2021, Deneke, Hartwig, Barrientos-Velasco, Carola, Bley, Sebastian, Hünerbein, Anja, Lenk, Stephan, Macke, Andreas, Meirink, Jan Fokke, Schroedter-Homscheidt, Marion, Senf, Fabian, Wang, Ping, Werner, Frank, Witthuhn, Jonas

The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1ĝ€¯km2 compared to the standard 3×3ĝ€¯km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6ĝ€¯μm, 0.8ĝ€¯μm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6ĝ€¯μm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6ĝ€¯μm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.

2018, Wandinger, Ulla, Hünerbein, Anja, Horn, Stefan, Schneider, Florian, Donovan, David, van Zadelhoff, Gerd-Jan, Daou, David, Docter, Nicole, Fischer, Jürgen, Filipitsch, Florian, Nicolae, D., Makoto, A., Vassilis, A., Balis, D., Behrendt, A., Comeron, A., Gibert, F., Landulfo, E., McCormick, M.P., Senff, C., Veselovskii, I., Wandinger, U.

We introduce the development of EarthCARE Level 2 layer products derived from profile measurements of the high-spectral-resolution lidar ATLID and column products obtained from combined information of ATLID and the Multi-Spectral Imager (MSI). Layer products include cloud top height as well as aerosol layer boundaries and mean optical properties along the satellite nadir track. Synergistic column products comprise cloud top height, Ångström exponent, and aerosol type both along-track and across the MSI swath.

2016, Wandinger, Ulla, Baars, Holger, Engelmann, Ronny, Hünerbein, Anja, Horn, Stefan, Kanitz, Thomas, Donovan, David, van Zadelhoff, Gerd-Jan, Daou, David, Fischer, Jürgen, von Bismarck, Jonas, Filipitsch, Florian, Docter, Nicole, Eisinger, Michael, Lajas, Dulce, Wehr, Tobias

We introduce the Hybrid End-To-End Aerosol Classification (HETEAC) model for the upcoming EarthCARE mission. The model serves as the common baseline for development, evaluation, and implementation of EarthCARE algorithms. It shall ensure the consistency of different aerosol products from the multi-instrument platform as well as facilitate the conform specification of broad-band optical properties necessary for the EarthCARE radiative closure efforts. The hybrid approach ensures the theoretical description of aerosol microphysics consistent with the optical properties of various aerosol types known from observations. The end-to-end model permits the uniform representation of aerosol types in terms of microphysical, optical and radiative properties.

2018, Banks, Jamie R., Schepanski, Kerstin, Heinold, Bernd, Hünerbein, Anja, Brindley, Helen E.

Satellite imagery of atmospheric mineral dust is sensitive to the optical properties of the dust, governed by the mineral refractive indices, particle size, and particle shape. In infrared channels the imagery is also sensitive to the dust layer height and to the surface and atmospheric environment. Simulations of mineral dust in infrared "Desert Dust" imagery from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) have been performed, using the COSMO-MUSCAT (COSMO: COnsortium for Small-scale MOdelling; MUSCAT: MUltiScale Chemistry Aerosol Transport Model) dust transport model and the Radiative Transfer for TOVS (RTTOV) program, in order to investigate the sensitivity of the imagery to assumed dust properties. This paper introduces the technique and performs initial validation and comparisons with SEVIRI measurements over North Africa for daytime hours during 6 months covering June and July of 2011–2013. Using T-matrix scattering theory and assuming the dust particles to be spherical or spheroidal, wavelength- and size-dependent dust extinction values are calculated for a number of different dust refractive index databases, along with several values of the particle aspect ratio, denoting the particle shape. The consequences for the infrared extinction values of both the particle shape and the particle orientation are explored: this analysis shows that as the particle asphericity increases, the extinctions increase if the particles are aligned horizontally, and decrease if they are aligned vertically. Randomly oriented spheroidal particles have very similar infrared extinction properties as spherical particles, whereas the horizontally and vertically aligned particles can be considered to be the upper and lower bounds on the extinction values. Inputting these values into COSMO-MUSCAT-RTTOV, it is found that spherical particles do not appear to be sufficient to describe fully the resultant colour of the dust in the infrared imagery. Comparisons of SEVIRI and simulation colours indicate that of the dust types tested, the dust refractive index dataset produced by Volz (1973) shows the most similarity in the colour response to dust in the SEVIRI imagery, although the simulations have a smaller range of colour than do the observations. It is also found that the thermal imagery is most sensitive to intermediately sized particles (radii between 0.9 and 2.6 µm): larger particles are present in too small a concentration in the simulations, as well as with insufficient contrast in extinction between wavelength channels, to have much ability to perturb the resultant colour in the SEVIRI dust imagery.

