Rossby Centre Regional Atmospheric Model Research Articles

Towards an intelligent malaria outbreak warning model based intelligent malaria outbreak warning in the northern part of Benin, West Africa

BackgroundMalaria is one of the major vector-borne diseases most sensitive to climatic change in West Africa. The prevention and reduction of malaria are very difficult in Benin due to poverty, economic insatiability and the non control of environmental determinants. This study aims to develop an intelligent outbreak malaria early warning model driven by monthly time series climatic variables in the northern part of Benin.MethodsClimate data from nine rain gauge stations and malaria incidence data from 2009 to 2021 were extracted from the National Meteorological Agency (METEO) and the Ministry of Health of Benin, respectively. Projected relative humidity and temperature were obtained from the coordinated regional downscaling experiment (CORDEX) simulations of the Rossby Centre Regional Atmospheric regional climate model (RCA4).A structural equation model was employed to determine the effects of climatic variables on malaria incidence. We developed an intelligent malaria early warning model to predict the prevalence of malaria using machine learning by applying three machine learning algorithms, including linear regression (LiR), support vector machine (SVM), and negative binomial regression (NBiR).ResultsTwo ecological factors such as factor 1 (related to average mean relative humidity, average maximum relative humidity, and average maximal temperature) and factor 2 (related to average minimal temperature) affect the incidence of malaria. Support vector machine regression is the best-performing algorithm, predicting 82% of malaria incidence in the northern part of Benin.The projection reveals an increase in malaria incidence under RCP4.5 and RCP8.5 over the studied period.ConclusionThese results reveal that the northern part of Benin is at high risk of malaria, and specific malaria control programs are urged to reduce the risk of malaria.

Analysis of past and projected changes in extreme precipitation indices in some watersheds in Côte d'Ivoire

Abstract The purpose of this study is to analyse trends in annual rainfall extremes over five watersheds within Côte d'Ivoire using observed (1976–2017) and projected (2020–2050) rainfall data from the fourth version of the Rossby Centre regional atmospheric model, RCA4, for the representative concentration pathways RCP 4.5 and RCP 8.5. Four rainfall extreme indices, namely, the consecutive dry days (CDD), maximum annual rainfall (Pmaxan), very wet day (R95p), and maximum 5-day rainfall (Rx5days), were considered for trend analysis by using the non-parametric modified Mann–Kendall test and the distribution mapping bias-correction technique to adjust the simulated regional climate model of the simulated daily precipitation. As a result, it is found that during the period 1976–2017, there was a significant downward trend in the drought-related index (CDD) at the Bagoue, Baya, Agneby, and Lobo watersheds. The Baya and N'zo watersheds also experienced a significant downward trend under the RCP 4.5 and RCP 8.5 scenarios. The flood-related indices (Pmaxan, R95p, and Rx5days) show a clear downward trend in the recorded data for almost all the considered watersheds and generally a significant upward trend for both cases. These findings indicate that the watersheds are vulnerable to climate-induced disasters.

An evaluation of the synergy between the wave and wind energy along the west Iberian nearshore

There is a growing interest in extracting marine renewable energy and contributing in this way to the green road towards a low-carbon future. From this perspective, the Iberian nearshore represents a coastal environment with very high potential. In this context, the objective of the work proposed herewith is to perform a joint evaluation of the wave and wind power along the west Iberian coastal environment. The analysis is structured in two time intervals. The first is the 20-year period (2001–2020), for which the ERA5 wind data have been considered. The second 20-year period (2026–2045) corresponds to the near future and in this case, wind data provided by the climate model RCA4 (Rossby Centre regional atmospheric model, version 4) have been processed and analysed, corresponding to the climate scenario RCP4.5. (Representative Concentration Pathway). The same two periods have been considered for the evaluation of wave power. In this case simulations with spectral phase averaged model SWAN (Simulating WAves Nearshore) have been performed. This wave modelling system was implemented for the entire North Atlantic basin and focused on the west Iberian coastal environment. Finally, the results also indicate that there is a good synergy between wind and wave power in the west Iberian nearshore. As a conclusion, the development of joint wind–wave projects along the west Iberian coastal environment represents a viable direction for the near future. Especially, the Northwestern part of the Iberian nearshore has a very good potential both in terms of wave and wind energy.

