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Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: Evaluation of candidate approaches with MODIS observations
This study presents and evaluates several candidate approaches for downscaling observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) in order to increase the horizontal resolution of subsequent cloud optical thickness (τ) and effective droplet radius (reff) retrievals from the native ≈ 3km×3km spatial resolution of the narrowband channels to ≈ 1km×1km. These methods make use of SEVIRI's coincident broadband high-resolution visible (HRV) channel. For four example cloud fields, the reliability of each downscaling algorithm is evaluated by means of collocated 1km×1km MODIS radiances, which are reprojected to the horizontal grid of the HRV channel and serve as reference for the evaluation. By using these radiances, smoothed with the modulation transfer function of the native SEVIRI channels, as retrieval input, the accuracy at the SEVIRI standard resolution can be evaluated and an objective comparison of the accuracy of the different downscaling algorithms can be made. For the example scenes considered in this study, it is shown that neglecting high-frequency variations below the SEVIRI standard resolution results in significant random absolute deviations of the retrieved τ and reff of up to ≈ 14 and ≈ 6μm, respectively, as well as biases. By error propagation, this also negatively impacts the reliability of the subsequent calculation of liquid water path (WL) and cloud droplet number concentration (ND), which exhibit deviations of up to ≈ 89gm-2 and ≈ 177cm-3, respectively. For τ , these deviations can be almost completely mitigated by the use of the HRV channel as a physical constraint and by applying most of the presented downscaling schemes. Uncertainties in retrieved reff at the native SEVIRI resolution are smaller, and the improvements from downscaling the observations are less obvious than for τ. Nonetheless, the right choice of downscaling scheme yields noticeable improvements in the retrieved reff. Furthermore, the improved reliability in retrieved cloud products results in significantly reduced uncertainties in derived WL and ND. In particular, one downscaling approach provides clear improvements for all cloud products compared to those obtained from SEVIRI's standard resolution and is recommended for future downscaling endeavors. This work advances efforts to mitigate impacts of scale mismatches among channels of multiresolution instruments on cloud retrievals. © Author(s) 2020.
Increasing Resolution and Resolving Convection Improve the Simulation of Cloud-Radiative Effects Over the North Atlantic
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.
Spatiotemporal variability of solar radiation introduced by clouds over Arctic sea ice
The role of clouds in recent Arctic warming is not fully understood, including their effects on the solar radiation and the surface energy budget. To investigate relevant small-scale processes in detail, the intensive Physical feedbacks of Arctic planetary boundary layer, Sea ice, Cloud and AerosoL (PASCAL) drifting ice floe station field campaign was conducted during early summer in the central arctic. During this campaign, the small-scale spatiotemporal variability of global irradiance was observed for the first time on an ice floe with a dense network of autonomous pyranometers. A total of 15 stations were deployed covering an area of 0.83 km×1.59 km from 4–16 June 2017. This unique, open-access dataset is described here, and an analysis of the spatiotemporal variability deduced from this dataset is presented for different synoptic conditions. Based on additional observations, five typical sky conditions were identified and used to determine the values of the mean and variance of atmospheric global transmittance for these conditions. Overcast conditions were observed 39.6 % of the time predominantly during the first week, with an overall mean transmittance of 0.47. The second most frequent conditions corresponded to multilayer clouds (32.4 %), which prevailed in particular during the second week, with a mean transmittance of 0.43. Broken clouds had a mean transmittance of 0.61 and a frequency of occurrence of 22.1 %. Finally, the least frequent sky conditions were thin clouds and cloudless conditions, which both had a mean transmittance of 0.76 and occurrence frequencies of 3.5 % and 2.4 %, respectively. For overcast conditions, lower global irradiance was observed for stations closer to the ice edge, likely attributable to the low surface albedo of dark open water and a resulting reduction of multiple reflections between the surface and cloud base. Using a wavelet-based multi-resolution analysis, power spectra of the time series of atmospheric transmittance were compared for single-station and spatially averaged observations and for different sky conditions. It is shown that both the absolute magnitude and the scale dependence of variability contains characteristic features for the different sky conditions.
