Mario Mech

Radiative Transfer Simulations Using Mesoscale Cloud Model Outputs: Comparisons with Passive Microwave and Infrared Satellite Observations for Midlatitudes

Abstract Real midlatitude meteorological cases are simulated over western Europe with the cloud mesoscale model Meso-NH, and the outputs are used to calculate brightness temperatures at microwave frequencies with the Atmospheric Transmission at Microwave (ATM) radiative transfer model. Satellite-observed brightness temperatures (TBs) from the Advanced Microwave Scanning Unit B (AMSU-B) and the Special Sensor Microwave Imager (SSM/I) are compared to the simulated ones. In this paper, one specific situation is examined in detail. The infrared responses have also been calculated and compared to the Meteosat coincident observations. Overall agreement is obtained between the simulated and the observed brightness temperatures in the microwave and in the infrared. The large-scale dynamical structure of the cloud system is well captured by Meso-NH. However, in regions with large quantities of frozen hydrometeors, the comparison shows that the simulated microwave TBs are higher than the measured ones in the window...

The general observation period 2007 within the priority program on quantitative precipitation forecasting: concept and first results

In the year 2007 a General Observation Period (GOP) has been performed within the German Priority Program on Quantitative Precipitation Forecasting (PQP). By optimizing the use of existing instrumentation a large data set of in-situ and remote sensing instruments with special focus on water cycle variables was gathered over the full year cycle. The area of interest covered central Europe with increasing focus towards the Black Forest where the Convective and Orographically-induced Precipitation Study (COPS) took place from June to August 2007. Thus the GOP includes a variety of precipitation systems in order to relate the COPS results to a larger spatial scale. For a timely use of the data, forecasts of the numerical weather prediction models COSMO-EU and COSMO-DE of the German Meteorological Service were tailored to match the observations and perform model evaluation in a near real-time environment. The ultimate goal is to identify and distinguish between different kinds of model deficits and to improve process understanding.

A Midlatitude Precipitating Cloud Database Validated with Satellite Observations

The simulations of five midlatitude precipitating events by the nonhydrostatic mesoscale model Meso-NH are analyzed. These cases cover contrasted precipitation situations from 30° to 60°N, which are typical of midlatitudes. They include a frontal case with light precipitation over the Rhine River area (10 February 2000), a long-lasting precipitation event at Hoek van Holland, Netherlands (19 September 2001), a moderate rain case over the Elbe (12 August 2002), an intense rain case over Algiers (10 November 2001), and the “millennium storm” in the United Kingdom (30 October 2000). The physically consistent hydrometeor and thermodynamic outputs are used to generate a database for cloud and precipitation retrievals. The hydrometeor vertical profiles that were generated vary mostly with the 0°C isotherm, located between 1 and 3 km in height depending on the case. The characteristics of this midlatitude database are complementary to the GPROF database, which mostly concentrates on tropical situations. The realism of the simulations is evaluated against satellite observations by comparing synthetic brightness temperatures (BTs) with Advanced Microwave Sounding Unit (AMSU), Special Sensor Microwave Imager (SSM/I), and Meteosat observations. The good reproduction of the BT distributions by the model is exploited by calculating categorical scores for verification purposes. The comparison with 3-hourly Meteosat observations demonstrates the ability of the model to forecast the time evolution of the cloud cover, the latter being better predicted for the stratiform cases than for others. The comparison with AMSU-B measurements shows the skill of the model to predict rainfall at the correct location.

Information Content of Millimeter-Wave Observations for Hydrometeor Properties in Mid-Latitudes

