Large-eddy simulations (LES) with the newThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. R. Heinze et al.at building confidence in the model's ability to simulate small-to mesoscale variability in turbulence, clouds and precipitation. The results are encouraging: the high-resolution model matches the observed variability much better at small-to mesoscales than the coarser resolved reference model. In its highest grid resolution, the simulated turbulence profiles are realistic and column water vapour matches the observed temporal variability at short time-scales. Despite being somewhat too large and too frequent, small cumulus clouds are well represented in comparison with satellite data, as is the shape of the cloud size spectrum. Variability of cloud water matches the satellite observations much better in ICON than in the reference model. In this sense, it is concluded that the model is fit for the purpose of using its output for parametrization development, despite the potential to improve further some important aspects of processes that are also parametrized in the high-resolution model.
An advanced package of microwave remote sensing instrumentation has been developed for the operation on the new German High Altitude LOng range research aircraft (HALO). The HALO Microwave Package, HAMP, consists of two nadir-looking instruments: a cloud radar at 36 GHz and a suite of passive microwave radiometers with 26 frequencies in different bands between 22.24 and 183.31 ± 12.5 GHz. We present a description of HAMP's instrumentation together with an illustration of its potential. To demonstrate this potential, synthetic measurements for the implemented passive microwave frequencies and the cloud radar based on cloud-resolving and radiative transfer model calculations were performed. These illustrate the advantage of HAMP's chosen frequency coverage, which allows for improved detection of hydrometeors both via the emission and scattering of radiation. Regression algorithms compare HAMP retrieval with standard satellite instruments from polar orbiters and show its advantages particularly for the lower atmosphere with a root-mean-square error reduced by 5 and 15 % for temperature and humidity, respectively. HAMP's main advantage is the high spatial resolution of about 1 km, which is illustrated by first measurements from test flights. Together these qualities make it an exciting tool for gaining a better understanding of cloud processes, testing retrieval algorithms, defining future satellite instrument specifications, and validating platforms after they have been placed in orbit.Published by Copernicus Publications on behalf of the European Geosciences Union.
This study investigates the benefits of a satellite HYperspectral Microwave Sensor (HYMS) for the retrieval of atmospheric temperature and humidity profiles, in the context of numerical weather prediction (NWP). In the infrared, hyperspectral instruments have already improved the accuracy of NWP forecasts. Microwave instruments so far only provide observations for a limited number of carefully selected channels. An information content analysis is conducted here to assess the impact of hyperspectral microwave measurements on the retrieval of temperature and water vapor profiles under clear‐sky conditions. It uses radiative transfer simulations over a large variety of atmospheric situations. It accounts for realistic observation (instrument and radiative transfer) noise and for a priori information assumptions compatible with NWP practices. The estimated retrieval performance of the HYMS instrument is compared to those of the microwave instruments to be deployed on board the future generation of European operational meteorological satellites (MetOp‐SG). The results confirm the positive impact of a HYMS instrument on the atmospheric profiling capabilities compared to MetOp‐SG. Temperature retrieval uncertainty, compared to a priori information, is reduced by 2 to 10%, depending on the atmospheric height, and improvement rates are much higher than what will be obtained with MetOp‐SG. For humidity sounding these improvements can reach 30%, a significant benefit as compared to MetOp‐SG results especially below 250 hPa. The results are not very sensitive to the instrument noise, under our assumptions. The main impact provided by the hyperspectral information originates from the higher resolution in the O2 band around 60 GHz. The results are presented over ocean at nadir, but similar conclusions are obtained for other incidence angles and over land.
Abstract. Forward models are a key tool to generate synthetic observations given knowledge of the atmospheric state. In this way, they are an integral part of inversion algorithms that aim to retrieve geophysical variables from observations or in data assimilation. Their application for the exploitation of the full information content of remote sensing observations becomes increasingly important when these are used to evaluate the performance of cloud-resolving models (CRMs). Herein, CRM profiles or fields provide the input to the forward model whose simulation results are subsequently compared to the observations. This paper introduces the freely available comprehensive microwave forward model PAMTRA (Passive and Active Microwave TRAnsfer), demonstrates its capabilities to simulate passive and active measurements across the microwave spectral region for upward- and downward-looking geometries, and illustrates how the forward simulations can be used to evaluate CRMs and to interpret measurements to improve our understanding of cloud processes. PAMTRA is unique as it treats passive and active radiative transfer (RT) in a consistent way with the passive forward model providing upwelling and downwelling polarized brightness temperatures and radiances for arbitrary observation angles. The active part is capable of simulating the full radar Doppler spectrum and its moments. PAMTRA is designed to be flexible with respect to instrument specifications and interfaces to many different formats of input and output, especially CRMs, spanning the range from bin-resolved microphysical output to one- and two-moment schemes, and to in situ measured hydrometeor properties. A specific highlight is the incorporation of the self-similar Rayleigh–Gans approximation (SSRGA) for both active and passive applications, which becomes especially important for the investigation of frozen hydrometeors.
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