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The population in the Lake Victoria Basin (LVB) is affected by extreme weather both on land, where flooding regularly occurs and on the lake, where nightly storms often catch fishermen by surprise. The CORDEX Flagship Pilot Study ELVIC investigates how extreme weather events will evolve in this region of the world and to provide improved information for the climate impact community. Here we evaluate the performance of five regional climate models at convection-permitting resolution and present projections for the future using COSMO-CLM in a pseudo global warming approach. Most substantial systematic improvements were found in metrics related to deep convection in convection-permitting models compared to their coarser scale counterparts. For the future, extreme precipitation and wind gusts are expected to increase over the lake due to an thermodynamically induced increase in water vapor whereas the impacts of weaker meso-scale circulation over the lake and stronger thunderstorm dynamics compensate each other. More compound events are expected for the future during which both rainfall and wind gusts are intense. Interestingly, the mean precipitation is strongly affected by uncertainties in large-scale dynamics whereas thermodynamics dominate extreme precipitation. This might imply that uncertainties in future projected extremes are smaller than those in mean precipitation.

The observed evolution of Antarctic sea ice extent is marked by an abrupt decrease in 2016/2017. After several years of gradual increase culminated in an all-time record high in 2014/2015, a rapid decline in 2016 led to an unprecedented minimum, and unusual low extents have been observed since then. Even though this record has now been beaten, the sudden drop from extreme high values to a minimum in less than two years is unique to this event, whose dynamics are still uncertain. While it was likely triggered by anomalous atmospheric conditions in the prior months, the contribution of the ocean conditions, as a preconditioning which amplified the response of the sea ice or helped to maintain the anomalies for a longer period, still needs to be quantified. To evaluate the respective influences of the atmosphere and ocean on this 2016 event, we have performed sensitivity experiments using the circum-Antarctic fully coupled model (ice-sheet–ocean–sea-ice–atmosphere) PARASO. First, a control experiment with the model forced by lateral boundary conditions derived from observations (ERA5 in the atmosphere, ORAS5 in the ocean) is performed over the period 1985-2018. In such a set-up, the model correlates well with the observations and is able to capture the 2016 drop. Then, the model is integrated again between 2016 and 2018 with the same atmospheric boundary forcing, but with different initial conditions in the ocean: namely, ocean conditions from previous years in the control run are used as initial state in 2016 in the sensitivity experiments, producing an ensemble of 5 members. Preliminary results indicate that the 2016 drop is captured by all members, suggesting the atmospheric boundary forcing as the dominant driver and confirming that the event is induced by large-scale atmospheric dynamics. However, some variability is present in the amplitude and timing of the drop, as well as in the evolution and recovery of the sea ice in the following months, which may be influenced by the different states of the ocean. Related processes are further investigated by examining different oceanic and atmospheric fields, focussing on the role of ocean preconditioning by identifying the differences between the members and their impact.

The remoteness of the Antarctic continent has important implications for the microphysical properties of clouds: In particular, the rare abundance of ice-nucleating particles (INP) limits the primary nucleation of ice crystals. Yet, persistent mixed-phase clouds with ice crystal number concentrations of 0.1-1l-1 are still observed in the Arctic and Antarctic. However, the ability of regional climate models to reproduce these mixed-phase clouds remains limited, much like the knowledge about their climatological effects. Thus, we added a module to the regional climate model COSMO-CLM² aimed at improving the parametrisation of the aerosol-cycle, which allows us to prescribe different concentrations of INPs. We examined the model response to different concentrations by running it in an area around the Belgian Princess Elisabeth Station in Dronning Maud Land for one month and with four different concentration settings: The first, corresponding to the low end of INP concentrations we observed at the station, the second, corresponding to the high end of INP concentrations we observed at the station, and the third and fourth, to the low and high end of continental observations. The performance was evaluated by comparing the simulation results with radar and ceilometer observations taken at the station. Finally, we analysed the differences between the four simulations to determine the overall sensitivity of the model to variability in INP concentrations, which allows us to draw conclusions about the importance of accurately simulating processes related to ice nucleation, and about the climatological implications that a change in aerosol concentrations would have.

Offshore wind zones are reaching sizes at which they start to affect each other and potentially also alter mesoscale weather systems, impacting the energy production. Here, we assess the impact of future wind farm characteristics, like turbine type and capacity density, on cluster-scale wake losses. For this we use the mesoscale model COSMO-CLM at the km-scale resolution, which skillfully models frequency distributions of wind speed and wind direction at turbine level compared to measurement masts, wind lidars and satellite data. It was found that inter-farm wakes can reduce the long-term capacity factor at the inflow edge of wind farms from 59% to between 55% and 40% depending on the degree of clustering and the size of the upwind farms, for a layout equipped with 5MW turbines at a capacity density of 8.1 MW / km². Moving to next-generation wind turbines (15MW) partly mitigates this degradation, as the total generation over all windfarms (TWh) is increased by 19% under the same wind farm capacity density. On the other hand, increases in the capacity density in this future layout lead to a less than proportional (0.8 to 1) increase in the basin-integrated, total generation as a consequence of more intense intra- and inter-farm wake effects. Generally, wind farm characteristics play an essential role in inter-farm wake losses, which should be included in future wind farm planning.

Vertical temperature profiles influence the wind power generation of large offshore wind farms through stability-dependent effects such as blockage and gravity waves. However, wind energy resource assessments often only consider idealized temperature profiles, which are not guaranteed to represent the atmospheric state and its variation. To assist the selection of atmospheric states, we created a temperature profile atlas and representative temperature profiles for Europe. To achieve this, we developed a new, generally applicable, analytical temperature model for the atmospheric boundary layer and lower troposphere with which the European temperature profiles over the period 2016-2020 are analyzed using a double clustering approach. This methodology results in eight representative profiles and spatial clusters with similarly behaving temperature profiles, which are quantified in cluster fingerprints. These representative profiles and cluster fingerprints can be used in the selection of background profiles for wind energy simulations such as LES models and can furthermore be used to make informed comparisons of results from different wind farm sites.

Offshore wind energy has seen a steady increase in the latest years as it serves as an ideal alternative energy source to meet our renewable energy goals. Due to this increase in interest and in installations of offshore wind farms a better understanding of the impact of waves on the power production of wind farms in necessary. This wave-wind farm power production interaction has scarcely been examined, however, some exceptions of small scale large-eddy-simulations exist. Unfortunately, these studies are not able to take multiple wind farms under real weather conditions into account. Here, we show the power production and wake lengths of 1250 offshore wind turbines located in the German Bight simulated by a stand-alone atmospheric (WRF) model and a coupled atmosphere-wave (WRF-SWAN) model. The coupled atmosphere-wave model estimates larger (smaller) power production in case of waves and wind traveling in the same (opposed) direction compared to the stand-alone atmospheric model. The relative difference between the two models can be as much as 20% for the two-week averaged grid power production, while the difference in total power over this two-week period is equal to 9%. Moreover, the wind farm wake lengths of waves and wind traveling in the same (opposed) direction are longer (shorter) for the coupled atmosphere-wave model compared to the stand-alone atmospheric model. Here, the relative difference of the mean wake length between the two models can be up to 25%. This shows the importance of waves as a part of the offshore wind environment and can be an important factor in future wind assessment or power production estimation studies.

Recent research suggests that atmospheric gravity waves can affect offshore wind-farm performance. A fast wind-farm boundary layer model has been proposed to simulate the effects of these gravity waves on wind-farm operation by Allaerts and Meyers (2019). The current work extends the applicability of that model to free atmospheres in which wind and stability vary with altitude. We validate the model using reference cases from literature on mountain waves. Analysis of a reference flow shows that internal gravity-wave resonance caused by the atmospheric non-uniformity can prohibit perturbations in the atmospheric boundary layer (ABL) at the wavelengths where it occurs. To determine the overall impact of the vertical variations in the atmospheric conditions on wind-farm operation, we consider 1 year of operation of the Belgian–Dutch wind-farm cluster with the extended model. We find that this impact on individual flow cases is often of the same order of magnitude as the total flow perturbation. In 16.6 % of the analyzed flows, the relative difference in upstream velocity reduction between uniform and non-uniform free atmospheres is more than 30 %. However, this impact is small when averaged over all cases. This suggests that variations in the atmospheric conditions should be taken into account when simulating wind-farm operation in specific atmospheric conditions.

