Several studies estimated trends both regionally and globally in the UT/LS, using both satellite and ground-based data and different measurement techniques. However, the measurement quality and coverage, in time and space, may significantly affect the estimated trends. In this work the temperature and relative humidity in the UT/LS from upper-air reference and homogenized datasets are compared with satellite GNSS-RO (Global Navigation Satellite System - Radio Occultation) and, in particular, the dataset RHARM (Radiosounding HARMonization), and the GNSS-RO with respect to GRUAN (Global Climate Observing System (GCOS) Reference Upper-Air Network) are investigated. Bias from these datasets have been estimated and compared at the GRUAN stations, used as the reference. Same quantities are also intercompared since 2001 at all the stations available in RHARM.

The comparison with GRUAN includes ascents since 2008 to 2024 and covers only mandatory levels from 850 hPa to 10 hPa on data provided by five stations (Sodankyla, Lindenberg, Ny Alesund, Lamont and Barrow), selected because of their long and dense data records. The RHARM data are matched to the GRUAN data applying an interpolation in a range of 40 Pa around mandatory levels between 850 hPa and 300 hPa and of 5 Pa below 300 hPa pressure. Then, a linear interpolation is applied between the minimum and the maximum pressures selected according to these criteria, Madonna (2022), Haimberger (2014).

Instead, the GNSS-RO data are matched to the GRUAN stations:

• selecting all the profiles provided within a space-time mismatch of 200km - 3h, interpolating the samples at the mandatory pressure levels;
• analyzing the profiles in function of the bending angle provided by GNSS-RO data.

The results of the comparison will be discussed: preliminary analysis, in terms of bias, shows a good agreement between RHARM and GRUAN, and a closer agreement of GNSS-RO with RHARM.

 

REFERENCES

 

Haimberger, L., 2012: Homogenization of the Global Radiosonde Temperature Dataset through Combined Comparison with Reanalysis Background Series and Neighboring Stations. J. Climate, 25, 8108–8131.

Madonna, F., 2022: The new Radiosounding HARMonization (RHARM) data set of homogenized radiosounding temperature, humidity, and wind profiles with uncertainties. Journal of Geophysical Research: Atmospheres, 127, e2021JD035220.