Reduction of systematic biases in regional climate downscaling through ensemble forcing

Simulations of the East Asian summer monsoon for the period of 1979–2001 were carried out using the Weather Research and Forecast (WRF) model forced by three reanalysis datasets (NCEP-R2, ERA-40, and JRA-25). The experiments forced by different reanalysis data exhibited remarkable differences, primarily caused by uncertainties in the lateral boundary (LB) moisture fluxes over the Bay of Bengal and the Philippine Sea. The climatological mean water vapor convergence into the model domain computed from ERA-40 was about 24% higher than that from the NCEP-R2 reanalysis. We demonstrate that using the ensemble mean of NCEP-R2, ERA-40, and JRA-25 as LB forcing considerably reduced the biases in the model simulation. The use of ensemble forcing improved the performance in simulated mean circulation and precipitation, inter-annual variation in seasonal precipitation, and daily precipitation. The model simulated precipitation was superior to that in the reanalysis in both climatology and year-to-year variations, indicating the added value of dynamic downscaling. The results suggest that models having better performance under one set of LB forcing might worsen when another set of reanalysis data is used as LB forcing. Use of ensemble mean LB forcing for assessing regional climate model performance is recommended.     

Precipitation climate of Central Asia and the large-scale atmospheric circulation

The precipitation climate in the larger Tian Shan region of Central Asia is described in terms of the climatological seasonal moisture fluxes and background circulation based on the ERA-40 reanalysis data and a precipitation reanalysis. The study area is partitioned into (1) the Tarim river basin, (2) bordering regions of China, Kyrgyzstan and Kazakhstan, and (3) Northwestern China. Moisture supply to these areas is primarily due to the midlatitude westerlies with contributions from higher latitudes. In addition, moisture from the Indian Ocean is notably imported into the Tarim drainage area. Monthly interannual precipitation variability relates to the variability of hemispheric circulation patterns. Extreme precipitation above and below normal in Western China and Central Asia is analyzed using the standardized precipitation index. Related circulation composites show that, despite regional and seasonal differences, episodes of extreme and severe dryness are dominated by various upstream standing wave patterns from the North Atlantic to Central Asia. These features extend further downstream to the North Pacific. Non-symmetry between wet and dry composites is noted upstream and in regional moisture flux composites.     

Simulating the impact of the large-scale circulation on the 2-m temperature and precipitation climatology

The impact of the simulated large-scale atmospheric circulation on the regional climate is examined using the Weather Research and Forecasting (WRF) model as a regional climate model. The purpose is to understand the potential need for interior grid nudging for dynamical downscaling of global climate model (GCM) output for air quality applications under a changing climate. In this study we downscale the NCEP-Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) Reanalysis using three continuous 20-year WRF simulations: one simulation without interior grid nudging and two using different interior grid nudging methods. The biases in 2-m temperature and precipitation for the simulation without interior grid nudging are unreasonably large with respect to the North American Regional Reanalysis (NARR) over the eastern half of the contiguous United States (CONUS) during the summer when air quality concerns are most relevant. This study examines how these differences arise from errors in predicting the large-scale atmospheric circulation. It is demonstrated that the Bermuda high, which strongly influences the regional climate for much of the eastern half of the CONUS during the summer, is poorly simulated without interior grid nudging. In particular, two summers when the Bermuda high was west (1993) and east (2003) of its climatological position are chosen to illustrate problems in the large-scale atmospheric circulation anomalies. For both summers, WRF without interior grid nudging fails to simulate the placement of the upper-level anticyclonic (1993) and cyclonic (2003) circulation anomalies. The displacement of the large-scale circulation impacts the lower atmosphere moisture transport and precipitable water, affecting the convective environment and precipitation. Using interior grid nudging improves the large-scale circulation aloft and moisture transport/precipitable water anomalies, thereby improving the simulated 2-m temperature and precipitation. The results demonstrate that constraining the RCM to the large-scale features in the driving fields improves the overall accuracy of the simulated regional climate, and suggest that in the absence of such a constraint, the RCM will likely misrepresent important large-scale shifts in the atmospheric circulation under a future climate.     

