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 für Luft- und Raumfahrt (DLR) Dassault Falcon 20, the French Service des Avions Français Instrumentés pour la Recherche en Environnement (SAFIRE) Falcon 20, and the British Facility for Airborne Atmospheric Measurements (FAAM) BAe 146. The observation period from 17 September to 22 October 2016 with frequently occurring extratropical and tropical cyclones was ideal for investigating midlatitude weather over the North Atlantic. NAWDEX featured three sequences of upstream triggers of waveguide disturbances, as well as 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 multifaceted 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 the downstream impacts of weather systems affecting Europe.

Between 1 September and 4 October 2014, a combined airborne and ground-based measurement campaign was conducted to study tropical deep convective clouds over the Brazilian Amazon rain forest. The new German research aircraft, High Altitude and Long Range Research Aircraft (HALO), a modified Gulfstream G550, and extensive ground-based instrumentation were deployed in and near Manaus (State of Amazonas). The campaign was part of the German–Brazilian Aerosol, Cloud, Precipitation, and Radiation Interactions and Dynamics of Convective Cloud Systems–Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modeling and to the GPM (Global Precipitation Measurement) (ACRIDICON– CHUVA) venture to quantify aerosol–cloud–precipitation interactions and their thermodynamic, dynamic, and radiative effects by in situ and remote sensing measurements over Amazonia. The ACRIDICON–CHUVA field observations were carried out in cooperation with the second intensive operating period of Green Ocean Amazon 2014/15 (GoAmazon2014/5). In this paper we focus on the airborne data measured on HALO, which was equipped with about 30 in situ and remote sensing instruments for meteorological, trace gas, aerosol, cloud, precipitation, and spectral solar radiation measurements. Fourteen research flights with a total duration of 96 flight hours were performed. Five scientific topics were pursued: 1) cloud vertical evolution and life cycle (cloud profiling), 2) cloud processing of aerosol particles and trace gases (inflow and outflow), 3) satellite and radar validation (cloud products), 4) vertical transport and mixing (tracer experiment), and 5) cloud formation over forested/deforested areas. Data were collected in near-pristine atmospheric conditions and in environments polluted by biomass burning and urban emissions. The paper presents a general introduction of the ACRIDICON– CHUVA campaign (motivation and addressed research topics) and of HALO with its extensive instrument package, as well as a presentation of a few selected measurement results acquired during the flights for some selected scientific topics.

Cb-TRAM is a new fully automated tracking and nowcasting algorithm. Intense convective cells are detected, tracked and discriminated with respect to onset, rapid development, and mature phase. The detection is based on Meteosat-8 SEVIRI (Spinning Enhanced Visible and Infra-Red Imager) data from the broad band high resolution visible, infra-red 6.2 mm (water vapour), and the infra-red 10.8 mm channels. In addition, tropopause temperature data from ECMWF operational model analyses is utilised as an adaptive detection criterion. The tracking is based on geographical overlap between current detections and first guess patterns of cells predicted from preceeding time steps. The first guess patterns as well as short range forecast extrapolations are obtained with the aid of a new image matching algorithm providing complete fields of approximate differential cloud motion. Based on these motion vector fields interpolation and extrapolation of satellite data are obtained which allow to generate synthetic intermediate data fields between two known fields as well as nowcasts of motion and development of detected areas. Examples of the application of Cb-TRAM and a comparison to precipitation radar and lightning data as independent data sources demonstrate the capabilities of the new technique.

A configuration of the High-Altitude Long-Range Research Aircraft (HALO) as a remote sensing cloud observatory is described, and its use is illustrated with results from the first and second Next-Generation Aircraft Remote Sensing for Validation (NARVAL) field studies. Measurements from the second NARVAL (NARVAL2) are used to highlight the ability of HALO, when configured in this fashion, to characterize not only the distribution of water condensate in the atmosphere, but also its impact on radiant energy transfer and the covarying large-scale meteorological conditions—including the large-scale velocity field and its vertical component. The NARVAL campaigns with HALO demonstrate the potential of airborne cloud observatories to address long-standing riddles in studies of the coupling between clouds and circulation and are helping to motivate a new generation of field studies.

[1] Standard cloud remote sensing techniques rely on two basic assumptions: First, clouds are assumed to be plane-parallel and homogeneous within each satellite pixel. Second, pixels are assumed independent and the net horizontal radiative transport between pixels is neglected. These assumptions cause considerable uncertainty and bias in the retrieval of cloud properties, which depend on the sensors spatial resolution as well as the illumination and observation geometry. The errors are quantified for several typical sensor settings. The basis of the investigation is a data set of high-resolution threedimensional cloud property distributions of marine stratocumulus obtained from airborne radiance observations. For this predefined cloud data the sensor signals are simulated using a three-dimensional Monte Carlo radiative transfer model. Cloud properties (optical thickness, effective radius) are retrieved for the simulated observations using a twochannel retrieval, which are then compared to the given cloud data. For the retrieval of the optical thickness the main findings are large uncertainty of individual pixel values occurs for a high spatial resolution (e.g., airborne sensors) due to nonnegligible horizontal photon transport at this pixel size. For the typical polar-orbiting and geostationary sensor settings the neglect of subpixel inhomogeneity takes effect as well. Nonetheless, biases are generally small within ±5%, if pixels are overcast. If this is not guaranteed, the bias grows rapidly, for example, to typical underestimations of 20% and more for a geostationary sensor. For the retrieval of effective radius values are generally found to be about 5% larger than expected for idealized homogeneous plane-parallel cloud conditions. Citation: Zinner, T., and B. Mayer (2006), Remote sensing of stratocumulus clouds: Uncertainties and biases due to inhomogeneity,