Predicting Groundwater Level Using Climate Change Scenarios in the Southern Part of Mali

Groundwater is mainly demanded in all the activities for the population of the southern part especially in the Koda catchment, the studied area. These resources are affected by various factors especially climate change. Therefore, knowing the impact of projected climate change on groundwater recharge is an important issue for water resources management, especially for those responsible for the Koda catchment. In this work, the impact of climate change on groundwater resources in the study area in Mali, West Africa is investigated. The Hydrogeological modeling was performed using the Gardenia model, and the monthly precipitation and temperature data were used as the Baseline. These data considered the past 30-year period (1987-2016) and the projections for the next 30 years (2021-2050). Projected precipitation and air temperatures, extracted from the Rossby Centre regional Atmospheric climate model (RCA 4) statistically downscaled from the GCM-IHEC-EC-EARTH and the GCM-MPI-M-MPI-ESM-LR under the Representative Concentration Pathways RCP 4.5 and RCP 8.5 and corrected with the Multiscale Quantile Mapping bias correction method, were used as input data to the gardenia model. Potential evapotranspiration (PET) values estimated from Blaney Criddle method and groundwater levels measured in three piezometers were used to calibrate the Gardenia model. The outputs display the reduction of groundwater level in the three piezometers in the Koda catchment for all the two Regional Climate Models (RCMs) during the periods of rainy season from July to October. From the results of GCM IHEC-EC-EARTH, the projected decline in GWL reaches 1.09 m for the RCP 4.5 and it up to 1.26 m for the RCP 8.5 in the study area while the GCM MPI-M-MPI-ESM-LR presentes the decline in groundwater level (GWL) during winter season from about 0.62 m for the RCP 4.5 up to 1.93 m for the RCP 8:5. Both RCMs project a reduction trend of groundwater recharge over time. It is noticeable that this decline is greater in RCP8.5 for all the three piezometers. The results also show that the average groundwater recharge (90 mm) in the future (2021-2050) is lower (180 mm) than that of the current drought (1987-2016), which could lead to severe drought events. The projected impacts of climate change would have a significant impact on groundwater in the period of 2029-2039; this situation could have a negative impact the socioeconomic activities especially on agriculture, which depends on water resources. The results will help also to take some adaptation measures to climate change, the famers could have a possibility to know the period of groundwater recharge where they have more water infiltration therefore, where to seek crops that need less or more water. The study area presents numerous potential of groundwater, the results could be a tool for groundwater management and to determine the favorable sites to implant new boreholes.

Evaluation of future wind power potential and their projected changes in the Black Sea and possible stable locations for wind farms

This study aimed to evaluate the possible impacts of climate change on the wind power potential and assign possible stable locations in the Black Sea until the end of the 21st century. The wind fields simulated by a regional climate model (Rossby Centre regional atmospheric climate model, version RCA4) were analyzed considering two future periods (2021–2060, 2061–2100) under RCP4.5 and RCP8.5 scenarios. The temporal variability of the wind power density (WPD) was investigated using both spatial and local analyses for the future period (2021–2100). Three temporal variability indices (namely the coefficient of variation (CV), monthly (MV), and seasonal variability (SV)) were in agreement that the mean WPD in the eastern basin is significantly more variable than in other parts of the basin. Considering the impact of climate change, the future projections for both climate scenarios indicate changes, and the eastern basin will experience more changes under the RCP8.5 scenario. For the most predictable future developments of the wind power potential, 15 reference points along the Black Sea were analyzed using the intra- and inter-annual variability of the mean WPD. In the future, strong, durable, and stable wind resources in the western basin will ensure reliable, permanent, and sustainable WPD.

Evaluation of regional climate models and future wave characteristics in an enclosed sea: A case study of the Black Sea

The main objective of this study is to evaluate a possible climate change impact on wave climate in an enclosed sea (Black Sea) until the end of the 21st century. To achieve the goal, the wave data are generated from a third-generation wave model forced with the widely used reanalysis data (Climate Forecast System Reanalysis), and the hindcast wind fields simulated by a Regional Climate Model, namely Rossby Centre regional atmospheric model (version RCA4). The pattern of change in the wave climate is discussed by comparing the historical (1970–2005) with the future for periods 2021–2060 and 2061–2100 under two climate scenarios. The projected changes in the mean wave characteristics are characterized by an increase in the near future for both RCP scenarios that is more prominent under RCP8.5 scenario in the eastern basin. The middle future under RCP8.5 scenario suggests more significant changes in annual mean values than those obtained under RCP4.5 scenario. In the context of climate change, the possible effects are more prominent on extreme wave heights. For example, the increases in the wave heights for the 100-year return period reach the value of 5% and 25% in the western and eastern Black Sea, respectively.

