Cold and dry Arctic air masses moving from sea ice southward over the open ocean rapidly heat up, moisten, and form clouds. Diabatic heating and moistening rates in such marine cold air outbreaks (CAOs) are key to understanding their dynamics. While state-of-the-art atmospheric reanalysis products are commonly used to estimate these rates, the uncertainties of these reanalysis data sets especially in 4-dimensional space required to calculate them remain largely unspecified. Therefore, we present an analysis based on actual quasi-Lagrangian observations, which offer direct insights into these processes and which were conducted during the HALO-(AC)3 Arctic airborne campaign. From the measurements during a case study of a CAO on 01 April 2022, a maximum moistening and diabatic heating larger than 0.25 g kg-1h-1 and 6 K h-1, respectively, were deduced. Clouds forming within 30 minutes of the off-ice drift then intensified the vertical mixing. In the later stages of the CAO, maximum increases of solar albedo of around 0.03-0.06 h-1 were observed. We suggest that such data collected in a dedicated Lagrangian framework will serve as invaluable input for the benchmarking of numerical weather-prediction models and modern reanalysis products.

Arctic air masses undergo intense transformations when moving southward from closed sea ice to warmer open waters in marine cold-Air outbreaks (CAOs). Due to the lack of measurements of diabatic heating and moisture uptake rates along CAO flows, studies often depend on atmospheric reanalysis output. However, the uncertainties connected to those datasets remain unclear. Here, we present height-resolved airborne observations of diabatic heating, moisture uptake, and cloud evolution measured in a quasi-Lagrangian manner. The investigated CAO was observed on 1 April 2022 during the HALO-(AC)3 campaign. Shortly after passing the sea-ice edge, maximum diabatic heating rates over 6ĝ€¯Kh-1 and moisture uptake over 0.3ĝ€¯gkg-1h-1 were measured near the surface. Clouds started forming and vertical mixing within the deepening boundary layer intensified. The quasi-Lagrangian observations are compared with the fifth-generation global reanalysis (ERA5) and the Copernicus Arctic Regional Reanalysis (CARRA). Compared to these observations, the mean absolute errors of ERA5 versus CARRA data are 14ĝ€¯% higher for air temperature over sea ice (1.14ĝ€¯K versus 1.00ĝ€¯K) and 62ĝ€¯% higher for specific humidity over ice-free ocean (0.112ĝ€¯gkg-1 versus 0.069ĝ€¯gkg-1). We relate these differences to issues with the representation of the marginal ice zone and corresponding surface fluxes in ERA5, as well as the cloud scheme producing excess liquid-bearing, precipitating clouds, which causes a too-dry marine boundary layer. CARRA's high spatial resolution and demonstrated higher fidelity towards observations make it a promising candidate for further studies on Arctic air mass transformations.