The sub-adiabatic model as a concept for evaluating therepresentation and radiative effects of low-level cloudsin a high-resolution atmospheric model
The realistic representation of low-level clouds, including their radiative effects, in atmospheric models remains challenging. A sensitivity study is presented to establish a conceptual approach for the evaluation of low-level clouds and their radiative impact in a highly resolved atmospheric model. Considering simulations for six case days, the analysis supports the notion that the properties of clouds more closely match the assumptions of the sub-adiabatic rather than the vertically homogeneous cloud model, suggesting its use as the basis for evaluation. For the considered cases, 95.7 % of the variance in cloud optical thickness is explained by the variance in the liquid water path, while the droplet number concentration and the sub-adiabatic fraction contribute only 3.5 % and 0.2 % to the total variance, respectively. A mean sub-adiabatic fraction of 0.45 is found, which exhibits strong inter-day variability. Applying a principal component analysis and subsequent varimax rotation to the considered set of nine properties, four dominating modes of variability are identified, which explain 97.7 % of the total variance. The first and second components correspond to the cloud base and top height, and to liquid water path, optical thickness, and cloud geometrical extent, respectively, while the cloud droplet number concentration and the sub-adiabatic fraction are the strongest contributors to the third and fourth components. Using idealized offline radiative transfer calculations, it is confirmed that the shortwave and longwave cloud radiative effects exhibit little sensitivity to the vertical structure of clouds. This reconfirms, based on an unprecedented large set of highly resolved vertical cloud profiles, that the cloud optical thickness and the cloud top and bottom heights are the main factors dominating the shortwave and longwave radiative effect of clouds and should be evaluated together with radiative fluxes using observations to attribute model deficiencies in the radiative fluxes to deficiencies in the representation of clouds. Considering the different representations of cloud microphysical processes in atmospheric models, the analysis has been further extended and the deviations between the radiative impact of the single- and double-moment schemes are assessed. Contrasting the shortwave cloud radiative effect obtained from the double-moment scheme to that of a single-moment scheme, differences of about ∼40 W m−2 and significant scatter are observed. The differences are attributable to a higher cloud albedo resulting from the high values of droplet number concentration in particular in the boundary layer predicted by the double-moment scheme, which reach median values of around ∼600 cm−3.
The day-to-day co-variability between mineral dust and cloud glaciation: a proxy for heterogeneous freezing
To estimate the global co-variability between mineral dust aerosol and cloud glaciation, we combined an aerosol model reanalysis with satellite retrievals of cloud thermodynamic phase. We used the CALIPSO-GOCCP product from the A-Train satellite constellation to assess whether clouds are composed of liquid or ice and the MACC reanalysis to estimate the dust mixing ratio in the atmosphere. Night-time retrievals within a temperature range from +3 to −42 ∘C for the period 2007–2010 were included. The results confirm that the cloud thermodynamic phase is highly dependent on temperature and latitude. However, at middle and high latitudes, at equal temperature and within narrow constraints for humidity and static stability, the average frequency of fully glaciated clouds increases by +5 to +10 % for higher mineral dust mixing ratios. The discrimination between humidity and stability regimes reduced the confounding influence of meteorology on the observed relationship between dust and cloud ice. Furthermore, for days with similar mixing ratios of mineral dust, the cloud ice occurrence frequency in the Northern Hemisphere was found to be higher than in the Southern Hemisphere at −30 ∘C but lower at −15 ∘C. This contrast may suggest a difference in the susceptibility of cloud glaciation to the presence of dust. Based on previous studies, the differences at −15 ∘C could be explained by higher feldspar fractions in the Southern Hemisphere, while the higher freezing efficiency of clay minerals in the Northern Hemisphere may explain the differences at −30 ∘C.
How organized is deep convection over Germany?
