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.

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. The climate models used in the IPCC AR4 show large differences in monthly mean ice water path (IWP). The most valuable source of information that can be used to potentially constrain the models is global satellite data. The satellite datasets also have large differences. The retrieved IWP depends on the technique used, as retrievals based on different techniques are sensitive to different parts of the cloud column. Building on the foundation of Waliser et al. (2009), this article provides a more comprehensive comparison between satellite datasets. IWP data from the CloudSat cloud profiling radar provide the most advanced dataset on clouds. For all its unmistakable value, CloudSat data are too short and too sparse to assess climatic distributions of IWP, hence the need to also use longer datasets. We evaluate satellite datasets from CloudSat, PATMOS-x, ISCCP, MODIS and MSPPS in terms of monthly mean IWP, in order to determine the differences and relate them to the sensitivity of the instrument used in the retrievals. This information is also used to evaluate the climate models, to the extent that is possible.ISCCP and MSPPS were shown to have comparatively low IWP values. ISCCP shows particularly low values in the tropics, while MSPPS has particularly low values outside the tropics. MODIS and PATMOS-x were in closest agreement with CloudSat in terms of magnitude and spatial distribution, with MODIS being the better of the two. Additionally PATMOS-x and ISCCP, which have a temporal range long enough to capture the inter-annual variability of IWP, are used in conjunction with CloudSat IWP (after removing profiles that contain precipitation) to assess the IWP Correspondence to: S. Eliasson (s.eliasson@ltu.se) variability and mean of the climate models. In general there are large discrepancies between the individual climate models, and all of the models show problems in reproducing the observed spatial distribution of cloud-ice. Comparisons consistently showed that ECHAM-5 is probably the GCM from IPCC AR4 closest to satellite observations.

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.

Abstract. WIRA is a ground-based microwave Doppler spectroradiometer specifically designed for the measurement of profiles of horizontal wind in the upper stratosphere and lower mesosphere region where no other continuously running measurement technique exists. A proof of principle has been delivered in a previous publication. A technical upgrade including a new high-frequency amplifier and sideband filter has improved the signal to noise ratio by a factor of 2.4. Since this upgrade the full horizontal wind field comprising zonal and meridional wind profiles is continuously measured. A completely new retrieval based on optimal estimation has been set up. Its characteristics are detailed in the present paper.Since the start of the routine operation of the first prototype in September 2010, WIRA has been measuring at four different locations at polar, mid-and tropical latitudes (67 • 22 N/26 • 38 E, 46 • 57 N/7 • 26 E, 43 • 56 N/5 • 43 E and 21 • 04 S/55 • 23 E) for time periods between 5.5 and 11 months. The data presented in this paper are daily average wind profiles with typical uncertainties and resolutions of 10 to 20 m s −1 and 10 to 16 km, respectively. A comparison between the data series from WIRA and European Centre for Medium-Range Weather Forecasts (ECMWF) model data revealed agreement within 10 % in the stratospheric zonal wind. The meridional wind profiles agree within their error bars over the entire sensitive altitude range of WIRA. However, significant differences in the mesospheric zonal wind speed of up to 50 % have been found.