Seasonal Predictions of Summer Precipitation in the Middle-lower Reaches of the Yangtze River with Global and Regional Models Based on NUIST-CFS1.0

Accurate prediction of the summer precipitation over the middle and lower reaches of the Yangtze River (MLYR) is of urgent demand for the local economic and societal development. This study assesses the seasonal forecast skill in predicting summer precipitation over the MLYR region based on the global Climate Forecast System of Nanjing University of Information Science and Technology (NUIST-CFS1.0, previously SINTEX-F). The results show that the model can provide moderate skill in predicting the interannual variations of the MLYR rainbands, initialized from 1 March. In addition, the nine-member ensemble mean can realistically reproduce the links between the MLYR precipitation and tropical sea surface temperature (SST) anomalies, but the individual members show great discrepancies, indicating large uncertainty in the forecasts. Furthermore, the NUIST-CFS1.0 can predict five of the seven extreme summer precipitation anomalies over the MLYR during 1982–2020, albeit with underestimated magnitudes. The Weather Forecast and Research (WRF) downscaling hindcast experiments with a finer resolution of 30 km, which are forced by the large-scale information of the NUIST-CFS1.0 predictions with a spectral nudging method, display improved predictions of the extreme summer precipitation anomalies to some extent. However, the performance of the downscaling predictions is highly dependent on the global model forecast skill, suggesting that further improvements on both the global and regional climate models are needed.     

Evaluation of the regional climate model ALADIN to simulate the climate over North America in the CORDEX framework

In this study, an ensemble of four multi-year climate simulations is performed with the regional climate model ALADIN to evaluate its ability to simulate the climate over North America in the CORDEX framework. The simulations differ in their driving fields (ERA-40 or ERA-Interim) and the nudging technique (with or without large-scale nudging). The validation of the simulated 2-m temperature and precipitation with observationally-based gridded data sets shows that ALADIN performs similarly to other regional climate models that are commonly used over North America. Large-scale nudging improves the temporal correlation of the atmospheric circulation between ALADIN and its driving field, and also reduces the warm and dry summer biases in central North America. The differences between the simulations driven with different reanalyses are small and are likely related to the regional climate model’s induced internal variability. In general, the impact of different driving fields on ALADIN is smaller than that of large-scale nudging. The analysis of the multi-year simulations over the prairie and the east taiga indicates that the ALADIN 2-m temperature and precipitation interannual variability is similar or larger than that observed. Finally, a comparison of the simulations with observations for the summer 1993 shows that ALADIN underestimates the flood in central North America mainly due to its systematic dry bias in this region. Overall, the results indicate that ALADIN can produce a valuable contribution to CORDEX over North America.     

Regional climate of hazardous convective weather through high-resolution dynamical downscaling

We explore the use of high-resolution dynamical downscaling as a means to simulate the regional climatology and variability of hazardous convective-scale weather. Our basic approach differs from a traditional regional climate model application in that it involves a sequence of daily integrations. We use the weather research and forecasting (WRF) model, with global reanalysis data as initial and boundary conditions. Horizontal grid lengths of 4.25?km allow for explicit representation of deep convective storms and hence a compilation of their occurrence statistics over a large portion of the conterminous United States. The resultant 10-year sequence of WRF model integrations yields precipitation that, despite its positive bias, has a diurnal cycle consistent with observations, and otherwise has a realistic geographical distribution. Similarly, the occurrence frequency of short-duration, potentially flooding rainfall compares well to analyses of hourly rain gauge data. Finally, the climatological distribution of hazardous-thunderstorm occurrence is shown to be represented with some degree of skill through a model proxy that relates rotating convective updraft cores to the presence of hail, damaging surface winds, and tornadoes. The results suggest that the proxy occurrences, when coupled with information on the larger-scale atmosphere, could provide guidance on the reliability of trends in the observed occurrences.     

Storm track sensitivity to sea surface temperature resolution in a regional atmosphere model

A high resolution regional atmosphere model is used to investigate the sensitivity of the North Atlantic storm track to the spatial and temporal resolution of the sea surface temperature (SST) data used as a lower boundary condition. The model is run over an unusually large domain covering all of the North Atlantic and Europe, and is shown to produce a very good simulation of the observed storm track structure. The model is forced at the lateral boundaries with 15–20 years of data from the ERA-40 reanalysis, and at the lower boundary by SST data of differing resolution. The impacts of increasing spatial and temporal resolution are assessed separately, and in both cases increasing the resolution leads to subtle, but significant changes in the storm track. In some, but not all cases these changes act to reduce the small storm track biases seen in the model when it is forced with low-resolution SSTs. In addition there are several clear mesoscale responses to increased spatial SST resolution, with surface heat fluxes and convective precipitation increasing by 10–20% along the Gulf Stream SST gradient.     