Impact of future climate change on malaria in West Africa

Understanding the regional impact of future climate change is one of the major global challenges of this century. This study investigated possible effects of climate change on malaria in West Africa in the near future (2006–2035) and the far future (2036–2065) under two representative concentration pathway (RCP) scenarios (RCP4.5 and RCP8.5), compared to an observed evaluation period (1981–2010). Projected rainfall and temperature were obtained from the coordinated regional downscaling experiment (CORDEX) simulations of the Rossby Centre Regional Atmospheric regional climate model (RCA4). The malaria model used is the Liverpool malaria model (LMM), a dynamical malaria model driven by daily time series of rainfall and temperature obtained from the CORDEX data. Our results highlight the unimodal shape of the malaria prevalence distribution, and the seasonal malaria transmission contrast is closely linked to the latitudinal variation of the rainfall. Projections showed that the mean annual malaria prevalence would decrease in both climatological periods under both RCPs but with a larger magnitude of decreasing under the RCP8.5. We found that the mean malaria prevalence for the reference period is greater than the projected prevalence for 6 of the 8 downscaled GCMs. The study enhances understanding of how malaria is impacted under RCP4.5 and RCP8.5 emission scenarios. These results indicate that the southern area of West Africa is at most risk of epidemics, and the malaria control programs need extra effort and help to make the best use of available resources by stakeholders.

Evaluation of regional climate models and future wind characteristics in the Black Sea

AbstractThe main objective of the present study is to provide a comprehensive image of the expected wind patterns along the 21st century in the Black Sea using the wind fields simulated by Regional Climate Model (RCM), namely Rossby Centre regional atmospheric model (version RCA4). Long‐term averages, long‐term variability, and long‐term trends in wind characteristics over the Black Sea are evaluated in two future time slices (near future 2021–2060 and middle future 2061–2100) under the two climate scenarios (RCP4.5 and 8.5). Detailed analysis of wind (annual mean and 99th percentile wind speeds) and storm characteristics (number and duration of storms) are conducted for three different locations selected on the same meridional section to assess the variability on the wind characteristics from west to east. Spatiotemporal variability on the wind characteristics indicates that the eastern Black Sea will be characterized by lower mean wind speed, stronger 99th percentile wind speed, and higher variability. Considering the global indicators of climate change (e.g., increasing frequency and intensity of extreme events), the eastern Black Sea, characterized by complex atmospheric circulation due to surrounding mountains, is more likely to be subjected to the impacts of climate change as the occurrence of extreme wind speeds in future periods is more prominent in this region. In the future periods, the 100‐year return period wind speeds increase approximately 7% and 27% in the western and eastern Black Sea, respectively, compared to the historical period. The strong and relatively stable winds with low variability in the western Black Sea indicate a reliable, persistent, and sustainable wind energy potential in this region in the future.

Assessment of the performance of CORDEX regional climate models in simulating rainfall and air temperature over southwest Ethiopia

This study analyzed the performance of four (REgional MOdel (REMO2009), High-Resolution Hamburg Climate Model 5 (HIRAM5), Climate Limited-Area Modeling Community (CCLM4-8) and Rossby Centre Regional Atmospheric Model (RCA4)) Regional Climate Models (RCMs) simulations from Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa program. The simulation period of 1985–2005 was evaluated considering how each RCM simulated the observed rainfall and air temperature over southwest Ethiopia. It was found that all the RCMs simulated the seasonal rainfall, but not the peak rainfall, with all models including their ensemble underestimating the peak rainfall. However, the ensemble was better than the individual RCMs in simulating both rainfall and air temperature. All models were slightly biased around a warm climate zone in simulating maximum air temperature when compared to the simulation of air minimum temperature. Of the four RCMs, REMO2009 performed well in simulating the maximum and minimum air temperatures. The interseasonal variation in rainfall was greater than the seasonal variation in air temperature. In terms of cumulative distribution, the HIRAM5 captured more extreme rainfall events and overestimated the return period. Overall, the differences in performance among the RCMs provided strong evidence for the use of regional-scale data at the local scale in climate impact assessments being controversial. In relation to the spatial pattern of the rainfall, most of the models simulated the observed minimum rainfall in the north and northeast, medium rainfall in the central region, and maximum rainfall in the south and southwest of the study area. The overall results indicate that choosing a reliable RCM is fundamentally necessary to delivering a strong basis for any climate-change impact study.

