Fabrizio Marra[1]
CNR-IMAA, Tito Scalo (PZ), Italy
1. INTRODUCTION
The study of termodinamical 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 measurements 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), CUON (Comprehensive upper-air observation networks are compared) 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 intercompares since 2001 at all the stations available in CUON and RHARM.
2. TEMPERATURE AND RELATIVE HUMIDITY COMPARISON
The comparison with GRUAN includes ascents since 2008 to 2023 and covers only mandatory levels from 850 hPa to 10 hPa on data provided by six stations (Sodankyla, Lindenberg, Tateno, Ny Alesund, Payerne and Lamont), selected because of their long and dense data records. The CUON and RHARM data are matched to the GRUAN data applying a threshold of 40 Pa for levels between 850 hPa and 300 hPa and of 5 hPa 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. Preliminary analysis, in terms of bias, shows a good agreement between RHARM and GRUAN, and a closer agreement of GNSS-RO with CUON, Dirksen (2014).
3. TREND ESTIMATION AND COMPARISON
Temperature and relative humidity trends, calculated on the stations average monthly anomalies, are under investigation.
4. REFERENCES
Dirksen, R. J., 2014: Reference quality upper-air measurements: GRUAN data processing for the Vaisala RS92 radiosonde, Atmos. Meas. Tech., 7, 4463–4490.
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.
[1]Corresponding author address: Fabrizio Marra, CNR-IMAA, Tito Scalo (PZ); e-mail: fabriziomarra@cnr.it.
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