Seasonal to yearly assessment of temperature and precipitation trends in the North Western Mediterranean Basin by dynamical downscaling of climate scenarios at high resolution (1971–2050)

The complex topography and high climatic variability of the North Western Mediterranean Basin (NWMB) require a detailed assessment of climate change projections at high resolution. ECHAM5/MPIOM global climate projections for mid-21st century and three different emission scenarios are downscaled at 10 km resolution over the NWMB, using the WRF-ARW regional model. High resolution improves the spatial distribution of temperature and precipitation climatologies, with Pearson's correlation against observation being higher for WRF-ARW (0.98 for temperature and 0.81 for precipitation) when compared to the ERA40 reanalysis (0.69 and 0.53, respectively). However, downscaled results slightly underestimate mean temperature (≈1.3 K) and overestimate the precipitation field (≈400 mm/year). Temperature is expected to raise in the NWMB in all considered scenarios (up to 1.4 K for the annual mean), and particularly during summertime and at high altitude areas. Annual mean precipitation is likely to decrease (around ?5 % to ?13 % for the most extreme scenarios). The climate signal for seasonal precipitation is not so clear, as it is highly influenced by the driving GCM simulation. All scenarios suggest statistically significant decreases of precipitation for mountain ranges in winter and autumn. High resolution simulations of regional climate are potentially useful to decision makers. Nevertheless, uncertainties related to seasonal precipitation projections still persist and have to be addressed.     

High resolution re-analysis for the Baltic Sea region during 1965–2005 period

Regional reanalysis database BaltAn65+ comprising meteorological data for Baltic Sea region for the time period 1965–2005 is described. For data assimilation and hindcasts, the numerical weather prediction model HIRLAM 7.1.4 is applied, with 11 km horizontal and 60-layer vertical resolution. Reanalysis includes three-dimensional weather analysis data. Standard surface observations and meteorological soundings together with ship and buoy measurements from WMO observational network are used in analysis. Boundary fields are obtained from ECMWF ERA-40 global re-analysis. The BaltAn65+ can be considered as a regional refinement of ERA-40 for Baltic Sea region, providing the historical weather and climate data with enhanced spatial resolution, which is main motivation for creation of this novel reanalysis database.     

Characteristics of autumn-winter extreme precipitation on the Norwegian west coast identified by cluster analysis

Extremely high autumn and winter precipitation events on the European west coast are often driven by low-pressure systems in the North Atlantic. Climate projections suggest the number and intensity of these events is likely to increase far more than the mean precipitation. In this study we investigate the autumn-winter extreme precipitation on the Norwegian west coast and the connection between its spatial distribution and sea level pressure (SLP) patterns using the k-means cluster analysis. We use three relatively high resolved downscalings of one global coupled model: the Arpège global atmospheric model (stretched grid with 35-km horizontal resolution over Norway) and the WRF-downscaled Arpège model (30 and 10-km) for the 30-year periods of 1961–1990 and 2021–2050. The cluster analysis finds three main SLP patterns responsible for extreme precipitation in different parts of the country. The SLP patterns found are similar to the NAO positive pattern known to strengthen the westerly flow towards European coast. We then apply the method to investigate future change in extreme precipitation. We find an increase in the number of days with extreme precipitation of 15, 39 and 35% in the two simulations (Arpège 35-km and WRF 30 and 10-km, respectively). We do not find evidence of a significant change in the frequency of weather patterns between the present and the future periods. Rather, it is the probability of a given weather pattern to cause extreme precipitation which is increased in the future, probably due to higher temperatures and an increased moisture content of the air. The WRF model predicts the increase in this probability caused by the most important SLP patterns to be >50%. The Arpège model does not predict such a significant change because the general increase in extreme precipitation predicted is smaller, probably due to its coarser resolution over ocean which leads to smoother representation of the low pressure systems.     

Impacts of the spectral nudging technique on simulation of the East Asian summer monsoon

This study assesses the performance of spectral nudging methodology in dynamical regional climate downscaling for summer climate over East Asia. The regional climate model NCAR-MM5v3 was used to dynamically downscale the 2.5-degree NCEP/NCAR reanalysis (NNRP) data onto 50-km regional grids. The main focus is the model’s simulation of precipitation. The NCEP/CPC precipitation analysis data were used as the verification. Boreal summers (June, July, and August) in 1991, 1998, and 2003 and heavy floods that occurred in Eastern China were selected for the study. Compared to the control runs (CTLs) without spectral nudging (SN), experiments with SNs greatly reduced systematic errors in upper-level large-scale circulations and were in better agreement with the NNRP. At the same time, SNs outperformed CTLs in simulating model variables near the surface. In comparison with observational precipitation data, spectral nudging also improved the model’s simulation of precipitation in spatial and temporal distributions. SN-simulated precipitation field patterns, including the spatial distribution of monthly mean precipitation band, the seasonal march of major precipitation bands, and the daily variability of regional-averaged time series, show much more consistency with observations than those of the CTL runs.     

