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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.
Several past summer floods in Central Europe were associated with so-called Vb‑cyclones propagating from the Mediterranean Sea north-eastward to Central Europe. This study illustrates the usefulness of the parametric transfer entropy measure TE‑linear in investigating heavy Vb‑cyclone precipitation events in the Odra catchment (Poland). With the application of the TE‑linear approach, we confirm the impact of the Mediterranean Sea on precipitation intensification. Moreover, we also detect significant information exchange to Vb‑cyclone precipitation from evaporation over the European continent along the typical Vb‑cyclone pathway. Thus, the Mediterranean Sea could enhance the Vb‑cyclone precipitation by pre-moistening continental moisture source regions that contribute to precipitation downstream in the investigated catchments. Overall, the transfer entropy approach with the measure TE‑linear proved to be computationally effective and complementary to traditional methods such as Lagrangian and Eulerian diagnostics.
Convective rain cell properties and the resulting precipitation scaling in a warm-temperate climate
(2022)
Convective precipitation events have been shown to intensify at rates exceeding the Clausius–Clapeyron rate (CC rate) of ca. 7% K−1 under current climate conditions. In this study, we relate atmospheric variables (low-level dew point temperature, convective available potential energy, and vertical wind shear), which are regarded as ingredients for severe deep convection, to properties of convective rain cells (cell area, maximum precipitation intensity, lifetime, precipitation sum, and cell speed). The rain cell properties are obtained from a rain gauge-adjusted radar dataset in a mid-latitude region, which is characterized by a temperate climate with warm summers (Germany). Different Lagrangian cell properties scale with dew point temperature at varying rates. While the maximum precipitation intensity of cells scales consistently at the CC rate, the area and precipitation sum per cell scale at varying rates above the CC rate. We show that this super-CC scaling is caused by a covarying increase of convective available potential energy with dew point temperature. Wind shear increases the precipitation sum per cell mainly by increasing the spatial cell extent. From a Eulerian point of view, this increase is partly compensated by a higher cell velocity, which leads to Eulerian precipitation scaling rates close to and slightly above the CC rate. Thus, Eulerian scaling rates of convective precipitation are modulated by convective available potential energy and vertical wind shear, making it unlikely that present scaling rates can be applied to future climate conditions. Furthermore, we show that cells that cause heavy precipitation at fixed locations occur at low vertical wind shear and, thus, move relatively slowly compared to typical cells.
Moisture sources of heavy precipitation in Central Europe in synoptic situations with Vb-cyclones
(2022)
During the past century, several extreme summer floods in Central Europe were associated with so-called Vb-cyclones propagating from the Mediterranean Sea north-eastward to Central Europe. The processes intensifying the precipitation in synoptic situations with Vb-cyclones in the Danube, Elbe, and Odra catchments are only partially understood. Our study aims to investigate these processes with Lagrangian moisture-source diagnostics for 16 selected Vb-events. Moreover, we analyse the characteristics of typical moisture source regions during 1107 Vb-events from 1901 to 2010 based on ERA-20C reanalysis dynamically downscaled with COSMO-CLM+NEMO. We observe moisture contributions by various source regions highlighting the complex dynamical interplay of different air masses leading to moisture convergence in synoptic situations with Vb-cyclones. Overall, up to 80% of the precipitation originates from the European continent, indicating the importance of continental moisture recycling, especially within the respective river catchment. Other major moisture uptake regions are the North Sea, the Baltic Sea, the North Atlantic, and for a few events the Black Sea. Remarkably, anomalies in these oceanic source regions show no connection to precipitation amounts in synoptic situations with Vb-cyclones. In contrast, the Vb-cyclones with the highest precipitation are associated with anomalously high evaporation in the Mediterranean Sea, even though the Mediterranean Sea is only a minor moisture source region on average. Interestingly, the evaporation anomalies are not connected with sea-surface temperature but with wind-speed anomalies (Spearman’s rank correlation coefficient R≈0.7, significant with p<0.01) indicating mainly dynamically driven evaporation. The particular role of the Mediterranean Sea hints towards possible importance of Mediterranean moisture for the early-stage intensification of Vb-cyclones and the pre-moistening of the continental uptake regions upstream of the target catchments.
