Hartwig Deneke

View angle dependence of MODIS liquid water path retrievals in warm oceanic clouds

We investigated the view angle dependence of domain mean Moderate Resolution Imaging Spectroradiometer (MODIS) liquid water path (LWP) and that of corresponding cloud optical thickness, effective radius, and liquid cloud fraction as proxy for plane-parallel retrieval biases. Independent Advanced Microwave Scanning Radiometer-EOS LWP was used to corroborate that the observed variations with sun-view geometry were not severely affected by seasonal/latitudinal changes in cloud properties. Microwave retrievals showed generally small (<10%) cross-swath variations. The view angle (cross-swath) dependence of MODIS optical thickness was weaker in backscatter than forward scatter directions and transitioned from mild ∩ shape to stronger ∪ shape as heterogeneity, sun angle, or latitude increased. The 2.2 µm effective radius variations always had a ∪ shape, which became pronounced and asymmetric toward forward scatter in the most heterogeneous clouds and/or at the lowest sun. Cloud fraction had the strongest and always ∪-shaped view angle dependence. As a result, in-cloud MODIS cloud liquid water path (CLWP) showed surprisingly good view angle (cross-swath) consistency, usually comparable to that of microwave retrievals, due to cancelation between optical thickness and effective radius biases. Larger (20-40%) nadir-relative increases were observed in the most extreme heterogeneity and sun angle bins, that is, typically in the polar regions, which, however, constituted only 3-8% of retrievals. The good consistency of MODIS in-cloud CLWP was lost for gridbox mean LWP, which was dominated by the strong cloud fraction increase with view angle. More worryingly, MODIS LWP exhibited significant and systematic absolute increases with heterogeneity and sun angle that is not present in microwave LWP. KEY POINTS Microwave LWP shows small overall and cross-swath variationsMODIS in-cloud LWP also shows good view angle consistency in most casesMODIS retrievals show strong overall increase with heterogeneity and sun angle.

Initial phase of the Hans-Ertel Centre for Weather Research - A virtual centre at the interface of basic and applied weather and climate research

The Hans-Ertel Centre for Weather Research is a network of German universities, research institutes and the German Weather Service (Deutscher Wetterdienst, DWD). It has been established to trigger and intensify basic research and education on weather forecasting and climate monitoring. The performed research ranges from nowcasting and short-term weather forecasting to convective-scale data assimilation, the development of parameterizations for numerical weather prediction models, climate monitoring and the communication and use of forecast information. Scientific findings from the network contribute to better understanding of the life-cycle of shallow and deep convection, representation of uncertainty in ensemble systems, effects of unresolved variability, regional climate variability, perception of forecasts and vulnerability of society. Concrete developments within the research network include dual observation-microphysics composites, satellite forward operators, tools to estimate observation impact, cloud and precipitation system tracking algorithms, large-eddy-simulations, a regional reanalysis and a probabilistic forecast test product. Within three years, the network has triggered a number of activities that include the training and education of young scientists besides the centres core objective of complementing DWDs internal research with relevant basic research at universities and research institutes. The long term goal is to develop a self-sustaining research network that continues the close collaboration with DWD and the national and international research community.

Using MSG-SEVIRI Cloud Physical Properties and Weather Radar Observations for the Detection of Cb/TCu Clouds

AbstractA new automated daytime cumulonimbus/towering cumulus (Cb/TCu) cloud detection method for the months of May–September is presented that combines information on cloud physical properties retrieved from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat Second Generation (MSG) satellites and weather radar reflectivity factors. First, a pixel-based convective cloud mask (CCM) is constructed on the basis of cloud physical properties [cloud-top temperature, cloud optical thickness (COT), effective radius, and cloud phase] derived from SEVIRI. Second, a logistic regression model is applied to determine the probability of Cb/TCu clouds for the collection of pixels that pass the CCM. In this model, MSG-SEVIRI cloud physical properties and weather radar reflectivity factors are used as potential predictor sources. The predictand is derived from aviation routine weather reports (METAR) made by human observers at Amsterdam Airport Schiphol for 2004–07. Results show that the CCM filt...

Characterization of Initiation and Growth of Selected Severe Convective Storms over Central Europe with MSG-SEVIRI

AbstractThe early development of severe convective storms over central Europe was investigated on the basis of nine cases from 2012. Using data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) imaging radiometer aboard a geostationary Meteosat Second Generation (MSG) satellite, dynamical and microphysical properties of developing storms were monitored and combined. Several satellite-based storm properties, for example, cloud-top temperature, cloud-top cooling rate, and cloud particle effective radius, were investigated following the storm tracks. A framework for quantification of uncertainties of along-track properties resulting from tracking errors was also introduced. The majority of studied storms show a distinct maximum in cloud-top cooling rate; the corresponding time was used for track synchronization. The cloud growth phase was divided into an initial updraft intensification period before the maximum cooling and a continued growth period afterward. The initial updraft intensification...

