Observed and model clouds from a satellite perspective

Over the past decade, a highly efficient and accurate forward operator for visible geostationary satellite observations, known as VISOP, has been developed at LMU (Kostka et al., 2014; Scheck et al., 2016, 2018; Geiss et al., 2021). This operator is based on a fast 1D radiative transfer method and has been adapted for use in operational applications. We used this operator to compare satellite observations of clouds with synthetic visible satellite images generated using 3D model output fields, including pressure, temperature, specific humidity, cloud water, etc. This comparison allowed us to determine the effect of the physically based perturbation scheme (PSP, Kober and Craig, 2016; Hirt et al., 2019; Puh et al., 2023) on clouds in the ICON-D2 model, particularly on their structure. One problem with the PSP scheme is the dry anomaly it introduces in the boundary layer, which manifests itself in a degradation of the prediction of dew point temperature at 2 m and low cloud cover. This is due to the additional mixing caused by the added perturbations, which entrains drier air from above into the boundary layer. Our approach to mitigate these unwanted effects was to first apply the perturbations to a lower height, which improved the forecast with PSP. Thanks to the VISOP operator, we conclude that the effect of PSP on clouds is not as large as initially thought. The resulting clouds are not too unrealistic compared to the unperturbed reference model.

References:

• Geiss, S., Scheck, L., de Lozar, A. & Weissmann, M. (2021) Understanding the model representation of clouds based on visible and infrared satellite observations. Atmospheric Chemistry and Physics, 21(16), 12273–12290. https://doi.org/10.5194/acp-21-12273-2021.
• Hirt, M., S. Rasp, U. Blahak, and G. C. Craig, 2019: Stochastic Parameterization of Processes Leading to Convective Initiation in Kilometer-Scale Models. Mon. Wea. Rev., 147, 3917–3934, https://doi.org/10.1175/MWR-D-19-0060.1.
• Kober, K., and G. C. Craig, 2016: Physically Based Stochastic Perturbations (PSP) in the Boundary Layer to Represent Uncertainty in Convective Initiation. J. Atmos. Sci., 73, 2893–2911, https://doi.org/10.1175/JAS-D-15-0144.1.
• Kostka, P.M., Weissmann, M., Buras, R., Mayer, B. & Stiller, O. (2014) Observation operator for visible and near-infrared satellite reflectances. Journal of Atmospheric and Oceanic Technology, 31(6), 1216–1233.
• Puh, M., Keil, C., Gebhardt, C., Marsigli, C., Hirt, M., Jakub, F., et al. (2023) Physically based stochastic perturbations improve a high-resolution forecast of convection. Quarterly Journal of the Royal Meteorological Society, 149(757), 3582–3592. Available from: https://doi.org/10.1002/qj.4574.
• Scheck, L., Frerebeau, P., Buras-Schnell, R. & Mayer, B. (2016) A fast radiative transfer method for the simulation of visible satellite imagery. Journal of Quantitative Spectroscopy and Radiative Transfer, 175, 54–67.
• Scheck, L., Weissmann, M. & Mayer, B. (2018) Efficient methods to account for cloud-top inclination and cloud overlap in synthetic visible satellite images. Journal of Atmospheric and Oceanic Technology, 35(3), 665–685.