2023, Hünerbein, Anja, Bley, Sebastian, Horn, Stefan, Deneke, Hartwig, Walther, Andi

The EarthCARE (Earth Clouds, Aerosols and Radiation Explorer) satellite mission will provide new insights into aerosol-cloud-radiation interactions by means of synergistic observations of the Earth's atmosphere from a collection of active and passive remote sensing instruments, flying on a single satellite platform. The Multi-Spectral Imager (MSI) will provide visible and infrared images in the cross-track direction with a 150km swath and a pixel sampling at 500m. The suite of MSI cloud algorithms will deliver cloud macro- and microphysical properties complementary to the vertical profiles measured from the Atmospheric Lidar (ATLID) and the Cloud Profiling Radar (CPR) instruments. This paper provides an overview of the MSI cloud mask algorithm (M-CM) being developed to derive the cloud flag, cloud phase and cloud type products, which are essential inputs to downstream EarthCARE algorithms providing cloud optical and physical properties (M-COP) and aerosol optical properties (M-AOT). The MSI cloud mask algorithm has been applied to simulated test data from the EarthCARE end-to-end simulator and satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as from the Spinning Enhanced Visible InfraRed Imager (SEVIRI). Verification of the MSI cloud mask algorithm to the simulated test data and the official cloud products from SEVIRI and MODIS demonstrates a good performance of the algorithm. Some discrepancies are found, however, for the detection of thin cirrus clouds over bright surfaces like desert or snow. This will be improved by tuning of the thresholds once real observations are available.

2018, Grosvenor, Daniel P., Sourdeval, Odran, Zuidema, Paquita, Ackerman, Andrew, Alexandrov, Mikhail D., Bennartz, Ralf, Boers, Reinout, Cairns, Brian, Chiu, J. Christine, Christensen, Matthew, Deneke, Hartwig, Diamond, Michael, Feingold, Graham, Fridlind, Ann, Hünerbein, Anja, Knist, Christine, Kollias, Pavlos, Marshak, Alexander, McCoy, Daniel, Merk, Daniel, Painemal, David, Rausch, John, Rosenfeld, Daniel, Russchenberg, Herman, Seifert, Patric, Sinclair, Kenneth, Stier, Philip, van Diedenhoven, Bastiaan, Wendisch, Manfred, Werner, Frank, Wood, Robert, Zhang, Zhibo, Quaas, Johannes

The cloud droplet number concentration (Nd) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol-cloud interactions. Current standard satellite retrievals do not operationally provide Nd, but it can be inferred from retrievals of cloud optical depth (τc) cloud droplet effective radius (re) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel-level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. Nd uncertainty is dominated by errors in re, and therefore, improvements in re retrievals would greatly improve the quality of the Nd retrievals. Recommendations are made for how this might be achieved. Some existing Nd data sets are compared and discussed, and best practices for the use of Nd data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative Nd estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high-quality ground-based observations are examined.

2020, Senf, Fabian, Voigt, Aiko, Clerbaux, Nicolas, Hünerbein, Anja, Deneke, Hartwig

Clouds interact with atmospheric radiation and substantially modify the Earth's energy budget. Cloud formation processes occur over a vast range of spatial and temporal scales, which make their thorough numerical representation challenging. Therefore, the impact of parameter choices for simulations of cloud-radiative effects is assessed in the current study. Numerical experiments are carried out using the ICOsahedral Nonhydrostatic (ICON) model with varying grid spacings between 2.5 and 80 km and with different subgrid-scale parameterization approaches. Simulations are performed over the North Atlantic with either one-moment or two-moment microphysics and with convection being parameterized or explicitly resolved by grid-scale dynamics. Simulated cloud-radiative effects are compared to products derived from Meteosat measurements. Furthermore, a sophisticated cloud classification algorithm is applied to understand the differences and dependencies of simulated and observed cloud-radiative effects. The cloud classification algorithm developed for the satellite observations is also applied to the simulation output based on synthetic infrared brightness temperatures, a novel approach that is not impacted by changing insolation and guarantees a consistent and fair comparison. It is found that flux biases originate equally from clear-sky and cloudy parts of the radiation field. Simulated cloud amounts and cloud-radiative effects are dominated by marine, shallow clouds, and their behavior is highly resolution dependent. Bias compensation between shortwave and longwave flux biases, seen in the coarser simulations, is significantly diminished for higher resolutions. Based on the analysis results, it is argued that cloud-microphysical and cloud-radiative properties have to be adjusted to further improve agreement with observed cloud-radiative effects. © 2020. The Authors.

