Cloud properties from both ground-based as well as from geostationary passive satellite observations have been used previously for diagnosing aerosol–cloud interactions. In this investigation, a ...2-year data set together with four selected case studies are analyzed with the aim of evaluating the consistency and limitations of current ground-based and satellite-retrieved cloud property data sets. The typically applied adiabatic cloud profile is modified using a sub-adiabatic factor to account for entrainment within the cloud. Based on the adiabatic factor obtained from the combination of ground-based cloud radar, ceilometer and microwave radiometer, we demonstrate that neither the assumption of a completely adiabatic cloud nor the assumption of a constant sub-adiabatic factor is fulfilled (mean adiabatic factor 0.63 ± 0.22). As cloud adiabaticity is required to estimate the cloud droplet number concentration but is not available from passive satellite observations, an independent method to estimate the adiabatic factor, and thus the influence of mixing, would be highly desirable for global-scale analyses. Considering the radiative effect of a cloud described by the sub-adiabatic model, we focus on cloud optical depth and its sensitivities. Ground-based estimates are here compared vs. cloud optical depth retrieved from the Meteosat SEVIRI satellite instrument resulting in a bias of −4 and a root mean square difference of 16. While a synergistic approach based on the combination of ceilometer, cloud radar and microwave radiometer enables an estimate of the cloud droplet concentration, it is highly sensitive to radar calibration and to assumptions about the moments of the droplet size distribution. Similarly, satellite-based estimates of cloud droplet concentration are uncertain. We conclude that neither the ground-based nor satellite-based cloud retrievals applied here allow a robust estimate of cloud droplet concentration, which complicates its use for the study of aerosol–cloud interactions.
A satellite retrieval of surface solar irradiance based on METEOSAT SEVIRI-derived cloud properties is presented and validated for the Netherlands with one year of pyranometer measurements from 35 ...stations. The approach requires two independent steps: 1. Cloud properties are determined from narrow-band satellite radiances. 2. These cloud properties are used together with data on water vapor column and surface albedo to calculate the atmospheric flux transmittance. The retrieved irradiance is biased low by about 3–4 W/m
2 throughout the year, corresponding to an underestimate in atmospheric flux transmittance of about 0.015 in summer and 0.04 in winter. From a least-squares linear regression, residual standard deviations of 56 W/m
2 (0.072, 17.0%), 11 W/m
2 (0.052, 10.8%), and 4 W/m
2 (0.021, 4.2%) are found for hourly, daily and monthly mean irradiance (transmittance, relative error), respectively. These findings indicate that the accuracy of the retrieval is comparable to first-class pyranometers in the summer half year (5% of daily-mean values), but significantly lower in winter. Two aspects requiring further investigation have been identified: 1. For thin clouds, the atmospheric flux transmittance is strongly underestimated. 2. The retrieval accuracy is reduced for snow-covered surfaces.
A threshold-based cloud mask for the high-resolution visible (HRV) channel (1 × 1 km2) of the Meteosat SEVIRI (Spinning Enhanced Visible and Infrared Imager) instrument is introduced and evaluated. ...It is based on operational EUMETSAT cloud mask for the low-resolution channels of SEVIRI (3 × 3 km2), which is used for the selection of suitable thresholds to ensure consistency with its results. The aim of using the HRV channel is to resolve small-scale cloud structures that cannot be detected by the low-resolution channels. We find that it is of advantage to apply thresholds relative to clear-sky reflectance composites, and to adapt the threshold regionally. Furthermore, the accuracy of the different spectral channels for thresholding and the suitability of the HRV channel are investigated for cloud detection. The case studies show different situations to demonstrate the behavior for various surface and cloud conditions. Overall, between 4 and 24% of cloudy low-resolution SEVIRI pixels are found to contain broken clouds in our test data set depending on considered region. Most of these broken pixels are classified as cloudy by EUMETSAT's cloud mask, which will likely result in an overestimate if the mask is used as an estimate of cloud fraction. The HRV cloud mask aims for small-scale convective sub-pixel clouds that are missed by the EUMETSAT cloud mask. The major limit of the HRV cloud mask is the minimum cloud optical thickness (COT) that can be detected. This threshold COT was found to be about 0.8 over ocean and 2 over land and is highly related to the albedo of the underlying surface.