Possible influence of climate change on water balance over West Africa under the global warming levels of 2 and 3 °C

Abstract Reliable projection of water balance components for the future over a climate change vulnerable region such as West Africa is exigent for proper adaptation strategies. This paper analyses the expected water balance in the 21st century over West Africa at 2 and 3 °C global warming level (GWL) based on Rossby Centre Regional Atmospheric Climate Model (RCA4) downscaled projections. Precipitation is expected to increase at the south-western (−5 to 10°N, 15 to 25°W) ocean area of West Africa domain with SW–NE orientation, towards the Sahel, while other areas would be drier, at 2 °C GWL. This would intensify under 3 °C GWL. Responses of evapotranspiration and storage change are similar to that of precipitation except for more spatial spread of increased evapotranspiration on the ocean. Runoff would increase over the ocean, Sahara and part of Sahel and reduce in Savannah and Guinea Coast under 2 °C GWL, but reduce under a warmer world with isolated increase.

How far the CORDEX high-resolution data represents observed precipitation: an analysis across Indian mainland

Coordinated Regional Climate Downscaling Experiment (CORDEX) has developed high-resolution, dynamically downscaled data across the world. This paper investigates the spatio-temporal correspondence between CORDEX data for South Asia (CORDEX-SA) and observed precipitation data to assess its reliability. The entire Indian mainland is considered as study region. Both monthly and seasonal analyses are undertaken along with the extreme magnitudes during historical (1971–2005) and future (2006–2100) periods. The outputs of two regional climate models (RCMs), viz. regional climate model, version-4.4 (RegCM4) and Rossby Centre regional Atmospheric model, version-4 (RCA4), participating in CORDEX-SA program, are considered for medium (RCP4.5) and high (RCP8.5) emission scenarios. The CORDEX-SA is found to well represents in central India, but significant bias in the mean precipitation (± 200 mm) is noticed at northern, north-eastern, southern and coastal regions. The inferior performance of both the RCMs is noticed over high rainfall regions. Specifically, more than 70% area is found to have mean bias more than ± 100 mm. Performance of RCA4 is better in North and Himalayan regions, where 67% of area is found to be within the aforementioned threshold, which is 23.64% in case of RegCM4. Performance of RegCM4 is marginally better in the peninsular India as compared with RCA4. In case of extreme magnitudes, the insignificant correspondance between CORDEX-SA data and observed precipitation is noticed over the many parts of India. Results of this study are important to check the applicability of CORDEX data in various impact assessment studies.

Spatial-Temporal Characteristics of Past and Projected Climate Over Dairy Production Zones: A Case of Nandi County, Kenya

Climate change is regarded as a significant global environmental threat. This study assesses downscaled projections of climate change over dairy production regions (Nandi County) of Kenya using Rossby Centre Regional Atmospheric Model (RCA4) outputs driven by the eight (8) coordinated regional Downscaling Experiment (CORDEX) models. Climate baseline period (1971-2000) was used to evaluate CORDEX model performance against different sources of precipitation and temperature observations. Graphical and statistical approaches which correlation; Mann-Kendall test and nonparametric Sen’s method were used to assess the trends in both past and future climate. Spatial analysis involved mapping of climate variables. Assessment of the skill of CORDEX models shows significant bias in the individual models in simulating precipitation. However, maximum and minimum temperatures performed well based on both individual and ensemble based outputs. CORDEX model outputs were comparable to observations, and either overestimated or underestimated the climate. Past and projected precipitation remains bimodal and highly variable (increasing/decreasing) in both space and time. Positive change between baseline and projected temperatures were noted for RCP45 and RCP85. As a response to the effects of climate variability and change, adoption of climate smart agricultural technologies is necessary to ensure that smallholder farmers put adequate measures to adapt and mitigate impact of climate change Keywords: Precipitation; temperature; climate; projections; CORDEX DOI: 10.7176/JEES/10-6-06 Publication date: June 30 th 2020