The boreal zone has experienced more severe fires over the last years, often coinciding with years of anomalously high lightning frequencies. These lightning frequencies might increase even further with global warming. Current lightning predictions are however highly uncertain, either relying on empirical relationships derived from present climate, or coarse-scale climate scenario simulations in which the critical process of deep convection is parameterized, and the detailed representation of land-atmosphere interactions is lacking. In this study, we used the NASA Unified-Weather Research and Forecasting (NU-WRF) modeling framework to simulate lightning over a 550,000 km2 domain including the Great Slave Lake in Canada. Simulations were run for the six lightning seasons (June-August; 2015-2020) at both a convection-parameterized (9 km) and convection-permitting (3 km) spatial resolution. Additionally, two microphysics (MP) schemes (Goddard 4ICE and Thompson) were compared at both resolutions. From the simulation output, we derived four diagnostic lightning indices which were evaluated against observations from the Canadian Lightning Detection Network (CLDN). This evaluation was done in terms of the capability of the indices to match the observational spatial pattern (temporally averaged), spatiotemporal frequency distribution, daily and seasonal climatology (spatially averaged), and an event-based overall skill assessment. Our results show that the Thompson MP scheme better predicts the daily climatology than the Goddard 4ICE MP scheme. The Goddard 4ICE MP scheme, on the other hand, predicts the spatial pattern best. Both MP schemes predict the seasonality equally well. Concerning the spatial resolution, a clear improvement when simulating at convection-permitting resolution is only seen for the Goddard 4ICE MP scheme. Regarding the different lightning indices, no clear superior index is found as the relative performance of each index strongly depends on the evaluation criteria. Finally, the study shows that models are in particular poor in reproducing the long-term averaged observed spatial pattern of lightning occurrence. This might be related to an insufficient representation of the land surface heterogeneity in the study area.

With ongoing climate change and rapid urbanization, exposure to severe heat is expected to accelerate in tropical East African cities. Yet not all parts of the city are equally vulnerable. The present-day intra-urban heat stress variation in Kampala, the capital city of Uganda, is quantified by deriving the daily mean, minimum and maximum Humidex Index from a network of low-cost temperature and humidity sensors operational in 2018-2019. Heat is shown to be heterogeneously distributed over the city, with a daily maximum intra-urban Humidex Index deviation of 6.4°C averaged over the observational period, but reaching 14.5°C on the most extreme day.Also extreme heat is heterogeneously distributed over the city, putting local populations at risk of great discomfort or health danger. One station in a dense settlement reports a daily maximum Humidex Index above 40°C in 68% of the observation days, a level which was never reached at the nearby campus of the Makerere University, and only a few times at the city outskirts. About 75% of this intra-urban heat stress variability is explained by the Normalized Difference Vegetation Index (NDVI), though strong collinearity is found with other variables like impervious surface fraction and population density.Overall, our results highlight the importance of (i) including both temperature and humidity in heat stress studies, (ii) urban greening in city planning, and (iii) large intra-urban heat stress variations in heat action planning in tropical humid cities.

The Antarctic Climate is characterized by strong interactions between the Southern Ocean, its sea ice cover, and the overlying atmosphere taking place over a wide range of spatio-temporal scales. This coupling constrains our ability to isolate the role of specific components of the climate system on the dynamics of the Antarctic Climate, especially with stand-alone approaches neglecting the feedbacks at play. Based on coupled model simulations, we explore how the ocean can drive the interactions with the cryosphere and atmosphere at two distinct spatio-temporal scales. First, the role of ocean mesoscale eddies is investigated. We describe the imprint of mesoscale eddies on the sea ice and atmosphere in a high-resolution simulation of the Adélie Land sector (East Antarctica) performed with a regional coupled ocean--sea ice--atmosphere model (NEMO-MAR). Specific attention is given to the role of the sea ice in the modulation of the air-sea interactions at mesoscale and to the influence of eddy-driven fluxes on the ocean and sea ice. We show that mesoscale eddies affect near-surface winds and air temperature both in ice-free and ice-covered conditions due to their imprint on the sea ice cover. In addition, eddies promote northward sea ice transport and decrease momentum transfer by surface stress to the ocean. In a second section, we move to larger spatial and temporal scales and delve into the influence of the ocean on the seasonal to interannual variability of the sea ice, atmosphere, and ice shelves basal melt at the scale of the Southern Ocean. This work is based on early results from a new coupled ocean–sea ice--atmosphere--ice sheet configuration with explicit under-ice shelf cavities called PARASO. We focus on subsurface heat content variability and its influence on the interactions between the ocean, the sea ice, the atmosphere, and the Antarctic Ice Sheet.

By serving as condensation and ice nuclei, aerosols play a vital role in the formation of clouds. This has significant implications for the radiation balance and precipitation amounts over the Antarctic Ice Sheet, where type and amount of aerosols differ significantly from other places because of its remote location. However, that is also the reason observations are sparse, and consequently, few studies exist examining this effect. Recently, a module was added to the COSMO-CLM² regional climate model to account for the aerosol-cycle. The model was integrated for the region around the Princess Elisabeth Antarctic research station (PEA) in Dronning Maud Land for a period of 10 days in January 2016, of which the first 3 days were discarded. Varying cloud condensation and ice nuclei were prescribed to the model, based on observations from PEA. The model output was compared to observations of cloud structure and precipitation amounts taken at PEA, as well as the unmodified COSMO-CLM² model. The model integrations indicate that the number of ice nuclei has a significant impact on the microphysical composition of clouds, with higher numbers being associated with a lower amount of liquid water content of clouds and higher precipitation amounts. Additional runs are performed to confirm and extend these findings for an entire year. Recent measurements of ice nuclei particle concentrations obtained during two austral summers are also considered. Moreover, we analysed how atmospheric dynamics affect the cloud-aerosol interaction by analysing the model sensitivity for different weather regimes.

The rapid growth of the offshore wind energy sector emphasizes the need for realistic projections of the lifetime energy yield of existing and planned offshore windfarms. Analyses of CMIP5 data show that, even though near-future wind speed changes over Europe and the North Sea are uncertain across models, these changes should be taken into account by wind industries due to the potentially large impact on the energy. Thanks to advances in model design and the increase in computing resources over the past decades, regional climate models (RCMs) can be used for multi-decadal simulations and that at a spatial resolution of a couple of kilometers or less. These high-resolution simulations not only allow for an improved representation of weather systems, but also allow to represent the interactions between windfarms and the atmosphere through a wind farm parametrization. In this way, RCMs can be employed for a detailed wind resource assessment for the coming decades that takes into account the wakes and energy losses induced by upwind arrays and clusters.In our wind resource assessment, we use the regional climate model COSMO-CLM, extended with the Fitch wind farm parametrization. An evaluation of a 10-year, ERA5-driven simulation at 2.8km resolution against in-situ anemometers, lidar measurements and satellite-borne ASCAT measurements that has been performed for the North Sea will be discussed. For the year 2019, the spatially-variable bias in the mean wind speed was found to be generally within +- 0.4 m/s and the overlap in the wind speed distributions generally larger than 92%. Next, array- and cluster-scale wakes, modelled at horizontal resolutions of 2.8km and 1km were analysed and compared for a present and near-future windfarm layout over the southern North Sea, providing valuable information on how regional changes to the wind farm layout will impact the farm-specific energy yields due to additional upwind wake generation under different atmospheric conditions. This research frames within the FREEWIND project of KU Leuven (freewind-project.eu), which aims to contribute to the scientific research of offshore wind energy and plans to provide wind farm planning and forecasting tools on multiple time scales over the coming years.