An algorithm is introduced to downscale the 0.6 and 0.8 μm spectral channels of the METEOSTAT SEVIRI satellite imager from 3×3 km2 (LRES) to 1×1 km2 (HRES) resolution utilizing SEVIRI's ...high-resolution visible channel (HRV). Intermediate steps include the coregistration of low- and high-resolution images, lowpass filtering of the HRV channel with the spatial response function of the narrowband channels, and the estimation of a least-squares linear regression model for linking high-frequency variations in the HRV and narrowband images. The importance of accounting for the sensor spatial response function for matching reflectances at different spatial resolutions is demonstrated, and an estimate of the accuracy of the downscaled reflectances is provided. Based on a 1-year dataset of Meteosat SEVIRI images, it is estimated that on average, the reflectance of a HRES pixel differs from that of an enclosing LRES pixel by standard deviations of 0.049 and 0.052 in the 0.6 and 0.8 μm channels, respectively. By applying our downscaling algorithm, explained variance of 98.2 and 95.3 percent are achieved for estimating these deviations, corresponding to residual standard deviations of only 0.007 and 0.011 for the respective channels. For this dataset, a minor misregistration of the HRV channel relative to the narrowband channels of 0.36±0.11 km in East and 0.06±0.10 km in South direction is observed and corrected for, which should be negligible for most applications.
The accuracy and precision are determined of cloud liquid water path (LWP) retrievals from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on boardMeteosat-8using 1 yr of LWP retrievals ...from microwave radiometer (MWR) measurements of two CloudNET stations in northern Europe. The MWR retrievals of LWP have a precision that is superior to current satellite remote sensing techniques, which justifies their use as validation data. The Cloud Physical Properties (CPP) algorithm of the Satellite Application Facility on Climate Monitoring (CM-SAF) is used to retrieve LWP from SEVIRI reflectances at 0.6 and 1.6μm. The results show large differences in the accuracy and precision of LWP retrievals from SEVIRI between summer and winter. During summer, the instantaneous LWP retrievals from SEVIRI agree well with those from the MWRs. The accuracy is better than 5 g m−2and the precision is better than 30 g m−2, which is similar to the precision of LWP retrievals from MWR. The added value of the 15-min sampling frequency ofMeteosat-8becomes evident in the validation of the daily median and diurnal variations in LWP retrievals from SEVIRI. The daily median LWP values from SEVIRI and MWR are highly correlated (correlation > 0.95) and have a precision better than 15 g m−2. In addition, SEVIRI and MWR reveal similar diurnal variations in retrieved LWP values. The peak LWP values occur around noon. During winter, SEVIRI generally overestimates the instantaneous LWP values from MWR, the accuracy drops to about 10 g m², and the precision to about 30 g m−2. The most likely reason for these lower accuracies is the shortcoming of CPP, and similar one-dimensional retrieval algorithms, to model inhomogeneous clouds. It is suggested that neglecting cloud inhomogeneities leads to a significant overestimation of LWP retrievals from SEVIRI over northern Europe during winter.
In this study the shortwave cloud radiative effect (SWCRE) over ocean calculated by the ECHAM 5 climate model is evaluated for the cloud property input derived from ship based measurements and ...satellite based estimates and compared to ship based radiation measurements. The ship observations yield cloud fraction, liquid water path from a microwave radiometer, cloud bottom height as well as temperature and humidity profiles from radiosonde ascents. Level-2 products of the Satellite Application Facility on Climate Monitoring (CM~SAF) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) have been used to characterize clouds. Within a closure study six different experiments have been defined to find the optimal set of measurements to calculate downward shortwave radiation (DSR) and the SWCRE from the model, and their results have been evaluated under seven different synoptic situations. Four of these experiments are defined to investigate the advantage of including the satellite-based cloud droplet effective radius as additional cloud property. The modeled SWCRE based on satellite retrieved cloud properties has a comparable accuracy to the modeled SWCRE based on ship data. For several cases, an improvement through introducing the satellite-based estimate of effective radius as additional information to the ship based data was found. Due to their different measuring characteristics, however, each dataset shows best results for different atmospheric conditions.
