Abstract
AbstractExtreme convective precipitation is expected to increase with global warming. However, the rate of increase and the understanding of contributing processes remain highly uncertain. We investigated characteristics of convective rain cells like area, intensity, and lifetime as simulated by a convection‐permitting climate model in the area of Germany under historical (1976–2005) and future (end‐of‐century, RCP8.5 scenario) conditions. To this end, a tracking algorithm was applied to 5‐min precipitation output. While the number of convective cells is virtually similar under historical and future conditions, there are more intense and larger cells in the future. This yields an increase in hourly precipitation extremes, although mean precipitation decreases. The relative change in the frequency distributions of area, intensity, and precipitation sum per cell is highest for the most extreme percentiles, suggesting that extreme events intensify the most. Furthermore, we investigated the temperature and moisture scaling of cell characteristics. The temperature scaling drops off at high temperatures, with a shift in drop‐off towards higher temperatures in the future, allowing for higher peak values. In contrast, dew point temperature scaling shows consistent rates across the whole dew point range. Cell characteristics scale at varying rates, either below (mean intensity), at about (maximum intensity and area), or above (precipitation sum) the Clausius–Clapeyron rate. Thus, the widely investigated extreme precipitation scaling at fixed locations is a complex product of the scaling of different cell characteristics. The dew point scaling rates and absolute values of the scaling curves in historical and future conditions are closest for the highest percentiles. Therefore, near‐surface humidity provides a good predictor for the upper limit of for example, maximum intensity and total precipitation of individual convective cells. However, the frequency distribution of the number of cells depending on dew point temperature changes in the future, preventing statistical inference of extreme precipitation from near‐surface humidity.
Highlights
The question of how extreme precipitation will change in the future due to climate change is of high relevance due to the potentially severe hazards accompanying it
We investigated how the characteristics of convective cells might change in a climate change scenario by applying a tracking algorithm to CPM precipitation with high temporal resolution
Changes in the frequency distribution of cell characteristics show a complex picture of the response of deep convection to climate warming
Summary
The question of how extreme precipitation will change in the future due to climate change is of high relevance due to the potentially severe hazards accompanying it. Varying scaling rates in observations and shifting scaling curves in CPMs indicate that the dynamics of deep convection and changes in the large-scale environment have a strong influence on the scaling rate and that the temperature scaling of extreme hourly precipitation under current climate conditions cannot be used to infer how convective events might react to climate change. We apply a tracking algorithm to 5-min precipitation output from the regional climate model COSMO-CLM to investigate convective rain cells' characteristics under historical and future conditions. Prein et al (2017b) investigated the characteristics of Mesoscale Convective Systems in the USA by applying a tracking algorithm to hourly precipitation data from a CPM They found an increase in the storm size and storm intensity for future conditions using a pseudo-global warming approach. We discuss the influence of the large-scale environment described by CAPE and wind shear and potential limitations of the current study
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