Before an off-shore wind farm is built a thorough resource assessment of all available locations for the farm needs to be performed. Since the power extraction of a wind farm depends on the cube of the wind speed even the mesoscale variability in the wind speed plays an important role in the resource assessment of a wind farm. In order to study mesoscale systems that occur in the vicinity of off-shore wind farms we've set up a convection permitting simulation in COSMO-CLM for the Kattegat sea strait. The Kattegat is particularly interesting since it is an area which features a very irregularly shaped coastline and pronounced coastal effects. Centrally located in the Kattegat lays the 400 MW Anholt wind farm. Operational data of the Anholt wind farm and scatterometer data of the Kattegat are used to validate our simulation. A relatively good agreement between observations and the model output has been found. A variety of mesoscale systems has been identified, both in unstable (e.g. a downburst) as in stable (e.g. gravity waves) conditions. The wind speed variability on temporal scales and on spatial scales over the Kattegat has been investigated. The interactions of the Anholt wind farm with these systems have been investigated using the COSMO-CLM model which incorporates the Fitch wind farm parametrisation. This research is part of a larger project aiming at developing a fast and accurate resource planning and forecasting platform for off-shore wind farms. More information about this project can be found on freewind-project.eu.

Sub-daily precipitation extremes can have a huge impact on society as they cause hazards such as flooding, erosion and landslides. For example, the July floods in Germany, Belgium and nearby countries, were one of the costliest events in Europe, with insured losses up to USD 13 billion. Climate change is expected to intensify precipitation extremes as atmospheric water content increases by 6-7% per degree of warming, underscoring the need to predict future hydrological hazards. Regional Climate Models (RCMs) typically run at a spatial resolution of 12-25 km, but they insufficiently describe the small-scale features of observed sub-daily precipitation extremes. The past decade, convection-permitting RCMs were developed which run at high resolution (1-4 km), and explicitly resolve deep convection. Confidence in future projections requires that RCMs adequately simulate the statistical features of observed sub-daily extreme precipitation and also represent the physical processes associated with convective events. We propose a diagnostic framework for simulated 1h-24h rainfall extremes that summarizes the overall RCM performance. This includes the following metrics: the seasonal/diurnal cycle, temperature and humidity dependency, temporal scaling, and spatiotemporal clustering. A substantial part of the work is devoted to the statistical modelling of the metrics with Extreme Value Theory (EVT). We illustrate the evaluation tool with convection-permitting RCM simulations over Belgium against high-frequency observations and assess the benefit of the convection-permitting RCMs with respect to coarser scales. Finally, we give some guidelines for bias correction of simulated precipitation extremes.

International trade enables us to exploit regional differences in climate change impacts and is increasingly regarded as a potential adaptation mechanism. Here, we focus on hunger reduction through international trade under alternative trade scenarios for a wide range of climate futures. Under the current level of trade integration, climate change would lead to up to 55 million people who are undernourished in 2050. Without adaptation through trade, the impacts of global climate change would increase to 73 million people who are undernourished (+33%). Reduction in tariffs as well as institutional and infrastructural barriers would decrease the negative impact to 20 million (-64%) people. We assess the adaptation effect of trade and climate-induced specialization patterns. The adaptation effect is strongest for hunger-affected import-dependent regions. However, in hunger-affected export-oriented regions, partial trade integration can lead to increased exports at the expense of domestic food availability. Although trade integration is a key component of adaptation, it needs sensitive implementation to benefit all regions. ispartof: Nature Climate Change vol:2020 issue:10 pages:829-835 ispartof: location:England status: Published online

Recent research suggests that atmospheric gravity waves can affect off-shore wind farm performance. A fast wind-farm boundary-layer model has been proposed to simulate the effects of these gravity waves on wind-farm operation by Allaerts and Meyers (2019). The current work extends the applicability of that model to free atmospheres in which wind and stability vary with altitude. We validate the model using reference cases from literature on mountain waves. Analysis of two reference flows shows that internal gravity wave resonance caused by the atmospheric non-uniformity can prohibit perturbations in the ABL at the wavelengths where it occurs. To determine the overall impact of the vertical variations in the atmospheric conditions on wind farm operation, we consider one year of operation of the Belgian–Dutch wind-farm cluster with the extended model. We find that this impact on individual flow cases is often of the same order of magnitude as the total flow perturbation. In 16.5 % of the analysed flows, the relative difference in upstream velocity reduction between uniform and non-uniform free atmospheres is more than 30 %. However, this impact is small when averaged over all cases. This suggests that variations in the atmospheric conditions should be taken into account when simulating wind-farm operation in specific atmospheric conditions.

We introduce PARASO, a novel five-component fully-coupled regional climate model over an Antarctic circumpolar domain covering the full Southern Ocean. The state-of-the-art models used are f.ETISh1.7 (ice sheet), NEMO3.6 (ocean), LIM3.6 (sea ice), COSMO5.0 (atmosphere) and CLM4.5 (land), which are here run at an horizontal resolution close to 1/4°. One key-feature of this tool resides in a novel two-way coupling interface for representing ocean – ice-sheet interactions, through explicitly resolved ice-shelf cavities. The impact of atmospheric processes on the Antarctic ice sheet is also conveyed through computed COSMO-CLM – f.ETISh surface mass exchanges. In this technical paper, we briefly introduce each model's configuration and document the developments that were carried out in order to establish PARASO. The new offline-based NEMO – f.ETISh coupling interface is thoroughly described. Our developments also include a new surface tiling approach to combine open-ocean and sea-ice covered cells within COSMO, which was required to make this model relevant in the context of coupled simulations in polar regions. We present results from a 2000–2001 coupled two-year experiment. PARASO is numerically stable and fully operational. The 2-year simulation conducted without fine tuning of the model reproduced the main expected features, although remaining systematic biases provide perspectives for further adjustment and development.

Sub-daily precipitation extremes are high-impact events that can result in flash floods, sewer system overload, or landslides. Several studies have reported an intensification of projected short-duration extreme rainfall in a warmer future climate. Traditionally, regional climate models (RCMs) are run at a coarse resolution using deep-convection parameterization for these extreme events. As computational resources are continuously ramping up, these models are run at convection-permitting resolution, thereby partly resolving the small-scale precipitation events explicitly. To date, a comprehensive evaluation of convection-permitting models is still missing. We propose an evaluation strategy for simulated sub-daily rainfall extremes that summarizes the overall RCM performance. More specifically, the following metrics are addressed: the seasonal/diurnal cycle, temperature and humidity dependency, temporal scaling and spatio-temporal clustering. The aim of this paper is: (i) to provide a statistical modeling framework for some of the metrics, based on extreme value analysis, (ii) to apply the evaluation metrics to a micro-ensemble of convection-permitting RCM simulations over Belgium, against high-frequency observations, and (iii) to investigate the added value of convection-permitting scales with respect to coarser 12-km resolution. We find that convection-permitting models improved precipitation extremes on shorter time scales (i.e, hourly or two-hourly), but not on 6h-24h time scales. Some metrics such as the diurnal cycle or the Clausius-Clapeyron rate are improved by convection-permitting models, whereas the seasonal cycle appears robust across spatial scales. On the other hand, the spatial dependence is poorly represented at both convection-permitting scales and coarser scales. Our framework provides perspectives for improving high-resolution atmospheric numerical modeling and datasets for hydrological applications.

