Abstract
This paper evaluates convective precipitation as simulated by the convection-permitting climate model (CPM) Consortium for Small-Scale Modeling in climate mode (COSMO-CLM) (with 2.8 km grid-spacing) over Germany in the period 2001–2015. Characteristics of simulated convective precipitation objects like lifetime, area, mean intensity, and total precipitation are compared to characteristics observed by weather radar. For this purpose, a tracking algorithm was applied to simulated and observed precipitation with 5-min temporal resolution. The total amount of convective precipitation is well simulated, with a small overestimation of 2%. However, the simulation underestimates convective activity, represented by the number of convective objects, by 33%. This underestimation is especially pronounced in the lowlands of Northern Germany, whereas the simulation matches observations well in the mountainous areas of Southern Germany. The underestimation of activity is compensated by an overestimation of the simulated lifetime of convective objects. The observed mean intensity, maximum intensity, and area of precipitation objects increase with their lifetime showing the spectrum of convective storms ranging from short-living single-cell storms to long-living organized convection like supercells or squall lines. The CPM is capable of reproducing the lifetime dependence of these characteristics but shows a weaker increase in mean intensity with lifetime resulting in an especially pronounced underestimation (up to 25%) of mean precipitation intensity of long-living, extreme events. This limitation of the CPM is not identifiable by classical evaluation techniques using rain gauges. The simulation can reproduce the general increase of the highest percentiles of cell area, total precipitation, and mean intensity with temperature but fails to reproduce the increase of lifetime. The scaling rates of mean intensity and total precipitation resemble observed rates only in parts of the temperature range. The results suggest that the evaluation of coarse-grained (e.g., hourly) precipitation fields is insufficient for revealing challenges in convection-permitting simulations.
Highlights
The correct representation of deep convection in climate models is essential for assessing the risks associated with this phenomenon like wind gusts, hail, lightning, and flash floods.Convection-permitting climate models (CPMs) that simulate deep convection explicitly improve the representation of the diurnal cycle of precipitation and the simulation of extreme precipitation intensities on short time scales compared to models that parameterize convection [1,2,3,4]
The results suggest that the evaluation of coarse-grained precipitation fields is insufficient for revealing challenges in convection-permitting simulations
Since the temporal and spatial resolution of radar data is finer than the characteristic scales of convective clouds, it allows for continuous tracking of convective cells over their life cycle
Summary
The correct representation of deep convection in climate models is essential for assessing the risks associated with this phenomenon like wind gusts, hail, lightning, and flash floods. Since the temporal and spatial resolution of radar data is finer than the characteristic scales of convective clouds, it allows for continuous tracking of convective cells over their life cycle. Knowledge, sub-hourly precipitation output from continuous CPM simulation has not been evaluated yet This is why we apply a tracking algorithm to 5-min precipitation output of a CPM and to a newly developed 5-min precipitation climatology based on gauge adjusted radar data. Moseley et al [7] investigated the life cycle of convective precipitation cells by tracking radar data. They showed a stronger increase in mean intensity of convective precipitation cells with temperature than for stratiform cells. The results are summarized, and conclusions are drawn
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