2020, Witthuhn, Jonas, Hünerbein, Anja, Deneke, Hartwig

Reliable reference measurements over the ocean are essential for the evaluation and improvement of satelliteand model-based aerosol datasets. Within the framework of the Maritime Aerosol Network, shipborne reference datasets have been collected over the Atlantic Ocean since 2004 with Microtops Sun photometers. These were recently complemented by measurements with the multi-spectral GUVis- 3511 shadowband radiometer during five cruises with the research vessel Polarstern. The aerosol optical depth (AOD) uncertainty estimate of both shipborne instruments of ±0:02 can be confirmed if the GUVis instrument is cross calibrated to the Microtops instrument to account for differences in calibration, and if an empirical correction to account for the broad shadowband as well as the effects of forward scattering is introduced. Based on these two datasets, a comprehensive evaluation of aerosol products from the Moderate Resolution Imaging Spectroradiometer (MODIS) flown on NASA's Earth Observing System satellites, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) aboard the geostationary Meteosat satellite, and the Copernicus Atmosphere Monitoring Service reanalysis (CAMS RA) is presented. For this purpose, focus is given to the accuracy of the AOD at 630 nm in combination with the Ångström exponent (AE), discussed in the context of the ambient aerosol type. In general, the evaluation of MODIS AOD from the official level-2 aerosol products of C6.1 against the Microtops AOD product confirms that 76% of data points fall into the expected error limits given by previous validation studies. The SEVIRI-based AOD product exhibits a 25% larger scatter than the MODIS AOD products at the instrument's native spectral channels. Further, the comparison of CAMS RA and MODIS AOD versus the shipborne reference shows similar performance for both datasets, with some differences arising from the assimilation and model assumptions. When considering aerosol conditions, an overestimation of AE is found for scenes dominated by desert dust for MODIS and SEVIRI products versus the shipborne reference dataset. As the composition of the mixture of aerosol in satellite products is constrained by model assumptions, this highlights the importance of considering the aerosol type in evaluation studies for identifying problematic aspects. © Author(s) 2020.

2022, Tzallas, Vasileios, Hünerbein, Anja, Stengel, Martin, Meirink, Jan Fokke, Benas, Nikos, Trentmann, Jörg, Macke, Andreas

Given the important role of clouds in our planet’s climate system, it is crucial to further improve our understanding of their governing processes as well as the resulting spatio-temporal variability of their properties. This co-variability of different cloud optical properties is adequately represented through the well-established concept of cloud regimes. The focus of the present study lies on the creation of a cloud regime dataset over Europe, named “Cloud Regime dAtAset based on the CLAAS-2.1 climate data record” (CRAAS), in order to analyze their variability and their changes at different spatio-temporal scales. In addition, co-occurrences between the cloud regimes and large-scale weather patterns are investigated. The CLoud property dAtAset using Spinning Enhanced Visible and Infrared (SEVIRI) edition 2.1 (CLAAS-2.1) data record, which is produced by the Satellite Application Facility on Climate Monitoring (CM SAF), was used as the basis for the derivation of the cloud regimes over Europe for a 14-year period (2004–2017). In particular, the cloud optical thickness (COT) and cloud top pressure (CTP) products of CLAAS-2.1 were used in order to compute 2D histograms. Then, the k-means clustering algorithm was applied to the generated 2D histograms in order to derive the cloud regimes. Eight cloud regimes were identified, which, along with the geographical distribution of their frequency of occurrence, assisted in providing a detailed description of the climate of the cloud properties over Europe. The annual and diurnal variabilities of the eight cloud regimes were studied, and trends in their frequency of occurrence were also examined. Larger changes in the frequency of occurrence of the produced cloud regimes were found for a regime associated to alto- and nimbo-type clouds and for a regime connected to shallow cumulus clouds and fog (−0.65% and +0.70% for the time period of the study, respectively).