Reservoir expansion over the last century has largely affected downstream flow characteristics. Yet very little is known about the impacts of reservoir expansion on the climate. Here, we implement reservoir construction in the Community Land Model by enabling dynamical lake area changes, while conserving mass and energy. Transient global lake and reservoir extent are prescribed from the HydroLAKES and Global Reservoir and Dam databases. Land-only simulations covering the 20th century with reservoir expansion enabled, highlight increases in terrestrial water storage and decreases in albedo matching the increase in open water area. The comparison of coupled simulations including and excluding reservoirs shows only limited influence of reservoirs on global temperatures and the surface energy balance, but demonstrates substantial responses locally, in particular where reservoirs make up a large fraction of the grid cell. In those locations, reservoirs dampen the diurnal temperature range by up to −1.5 K (for reservoirs covering >15% of the grid cell), reduce temperature extremes, and moderate the seasonal temperature cycle. This study provides a first step towards a coupled representation of reservoirs in Earth System Models.

In order to build resilient cities in face of climate change in Sub-Saharan Africa, much is to be done to understand the impact of rapid and uncontrolled urbanization on the local climate in the region. Recent efforts by Brousse et al. (2019, 2020) demonstrated that using generic urban parameter information derived out of Local Climate Zones (LCZ ; Stewart and Oke, 2012) maps created through the World Urban Database and Access Portal Tool framework (Ching et al. 2018) may be used to model the impact of Sub-Saharan African cities on their local climate – using the case of Kampala, the capital city of Uganda. These studies showed that despite the characteristic data scarcity on urban typologies that is present in Sub-Saharan Africa, LCZ could be used as a solution for modelling and studying the urban climates in the region.Yet these conclusions were only obtained through the use of the bulk-level urban canopy model TERRA_URB, embedded in the COSMO-CLM regional climate model. We therefore test the applicability of a more complex urban canopy models – the Building Effect Parameterization coupled to the Building Energy Model (BEP-BEM) – over the region. To do so, we focus on short periods with specific meteorological conditions during the dry season spanning from December 2017 to February 2018. These are obtained through a k-means clustering over hourly weather measurements given by the automatic weather station located at the Makerere University, in the city-center of Kampala. Wind direction and speed, 2-meter air temperature, incoming short-wave radiation, precipitation, daily temperature range, 2-meter air relative humidity and near-surface pressure are used to depict 5 weather typologies (ie. clusters) during the dry season. We chose to keep only periods with 5 consecutive days of one weather typology, which results in three 5-day periods of distinct typology. We then run the model for these periods and evaluate its outputs against the state-of-the-art simulation by Brousse et al. (2020) as well as in-situ and satellite observations for certain meteorological variables. After that, we show the effect of the recent urbanization on the local climate for each of those three periods and relate it to the variability in urban heat.This study is the first to model a tropical African city at 1 km horizontal resolution using the BEP-BEM model embedded in WRF. The latter could have major implications as more complex urban canopy models coupled to building energy models could shed light on the impact of the built environment on the livability of indoor and outdoor environments in these cities. Furthermore, insights could indeed be gained on the contribution of air conditioning heat fluxes to outdoor temperatures and the energetic consumption needed to keep indoor environments at an optimal temperature. Additionally, by resolving the urban environment in three dimensions, BEP-BEM could help increase our understanding of how specific urban planning and architectural adaptation strategies (like green or cool roofs, roof top solar panel, new building materials, urban greening etc.) may increase the citizens’ thermal comfort and reduce negative health impacts under specific weather conditions.

By now, humans have constructed more than 45 000 large reservoirs across the globe, increasing the global lake area with 8%. These reservoirs have large impacts on freshwater processes and resources by impounding continental runoff and altering river flows. So far, the impact of reservoirs on the climate remains largely unknown, as they are typically not represented in current Earth System Models (ESMs). This is remarkable, as two-way interactions between reservoirs and climate are likely to alter hydrological extremes and impact future water availability.Here we present the implementation of the role of reservoirs in the Community Terrestrial Systems Model (CTSM), a land surface model, by accounting for the increase in open water surfaces due to reservoir construction throughout the 20th century. To this end, we allow lake area to expand in the model, while ensuring that the surface energy and mass balances remain closed. We use reservoir and lake extent from the state-of-the-art Global Reservoir and Dams (GRanD) and HydroLAKES data sets.By conducting both land-only and coupled simulations with CTSM and the Community Earth System Model (CESM), we assess the added value of accounting for reservoir expansion in the land surface model performance and investigate their impacts on the mean climate and extremes. Globally, the effect of reservoirs on temperatures and the surface energy balance is small, but responses can be substantial locally, in particular for grid cells where reservoirs make up a large fraction. Our results show that reservoirs reduce temperature extremes and moderate the seasonal temperature cycle, by up to -1.5 K (for reservoirs covering > 15% of the grid cell).This study is an important step towards incorporating human water management in ESMs.

In the last decade, the Climate Limited-area Modeling (CLM) Community has contributed to the Coordinated Re- gional 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 Fed- eration (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.

Rapid and uncontrolled urbanization in tropical Africa is increasingly leading to unprecedented socio-economical and environmental challenges in cities, particularly urban heat and climate change. The latter calls for a better representation of tropical African cities’ properties relevant for urban climate studies. Here, we demonstrate the possibility of collecting urban canopy parameters during a field campaign in the boreal summer months of 2018 for deriving a Local Climate Zone (LCZ) map and for improving the physical representation of climate-relevant urban morphological, thermal and radiative characteristics. The comparison of the resulting field-derived LCZ map with an existing map obtained from the World Urban Data and Access Portal Tool framework shows large differences. In particular, our map results in more vegetated open low-rise classes. In addition, site-specific fieldwork-derived urban characteristics are compared against the LCZ universal parameters. The latter shows that our fieldwork adds important information to the universal parameters by more specifically considering the presence of corrugated metal in the city of Kampala. This material is a typical roofing material found in densely built environments and informal settlements. It leads to lower thermal emissivity but higher thermal conductivity and capacity of buildings. To illustrate the importance of site-specific urban parameters, the newly derived site-specific urban characteristics are used as input fields to an urban parametrization scheme embedded in the regional climate model COSMO-CLM. This implementations decreases the surface temperature bias from 5.34 to 3.97 K. Based on our results, we recommend future research on tropical African cities to focus on a detailed representation of cities, with particular attention to impervious surface fraction and building materials.

BACKGROUND: The rapid and often uncontrolled rural-urban migration in Sub-Saharan Africa is transforming urban landscapes expected to provide shelter for more than 50% of Africa's population by 2030. Consequently, the burden of malaria is increasingly affecting the urban population, while socio-economic inequalities within the urban settings are intensified. Few studies, relying mostly on moderate to high resolution datasets and standard predictive variables such as building and vegetation density, have tackled the topic of modeling intra-urban malaria at the city extent. In this research, we investigate the contribution of very-high-resolution satellite-derived land-use, land-cover and population information for modeling the spatial distribution of urban malaria prevalence across large spatial extents. As case studies, we apply our methods to two Sub-Saharan African cities, Kampala and Dar es Salaam. METHODS: Openly accessible land-cover, land-use, population and OpenStreetMap data were employed to spatially model Plasmodium falciparum parasite rate standardized to the age group 2-10 years (PfPR2-10) in the two cities through the use of a Random Forest (RF) regressor. The RF models integrated physical and socio-economic information to predict PfPR2-10 across the urban landscape. Intra-urban population distribution maps were used to adjust the estimates according to the underlying population. RESULTS: The results suggest that the spatial distribution of PfPR2-10 in both cities is diverse and highly variable across the urban fabric. Dense informal settlements exhibit a positive relationship with PfPR2-10 and hotspots of malaria prevalence were found near suitable vector breeding sites such as wetlands, marshes and riparian vegetation. In both cities, there is a clear separation of higher risk in informal settlements and lower risk in the more affluent neighborhoods. Additionally, areas associated with urban agriculture exhibit higher malaria prevalence values. CONCLUSIONS: The outcome of this research highlights that populations living in informal settlements show higher malaria prevalence compared to those in planned residential neighborhoods. This is due to (i) increased human exposure to vectors, (ii) increased vector density and (iii) a reduced capacity to cope with malaria burden. Since informal settlements are rapidly expanding every year and often house large parts of the urban population, this emphasizes the need for systematic and consistent malaria surveys in such areas. Finally, this study demonstrates the importance of remote sensing as an epidemiological tool for mapping urban malaria variations at large spatial extents, and for promoting evidence-based policy making and control efforts., SCOPUS: ar.j, info:eu-repo/semantics/published