Extreme sea levels in the Baltic Sea under climate change scenarios – Part 1: Model validation and sensitivity

Abstract. We analyze extreme sea levels (ESLs) and related uncertainty in an ensemble of regional climate change scenarios for the Baltic Sea. The ERA-40 reanalysis and five Coupled Model Intercomparison Project phase 5 (CMIP5) global general circulation models (GCMs) have been dynamically downscaled with the coupled atmosphere–ice–ocean model RCA4-NEMO (Rossby Centre regional atmospheric model version 4 – Nucleus for European Modelling of the Ocean). The 100-year return levels along the Swedish coast in the ERA-40 hindcast are within the 95 % confidence limits of the observational estimates, except those on the west coast. The ensemble mean of the 100-year return levels averaged over the five GCMs shows biases of less than 10 cm. A series of sensitivity studies explores how the choice of different parameterizations, open boundary conditions and atmospheric forcing affects the estimates of 100-year return levels. A small ensemble of different regional climate models (RCMs) forced with ERA-40 shows the highest uncertainty in ESLs in the southwestern Baltic Sea and in the northeastern part of the Bothnian Bay. Some regions like the Skagerrak, Gulf of Finland and Gulf of Riga are sensitive to the choice of the RCM. A second ensemble of one RCM forced with different GCMs uncovers a lower sensitivity of ESLs against the variance introduced by different GCMs. The uncertainty in the estimates of 100-year return levels introduced by GCMs ranges from 20 to 40 cm at different stations and includes the estimates based on observations. It is of similar size to the 95 % confidence limits of 100-year return levels from tide gauge records.

Regional climate model RCA4 simulations of temperature and precipitation over the Arabian Peninsula: sensitivity to CORDEX domain and lateral boundary conditions

Regional Climate Models (RCMs) are increasingly used to add small-scale processes at higher grid resolution that are not represented by their Lateral Boundary Conditions (LBCs). Rossby Centre regional atmospheric model, RCA4, has downscaled three Global Climate Models (GCMs), namely, CNRM-CM5, EC-EARTH and GFDL-ESM2M in the COordinated Regional climate Downscaling EXperiment (CORDEX) framework for Middle East North Africa (MENA) and South Asia (SA) domains. Arabian Peninsula is covered in both MENA and SA simulations, which gives a unique opportunity to study the effects of CORDEX domain and LBCs on the simulation of temperature and precipitation by RCM. It is examined by calculating the differences between MENA and SA simulations for different driving GCMs in the historical (1976–2005) and future (2071–2100) periods under RCP8.5 emission scenario, for both summer (dry) and winter (wet) seasons. RCA4 performs generally well when simulating the observed temperature and precipitation patterns, with some local wet biases over Asir Mountains and cold bias over the north eastern parts of Saudi Arabia. The simulations of temperature seem to be very sensitive to the simulation domain (i.e., MENA and SA) and less sensitive to different LBCs, whereas in case of precipitation LBCs seems to play a dominant role. The MENA simulations generally project about 2 °C warmer and drier climate compared to SA simulations by the end of this century, which is comparable to the differences arising due to different LBCs and climate change.

Assessment of climatological tropical cyclone activity over the north Indian Ocean in the CORDEX-South Asia regional climate models

