The 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 period is variable and strongly depends on the convection initiation mechanism and detection conditions. The continued growth period is more confined, lasting between 30 and 45 min. The change in anvil size and the resulting average anvil edge velocity were determined from infrared satellite images. As a consequence of mass transport, the anvil edge velocity shows its highest correlation with the cloud-top vertical velocity approximately 20–30 min after the maximum in the cloud-top cooling rate. Larger effective radii of ice crystals were observed for vertically slower-growing clouds. The largest anticorrelation between cloud-top vertical velocity and effective radius was found at a time lag of 20 min after the maximum in cloud-top cooling.

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Abstract:Precipitation is still one of the most complex climate variables to observe, to understand, and to handle within climate monitoring and climate analysis as well as to simulate in numerical weather prediction and climate models. Especially over ocean, less is known about precipitation than over land due to the sparsity of in situ observations. Here, we introduce and discuss a global Expert Team on Climate Change and Indices (ETCCDI)-based precipitation climatology. The basis for computation of this climatology is the global precipitation dataset Daily Precipitation Analysis for Climate Prediction (DAPACLIP) which combines in situ observation data over land and satellite-based remote sensing data over ocean in daily temporal resolution, namely data from the Global Precipitation Climatology Centre (GPCC) and the Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) dataset. The DAPACLIP dataset spans the period 1988-2008 and thus the global ETCCDI-based precipitation climatology covers 21 years in total. Regional aspects of the climatology are also discussed with focus on Europe and the monsoon region of south-east Asia. To our knowledge, this is the first presentation and discussion of an ETCCDI-based precipitation climatology on a global scale.

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