With the increasing extraction of methane from Lake Kivu, there is a growing need to evaluate the effect of such operations on the lake’s permanent density stratification. This requires understanding of the spatial structure and variability of flow velocities and constituents in Lake Kivu. In this study, we develop a 3D hydrodynamic model of Lake Kivu, set-up within DELFT3D at a 750 m grid spacing and forced by COSMO-CLM atmosphere model results at a 2.8 km grid spacing. Validation shows that the model correctly reproduces the generation and breakdown of the temperature stratification in the upper mixed layer and predicts flow velocity magnitudes and directions similar to measurements both at the surface and at greater depth. Analysis of currents reveals a surface current pattern with two clockwise circulations, one around the whole lake and a smaller one in the northern part, with velocities around 0.1 m/s. This pattern is consistently present over an (ensemble-)averaged day, both in the wet and in the dry season, while day-by-day variations are large. Time-averaged deep currents are found to be a few mm/s at maximum. However, the variations can be substantial, with standard deviations up to 2 cm/s for the currents at 220 m depth, attributed to internal seiches. The temperature stratification, present during the entire wet season, is found to first break down in the dry season in the southern part of the lake. This is explained by the spatial differences in the wind stress and the evaporation heat fluxes during the dry season.

The Totten glacier is a highly dynamic outlet glacier, situated in E-Antarctica, that contains a potential sea level rise of about 3.5 meters. During recent years, this area has been influenced by sub-shelf intrusion of warm ocean currents, contributing to higher basal melt rates. Moreover, most of the ice over this area is grounded below sea level, which makes the ice shelf potentially vulnerable to the marine ice sheet instability mechanism. It is expected that, as a result of climate change, the latter mechanisms may contribute to significant ice losses in this region within the next decades, thereby contributing to future sea level rise. Up to now, most studies have been focusing on sub-shelf melt rates and the influence of the ocean, with much less attention for atmospheric processes (often ignored), which also play a key-role in determining the climatic conditions over this region. For example: surface melt is important because it contributes to hydrofracturing, a process that may lead to ice cliff instabilities. Also precipitation is an important atmospheric process, since it determines the input of mass to the ice sheet and contributes directly to the surface mass balance. In order to perform detailed studies on these processes, we need a well-evaluated climate model that represents all these processes well. Recently, the COSMO-CLM2 (CCLM2) model was adapted to the climatological conditions over Antarctica. The model was evaluated by comparing a 30 year Antarctic-wide hindcast run (1986-2016) at 25 km resolution with meteorological observational products (Souverijns et al., 2019). It was shown that the model performance is comparable to other state-of-the-art regional climate models over the Antarctic region. We now applied the CCLM2 model in a regional configuration over the Totten glacier area (E-Antarctica) at 5 km resolution and evaluated its performance over this region by comparing it to climatological observations from different stations. We show that the performance for temperature in the high resolution run is comparable to the performance of the Antarctic-wide run. Precipitation is, however, overestimated in the high-resolution run, especially over dome structures (Law-Dome). Therefore, we applied an orographic smoothening, which clearly improves the precipitation pattern with respect to observations. Wind speed is overestimated in some places, which is solved by increasing the surface roughness. This research frames in the context of the PARAMOUR project. Within PARAMOUR, CCLM2 is currently being coupled to an ocean model (NEMO) and an ice sheet model (f.ETISh/BISICLES) in order to understand decadal predictability over this region.

Local Climate Zones (LCZ) have now been widely accepted and used by the urban climate community (Ching et al., 2018). However, their use over Sub-Saharan Africa has still been limited because of data scarcity in the region. Brousse et al. (2019, 2020) demonstrated the added value of applying spatially variant urban canyon parameters derived from LCZ in the urban climate model TERRA_URB – embedded in the COSMO-CLM model. Despite its promising results, thermal and morphological parameters extracted out of the ranges proposed by Stewart and Oke (2012) are mostly derived from Western cities. Hence, uncertainties related to the use of unascertained urban forms and functions of African cities for urban climate modelling have not yet been evaluated.To quantify the sensitivity of the model to more representative urban canopy parameters of African cities, this study sets up a methodology for: (i) obtaining from in situ measurements archetypal parameters of LCZ classes for Kampala (Uganda); and (ii) simulating the potential effect of the newly defined urban structure on the local climate.In situ data were obtained during field work held in the summer months of 2018. A representative sample of 1300 measurement points was selected throughout the city of Kampala, for which both quantitative (road width, distance between houses, heights of buildings) and qualitatively estimated (vegetation fraction, road-wall-roof material) variables were collected. These variables enabled the development of an updated LCZ map of the city of Kampala.To evaluate the model’s sensitivity to the new spatially explicit urban morphological and thermal parameters, this new information was fed into the TERRA_URB scheme at a horizontal resolution of 1 km for a 3-months period (December 2017 – February 2018). The run was nested within a 12 km simulation forced by ERA-Interim reanalysis data. Results show tangible effects of the updated parameters on the 2-meter air temperature, land surface temperature and surface energy balance components. Still, no major improvements in model skill compared to the default LCZ framework proposed by Brousse et al. (2020) were found. [1] [WT2] This study is among the first studies to test the sensitivity of an urban climate model to more realistic urban parameters in Africa and aims at triggering more research to be done in the area with a variety of urban climate models.

Extreme weather events, like heavy precipitation, heat waves, droughts and wind storms have a detrimental impact on East African societies. The Lake Victoria Basin (LVB) is especially vulnerable, since nightly storms on the lake catch fishermen by surprise. As the frequency and intensity of climate extremes is projected to further increase substantially with climate change, so do the risks, with potentially major consequences for livelihoods and policy in the LVB.The ultimate aim of the ELVIC CORDEX-FPS is to investigate how extreme weather events evolve in the future in the LVB and to provide improved probabilistic information to the impact community. ELVIC (Climate Extremes in the Lake Victoria Basin) brings together different research groups that perform simulations with multiple high-resolution regional climate models operating at the convection-permitting scale (CPS) (https://ees.kuleuven.be/elvic).As a first step towards this overall goal, the added value of the CPS on the representation of deep convective systems in Equatorial Africa was assessed. For this purpose, 10-year present-day model simulations were carried out with five regional climate models both at the CPS and at the scale where convection was parameterized, namely COSMO-CLM, RegCM, HCLIM-AROME, WRF and the Met Office Unified Model. From a comparison of model output with different observational products, no robust improvement was found for seasonal average meteorological variables. Moreover, the change in the seasonal precipitation when going to CPS differs between the models. A robust improved performance was found for deep convection, reflected in an improved representation of the daily precipitation cycle. Preliminary results also point towards an improvement in the representation of extreme precipitation. This suggests that regional climate model simulations at the convection-permitting scale are indeed relevant to assess the climate sensitivity of extreme precipitation in the Lake Victoria Basin.

