Evaluation of downward and upward solar irradiances simulated by the Integrated Forecasting System of ECMWF using airborne observations above Arctic low-level clouds

• Published in: Atmospheric Chemistry and Physics
• Main Authors: Müller, Hanno, Ehrlich, André, Jäkel, Evelyn, Röttenbacher, Johannes, Kirbus, Benjamin, Schäfer, Michael, Hogan, Robin J., Wendisch, Manfred
• Format: Text
• Language: English
• Published: 2024
• Subjects: albedo; Sea ice
• Online Access: https://doi.org/10.5194/acp-24-4157-2024; https://acp.copernicus.org/articles/24/4157/2024/

The simulations of upward and downward irradiances by the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts are compared with broadband solar irradiance measurements from the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign. For this purpose, offline radiative transfer simulations were performed with the ecRad radiation scheme using the operational IFS output. The simulations of the downward solar irradiance agree within the measurement uncertainty. However, the IFS underestimates the reflected solar irradiances above sea ice significantly by − 35 W m −2 . Above open ocean, the agreement is closer, with an overestimation of 28 W m −2 . A sensitivity study using measured surface and cloud properties is performed with ecRad to quantify the contributions of the surface albedo, cloud fraction, ice and liquid water path and cloud droplet number concentration to the observed bias. It shows that the IFS sea ice albedo climatology underestimates the observed sea ice albedo, causing more than 50 % of the bias. Considering the higher variability of in situ observations in the parameterization of the cloud droplet number concentration leads to a smaller bias of − 27 W m −2 above sea ice and a larger bias of 48 W m −2 above open ocean by increasing the range from 36–69 to 36–200 cm −3 . Above sea ice, realistic surface albedos, cloud droplet number concentrations and liquid water paths contribute most to the bias improvement. Above open ocean, realistic cloud fractions and liquid water paths are most important for reducing the model–observation differences.