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.

This article reports on the accuracy in aerosol‐ and cloud‐free conditions of the radiation parameterizations used in climate models. Accuracy is assessed relative to observationally validated reference models for fluxes under present‐day conditions and forcing (flux changes) from quadrupled concentrations of carbon dioxide. Agreement among reference models is typically within 1 W/m2, while parameterized calculations are roughly half as accurate in the longwave and even less accurate, and more variable, in the shortwave. Absorption of shortwave radiation is underestimated by most parameterizations in the present day and has relatively large errors in forcing. Error in present‐day conditions is essentially unrelated to error in forcing calculations. Recent revisions to parameterizations have reduced error in most cases. A dependence on atmospheric conditions, including integrated water vapor, means that global estimates of parameterization error relevant for the radiative forcing of climate change will require much more ambitious calculations.

Abstract. Microwave (1–300 GHz) dual-polarization measurements above 100 GHz are so far sparse, but they consistently show polarized scattering signals of ice clouds. Existing scattering databases of realistically shaped ice crystals for microwaves and submillimeter waves (>300 GHz) typically assume total random orientation, which cannot explain the polarized signals. Conceptual models show that the polarization signals are caused by oriented ice particles. Only a few works that consider oriented ice crystals exist, but they are limited to microwaves only. Assuming azimuthally randomly oriented ice particles with a fixed but arbitrary tilt angle, we produced scattering data for two particle habits (51 hexagonal plates and 18 plate aggregates), 35 frequencies between 1 and 864 GHz, and 3 temperatures (190, 230 and 270 K). In general, the scattering data of azimuthally randomly oriented particles depend on the incidence angle and two scattering angles, in contrast to total random orientation, which depends on a single angle. The additional tilt angle further increases the complexity. The simulations are based on the discrete dipole approximation in combination with a self-developed orientation averaging approach. The scattering data are publicly available from Zenodo (https://doi.org/10.5281/zenodo.3463003). This effort is also an essential part of preparing for the upcoming Ice Cloud Imager (ICI) that will perform polarized observations at 243 and 664 GHz. Using our scattering data radiative transfer simulations with two liquid hydrometeor species and four frozen hydrometeor species of polarized Global Precipitation Measurement (GPM) Microwave Imager (GMI) observations at 166 GHz were conducted. The simulations recreate the observed polarization patterns. For slightly fluttering snow and ice particles, the simulations show polarization differences up to 11 K using plate aggregates for snow, hexagonal plates for cloud ice and totally randomly oriented particles for the remaining species. Simulations using strongly fluttering hexagonal plates for snow and ice show similar polarization signals. Orientation, shape and the hydrometeor composition affect the polarization. Ignoring orientation can cause a negative bias for vertically polarized observations and a positive bias for horizontally polarized observations.

Abstract. A neural-network-based retrieval method to determine the snow ice water path (SIWP), liquid water path (LWP), and integrated water vapor (IWV) from millimeter and submillimeter brightness temperatures, measured by using airborne radiometers (ISMAR and MARSS), is presented. The neural networks were trained by using atmospheric profiles from the ICON numerical weather prediction (NWP) model and by radiative transfer simulations using the Atmospheric Radiative Transfer Simulator (ARTS). The basic performance of the retrieval method was analyzed in terms of offset (bias) and the median fractional error (MFE), and the benefit of using submillimeter channels was studied in comparison to pure microwave retrievals. The retrieval is offset-free for SIWP > 0.01 kg m to 30 % at LWP = 1 kg m −2 . The MFE of IWV for IWV > 3 kg m −2 is 5 to 8 %. The SIWP retrieval strongly benefits from submillimeter channels, which reduce the MFE by a factor of 2, compared to pure microwave retrievals. The IWV and the LWP retrievals also benefit from submillimeter channels, albeit to a lesser degree. The retrieval was applied to ISMAR and MARSS brightness temperatures from FAAM flight B897 on 18 March 2015 of a precipitating frontal system west of the coast of Iceland. Considering the given uncertainties, the retrieval is in reasonable agreement with the SIWP, LWP, and IWV values simulated by the ICON NWP model for that flight. A comparison of the retrieved IWV with IWV from 12 dropsonde measurements shows an offset of 0.5 kg m −2 and an RMS difference of 0.8 kg m −2 , showing that the retrieval of IWV is highly effective even under cloudy conditions.

The state-dependence of the climate sensitivity is of great interest when studying climate change as it influences the interpretation of the proxy record (Kutzbach et al., 2013;Manabe & Bryan, 1985), historical temperature observations (Andrews, 2014;Gregory & Andrews, 2016), and the interpretation of differences among models (Bourdin et al., 2021). Recent modeling studies, ranging from conceptual (Meraner et al., 2013) to cloud-resolving models (Romps, 2020), find that after an initial decrease the magnitude of the clear-sky feedback parameter, λ, again increases at yet higher surface temperatures (T s ). This non-monotonicity manifests itself as a pronounced "bump," a maximum in the clear-sky climate sensitivity, 𝐴𝐴  , at T s ≈ 310 K. Some studies (e.g., Popp et al., 2016;Schneider et al., 2019;Wolf & Toon, 2015) detect different cloud mechanisms that may cause a local maximum in climate sensitivity. In this study, however, we focus on the growing but still inconclusive literature on the seemingly simpler question of the clear-sky radiative response to warming.Seeley and Jeevanjee (2021) describe a physical mechanism that explains the changing temperature-dependence of λ: when the rise of the temperature is tied to the rise of CO 2 , the increased CO 2 concentration broadens the spectral interval over which CO 2 is the dominant absorber, thereby coupling the outgoing-longwave radiation (OLR) in these spectral regions to the tropospheric temperature, and hence T s in a way that leads to a more negative λ with warming. The work by Seeley and Jeevanjee (2021) provides an elegant physical explanation for the climate sensitivity "bump" in studies with varying CO 2 concentration