Extreme weather is posing constant threat to more than 30 million people living near Lake Victoria or depending on its resources. Thousands of fishermen die every year by severe thunderstorms and associated water currents, while hazardous over-land thunderstorms largely affect people living inland, continuously facing flood risks. These risks call for better understanding of such climate extremes over the region. Climate models are a useful tool to gain insight in the complex behaviour of thunderstorms, especially when simulated at convection-permitting resolution. Such simulations, explicitly resolving deep convection at fine resolutions, have been shown to improve the representation of extreme events in many parts of the world, also in equatorial East-Africa (Finney et al., 2019; Kendon et al., 2019; Van de Walle et al., 2019). As a response, the CORDEX-Flagship Pilot Study “climate extremes in the Lake Victoria basin” (ELVIC) initiative is currently setting up an ensemble of convection-permitting simulations over the region.At this stage, future climate projections are needed to assess the impact of anthropogenic climate change on extreme weather the region. Therefore, a surrogate global warming approach following Schär et al. (1996), Kröner et al. (2016), Liu et al. (2016) and Rasmussen et al. (2017) has been applied to a convection-permitting COSMO-CLM simulation. In this approach, the lateral boundary conditions from the ERA5 (~31 km resolution) reanalysis are perturbed in accordance with the recent CMIP6 ensemble-mean end-of-century SSP5 8.5 climate change scenario. This approach confers three major advantages over the more conventional methods. First, by perturbing with the ensemble-mean, it excludes uncertainties of GCMs without the need for a time and computational intensive high resolution ensemble approach. Second, it avoids including present-day circulation biases. Third, no intermediate nesting steps are necessary, as the perturbed ERA5 allows a direct downscaling to the convection-permitting climate projection.Besides the methodology, results for the Lake Victoria basin will be presented. Although the occurrence of extreme over-lake precipitation in the present-day climate is mostly controlled by large- and mesoscale atmospheric dynamics (Van de Walle et al., 2019), its future intensification is mainly attributed to increased humidity (Thiery et al., 2016). Furthermore, the effect of changed large-scale dynamics is assessed, as not only temperature and humidity, but also wind forcing is modified.

Heat uptake is a key variable for understanding Earth system response to greenhouse gas forcing. Recent assessments highlighted that most of the excess energy is stored in the oceans, whereas the land, atmosphere and ice melt take up smaller amounts. However, despite the importance of this heat budget, heat uptake by inland waters has so far not been quantified. Here we use a unique combination of global-scale lake models, global hydrological models and Earth system models to, for the first time, quantify global heat uptake by lakes, reservoirs and rivers over the industrial period (1900-2020). We use a total of 16 different simulations of global-scale lake models and global hydrological models driven by the same bias-corrected climate forcing from four different global climate models, conducted within the framework of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). The model output is combined with reservoir and lake data from the Global Reservoir and Dam (GRanD) database and HydroLAKES. Total inland water heat uptake in the industrial period amounts to 2.8 ± 4.3x1020 J by the end of the period, with the largest uptake realised after 1990. The overall uptake is dominated by warming of natural lakes (2.9 ± 2.0x1020 J, the multi-model mean and standard deviation; 103% of total inland water heat uptake), followed by reservoir warming (5.9 ± 2.7x1018 J; 2.1%). The multi-model mean heat uptake by rivers contributes negatively to the total heat uptake (-0.15 ± 4.3x1020 J; -5.3%), but encompasses a large uncertainty originating from the river storage term, simulated by the global hydrological models. The global picture of positive heat uptake by natural lakes is confirmed at the regional scale in the major lake regions by all global-scale lake model and global climate model combinations. The heat uptake by inland waters makes up ~3.2% of continental heat uptake reported in the IPCC AR5 (2013). The rapid increase in dam construction and resulting reservoir expansion in the second half of the 20th century causes a heat redistribution from ocean to land by storing extra water on land. Remarkably, this heat redistribution exceeds the anthropogenic heat uptake by inland waters by a factor of ~ 9.6, adding up to 27 ± 2.1x1020 J. Our results overall underline the importance of inland waters for buffering atmospheric warming through enhanced anthropogenic greenhouse gas concentrations.

This study is set up in collaboration with the REACT5 project (Remote sensing for Epidemiology in sub-saharan African CiTies) led by ULB. The work aims at assessing and understanding the impact of recent urbanization on the urban heat island (UHI) under clear-sky conditions in a tropical African city using different sources of remotely sensed data sets together with an urban climate model (UCM). The observed UHI during clear sky conditions is found to be about 4⁰C on average over the capital city of Kampala, Uganda. The UCM, consisting of TERRA_URB embedded in COSMO-CLM, represents the UHI well during night but overestimates it by about 3⁰C in the mean during day. Moreover, a systematic warm land surface temperature bias of about 4⁰C is identified by night. Improved urban input parameters - derived from Local Climate Zones following the World Urban Database and Access Portal Tool (WUDAPT) framework - lead to a more realistic representation of spatial land surface temperatures patterns. In addition, this parameterization of the UCM can properly represent atmospheric variables such as air temperature, specific and relative humidity, as observed by the automated weather stations. A model sensitivity study furthermore demonstrates that the stronger urban heat island induced by the recent urbanization of Kampala over the past 15 years strongly interacts with the lake-land breeze circulation. Stronger daytime convection over the hotter city leads to areas of convergence that amplify the afternoon lake breeze in the southern parts of the metropolis. Overall, this study demonstrates that the city of Kampala has a tangible effect on the regional climate that needs to be considered when studying present and future climate impacts. ispartof: pages:4586-4608 ispartof: International Journal Of Climatology vol:40 issue:10 pages:4586-4608 status: published

Aiming for an improved understanding of the different factors that determine the regional climate of the Lake Victoria Basin, the COSMO-CLM regional climate model is set up in a tropical, convection-permitting configuration and is directly nested in a recent reanalysis product (ERA5). The convection-permitting simulation outperforms state-of-the-art climate integrations that rely on convection parametrisations. Yet the domain-averaged model precipitation is larger than in the multi-observational ensemble, but the latter shows large spread. Overestimations of outgoing TOA shortwave and longwave radiation are much reduced compared to the COSMO-CLM CORDEX-Africa integration, but still suggest a general underestimation of the cloud fraction or frequency. Comparing the control with a no-lake simulation, the presence of Lake Victoria implies strong intensification of over-lake rainfall, but it only slightly increases the total domain-averaged precipitation. In addition, the easterly trade winds are shown to largely affect the mesoscale circulation and precipitation patterns. During daytime, fast trades and anabatic slope winds trigger convection at the lee-wind slopes, and subsidence over the basin. Slow trades allow the stationary air to produce spontaneous convective cells and to develop anabatic winds that result in orographic precipitation. During night-time, trade winds curl around the eastern branch of the East African Rift, generating a southerly and northerly evening convergence front entering the Lake Victoria Basin. Thus, our results highlight the key importance of the easterly trade winds and the complex orography in determining the total accumulation and location of precipitation in the Lake Victoria region.

Owing to computational advances, an ever growing percentage of regional climate simulations are being performed at convection-permitting scale (CPS, or a horizontal grid scale below 4 km). One particular area where CPS could be of added value is in future projections of extreme precipitation, particularly for short timescales (e.g. hourly). However, recent studies that compare the sensitivity of extreme hourly precipitation at CPS and non-convection-permitting scale (nCPS) have produced mixed results, with some reporting a significantly higher future increase of extremes at CPS, while others do not. However, the domains used in these studies differ significantly in orographic complexity, and include both mountain ranges as well as lowlands with minimal topographical features. Therefore, the goal of this study is to investigate if and how the difference between nCPS and CPS future extreme precipitation projections might depend on topographic complexity and timescale. The study area is Belgium and surroundings, and is comprised of lowland in the north (Flanders) and a low mountain range in the south (Ardennes). These two distinct topographical regions are separated in the analysis. We perform and analyze three sets of 30 year climate simulations (hindcast, control and end-of-century RCP 8.5) at both nCPS (12 km resolution) and CPS (2.5 km resolution), using the regional climate model COSMO-CLM. Results show that for our study area, the difference between nCPS and CPS future extreme precipitation depends on both timescale and topography. Despite a background of general summer drying in our region caused by changes in large-scale circulation, the CPS simulations predict a significant increase in the frequency of daily and hourly extreme precipitation events, for both the lowland and mountain areas. The nCPS simulations are able to reproduce this increase for hourly extremes in mountain areas, but significantly underestimate the increase in hourly extremes in lowlands, as well as the increase in the most extreme daily precipitation events in both the lowland and mountain areas.

