The second version of the atmospheric radiative transfer simulator, ARTS, is introduced. This is a general software package for long wavelength radiative transfer simulations, with a focus on passive microwave observations. The core part provides a workspace environment, in line with script languages. New for this version is an agenda mechanism that gives a high degree of modularity. The framework is intended to be as general as possible: the polarisation state can be fully described, the model atmosphere can be one-(1D), two-(2D) or three-dimensional (3D), a full description of geoid and surface is possible, observation geometries from the ground, from satellite, and from aeroplane or balloon are handled, and surface reflection can be treated in simple or complex manners. Remote sensing applications are supported by a comprehensive and efficient treatment of sensor characteristics. Jacobians can be calculated for the most important atmospheric variables in non-scattering conditions. Finally, the most prominent feature is the rigorous treatment of scattering that has been implemented in two modules: a discrete ordinate iterative approach mainly used for 1D atmospheres, and a Monte Carlo approach which is the preferred algorithm for 3D atmospheres. ARTS is freely available, and maintained as an open-source project.

A recently launched project under the auspices of the World Climate Research Program's (WCRP) Coordinated Regional Downscaling Experiments Flagship Pilot Studies program (CORDEX-FPS) is presented. This initiative aims to build first-ofits-kind ensemble climate experiments of convection permitting models to investigate present and future convective processes and related extremes over Europe and the Mediterranean. In this manuscript the rationale, scientific aims and approaches are presented along with some preliminary results from the testing phase of the project. Three test cases were selected in order to obtain a first look at the ensemble performance. The test cases covered a summertime extreme precipitation event over Austria, a fall Foehn event over the Swiss Alps and an intensively documented fall event along the Mediterranean coast. The test cases were run in both "weather-like" (WL, initialized just before the event in question) and "climate" (CM, initialized 1 month before the event) modes. Ensembles of 18-21 members, representing six different modeling systems with different physics and modelling chain options, was generated for the test cases (27 modeling teams have committed to perform the longer climate simulations). Results indicate that, when run in WL mode, the ensemble captures all three events quite well with ensemble correlation skill scores of 0.67, 0.82 and 0.91. They suggest that the more the event is driven by large-scale conditions, the closer the agreement between the ensemble members. Even in climate mode the large-scale driven events over the Swiss Alps and the Mediterranean coasts are still captured (ensemble correlation skill scores of 0.90 and 0.62, respectively), but the inter-model spread increases as expected. In the case over Mediterranean the effects of local-scale interactions between flow and orography and land-ocean contrasts are readily apparent. However, there is a much larger, though not surprising, increase in the spread for the Austrian event, which was weakly forced by the large-scale flow. Though the ensemble correlation skill score is still quite high (0.80). The preliminary results illustrate both the promise and the challenges that convection permitting modeling faces and make a strong argument for an ensemble-based approach to investigating high impact convective processes. Keywords Convection-permitting • Ensemble models • Climate applicationsThis paper is a contribution to the special issue on Advances in Convection-Permitting Climate Modeling, consisting of papers that focus on the evaluation, climate change assessment, and feedback processes in kilometer-scale simulations and observations. The special issue is coordinated by

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of $$\sim $$ ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution ($$\sim $$ ∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from $$\sim \,$$ ∼  −40% at 12 km to $$\sim \,$$ ∼  −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.

Abstract. A main limitation today in simulations and inversions of microwave observations of ice hydrometeors (cloud ice, snow, hail, etc.) is the lack of data describing the interaction between electromagnetic waves and the particles. To improve the situation, the development of a comprehensive dataset of such scattering properties has been started. The database aims at giving a broad coverage in both frequency (1 to 886 GHz) and temperature (190 to 270 K), to support both passive and active current and planned measurements, and to provide data corresponding to the full Stokes vector. This first version of the database is restricted to totally random particle orientation. Data for 34 particle sets, i.e. habits, have been generated. About 17 of the habits can be classified as single crystals, three habits can be seen as heavily rimed particles, and the remaining habits are aggregates of different types, e.g. snow and hail. The particle sizes considered vary between the habits, but maximum diameters of 10 and 20 mm are typical values for the largest single crystal and aggregate particles, respectively, and the number of sizes per habit is at least 30. Particles containing liquid water are also inside the scope of the database, but this phase of water is so far only represented by a liquid sphere habit. The database is built upon the netCDF4 file format. Interfaces to browse, extract and convert data for selected radiative transfer models are provided in MATLAB and Python. The database and associated tools are publicly available from Zenodo (https://doi.org/10.5281/zenodo.1175572, Ekelund et al., 2018b), and https://doi.org/10.5281/zenodo.1175588, Mendrok et al., 2018, respectively). Planned extensions include non-spherical raindrops, melting particles and a second orientation case that can be denoted as azimuthally random.

Abstract. This article describes the latest stable release (version 2.2) of the Atmospheric Radiative Transfer Simulator (ARTS), a public domain software for radiative transfer simulations in the thermal spectral range (microwave to infrared). The main feature of this release is a planetary toolbox that allows simulations for the planets Venus, Mars, and Jupiter, in addition to Earth. This required considerable model adaptations, most notably in the area of gaseous absorption calculations. Other new features are also described, notably radio link budgets (including the effect of Faraday rotation that changes the polarization state) and the treatment of Zeeman splitting for oxygen spectral lines. The latter is relevant, for example, for the various operational microwave satellite temperature sensors of the Advanced Microwave Sounding Unit (AMSU) family.