This study evaluates the ability of the regional climate models (RCMs) in the Coordinated Regional Climate Downscaling Experiment for South Asia (CORDEX-SA) to simulate the tropical cyclone activity in the north Indian Ocean. The RCMs used in the CORDEX-SA are Rossby Centre regional atmospheric model version 4 (RCA4) and Regional Climatic Model version 4 (RegCM4) forced by the ECMWF Interim Reanalysis (ERA-Interim) from 1989 to 2008. Both models have reasonable skill in capturing the observed climatological seasonal and spatial distribution of the genesis and track of the tropical cyclones. However, the two issues faced are (i) in RegCM4 model, higher number of tropical cyclones throughout the year compared to observations in addition to the unrealistic simulation of tropical cyclones during winter and (ii) in the RCA4 model, relatively higher tropical cyclone activity over the Arabian Sea compared to the Bay of Bengal. In the RCA4, the anomalous large-scale lower tropospheric cyclonic circulation observed over the southern Arabian Sea might be responsible for the overestimation in the number of tropical cyclones over there. In both models, the relationship between minimum pressure and the maximum wind is well simulated even though there is an underestimation in the intensity of the tropical cyclones. Quantitative analysis of large-scale environmental parameters that influence the tropical cyclone activity using an index called genesis potential index showed that in the RegCM4 model, the model simulates seasonal variation (enhancement/suppression) of environmental conditions fairly good as seen in the observation. However, the model has higher number of tropical cyclones in all the seasons, which is due to the enhanced large scale dynamical and thermodynamical parameters. The cold and wet bias in the middle troposphere causes the reduction in the mid-layer saturation deficit throughout the year, which in turn favours an unrealistic high number of tropical cyclone genesis. Therefore, the changes in the large scale dynamics and relatively saturated middle troposphere in the model might be responsible for the higher number of tropical cyclones.

A 30-year projection of the future wind energy resources in the coastal environment of the Black Sea

The objective of the present work is to evaluate the wind energy resources in the coastal environment of the Black Sea by providing a reliable projection for the next 30 years. The wind power is assessed for water depths in the range 25–125 m. The wind speeds considered are those provided by the Rossby Centre regional atmospheric model, version (RCA4) and predicted under the Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 used in Climate Model Intercomparison Project phase 5 (CMIP5). The time interval is 2021–2050, the wind speeds having a spatial resolution of 0.11°, with 6-h temporal resolution. An analysis of the historical data provided by these climatic wind models performed for the 30-year time interval 1976–2005 shows reliable results in the basin of the Black Sea. This gives a reasonable degree of confidence for the model results corresponding to the 30-year future time window considered, providing at the same time a mean of comparison with the future wind climate Although from the point of view of the wave energy, the Black Sea cannot be considered with high potential, especially when compared to the ocean coasts, as regards the wind power resources the potential of this coastal environment is in line with other coastal areas where such marine wind farms already successfully operate. Finally, it can be concluded that the present work provides a comprehensive and useful picture of the future wind energy resources in the coastal environment of the Black Sea as well as on the changes expected in the wind climate.

Variable resolution modeling of near future mean temperature changes in the dry sub-humid region of Ghana

The study used two models from Rossby Centre Regional Atmospheric Model (RCA4) and two from Weather Research and Forecasting Model (WRF) plus the Statistical Downscaling Model—Decision Centric (SDSM-DC) at 44 km, 12 km and 2 m resolution respectively to project the impact of climate change on mean temperature in the Pra River Basin for the period 2020–2049. Results showed that the minimum temperature increased (+ 1.47 °C) faster than the increase (+ 1.11 °C) in maximum temperature for observed period 1981–2010. An evaluation of the performance of the models with time-series based metrics showed that SDSM-DC and RCA4 are better for projecting mean temperature in the study area compared to WRF despite its resolution. Analysis of variance (p < 0.05) indicated significant difference between the projected mean temperature of the five models but there was no significant difference between SDSM-DC and RCA4 models. Correlation between models was highest at R = 0.727 between SDSM-DC and RCA4. The years 2041, 2042 and 2047 were projected as hottest by minimum two different models. The mean temperature change was projected at + 1.36, + 1.42 and + 1.12 °C by SDSM-DC, RCA4 and WRF respectively. The ensemble of projection depicted same trend of February—April as the high mean temperature and July—September as the lowest as was for the observed period. However, January is projected to have the highest change in mean temperature of + 1.51 °C. The maximum temperature for observed period was found to be the mean temperature in the period 2020–2049. Future study will focus on the impact of projected temperature change on ecosystem services delivery in the region.