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 (35-year) 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 in a densely populated mid-latitude maritime region. We discover that the heat-stress increase towards the mid-21 st 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 novel insights exemplify the need to combine information from climate models, acting on different scales, for climatehange risk assessment in heterogeneous regions. Moreover, these results highlight the necessity for adaptation to increasing heat stress, especially in urban areas. ispartof: Geophysical Research Letters vol:44 issue:17 pages:8997-9007 status: published

In this study we assess the added value of convection permitting scale (CPS) simulations in studies using regional climate models to quantify the bio-geophysical climate impact of land-use change (LUC). To accomplish this, a comprehensive model evaluation methodology is applied to both non-CPS and CPS simulations. The main characteristics of the evaluation methodology are (1) the use of paired eddy-covariance site observations (forest vs open land) and (2) a simultaneous evaluation of all surface energy budget components. Results show that although generally satisfactory, non-CPS simulations fall short of completely reproducing the observed LUC signal because of three key biases. CPS scale simulations succeed at significantly reducing two of these biases, namely, those in daytime shortwave radiation and daytime sensible heat flux. Also, CPS slightly reduces a third bias in nighttime incoming longwave radiation. The daytime improvements can be attributed partially to the switch from parameterized to explicit convection, the associated improvement in the simulation of afternoon convective clouds, and resulting surface energy budget and atmospheric feedbacks. Also responsible for the improvements during daytime is a better representation of surface heterogeneity and thus, surface roughness. Meanwhile, the modest nighttime longwave improvement can be attributed to increased vertical atmospheric resolution. However, the model still fails at reproducing the magnitude of the observed nighttime longwave difference. One possible explanation for this persistent bias is the nighttime radiative effect of biogenic volatile organic compound emissions over the forest site. A correlation between estimated emission rates and the observed nighttime longwave difference, as well as the persistence of the longwave bias provide support for this hypothesis. However, more research is needed to conclusively determine if the effect indeed exists.

We performed five high resolution (2.8 km) decadal convection permitting scale (CPS) climate simulations over Belgium using the COSMO-CLM regional climate model and examined the future changes in daily precipitation extremes compared to coarser resolution simulations. The CPS model underestimates the higher percentiles during both seasons, however, some improvements in the higher percentile values are noticed during the summer season. Analysis of three future climate simulations indicates that the CPS model modifies the future signals of daily precipitation extremes compared to their forcing non-CPS simulations during summer. During this season, the increase (decrease) in the daily precipitation extremes is stronger in the CPS compared to the non-CPS simulations. During winter, no significant changes between CPS and non-CPS were found.

Convection-permitting models (CPMs) have been proven successful in simulating extreme precipitation statistics. However, when such models are used to study climate change, contrasting sensitivities with respect to resolution (CPM vs. models with parameterized convection) are found for different parts of the world. In this study, we explore to which extent this contrasting sensitivity is due to the specific characteristics of the model or due to the characteristics of the region. Therefore, we examine the results of 360 years of climate model data from two different climate models (COSMO-CLM driven by EC-EARTH and ALARO-0 driven by CNRM ARPEGE) both at convection-permitting scale (CPS, ~ 3 km resolution) and non-convection-permitting scale (non-CPS, 12.5 km resolution) over two distinct regions (flatland vs. hilly region) in Belgium. We found that both models show an overall consistent scale-dependency of the future increase in hourly extreme precipitation for day-time. More specifically, both models yield a larger discrepancy in the day-time climate change signal between CPS and non-CPS for extreme precipitation over flatland (Flanders) than for orographically induced extreme precipitation (Ardennes). This result is interesting, since both RCMs are very different (e.g., in terms of model physics and driving GCM) and use very different ways to represent deep convection processes. Despite those model differences, the scale-dependency of projected precipitation extremes is surprisingly similar in both models, suggesting that the this scale-dependency is more dependent on the characteristics of the region, than on the model used. ispartof: Climate Dynamics vol:54 issue:3-4 pages:1267-1280 status: Published online

© Author(s) 2019. Two-way feedback occurs between offshore wind and waves. However, the influence of the waves on the wind profile remains understudied, in particular the momentum transfer between the sea surface and the atmosphere. Previous studies showed that for swell waves it is possible to have increasing wind speeds in case of aligned wind-wave directions. However, the opposite is valid for opposed wind-wave directions, where a decrease in wind velocity is observed. Up to now, this behavior has not been included in most numerical models due to the lack of an appropriate parameterization of the resulting effective roughness length. Using an extensive data set of offshore measurements in the North Sea and the Atlantic Ocean, we show that the wave roughness length affecting the wind is indeed dependent on the alignment between the wind and wave directions. Moreover, we propose a new roughness length parameterization, taking into account the dependence on alignment, consisting of an enhanced roughness length for increasing misalignment. Using this new roughness length parameterization in numerical models might facilitate a better representation of offshore wind, which is relevant to many applications including offshore wind energy and climate modeling. ispartof: ATMOSPHERIC CHEMISTRY AND PHYSICS vol:19 issue:10 pages:6681-6700 status: published

In order to reduce climate-related health issues in Sub-Saharan cities, a better understanding of the spatial and temporal processes affecting urban climates is required. In this context, this paper mobilizes the potential of urban climate modelling and remote sensing to improve the understanding of urban health risk variations in Sub-Saharan Africa. The combination of Stewart and Oke's (2012) universal classification of Local Climate Zones with very high resolution satellite imagery is explored for the parameterization of a simple urban canopy model (TERRA_URB) over two cities: Kampala (Uganda) and Dakar (Senegal). Key challenges, such as data scarcity and performing analyses on multi spatio-temporal scales are emphasized. Applications for a better understanding of links between urban climates and intra-urban health issues in highly dynamic urban environments are illustrated and discussed taking intra-urban malaria risk as an example., SCOPUS: ar.j, info:eu-repo/semantics/published

Continuous measurements of blowing snow are scarce, both in time and space. Satellites now provide the opportunity to derive blowing snow occurrences, transport and sublimation rates over Antarctica. However, little ground truth is available to validate these retrievals. The recent application of ceilometers for detection of blowing snow frequencies provides an opportunity to validate the satellite retrievals of blowing snow frequencies at the Princess Elisabeth and Neumayer stations, East Antarctica for the 2011–2016 time period. A routine to detect blowing snow occurrence from remote sensing ceilometers has been developed at those locations. Thanks to their ground-based location, ceilometers are able to detect blowing snow events in the presence of clouds and precipitation, which can be missed by the satellite, since optically thick clouds impede the penetration of the signal. This is important, since ≈ 90 % of blowing snow happens under cloudy conditions at Neumayer and Princess Elisabeth station and represent 30 % of all cloudy conditions at both stations. Although both detection methods have their limitations, 10 % (4 %) of the measurements at Princess Elisabeth (and Neumayer) are identified as blowing snow by the satellite but not by the ceilometer, likely due to differences in sensors, limitation of the surface identification by the satellite, or the spatial inhomogeneity of the blowing snow event. While the satellite blowing snow retrieval is a useful product, further investigation is needed to reduce the uncertainties on blowing snow frequencies associated with clouds.

