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TEsten von Isotopologen als Diabatischer Heizratenindikator für atmosphärische DatenanalYsen

Antragsteller Dr. Matthias Schneider
Fachliche Zuordnung Physik und Chemie der Atmosphäre
Förderung Förderung von 2019 bis 2023
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 416767181
 
Erstellungsjahr 2023

Zusammenfassung der Projektergebnisse

Clouds and water vapour control atmospheric radiative heating/cooling and condensation or evaporation of water determines the latent heating patterns. The heating then drives atmospheric circulation, thereby causing additional evaporation/condensation and impacting on the distribution of water vapour and clouds, which in turn again modify the atmospheric heating patterns. This strong coupling between moisture pathways, heating and atmospheric circulation is responsible for important climate feedback mechanisms and for the evolution of many severe weather events. Despite of their importance, the heating rates obtained from different current global analyses show significant inconsistencies. This project has investigated the potential of the free tropospheric water vapour isotopologue ratio δD (δD=1000*{(HDO/H2O) / VSMOW - 1} with VSMOW = 3.1152*10^-4 standing for the “Vienna Standard Mean Ocean Water”) for better constraining the analyses uncertainties. Free tropospheric observations of δD are promising in this regard, because they have recently become available with daily and quasi-global coverage, and they are affected by phase transitions and thus directly linked to latent heating. We developed a quasi-operational chain for the processing of a large amount of satellite data. This enabled us to process more than 2 billion satellite observations, representing the whole globe and the 2014-2021 period, and to generate atmospheric profiles products of the various trace gases (H 2O, δD, CH4, N2O, and HNO3) and of temperature (T). These novel datasets were published, and led to international research collaborations in the field of the water cycle and greenhouse gas emissions. We refined an already existing Local Ensemble Transform Kalman Filter (LETKF) tool in order to ensure an optimal setup for the assimilation of the satellite data. In a first study, we investigated the additional impact of assimilating the δD satellite observations on top of the assimilation of “conventional” observations (radiosondes, wind profilers, aircrafts, ships, buoys, surface stations, and wind data derived from satellite and radar) used routinely by the operational assimilation systems. We were able to demonstrate that the additional δD assimilation not only improves the analyses fields of δD, instead there is also a positive impact on the atmospheric dynamics (analysed wind fields). In a second study, we only use observations having the same temporal and horizontal coverage (we use H2O, T, and δD satellite observations). This ensures that the assimilation impacts are caused exclusively by the unique δD information content and not by a possible complementary observational coverage. We found a weak impact of the δD observations for atmospheric situation characterised by a negligible latent heating rate (a negligible heating rate is equivalent to negligible net condensation/evaporation taking place). On the other hand, there is strong positive impact for high latent heating rates. These are the atmospheric situations where a lot of condensation takes place in the context of convective events, and they are the situations with the largest analyses uncertainties and at the same time have the strongest societal impact (determine annual precipitation amounts and are linked to extreme precipitation/flooding). With the additional assimilation of δD we can significantly reduce the analyses uncertainties, where a reduction is most important. In addition, we applied the LETKF water vapour isotopologue assimilation tool within an impact assessment study of a new water vapour isotopologue product (generated from the satellite sensor TROPOMI). The tool allows for comprehensively assessing the uncertainty requirements of a new product in order to be complementary to already existing data products. So far, all our studies have been made in the simulated world (assimilation of simulated data). However, by analysing the {H2O,δD}-pair distribution, we found that the satellite δD observations are frequently affected by the most interesting strong latent heating events. We interpret this as a promising indication for the possibility of improving the analyses in the real world similarly to the improvement demonstrated so far for the simulated world, whereby the availability of a growing number of high-resolution atmospheric isotopologue enabled models will importantly support progress in this field.

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