Representation of precipitation and top-of-atmosphere radiation in a multi-model convection-permitting ensemble for the Lake Victoria Basin (East-Africa)

The CORDEX Flagship Pilot Study ELVIC (climate Extremes in the Lake VICtoria basin) was recently established to investigate how extreme weather events will evolve in this region of the world and to provide improved information for the climate impact community. Here we assess the added value of the convection-permitting scale simulations on the representation of moist convective systems over and around Lake Victoria. With this aim, 10 year present-day model simulations were carried out with five regional climate models at both PARameterized (PAR) scales (12–25 km) and Convection-Permitting (CP) scales (2.5–4.5 km), with COSMO-CLM, RegCM, AROME, WRF and UKMO. Most substantial systematic improvements were found in metrics related to deep convection. For example, the timing of the daily maximum in precipitation is systematically delayed in CP compared to PAR models, thereby improving the agreement with observations. The large overestimation in the total number of rainy events is alleviated in the CP models. Systematic improvements were found in the diurnal cycle in Top-Of-Atmosphere (TOA) radiation and in some metrics for precipitation intensity. No unanimous improvement nor deterioration was found in the representation of the spatial distribution of total rainfall and the seasonal cycle when going to the CP scale. Furthermore, some substantial biases in TOA upward radiative fluxes remain. Generally our analysis indicates that the representation of the convective systems is strongly improved in CP compared to PAR models, giving confidence that the models are valuable tools for studying how extreme precipitation events may evolve in the future in the Lake Victoria basin and its surroundings

COSMO-CLM regional climate simulations in the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework: a review

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

Heat stress increase under climate change twice as large in cities as in rural areas : a study for a densely populated midlatitude maritime region

Urban areas are usually warmer than their surrounding natural areas, an effect known as the urban heat island effect. As such, they are particularly vulnerable to global warming and associated increases in extreme temperatures. Yet ensemble climate-model projections are generally performed on a scale that is too coarse to represent the evolution of temperatures in cities. Here, for the first time, we combine unprecedented long-term (35years) urban climate model integrations at the convection-permitting scale (2.8km resolution) with information from an ensemble of general circulation models to assess temperature-based heat stress for Belgium, a densely populated midlatitude maritime region. We discover that the heat stress increase toward the mid-21st century is twice as large in cities compared to their surrounding rural areas. The exacerbation is driven by the urban heat island itself, its concurrence with heat waves, and urban expansion. Cities experience a heat stress multiplication by a factor 1.4 and 15 depending on the scenario. Remarkably, the future heat stress surpasses everywhere the urban hot spots of today. Our results demonstrate the need to combine information from climate models, acting on different scales, for climate change risk assessment in heterogeneous regions. Moreover, these results highlight the necessity for adaptation to increasing heat stress, especially in urban areas

A new method to estimate air-quality levels using a synoptic-regression approach, part 2 : future O3 concentrations

Using the synoptic-regression based approach developed in Part! of this research, this study estimates future maximum 8 hourly mean O-3 levels (m8hO(3)) using three future SRES (Special Report on Emission) scenarios for a rural background area situated in The Netherlands. The statistical downscaling tool was used to downscale the Atmospheric-Ocean Coupled General Circulation Model (AOGCM) ECHAM5-MPI/OM for the present-day 20 Century (20C) control run (1991-2000) and the future SRES scenarios A2, A1B and B1 for two periods (2051-2060 and 2091-2100). First, the statistical downscaling tool is evaluated in terms of down-scaled m8hO(3) levels for the present-day climate, using a long record of observed m8hO(3) concentrations. It was found that a bias correction is needed and this bias correction is then further used to estimate future m8hO(3) concentrations. Under the various SRES scenarios, the overall mean m8hO(3) increases with 2.5-6.5 and 6.1-10.9 mu g m(-3), for the 2051-2060 and 2091-2100 period respectively, which is about 20% of the present-day 10-year average. This effect is enhanced when considering the summer season only, with a range of increase between the different future scenarios of 5.4-12.5 mu g m(-3) and 13.4-26 mu g m(-3) (for 2051-2060 and 2091-2100 respectively) against a present-day summer average of 73.514 mu g m(-3). An increase in maximum temperature and shortwave radiation, associated with a decrease in cloud cover under the various future scenarios are the main drivers of ozone increase. A comparison with August 2003 shows the physical plausibility of our results and reflects that the extreme summer of 2003 might show a close resemblance to future European summers in terms of m8hO(3) and meteorological characteristics. (C) 2009 Elsevier Ltd. All rights reserved

