Airborne Water Vapor Observations for ISSR Analysis and improved Humidity Prediction in the Upper Troposphere using the ICON Model

The persistence of aircraft contrails and their climate impact are strongly controlled by the extent, lifetime, and properties of ice-supersaturated regions (ISSRs). Reliable prediction of such conditions remains challenging due to uncertainties in the representation of water vapor in numerical weather prediction models at typical cruising altitudes in the upper troposphere. In-situ airborne observations are therefore essential for evaluating model performance and assessing the potential benefit of additional humidity data sources.

This study employs three complementary data sources: (1) high-resolution in-situ water vapor measurements obtained with the Sophisticated Hygrometer for Atmospheric Research (SHARC) and a modified Water Vapor Sensing System II (WVSS-II) aboard the High Altitude and Long-Range Research Aircraft (HALO); (2) routine aircraft observations from the Aircraft Meteorological Data Relay (AMDAR) program using WVSS-II sensors; and (3) numerical weather model output from the ICON-DREAM reanalysis of the German Weather Service (DWD).

To evaluate the data quality of WVSS-II sensors on commercial aircraft, comparisons between HALO reference measurements and AMDAR observations with spatial overlap during the Arctic Springtime Chemistry Climate Investigations (ASCCI) field campaign are conducted. An indirect comparison uses the entire dataset to analyze water vapor concentration (H₂O) and relative humidity with respect to ice (RH_i) as a function of potential temperature. In addition, a short parallel flight segment of HALO and a commercial flight at the same altitude was performed which allows for a direct comparison of both sensors. For both comparison approaches, agreement and variability between the datasets are assessed using statistical metrics. Furthermore, the HALO dataset is used to evaluate and quantify the representation of RH_i in ICON first-guess fields, covering multiple campaign periods between 2012 and 2025 with a total of 878 flight hours.

Building on the previous steps, ongoing work investigates the use of AMDAR humidity observations in dedicated ICON data assimilation experiments to evaluate their impact on humidity prediction. Differences between routine model simulations and assimilation runs are analyzed to assess potential improvements in upper-tropospheric humidity forecasts relevant for ISSR prediction.