Refine
Document Type
- Article (2)
Language
- English (2)
Has Fulltext
- yes (2)
Is part of the Bibliography
- no (2)
Keywords
- Convection-permitting climate model (2) (remove)
Institute
Convection-permitting climate model are promising tools for improved representation of extremes, but the number of regions for which these models have been evaluated are still rather limited to make robust conclusions. In addition, an integrated interpretation of near-surface characteristics (typically temperature and precipitation) together with cloud properties is limited. The objective of this paper is to comprehensively evaluate the performance of a ‘state-of-the-art’ regional convection-permitting climate model for a mid-latitude coastal region with little orographic forcing. For this purpose, an 11-year integration with the COSMO-CLM model at Convection-Permitting Scale (CPS) using a grid spacing of 2.8 km was compared with in-situ and satellite-based observations of precipitation, temperature, cloud properties and radiation (both at the surface and the top of the atmosphere). CPS clearly improves the representation of precipitation, in especially the diurnal cycle, intensity and spatial distribution of hourly precipitation. Improvements in the representation of temperature are less obvious. In fact the CPS integration overestimates both low and high temperature extremes. The underlying cause for the overestimation of high temperature extremes was attributed to deficiencies in the cloud properties: The modelled cloud fraction is only 46 % whereas a cloud fraction of 65 % was observed. Surprisingly, the effect of this deficiency was less pronounced at the radiation balance at the top of the atmosphere due to a compensating error, in particular an overestimation of the reflectivity of clouds when they are present. Overall, a better representation of convective precipitation and a very good representation of the daily cycle in different cloud types were demonstrated. However, to overcome remaining deficiencies, additional efforts are necessary to improve cloud characteristics in CPS. This will be a challenging task due to compensating deficiencies that currently exist in ‘state-of-the-art’ models, yielding a good representation of average climate conditions. In the light of using the CPS models to study climate change it is necessary that these deficiencies are addressed in future research.
Lightning climate change projections show large uncertainties caused by limited empirical knowledge and strong assumptions inherent to coarse-grid climate modeling. This study addresses the latter issue by implementing and applying the lightning potential index parameterization (LPI) into a fine-grid convection-permitting regional climate model (CPM). This setup takes advantage of the explicit representation of deep convection in CPMs and allows for process-oriented LPI inputs such as vertical velocity within convective cells and coexistence of microphysical hydrometeor types, which are known to contribute to charge separation mechanisms. The LPI output is compared to output from a simpler flash rate parameterization, namely the CAPE × PREC parameterization, applied in a non-CPM on a coarser grid. The LPI’s implementation into the regional climate model COSMO-CLM successfully reproduces the observed lightning climatology, including its latitudinal gradient, its daily and hourly probability distributions, and its diurnal and annual cycles. Besides, the simulated temperature dependence of lightning reflects the observed dependency. The LPI outperforms the CAPE × PREC parameterization in all applied diagnostics. Based on this satisfactory evaluation, we used the LPI to a climate change projection under the RCP8.5 scenario. For the domain under investigation centered over Germany, the LPI projects a decrease of 4.8% in flash rate by the end of the century, in opposition to a projected increase of 17.4% as projected using the CAPE × PREC parameterization. The future decrease of LPI occurs mostly during the summer afternoons and is related to (i) a change in convection occurrence and (ii) changes in the microphysical mixing. The two parameterizations differ because of different convection occurrences in the CPM and non-CPM and because of changes in the microphysical mixing, which is only represented in the LPI lightning parameterization.