Modelling 60 years of glacier mass balance and runoff for Chhota Shigri Glacier, Western Himalaya, Northern India

ABSTRACTGlacier mass balance and runoff are simulated from 1955 to 2014 for the catchment (46% glacier cover) containing Chhota Shigri Glacier (Western Himalaya) using gridded data from three regional climate models: (1) the Rossby Centre regional atmospheric climate model v.4 (RCA4); (2) the REgional atmosphere MOdel (REMO); and (3) the Weather Research and Forecasting Model (WRF). The input data are downscaled to the simulation grid (300 m) and calibrated with point measurements of temperature and precipitation. Additional input is daily potential global radiation calculated using a DEM at a resolution of 30 m. The mass-balance model calculates daily snow accumulation, melt and runoff. The model parameters are calibrated with available mass-balance measurements and results are validated with geodetic measurements, other mass-balance model results and run-off measurements. Simulated annual mass balances slightly decreased from −0.3 m w.e. a−1 (1955–99) to −0.6 m w.e. a−1 for 2000–14. For the same periods, mean runoff increased from 2.0 m3 s−1 (1955–99) to 2.4 m3 s−1 (2000–14) with glacier melt contributing about one-third to the runoff. Monthly runoff increases are greatest in July, due to both increased snow and glacier melt, whereas slightly decreased snowmelt in August and September was more than compensated by increased glacier melt.

Characteristics of sub-daily precipitation extremes in observed data and regional climate model simulations

The study compares characteristics of observed sub-daily precipitation extremes in the Czech Republic with those simulated by Hadley Centre Regional Model version 3 (HadRM3) and Rossby Centre Regional Atmospheric Model version 4 (RCA4) regional climate models (RCMs) driven by reanalyses and examines diurnal cycles of hourly precipitation and their dependence on intensity and surface temperature. The observed warm-season (May–September) maxima of short-duration (1, 2 and 3 h) amounts show one diurnal peak in the afternoon, which is simulated reasonably well by RCA4, although the peak occurs too early in the model. HadRM3 provides an unrealistic diurnal cycle with a nighttime peak and an afternoon minimum coinciding with the observed maximum for all three ensemble members, which suggests that convection is not captured realistically. Distorted relationships of the diurnal cycles of hourly precipitation to daily maximum temperature in HadRM3 further evidence that underlying physical mechanisms are misrepresented in this RCM. Goodness-of-fit tests indicate that generalised extreme value distribution is an applicable model for both observed and RCM-simulated precipitation maxima. However, the RCMs are not able to capture the range of the shape parameter estimates of distributions of short-duration precipitation maxima realistically, leading to either too many (nearly all for HadRM3) or too few (RCA4) grid boxes in which the shape parameter corresponds to a heavy tail. This means that the distributions of maxima of sub-daily amounts are distorted in the RCM-simulated data and do not match reality well. Therefore, projected changes of sub-daily precipitation extremes in climate change scenarios based on RCMs not resolving convection need to be interpreted with caution.

Teleconnection responses in multi-GCM driven CORDEX RCMs over Eastern Africa

The ability of climate models to simulate atmospheric teleconnections provides an important basis for the use and analysis of climate change projections. This study examines the ability of COordinated Regional climate Downscaling EXperiment models, with lateral and surface boundary conditions derived from Coupled Global Climate Models (CGCMs), to simulate the teleconnections between tropical sea surface temperatures and rainfall over Eastern Africa. The ability of the models to simulate the associated changes in atmospheric circulation patterns over the region is also assessed. The models used in the study are Rossby Centre regional atmospheric model (RCA) driven by eight CGCMs and COnsortium for Small scale MOdeling (COSMO) Climate Limited-area Modelling (COSMO-CLM or CCLM) driven by four of the same CGCMs. Teleconnection patterns are examined using correlation, regression and composite analysis. In order to identify the source of the errors, CGCM-driven regional climate model (RCM) results are compared with ERA-Interim driven RCM results. Results from the driving CGCMs are also analyzed. The RCMs driven by reanalysis (quasi-perfect boundary conditions) successfully capture rainfall teleconnections in most examined regions and seasons. Our analysis indicates that most of the errors in simulating the teleconnection patterns come from the driving CGCMs. RCMs driven by MPI-ESM-LR, HadGEM2-ES and GFDL-ESM2M tend to perform relatively better than RCMs driven by other CGCMs. CanESM2 and MIROC5, and their corresponding downscaled results capture the teleconnections in most of the sub-regions and seasons poorly. This highlights the relative importance of CGCM-derived boundary conditions in the downscaled product and the need to improve these as well as the RCMs themselves. Overall, the results produced here will be very useful in identifying and selecting CGCMs and RCMs for the use of climate change projecting over the Eastern Africa.