© Author(s) 2019. Precipitation over Antarctica is the main term in the surface mass balance of the Antarctic ice sheet, which is crucial for the future evolution of the sea level worldwide. Precipitation, however, remains poorly documented and understood mainly because of a lack of observations in this extreme environment. Two observatories dedicated to precipitation have been set up at the Belgian station Princess Elisabeth (PE) and at the French station Dumont d'Urville (DDU) in East Antarctica. Among other instruments, both sites have a vertically pointing micro rain radar (MRR) working at the K band. Measurements have been continuously collected at DDU since the austral summer of 2015-2016, while they have been collected mostly during summer seasons at PE since 2010, with a full year of observation during 2012. In this study, the statistics of the vertical profiles of reflectivity, vertical velocity, and spectral width are analyzed for all seasons. Vertical profiles were separated into surface precipitation and virga to evaluate the impact of virga on the structure of the vertical profiles. The climatology of the study area plays an important role in the structure of the precipitation: warmer and moister atmospheric conditions at DDU favor the occurrence of more intense precipitation compared with PE, with a difference of 8dBZ between both stations. The strong katabatic winds blowing at DDU induce a decrease in reflectivity close to the ground due to the sublimation of the snowfall particles. The vertical profiles of precipitation velocity show significant differences between the two stations. In general, at DDU the vertical velocity increases as the height decreases, while at PE the vertical velocity decreases as the height decreases. These features of the vertical profiles of reflectivity and vertical velocity could be explained by the more frequent occurrence of aggregation and riming at DDU compared to PE because of the lower temperature and relative humidity at the latter, located further in the interior. Robust and reliable statistics about the vertical profile of precipitation in Antarctica, as derived from MRRs for instance, are necessary and valuable for the evaluation of precipitation estimates derived from satellite measurements and from numerical atmospheric models. ispartof: The Cryosphere vol:13 issue:1 pages:247-264 status: published

Analysing the influence of urban planning on the financial and environmental impact of neighborhoods -- The ecological and conservative planning of traditional Vietnam-villages -- Socially inclusive and economically beneficial smart cities -- Affordable housing supply in Belgium – current situation -- Actual situation of high-rise office buildings in Vietnam and strategic development towards sustainability -- Interaction between innovative systems and buildings: a key factor for energy sustainability -- A review of residential grid-connected microgrid energy management strategies for grid power profile smoothing -- Linking neighborhoods into sustainable energy systems -- Wind energy -- Sustainable Cooling with Hybrid Concentrated Photovoltaic Thermal (CPVT) System and Hydrogen Energy Storage -- Energy sustainability through the use of thermoelectric materials in waste heat recovery processes applied to residential buildings -- Sustainability in ports: implementation of energy storage to reduce greenhouse gases emissions -- Novel method and molten salt electrolytic cell for implementing a hydrogen fuel, sustainable, closed clean energy cycle on a large scale -- Denmark on its way towards a 100% renewable energy-system -- Weather data for building energy performance in a context of climate change: literature review and future outlook -- Energy efficiency in residential buildings in Vietnam - high-tech or low-tech? -- Sustainable construction practices in West African countries -- The persistence of alternative energy mutual fund performance in Spanish market -- Community participation in urban planning for sustainable development in Vietnam- Prospect and Challenges -- Analyzing the alternative energy mutual funds’ performance in Spanish market.

The Antarctic continent is a vast desert and is the coldest and the most unknown area on Earth. It contains the Antarctic ice sheet, the largest continental water reservoir on Earth that could be affected by the current global warming, leading to sea level rise. The only significant supply of ice is through precipitation, which can be observed from the surface and from space. Remote-sensing observations of the coastal regions and the inner continent using CloudSat radar give an estimated rate of snowfall but with uncertainties twice as large as each single measured value, whereas climate models give a range from half to twice the space–time-averaged observations. The aim of this study is the evaluation of the vertical precipitation rate profiles of CloudSat radar by comparison with two surface-based micro-rain radars (MRRs), located at the coastal French Dumont d'Urville station and at the Belgian Princess Elisabeth station located in the Dronning Maud Land escarpment zone. This in turn leads to a better understanding and reassessment of CloudSat uncertainties. We compared a total of four precipitation events, two per station, when CloudSat overpassed within 10 km of the station and we compared these two different datasets at each vertical level. The correlation between both datasets is near-perfect, even though climatic and geographic conditions are different for the two stations. Using different CloudSat and MRR vertical levels, we obtain 10 km space-scale and short-timescale (a few seconds) CloudSat uncertainties from −13 % up to +22 %. This confirms the robustness of the CloudSat retrievals of snowfall over Antarctica above the blind zone and justifies further analyses of this dataset.

This study explores whether climate models with higher spatial resolutions provide higher accuracy for precipitation simulations and/or different climate change signals. The outputs from two convection-permitting climate models (ALARO and CCLM) with a spatial resolution of 3–4 km are compared with those from the coarse-scale driving models or reanalysis data for simulating/projecting daily and sub-daily precipitation quantiles. Validation of historical design precipitation statistics derived from intensity–duration–frequency (IDF) curves shows a better match of the convection-permitting model results with the observations based IDF statistics compared to the driving GCMs and reanalysis data. This is the case for simulation of local subdaily precipitation extremes during the summer season, while the convection-permitting models do not appear to bring added value to simulation of daily precipitation extremes. Results moreover indicate that one has to be careful in assuming spatial-scale independency of climate change signals for the delta change downscaling method, as high resolution models may show larger changes in extreme precipitation. These larger changes appear to be dependent on the timescale, since such intensification is not observed for daily timescales for both the ALARO and CCLM models. ispartof: Hydrology and Earth System Sciences vol:20 issue:9 pages:3843-3857 status: published

As buildings have a relatively long life span, it is important to consider climate change in energy performance modelling. Good quality weather data are needed to obtain accurate results. This chapter discusses widely used methods to predict future weather data (dynamical downscaling, stochastic weather generators and morphing) and provides an overview of available weather datasets (multi-year, typical years, extreme years and representative years) for building simulations. A Flemish office building is used for a comparative analysis of the estimated heating and cooling load making use of 1-year weather files (typical and extreme future climate conditions) derived from a recently developed convection-permitting climate model for Belgium. Climate models and weather generators are identified as the most preferred for the estimation of the average energy consumption and thermal comfort in average and extreme situations. Climate models have the advantage to better represent extreme weather events and climate differences due to territorial settings, while weather generators can generate multiple climate realizations. A combination of a typical year with an extreme cold and extreme warm year was found to result in an overall good representation of the energy need for heating and cooling in average and extreme weather conditions. Further, the influence of the methodological choices to extract 1-year weather files (typical or extreme years) from the 30-year climate data is highlighted as different results were obtained when different meteorological variables were considered for the creation of the 1-year files.

Lake Victoria, the second largest freshwater lake in the world, is one of the major sources of the Nile river. The outlet to the Nile is controlled by two hydropower dams of which the allowed discharge is dictated by the Agreed Curve, an equation relating outflow to lake level. Some regional climate models project a decrease in precipitation and an increase in evaporation over Lake Victoria, with potential important implications for its water balance and resulting level. Yet, little is known about the potential consequences of climate change for the water balance of Lake Victoria. In this second part of a two-paper series, we feed a new water balance model for Lake Victoria presented in the first part with climate simulations available through the COordinated Regional Climate Downscaling Experiment (CORDEX) Africa framework. Our results reveal that most regional climate models are not capable of giving a realistic representation of the water balance of Lake Victoria and therefore require bias correction. For two emission scenarios (RCPs 4.5 and 8.5), the decrease in precipitation over the lake and an increase in evaporation are compensated by an increase in basin precipitation leading to more inflow. The future lake level projections show that the dam management scenario and not the emission scenario is the main controlling factor of the future water level evolution. Moreover, inter-model uncertainties are larger than emission scenario uncertainties. The comparison of four idealized future management scenarios pursuing certain policy objectives (electricity generation, navigation reliability and environmental conservation) uncovers that the only sustainable management scenario is mimicking natural lake level fluctuations by regulating outflow according to the Agreed Curve. The associated outflow encompasses, however, ranges from 14m3day−1 (−85%) to 200m3day−1 (+100%) within this ensemble, highlighting that future hydropower generation and downstream water availability may strongly change in the next decades even if dam management adheres to he Agreed Curve. Our results overall underline that managing the dam according to the Agreed Curve is a key prerequisite for sustainable future lake levels, but that under this management scenario, climate change might potentially induce profound changes in lake level and outflow volume., Hydrology and Earth System Sciences, 22 (10), ISSN:1027-5606, ISSN:1607-7938