Extreme precipitation in WRF during the Newcastle East Coast Low of 2007

In the context of regional downscaling, we study the representation of extreme precipitation in the Weather Research and Forecasting (WRF) model, focusing on a major event that occurred on the 8^th of June 2007 along the coast of eastern Australia (abbreviated “Newy”). This was one of the strongest extra-tropical low-pressure systems off eastern Australia in the last 30 years and was one of several storms comprising a test bed for the WRF ensemble that underpins the regional climate change projections for eastern Australia (New South Wales/Australian Capital Territory Regional Climate Modelling Project, NARCliM). Newy provides an informative case study for examining precipitation extremes as simulated by WRF set up for regional downscaling. Here, simulations from the NARCliM physics ensemble of Newy available at ～10 km grid spacing are used. Extremes and spatio-temporal characteristics are examined using land-based daily and hourly precipitation totals, with a particular focus on hourly accumulations. Of the different physics schemes assessed, the cumulus and the boundary layer schemes cause the largest differences. Although the Betts-Miller-Janjic cumulus scheme produces better rainfall totals over the entire storm, the Kain-Fritsch cumulus scheme promotes higher and more realistic hourly extreme precipitation totals. Analysis indicates the Kain-Fritsch runs are correlated with larger resolved grid-scale vertical moisture fluxes, which are produced through the influence of parameterized convection on the larger-scale circulation and the subsequent convergence and ascent of moisture. Results show that WRF qualitatively reproduces spatial precipitation patterns during the storm, albeit with some errors in timing. This case study indicates that whilst regional climate simulations of an extreme event such as Newy in WRF may be well represented at daily scales irrespective of the physics scheme used, the representation at hourly scales is likely to be physics scheme dependent.     

Evaluating climate change at the Croatian Adriatic from observations and regional climate models’ simulations

The 2m temperature (T2m) and precipitation from five regional climate models (RCMs), which participated in the ENSEMBLES project and were integrated at a 25-km horizontal resolution, are compared with observed climatological data from 13 stations located in the Croatian coastal zone. The twentieth century climate was simulated by forcing RCMs with identical boundary conditions from the ERA-40 reanalysis and the ECHAM5/MPI-OM global climate model (GCM); climate change in the twenty-first century is based on the A1B scenario and assessed from the GCM-forced RCMs’ integrations. When forced by ERA-40, most RCMs exhibit cold bias in winter which contributes to an overestimation of the T2m annual cycle amplitude and the errors in interannual variability are in all RCMs smaller than those in the climatological mean. All models underestimate observed warming trends in the period 1951–2010. The largest precipitation biases coincide with locations/seasons with small observed amounts but large precipitation amounts near high orography are relatively well reproduced. When forced by the same GCM all RCMs exhibit a warming in the cold half-year and a cooling (or weak warming) in the warm period, implying a strong impact of GCM boundary forcing. The future eastern Adriatic climate is characterised by a warming, up to +5 °C towards the end of the twenty-first century; for precipitation, no clear signal is evident in the first half of the twenty-first century, but a reduction in precipitation during summer prevails in the second half. It is argued that land-sea contrast and complex coastal configuration of the Croatian coast, i.e. multitude of island and well indented coastline, have a major impact on small-scale variability. Orography plays important role only at small number of coastal locations. We hypothesise that the parameterisations related to land surface processes and soil hydrology have relatively stronger impact on variability than orography at those locations that include a relatively large fraction of land (most coastal stations), but affecting less strongly locations at the Adriatic islands.     

Dynamic downscaling of summer precipitation prediction over China in 1998 using WRF and CCSM4

To study the prediction of the anomalous precipitation and general circulation for the summer(June–July–August) of1998, the Community Climate System Model Version 4.0(CCSM4.0) integrations were used to drive version 3.2 of the Weather Research and Forecasting(WRF3.2) regional climate model to produce hindcasts at 60 km resolution. The results showed that the WRF model produced improved summer precipitation simulations. The systematic errors in the east of the Tibetan Plateau were removed, while in North China and Northeast China the systematic errors still existed. The improvements in summer precipitation interannual increment prediction also had regional characteristics. There was a marked improvement over the south of the Yangtze River basin and South China, but no obvious improvement over North China and Northeast China. Further analysis showed that the improvement was present not only for the seasonal mean precipitation, but also on a sub-seasonal timescale. The two occurrences of the Mei-yu rainfall agreed better with the observations in the WRF model,but were not resolved in CCSM. These improvements resulted from both the higher resolution and better topography of the WRF model.     