Meteosat-Based Characterization of the Spatiotemporal Evolution of Warm Convective Cloud Fields over Central Europe

AbstractThe spatiotemporal evolution of warm convective cloud fields over central Europe is investigated on the basis of 30 cases using observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board the geostationary Meteosat platforms. Cloud fields are tracked in successive satellite images using cloud motion vectors. The time-lagged autocorrelation is calculated for spectral reflectance and cloud property fields using boxes of 16 × 16 pixels and adopting both Lagrangian and Eulerian perspectives. The 0.6-μm reflectance, cloud optical depth, and water path show a similar characteristic Lagrangian decorrelation time of about 30 min. In contrast, significantly lower decorrelation times are observed for the cloud effective radius and droplet density. It is shown that the Eulerian decorrelation time can be decomposed into an advective component and a convective component using the spatial autocorrelation function. In an Eulerian frame cloud fields generally decorrelate faster than in a...

Remote Sensing of Droplet Number Concentration in Warm Clouds: A Review of the Current State of Knowledge and Perspectives

Abstract The cloud droplet number concentration (N d) 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 N d, but it can be inferred from retrievals of cloud optical depth (τ c) cloud droplet effective radius (r e) 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. N d uncertainty is dominated by errors in r e, and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d 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.

Satellite-Based Characterization of Convective Growth and Glaciation and Its Relationship to Precipitation Formation over Central Europe

AbstractThe growth phase of convective storms and their transition to maturity is investigated based on more than 100 cases selected from the years 2012–14 over central Europe. Dynamical growth properties as well as cloud-top glaciation and microphysical characteristics are derived from the SEVIRI imaging radiometer aboard the geostationary Meteosat satellites. In addition, onset and intensity of surface precipitation are related to growth and glaciation processes using observations from the radar network of the German Weather Service. The majority of analyzed cases shows a distinct maximum in cloud-top cooling rate, which is used here for temporal synchronization. Cloud growth spans a period of approximately half an hour. Glaciation rate indicators suggest that freezing 15 min prior to the maximum cooling plays an important role in invigorating convective updrafts through the release of latent heat. Smaller ice particles are found for larger cloud-top cooling, which provides observational evidence that i...

Using SEVIRI radiances to retrieve cloud optical properties of convective cloud systems

In this case study the development of cloud properties (cloud optical depth, effective radius and cloud top height) during the life-cycle of a convective cloud system over Europe was analyzed. To retrieve the properties we developed a retrieval scheme based on the radiative transfer code MOMO and an optimal estimation procedure. Input data are the visible to short-wavelength infrared channels from SEVIRI. In contrast to many other retrieval schemes we used 4 channels simultaneously. Especially the 3,9μm channel provides additional information due to the fact that it measures solar reflectance and thermal emission and allows the inclusion of cloud top height into the retrieval. By using a time series of SEVIRI measurements we want to provide and examine the microphysical development of the cloud over life-time. We monitored the growth of the system and found the most active parts of the convection with the highest water content and optical depth in those regions where the cloud top height is largest, too. The effective radius of the cloud particles is largest in older regions of the cloud system, where the cloud is already decaying.In this case study the development of cloud properties (cloud optical depth, effective radius and cloud top height) during the life-cycle of a convective cloud system over Europe was analyzed. To retrieve the properties we developed a retrieval scheme based on the radiative transfer code MOMO and an optimal estimation procedure. Input data are the visible to short-wavelength infrared channels from SEVIRI. In contrast to many other retrieval schemes we used 4 channels simultaneously. Especially the 3,9μm channel provides additional information due to the fact that it measures solar reflectance and thermal emission and allows the inclusion of cloud top height into the retrieval. By using a time series of SEVIRI measurements we want to provide and examine the microphysical development of the cloud over life-time. We monitored the growth of the system and found the most active parts of the convection with the highest water content and optical depth in those regions where the cloud top height is largest, too. ...

Object-Based Metrics for Forecast Verification of Convective Development with Geostationary Satellite Data

AbstractObject-based metrics are adapted and applied to geostationary satellite observations with the evaluation of cloud forecasts in convective situations as the goal. Forecasts of the convection-permitting German-focused Consortium for Small-Scale Modeling (COSMO-DE) numerical model are transformed into synthetic observations using the RTTOV radiative transfer model, and contrasted with the corresponding real observations. Threshold-based segmentation techniques are applied to the fields for object identification. The statistical properties of the traditional measures cold cloud cover and average brightness temperature amplitude are contrasted to object-based metrics of spatial aggregation and object structure. Based on 59 case days from the summer half-years between 2012 and 2014, a variance decomposition technique is applied to the time series of the metrics to identify deficits in day-to-day, diurnal, and weather-regime-related variability of cold cloud characteristics in the forecasts. Furthermore,...

Evaluation of the EUMETSAT Global AVHRR Wind Product

AbstractThe European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) MetOp-A and MetOp-B satellites fly in the same polar orbit with a 180° phase difference, which enables the global retrieval of atmospheric motion vectors (AMVs, or “winds”) by tracking clouds in a pair of Advanced Very High Resolution Radiometer (AVHRR) infrared-window-channel images taken successively by the tandem platforms within their swath overlap area. This novel global wind product has been operational since 2015. As part of ongoing validation efforts, two months of MetOp global AMVs were compared with a suite of independent wind data, including AMVs from geostationary and polar-orbiter satellites as well as radiosonde and model winds. The performance of the new wind product is generally comparable to that of more established satellite winds. In the tropics, however, high-level MetOp global AMVs show a strong fast speed bias, increased root-mean-square difference, and considerably reduced speed correlatio...