Evaluating Ice Microphysics in NWP Models with Satellite Observations

Ice clouds are an important part of the Earth’s atmospheric water cycle and have a large impact on the global radiation budget. Yet ice clouds are still poorly understood and their correct representation remains a major challenge for state-of-the-art atmospheric models. Also, the evaluation of the models’ performance with respect to ice clouds is not straightforward; remote sensing instruments, for example, measure other quantities than the models predict. Therefore, two basic evaluation approaches exist: observation-to-model (commonly termed retrieval) and model-to-observation (commonly termed forward operator). Both approaches introduce errors into the comparison of models and observations because of the necessary intrinsic assumptions. The common practice in model evaluation of choosing either the one or the other of these approaches might give an incomplete picture. The present study evaluates the ice microphysics of two numerical weather prediction (NWP) models currently operational at the German weather service (Deutscher Wetterdienst, DWD): the global model GME and the regional model COSMO-DE (an application of the Consortium for Small-scale Modelling, COSMO). In doing so, this study contributes significantly to ongoing model development at DWD. Both case studies and long-term evaluations are carried out. Cloud Satellite (CloudSat) Cloud Profiling Radar (CPR) observations are heavily relied on; the CPR is the first and — up to date — only cloud radar in space and is able to vertically resolve even optically thick clouds. This study focuses on one specific question raised for each of the respective models and while doing so applies both approaches; the standard CloudSat radar reflectivity factor–ice water content (IWC) retrieval for the observation-to-model approach and the forward operator QuickBeam for the model-to-observation approach. This enables for one, to profit from the full informational content, and for the other, to compare both approaches directly to each other and evaluate them. For the global model GME, two precipitation schemes, a diagnostic and a prognostic one, are compared and evaluated. The focus is on the question whether the new prognostic scheme is capable of capturing ice clouds more realistically than the old diagnostic scheme. The prognostic scheme is shown to exhibit improved performance in comparison to the diagnostic scheme in terms of IWC magnitude. In both models snow is found to dominate over cloud ice in total IWC, emphasizing the need for including snow in the model’s radiation budget in the future. Furthermore, one reason for the remaining difference between the prognostic scheme and the observations — the unrealistic fall speed of snow — is identified. As a consequence, the new prognostic scheme with an adapted parameterization for snow fall speed was successfully introduced into operational service at DWD. In the regional NWP model COSMO-DE, a long-known bias between brightness temperatures simulated from COSMO-DE forecasts and those observed by Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) is investigated. The pivotal question is whether a novel two-moment cloud ice scheme exhibits improved performance with respect to this bias and, if that is so, why. It is shown that the novel two-moment cloud ice scheme does indeed reduce this bias and can therefore be considered an improvement in comparison to two standard schemes, the two-category ice scheme and the currently operational three-category ice scheme. The improvement in simulated brightness temperatures is due to a vertical redistribution of cloud ice to lower model levels. Furthermore, sensitivity studies identify two of the four changes introduced, which are responsible for most of the improved performance: the change to a different heterogeneous nucleation scheme and the inclusion of cloud ice sedimentation. Enhanced vertical level number and modifications in aerosol number concentrations reveal comparatively little effect. As a consequence, cloud ice sedimention will be included per se in DWD’s future NWP model, the Icosahedral non-hydrostatic (ICON) model, currently still under development. Concerning the two evaluation approaches conducted, the present study finds the general features in the two evaluations to be captured by both approaches. Some details are captured merely by the one or the other approach, in which case both approaches together give the more complete picture. However, the model-to-observation approach appears to be easier to interpret; its uncertainties are easier to assess than those of the observation-to-model approach and it ensures a better control over the comparison.