For future remote sensing applications the potential of the millimeter wavelength range for precipitation observations from geostationary orbits is investigated. Therefore, a database consisting of hydrometeor profiles from various mid-latitude precipitation cases over Europe and corresponding simulated brightness temperatures at 18 microwave frequencies was built using the cloud resolving model Meso-NH and the radiative transfer model micro wave model. The information content of the database was investigated by applying simple statistical methods, as well as developing first-order retrieval approaches. The results show that, particularly for snow and graupel, the total column content can be retrieved accurately with relative errors smaller than 25% in dominantly stratiform precipitation cases over land and ocean surfaces. The performance for rain-water path is similar to the one for graupel and snow in light precipitation cases. For the cases with higher precipitation amounts, the relative errors for rain-water path are larger particularly over land. The same behavior can be seen in the surface rain rate retrieval with the difference that the relative errors are doubled in comparison to the rain-water path. Algorithms with reduced number of frequencies show that window channels at higher frequencies are important for the surface rain rate retrieval because these are sensitive to the scattering in the ice phase related to the rain below. For the frozen hydrometeor retrieval, good results can be achieved by retrieval algorithms based only on frequencies at 150 GHz and above which are suitable for geostationary applications due to their reduced demands concerning the antenna size.

Validating precipitation forecasts using remote sensor synergy: A case study approach

Several types of remote sensing data are applied synergistically to evaluate the chain of microphysical processes leading to precipitation in a high-resolution numerical weather prediction model. The data provides information relating to (i) cloud-top temperature and optical depth (SEVERI), (ii) ice cloud amount (AMSUB), (iii) type and amount of precipitation particles (polarimetric radar), and (iv) surface precipitation (raingauge-calibrated radar data). Forecasts are produced by the COSMO-DE model of the German weather service, with a horizontal resolution of 2.8 km. The comparison with data is done in a model-to-observation framework, that is, forward operators are applied to the model output to produce synthetic data sets that can be directly compared to the observations. Additional diagnostics based on diurnal cycle and system tracking are also considered. Two case studies over Germany from the summer of 2006 are examined. The first case is dominated by widespread stratiform precipitation. Together the various data sets show that the model overestimates the amount of high cloud, while underestimating the concentration of ice scatterers and overestimating reflectivity and differential reflectivity (ZDR). This indicates errors in both the amount and the size distributions of cloud and precipitation particles in the model’s microphysical parameterization. In the second case a narrow band of convective precipitation is embedded in a cold front, with significant modulation by the diurnal cycle. The model fails to show a significant diurnal cycle in cloud amount, and the timing and duration of convective cells is incorrect. In this case, both the microphysical parameterization, and errors in the interaction of the simulated front with the orography of the Alps appear to contribute. These results demonstrate the potential of combinations of remote sensing data for model evaluation, although a long-term trial will be required to determine whether the errors seen in the case studies are characteristic for COSMO-DE. Zusammenfassung Verschiedene Fernerkundungsdaten werden synergetisch zur Evaluierung der mikrophysikalischen Prozesskette der Niederschlagsgenerierung in einem hochaufgelosten numerischen Wettervorhersagemodell genutzt. Die Daten beinhalten Informationen uber (i) Wolkenobergrenzentemperatur und optische Dicke (SEVIRI), (ii) Vorkommen von Eis und Schnee (AMSU), (iii) Art und Gehalt an Niederschlagspartikeln (polarimetrisches Radar) und (iv) Bodenniederschlag (Radar mit Niederschlagssammler kalibriert). Die Vorhersagen stammen vom COSMO-DE des Deutschen Wetterdiensts mit einer horizontalen Auflosung von 2,8 km. Der Vergleich wird mittels eines “Modell zu Beobachtung”-Ansatzes durchgefuhrt, d. h. Vorwartsoperatoren werden auf den Modelloutput angewendet, um synthetische Beobachtungen zu generieren, die direkt mit den Beobachtungen verglichen werden konnen. Zusatzliche Diagnostiken basierend auf Tagesgang und Verfolgung einzelner Konvektionszellen werden ebenfalls angewendet. Zwei Fallstudien uber Deutschland aus dem Sommer 2006 werden untersucht. Die erste Fallstudie wird von ausgedehntem Niederschlag dominiert. Die verschiedenen Daten zeigen, dass das Modell den Anteil hoher, stratiformer Wolken uberschatzt, wahrend die Konzentration groserer streuender Eispartikel unter- und die bodennahe Reflektivitat und die differentielle Reflektivitat (ZDR) uberschatzt werden. Dies deutet auf Fehler in den mikrophysikalischen Parameterisierungen sowie in den Annahmen zur Grosenverteilung von Wolken- und Niederschlagspartikeln im Modell hin. In der zweiten Fallstudie ist ein enges Band konvektiven Niederschlages eingebettet in eine Kaltfront, mit signifikanter Modulation durch den Tagesgang. Dem Modell gelingt es nicht einen deutlichen Tagesgang in der Wolkenbedeckung zu reproduzieren und Einsetzen sowie Lebensdauer der konvektiven Zellen werden nicht getroffen. In diesem Fall scheinen sowohl die mikrophysikalischen Parametrisierungen als auch die Wechselwirkung der Front mit der Orographie der Alpen zum Fehler der Vorhersage beizutragen. Diese Resultate zeigen das Potential der Kombination verschiedener Fernerkundungsdaten fur die Modellevaluierung. Um zu uberprufen, dass diese Fehler charakteristisch fur das COSMO-DE sind, ist jedoch eine langfristige Vergleichsstudie notig.

