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Zoebisch, Isabella; Forster, Caroline; Zinner, Tobias; Bugliaro, Luca; Tafferner, Arnold and Wapler, Kathrin (2020): Characteristics of deep moist convection over Germany in multi-source data. In: Meteorologische Zeitschrift, Vol. 29, No. 5: pp. 393-407

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Abstract

This study analyses characteristics of deep moist convection (DMC) over Germany with the aim to select relevant parameters that have the skill to improve the identification of current life cycle phase and the forecast of a lifetime of DMCs in an operational weather forecasting environment. No differentiation between thunderstorm organization types is done, since no simple differentiation method is available in an operational environment. In contrast to previous analyses, multiple data sources are used synchronously to explore an extensive data set of DMCs at high resolution in space and time. Basis of our analysis are all DMC detections in satellite data (using Cb-TRAM - Thunderstorm Tracking and Monitoring) in a five month period (June 2016, May/June/July 2017, and June 2018). For each of these DMCs the time series of selected parameters from satellite, ground-based radar, lightning detection, and numerical weather prediction (NWP) model data are inspected. In search for clear signatures of expectable lifetime and differences between short and long-lived DMCs, all thunderstorm systems are sorted by their lifetime. In addition, they are separated into four life cycle phases: 1. early growth, 2. advanced growth, 3. maturity, and 4. decay. Generally, it turns out that satellite, radar, and lightning data are the most suitable data to determine the actual life cycle phase of a DMC. It is shown that long-lived DMCs are, on average, related to lower minimum cloud top temperature and mid-level relative humidity and higher maximum of coverage area, vertically integrated water and lightning activity during their life cycle than short-lived systems. The NWP model parameters have a diagnostic potential to identify the remaining lifetime in connection with the observational data, but do not contain information about the actual life cycle phase. The results obtained in this study will be used for an investigation of their potential application in a nowcasting model, in order to determine the current phase of an observed DMC and to predict its remaining lifetime.

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