A new method to estimate air-quality levels using a synoptic-regression approach, part 1 : present-day O3 and PM10 analysis

In order to make projections for future air-quality levels, a robust methodology is needed that succeeds in reconstructing present-day air-quality levels. At present, climate projections for meteorological variables are available from Atmospheric-Ocean Coupled Global Climate Models (AOGCMs) but the temporal and spatial resolution is insufficient for air-quality assessment. Therefore, a variety of methods are tested in this paper in their ability to hindcast maximum 8 hourly levels of O-3 and daily mean PM10 from observed meteorological data. The methods are based on a multiple linear regression technique combined with the automated Lamb weather classification. Moreover, we studied whether the above-mentioned multiple regression analysis still holds when driven by operational ECMWF (European Center for Medium-Range Weather Forecast) meteorological data. The main results show that a weather type classification prior to the regression analysis is superior to a simple linear regression approach. In contrast to PM10 downscaling, seasonal characteristics should be taken into account during the downscaling of O-3 time series. Apart from a lower explained variance due to intrinsic limitations of the regression approach itself, a lower variability of the meteorological predictors (resolution effect) and model deficiencies, this synoptic-regression-based tool is generally able to reproduce the relevant statistical properties of the observed O-3 distributions important in terms of European air quality Directives and air quality mitigation strategies. For PM10, the situation is different as the approach using only meteorology data was found to be insufficient to explain the observed PM10 variability using the meteorological variables considered in this study. (C) 2009 Elsevier Ltd. All rights reserved

The Impact of Size Distribution Assumptions in a Bulk One-Moment Microphysics Scheme on Simulated Surface Precipitation and Storm Dynamics during a Low-Topped Supercell Case in Belgium

In this research the impact of modifying the size distribution assumptions of the precipitating hydrometeors in a bulk one-moment microphysics scheme on simulated surface precipitation and storm dynamics has been explored for long-lived low-topped supercells in Belgium. It was shown that weighting the largest precipitating ice species of the microphysics scheme to small graupel results in an increase of surface precipitation because of counteracting effects. On the one hand, the precipitation formation process slowed down, resulting in lower precipitation efficiency. On the other hand, latent heat release associated with freezing favored more intense storms. In contrast to previous studies finding decreased surface precipitation when graupel was present in the microphysics parameterization, storms were rather shallow in the authors' simulations. This left little time for graupel sublimation. The impact of size distribution assumptions of snow was found to be small, but more realistic size distribution assumptions of rain led to the strongest effect on surface precipitation. Cold pools shrunk because of weaker rain evaporation at the cold pool boundaries, leading to a decreased surface rain area

A new statistical approach to downscale wind speed distributions at a site in northern Europe

This paper explores a statistical regression approach to downscale large-scale global circulation model output to the wind speed distribution at the hub-height of tall wind turbines. The methodology is developed for Cabauw, using observational, ERA-Interim and ECHAM5 data. The regression analysis is based on the parameters of the probability distribution functions (pdfs) and includes a variable evaluation prior to the development of the statistical models. During winter ECHAM5 performs very well in representing the ERA-Interim wind speed pdf at hub-height. However, during summer, the hub-height wind speed pdf is not well represented by ECHAM5. A regression analysis shows that during summer-day the hub-height wind speed is strongly linked to the wind speed at higher, skillfully represented levels. The summer-day hub-height wind speed can therefore be skillfully predicted using wind speed pdf parameters of higher levels (R-2 of the model using 500m wind speed scale parameter as a predictor is 0.84). During the summer-night, the stable boundary layer is much shallower and the statistical model shows that solely the higher level wind speed is not able to skillfully predict the hub-height wind speed pdf (R-2 of 0.59). Including temperature information in the downscaling model substantially improves the prediction of the summer-night hub-height wind speed pdf (R-2 adjusted of 0.68)