The North Atlantic Waveguide and Downstream Impact Experiment

Multi-aircraft and ground-based observations were made over the North Atlantic in fall 2016 to investigate the importance of diabatic processes for midlatitude weather. The North Atlantic Waveguide and Downstream Impact Experiment (NAWDEX) explored the impact of diabatic processes on disturbances of the jet stream and their influence on downstream high-impact weather through the deployment of four research aircraft, each with a sophisticated set of remote-sensing and in situ instruments, and coordinated with a suite of ground-based measurements. A total of 49 research flights were performed, including, for the first time, coordinated flights of the four aircraft; the German High Altitude and LOng Range Research Aircraft (HALO), the Deutsches Zentrum fur Luft- und Raumfahrt (DLR) Dassault Falcon 20, the French Service des Avions Francais Instrumentes pour la Recherche en Environnement (SAFIRE) Falcon 20, and the British Facility for Airborne Atmospheric Measurements (FAAM) BAe 146. The observation period from 17 Sep to 22 Oct 2016 with frequently occurring extratropical and tropical cyclones was ideal to investigate midlatitude weather over the North Atlantic. NAWDEX featured three sequences of upstream triggers of waveguide disturbances, their dynamic interaction with the jet stream, subsequent development, and eventual downstream weather impact on Europe. Examples are presented to highlight the wealth of phenomena that were sampled, the comprehensive coverage and the multi-faceted nature of the measurements. This unique dataset forms the basis for future case studies and detailed evaluations of weather and climate predictions to improve our understanding of diabatic influences on Rossby waves and downstream impact of weather systems affecting Europe.

Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities

Satellite and ground-based microwave radiometers are routinely used for the retrieval of liquid water path (LWP) under all atmospheric conditions. The retrieval of water vapor and LWP from ground-based radiometers during rain has proved to be a difficult challenge for two principal reasons: the inadequacy of the nonscattering approximation in precipitating clouds and the deposition of rain drops on the instrument’s radome. In this paper, we combine model computations and real ground-based, zenith-viewing passive microwave radiometer brightness temperature measurements to investigate how total, cloud, and rain LWP retrievals are affected by assumptions on the cloud drop size distribution (DSD) and under which conditions a nonscattering approximation can be considered reasonably accurate. Results show that until the drop effective diameter is larger than ~200

HAMP – the microwave package on the High Altitude and LOng range research aircraft (HALO)

\mu \text{m}

Evaluation of ice and snow content in the global numerical weather prediction model GME with CloudSat

, a nonscattering approximation yields results that are still accurate at frequencies less than 90 GHz. For larger drop sizes, it is shown that higher microwave frequencies contain useful information that can be used to separate cloud and rain LWP provided that the vertical distribution of hydrometeors, as well as the DSD, is reasonably known. The choice of the DSD parameters becomes important to ensure retrievals that are consistent with the measurements. A physical retrieval is tested on a synthetic data set and is then used to retrieve total, cloud, and rain LWP from radiometric measurements during two drizzling cases at the atmospheric radiation measurement Eastern North Atlantic site.