Deep moist convection shows a tendency to organize into mesoscale structures. To be able to understand the potential effect of convective organization on the climate, one needs first to characterize organization. In this study, we systematically characterize the organizational state of convection over Germany based on two years of cloud-top observations derived from the Meteosat Second Generation satellite and of precipitation cores detected by the German C-band radar network. The organizational state of convection is characterized by commonly employed organization indices, which are mostly based on the object numbers, sizes and nearest-neighbour distances. According to the organization index Iorg, cloud tops and precipitation cores are found to be in an organized state for 69% and 92% of the time, respectively. There is an increase in rainfall when the number of objects and their sizes increase, independently of the organizational state. Case-studies of specific days suggest that convectively organized states correspond to either local multi-cell clusters, with less numerous, larger objects close to each other, or to scattered clusters, with more numerous, smaller organized objects spread out over the domain. For those days, simulations are performed with the large-eddy model ICON with grid spacings of 625, 312 and 156 m. Although the model underestimates rainfall and shows a too large cold cloud coverage, the organizational state is reasonably well represented without significant differences between the grid spacings.
Constraining the Twomey effect from satellite observations: Issues and perspectives
The Twomey effect describes the radiative forcing associated with a change in cloud albedo due to an increase in anthropogenic aerosol emissions. It is driven by the perturbation in cloud droplet number concentration (1Nd; ant) in liquid-water clouds and is currently understood to exert a cooling effect on climate. The Twomey effect is the key driver in the effective radiative forcing due to aerosol cloud interactions, but rapid adjustments also contribute. These adjustments are essentially the responses of cloud fraction and liquid water path to 1Nd; ant and thus scale approximately with it. While the fundamental physics of the influence of added aerosol particles on the droplet concentration (Nd) is well described by established theory at the particle scale (micrometres), how this relationship is expressed at the large-scale (hundreds of kilometres) perturbation, 1Nd; ant, remains uncertain. The discrepancy between process understanding at particle scale and insufficient quantification at the climate-relevant large scale is caused by co-variability of aerosol particles and updraught velocity and by droplet sink processes. These operate at scales on the order of tens of me-Tres at which only localised observations are available and at which no approach yet exists to quantify the anthropogenic perturbation. Different atmospheric models suggest diverse magnitudes of the Twomey effect even when applying the same anthropogenic aerosol emission perturbation. Thus, observational data are needed to quantify and constrain the Twomey effect. At the global scale, this means satellite data. There are four key uncertainties in determining 1Nd; ant, namely the quantification of (i) the cloud-Active aerosol the cloud condensation nuclei (CCN) concentrations at or above cloud base, (ii) Nd, (iii) the statistical approach for inferring the sensitivity of Nd to aerosol particles from the satellite data and (iv) uncertainty in the anthropogenic perturbation to CCN concentrations, which is not easily accessible from observational data. This review discusses deficiencies of current approaches for the different aspects of the problem and proposes several ways forward: in terms of CCN, retrievals of optical quantities such as aerosol optical depth suffer from a lack of vertical resolution, size and hygroscopicity information, non-direct relation to the concentration of aerosols, difficulty to quantify it within or below clouds, and the problem of insufficient sensitivity at low concentrations, in addition to retrieval errors. A future path forward can include utilising co-located polarimeter and lidar instruments, ideally including high-spectral-resolution lidar capability at two wavelengths to maximise vertically resolved size distribution information content. In terms of Nd, a key problem is the lack of operational retrievals of this quantity and the inaccuracy of the retrieval especially in broken-cloud regimes. As for the Nd-To-CCN sensitivity, key issues are the updraught distributions and the role of Nd sink processes, for which empirical assessments for specific cloud regimes are currently the best solutions. These considerations point to the conclusion that past studies using existing approaches have likely underestimated the true sensitivity and, thus, the radiative forcing due to the Twomey effect. © 2020 BMJ Publishing Group. All rights reserved.
Evaluation of satellite-based aerosol datasets and the CAMS reanalysis over the ocean utilizing shipborne reference observations
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.