Seasonal forecasting systems still have difficulties predicting temperature over continental regions, while their performance is better over some maritime regions. On the other hand, the land surface is a substantial source of (sub-)seasonal predictability. A crucial land surface component in focus here is the snow cover, which stores water and modulates the surface radiation balance. This paper’s goal is to attribute snow cover seasonal forecasting biases and lack of skill to either initialization or parameterization errors. For this purpose, we compare the snow representation in five seasonal forecasting systems (from DWD, ECMWF, Météo-France, CMCC, and ECCC) and their performances in predicting snow and 2-m temperature over a Siberian region against ERA5 reanalysis and station data. Although all systems use similar atmospheric and land initialization approaches and data, their snow and temperature biases differ in sign and amplitude. Too-large initial snow biases persist over the forecast period, delaying and prolonging the melting phase. The simplest snow scheme (used in DWD’s system) shows too-early and fast melting in spring. However, systems including multi-layer snow schemes (Météo-France and CMCC) do not necessarily perform better. Both initialization and parameterization are causes of snow biases, but, depending on the system, one can be more dominant.
In the last decade, the Climate Limited-area Modeling (CLM) Community has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM community model, ERA-Interim reanalysis and eight Global Climate Models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44◦(∼50 km), 0.22◦ (∼25 km) and 0.11◦ (∼12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modelling communities is needed to increase the reliability of the GCM-RCM modelling chain.
The goal of limited area models (LAMs) is to downscale coarse-gridded general circulation model output to represent small-scale features of weather and climate. The LAM needs information from the driving coarse-gridded model passing through its lateral boundaries. The treatment of this information transfer causes inconsistencies between driving and nested models and, subsequently, issues in regional weather and climate simulations. This work examines errors arising from choices taken by the modeler (temporal update frequency of boundary data, spatial resolution jump, and numerical lateral boundary formulation) systematically in an idealized simulation environment. So-called Big-Brother Experiments were performed with the LAM COSMO-CLM (0.11° grid spacing). A baroclinic wave in a zonal channel was simulated over flat terrain with and without a Gaussian hill. The results reveal that the quality of the driving data, here represented by simulations only differing from the LAM simulations by reduced spatial resolution, dominates the performance of the nested model. Consequently, at the simulated mesoscale, the performance of the nested small-scale model simulations is weakly sensitive to the numerical lateral boundary formulation (Davies relaxation or the newly implemented, computationally less demanding Mesinger Eta-model formulation). The performance sensitivity to boundary update frequency and resolution jump is small when at least 6-hourly updates and a resolution jump factor of maximally six is used. Gaussian hill LAM simulations illustrated the strength of downscaling; they can represent small-scale features missing in the coarse-scale driving simulations. In the idealized simulation experiments, spectral nudging is not advisable as it imprints the driving models deficits on the nested simulation.
In the last decade, the Climate Limited-area Modeling Community (CLM-Community) has contributed to the Coordinated Regional Climate Downscaling Experiment (CORDEX) with an extensive set of regional climate simulations. Using several versions of the COSMO-CLM-Community model, ERA-Interim reanalysis and eight global climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were dynamically downscaled with horizontal grid spacings of 0.44∘ (∼ 50 km), 0.22∘ (∼ 25 km), and 0.11∘ (∼ 12 km) over the CORDEX domains Europe, South Asia, East Asia, Australasia, and Africa. This major effort resulted in 80 regional climate simulations publicly available through the Earth System Grid Federation (ESGF) web portals for use in impact studies and climate scenario assessments. Here we review the production of these simulations and assess their results in terms of mean near-surface temperature and precipitation to aid the future design of the COSMO-CLM model simulations. It is found that a domain-specific parameter tuning is beneficial, while increasing horizontal model resolution (from 50 to 25 or 12 km grid spacing) alone does not always improve the performance of the simulation. Moreover, the COSMO-CLM performance depends on the driving data. This is generally more important than the dependence on horizontal resolution, model version, and configuration. Our results emphasize the importance of performing regional climate projections in a coordinated way, where guidance from both the global (GCM) and regional (RCM) climate modeling communities is needed to increase the reliability of the GCM–RCM modeling chain.
Extreme 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.
The frequency of extreme events has changed, having a direct impact on human lives. Regional climate models help us to predict these regional climate changes. This work presents an atmosphere–ocean coupled regional climate system model (RCSM; with the atmospheric component COSMO-CLM and the ocean component NEMO) over the European domain, including three marginal seas: the Mediterranean, North, and Baltic Sea. To test the model, we evaluate a simulation of more than 100 years (1900–2009) with a spatial grid resolution of about 25 km. The simulation was nested into a coupled global simulation with the model MPI-ESM in a low-resolution configuration, whose ocean temperature and salinity were nudged to the ocean–ice component of the MPI-ESM forced with the NOAA 20th Century Reanalysis (20CR). The evaluation shows the robustness of the RCSM and discusses the added value by the coupled marginal seas over an atmosphere-only simulation. The coupled system is stable for the complete 20th century and provides a better representation of extreme temperatures compared to the atmosphere-only model. The produced long-term dataset will help us to better understand the processes leading to meteorological and climate extremes.