Impact of spectral nudging on the downscaling of tropical cyclones in regional climate simulations

This study investigated the simulations of three months of seasonal tropical cyclone (TC) activity over the western North Pacific using the Advanced Research WRF Model. In the control experiment (CTL), the TC frequency was considerably overestimated. Additionally, the tracks of some TCs tended to have larger radii of curvature and were shifted eastward. The large-scale environments of westerly monsoon flows and subtropical Pacific highs were unreasonably simulated. The overestimated frequency of TC formation was attributed to a strengthened westerly wind field in the southern quadrants of the TC center. In comparison with the experiment with the spectral nudging method, the strengthened wind speed was mainly modulated by large-scale flow that was greater than approximately 1000 km in the model domain. The spurious formation and undesirable tracks of TCs in the CTL were considerably improved by reproducing realistic large-scale atmospheric monsoon circulation with substantial adjustment between large-scale flow in the model domain and large-scale boundary forcing modified by the spectral nudging method. The realistic monsoon circulation took a vital role in simulating realistic TCs. It revealed that, in the downscaling from large-scale fields for regional climate simulations, scale interaction between model-generated regional features and forced large-scale fields should be considered, and spectral nudging is a desirable method in the downscaling method.     

Ability of an ensemble of regional climate models to reproduce weather regimes over Europe-Atlantic during the period 1961–2000

One of the main concerns in regional climate modeling is to which extent limited-area regional climate models (RCM) reproduce the large-scale atmospheric conditions of their driving general circulation model (GCM). In this work we investigate the ability of a multi-model ensemble of regional climate simulations to reproduce the large-scale weather regimes of the driving conditions. The ensemble consists of a set of 13 RCMs on a European domain, driven at their lateral boundaries by the ERA40 reanalysis for the time period 1961–2000. Two sets of experiments have been completed with horizontal resolutions of 50 and 25 km, respectively. The spectral nudging technique has been applied to one of the models within the ensemble. The RCMs reproduce the weather regimes behavior in terms of composite pattern, mean frequency of occurrence and persistence reasonably well. The models also simulate well the long-term trends and the inter-annual variability of the frequency of occurrence. However, there is a non-negligible spread among the models which is stronger in summer than in winter. This spread is due to two reasons: (1) we are dealing with different models and (2) each RCM produces an internal variability. As far as the day-to-day weather regime history is concerned, the ensemble shows large discrepancies. At daily time scale, the model spread has also a seasonal dependence, being stronger in summer than in winter. Results also show that the spectral nudging technique improves the model performance in reproducing the large-scale of the driving field. In addition, the impact of increasing the number of grid points has been addressed by comparing the 25 and 50 km experiments. We show that the horizontal resolution does not affect significantly the model performance for large-scale circulation.     

Regional climate model projections for the State of Washington

Global climate models do not have sufficient spatial resolution to represent the atmospheric and land surface processes that determine the unique regional climate of the State of Washington. Regional climate models explicitly simulate the interactions between the large-scale weather patterns simulated by a global model and the local terrain. We have performed two 100-year regional climate simulations using the Weather Research and Forecasting (WRF) model developed at the National Center for Atmospheric Research (NCAR). One simulation is forced by the NCAR Community Climate System Model version 3 (CCSM3) and the second is forced by a simulation of the Max Plank Institute, Hamburg, global model (ECHAM5). The mesoscale simulations produce regional changes in snow cover, cloudiness, and circulation patterns associated with interactions between the large-scale climate change and the regional topography and land-water contrasts. These changes substantially alter the temperature and precipitation trends over the region relative to the global model result or statistical downscaling. To illustrate this effect, we analyze the changes from the current climate (1970–1999) to the mid twenty-first century (2030–2059). Changes in seasonal-mean temperature, precipitation, and snowpack are presented. Several climatological indices of extreme daily weather are also presented: precipitation intensity, fraction of precipitation occurring in extreme daily events, heat wave frequency, growing season length, and frequency of warm nights. Despite somewhat different changes in seasonal precipitation and temperature from the two regional simulations, consistent results for changes in snowpack and extreme precipitation are found in both simulations.     