Collocated time series of narrowband 0.6 μm atmospheric flux transmittance at the surface and bidirectional reflectance at the top of atmosphere are decomposed into distinct frequency bands, so as to ...investigate the timescale dependences of their variance and correlation. Toward this goal, a multiresolution analysis based on the maximum overlap discrete wavelet transform and the Haar wavelet is applied to 5‐minute resolution measurements from two multifilter rotating shadowband radiometers operated at Cabauw, NL, and Heselbach, DE, and to observations of the geostationary METEOSAT8 SEVIRI satellite imager. Both time series are best correlated when the satellite data are shifted by about 1 pixel (6 km) to the North, which is likely attributable to the parallax effect caused by the height of cloud tops and the oblique satellite viewing angle. While variations in transmittance and reflectance with periods longer than an hour are found to be highly anticorrelated, the correlation breaks down for shorter periods. Below 1 hour, the transmittance time series also exhibits significantly higher variance than the reflectance. The larger extent of the satellite pixel (6 × 3 km2) versus the point nature of the ground measurements is proposed as an explanation. Due to the small contributions of high‐frequency variability to the total variance of the reflectance, aliasing effects caused by the 5‐minute repeat cycle of SEVIRI are expected to be small. Implications of our findings are discussed for the validation of satellite estimates of solar surface irradiance. Averaging of surface measurements over at least 40 minutes is recommended for a comparison.
This study presents a comprehensive assessment of the meteorological conditions and atmospheric flow during the Lagrangian-type "Hill Cap Cloud Thuringia 2010" experiment (HCCT-2010), which was ...performed in September and October 2010 at Mt. Schmücke in the Thuringian Forest, Germany and which used observations at three measurement sites (upwind, in-cloud, and downwind) to study physical and chemical aerosol–cloud interactions. A Lagrangian-type hill cap cloud experiment requires not only suitable cloud conditions but also connected airflow conditions (i.e. representative air masses at the different measurement sites). The primary goal of the present study was to identify time periods during the 6-week duration of the experiment in which these conditions were fulfilled and therefore which are suitable for use in further data examinations. The following topics were studied in detail: (i) the general synoptic weather situations, including the mesoscale flow conditions, (ii) local meteorological conditions and (iii) local flow conditions. The latter were investigated by means of statistical analyses using best-available quasi-inert tracers, SF6 tracer experiments in the experiment area, and regional modelling. This study represents the first application of comprehensive analyses using statistical measures such as the coefficient of divergence (COD) and the cross-correlation in the context of a Lagrangian-type hill cap cloud experiment. This comprehensive examination of local flow connectivity yielded a total of 14 full-cloud events (FCEs), which are defined as periods during which all connected flow and cloud criteria for a suitable Lagrangian-type experiment were fulfilled, and 15 non-cloud events (NCEs), which are defined as periods with connected flow but no cloud at the summit site, and which can be used as reference cases. The overall evaluation of the identified FCEs provides the basis for subsequent investigations of the measured chemical and physical data during HCCT-2010 (see https://www.atmos-chem-phys.net/special_issue287.html). Results obtained from the statistical flow analyses and regional-scale modelling performed in this study indicate the existence of a strong link between the three measurement sites during the FCEs and NCEs, particularly under conditions of constant southwesterly flow, high wind speeds and slightly stable stratification. COD analyses performed using continuous measurements of ozone and particle (49 nm diameter size bin) concentrations at the three sites revealed, particularly for COD values < 0.1, very consistent time series (i.e. close links between air masses at the different sites). The regional-scale model simulations provided support for the findings of the other flow condition analyses. Cross-correlation analyses revealed typical overflow times of ~15–30 min between the upwind and downwind valley sites under connected flow conditions. The results described here, together with those obtained from the SF6 tracer experiments performed during the experiment, clearly demonstrate that (a) under appropriate meteorological conditions a Lagrangian-type approach is valid and (b) the connected flow validation procedure developed in this work is suitable for identifying such conditions. Overall, it is anticipated that the methods and tools developed and applied in the present study will prove useful in the identification of suitable meteorological and connected airflow conditions during future Lagrangian-type hill cap cloud experiments.
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.
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