Impacts of Spectral Nudging on the Sensitivity of a Regional Climate Model to Convective Parameterizations in East Asia

The sensitivity of a regional climate model (RCM) to cumulus parameterization (CUPA) schemes in modeling summer precipitation over East Asia has been investigated by using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (PSU-NCAR MM5). The feasibility of physical ensemble and the effect of interior (spectral) nudging are also assessed. The RCM simulations are evaluated against the NCEP/NCAR reanalysis data and NCEP/CPC precipitation data for three summers (JJA) in 1991, 1998, and 2003. The results show that the RCM is highly sensitive to CUPA schemes. Different CUPA schemes cause distinctive characteristics in the modeling of JJA precipitation and the intraseasonal (daily) variability of regional precipitation. The sensitivity of the RCM simulations to the CUPA schemes is reduced by adopting the spectral nudging technique, which enables the RCM to reproduce more realistic large-scale circulations at the upper levels of the atmosphere as well as near the surface, and better precipitation simulation in the selected experiments. The ensemble simulations using different CUPA schemes show higher skills than individual members for both control runs and spectral nudging runs. The physical ensemble adopting the spectral nudging technique shows the highest downscaling skill in capturing the general circulation patterns for all experiments and improved temporal distributions of precipitation in some regions.     

On the capability of RegCM to capture extremes in long term regional climate simulation – comparison with the observations for Czech Republic

Summary We analyze daily precipitation and temperature extremes over the Czech Republic in a regional climate simulation for the 40-year period of 1961–2000 carried out with the RegCM3 regional climate model. The model is run at 45 km grid interval and is driven by NCEP/NCAR reanalysis lateral boundary conditions. Comparison with station data shows that the model performs reasonably well in simulating the frequency of daily precipitation events of medium to high intensity as well as the precipitation intensities (return levels) of long return periods, with the exception of mountain stations. While this is attributed mainly to the relatively coarse representation of topography across the area of the Czech Republic, the parameterization of convection can be another reason. The model underestimates daily maximum temperature (especially in the warm seasons) and as a result the occurrence of heat waves (high temperature episodes). The performance of the model improves in the simulation of daily minimum temperature and cold wave events. In order to apply this regional model to the simulation of extreme events over the complex terrain as for Czech Republic we recommend that a higher resolution is used in order to better describe the topography of the Czech Republic and that the daily maximum temperature bias is reduced.     

Scale dependency of regional climate modeling of current and future climate extremes in Germany

A 26-year simulation (1980–2005) was performed with the Weather Research and Forecast (WRF) model over the Volta Basin in West Africa. This was to investigate the ability of a climate version of WRF to reproduce present day temperature and precipitation over the Volta Basin. The ERA-Interim reanalysis and one realization of the ECHAM6 global circulation model (GCM) data were dynamically downscaled using two nested domains within the WRF model. The outer domain had a horizontal resolution of 50 km and covered the whole of West Africa while the inner domain had a horizontal resolution of 10 km. It was observed that biases in the respective forcing data were carried over to the RCM, but also the RCM itself contributed to the mean bias of the model. Also, the biases in the 50-km domain were transferred unchanged, especially in the case of temperature, to the 10-km domain, but, for precipitation, the higher-resolution simulations increased the mean bias in some cases. While in general, WRF underestimated temperature in both the outer (mean biases of ?1.6 and ?2.3 K for ERA-Interim and ECHAM6, respectively) and the inner (mean biases of ?0.9 K for the reanalysis and ?1.8 K for the GCM) domains, WRF slightly underestimated precipitation in the coarser domain but overestimated precipitation in the finer domain over the Volta Basin. The performance of the GCM, in general, is good, particularly for temperature with mean bias of ?0.7 K over the outer domain. However, for precipitation, the added value of the RCM cannot be overlooked, especially over the whole West African region on the annual time scale (mean biases of ?3% for WRF and ?8% for ECHAM6). Over the whole Volta Basin and the Soudano-Sahel for the month of April and spring (MAM) rainfall, respectively, mean bias close to 0% was simulated. Biases in the interannual variability in both temperature and precipitation over the basin were smaller in the WRF than the ECHAM6. High spatial pattern correlations between 0.7 and 0.8 were achieved for the autumn precipitation and low spatial correlation in the range of 0.0 and 0.2 for the winter season precipitation over the whole basin and all the three belts over the basin.