High resolution regional climate model simulations for Germany: Part II—projected climate changes

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of ?2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.     

Mid-Holocene and Last Glacial Maximum climate simulations with the IPSL model—part I: comparing IPSL_CM5A to IPSL_CM4

The climates of the mid-Holocene (MH), 6,000 years ago, and of the Last Glacial Maximum (LGM), 21,000 years ago, have extensively been simulated, in particular in the framework of the Palaeoclimate Modelling Intercomparion Project. These periods are well documented by paleo-records, which can be used for evaluating model results for climates different from the present one. Here, we present new simulations of the MH and the LGM climates obtained with the IPSL_CM5A model and compare them to our previous results obtained with the IPSL_CM4 model. Compared to IPSL_CM4, IPSL_CM5A includes two new features: the interactive representation of the plant phenology and marine biogeochemistry. But one of the most important differences between these models is the latitudinal resolution and vertical domain of their atmospheric component, which have been improved in IPSL_CM5A and results in a better representation of the mid-latitude jet-streams. The Asian monsoon’s representation is also substantially improved. The global average mean annual temperature simulated for the pre-industrial (PI) period is colder in IPSL_CM5A than in IPSL_CM4 but their climate sensitivity to a CO₂ doubling is similar. Here we show that these differences in the simulated PI climate have an impact on the simulated MH and LGM climatic anomalies. The larger cooling response to LGM boundary conditions in IPSL_CM5A appears to be mainly due to differences between the PMIP3 and PMIP2 boundary conditions, as shown by a short wave radiative forcing/feedback analysis based on a simplified perturbation method. It is found that the sensitivity computed from the LGM climate is lower than that computed from 2 × CO₂ simulations, confirming previous studies based on different models. For the MH, the Asian monsoon, stronger in the IPSL_CM5A PI simulation, is also more sensitive to the insolation changes. The African monsoon is also further amplified in IPSL_CM5A due to the impact of the interactive phenology. Finally the changes in variability for both models and for MH and LGM are presented taking the example of the El-Niño Southern Oscillation (ENSO), which is very different in the PI simulations. ENSO variability is damped in both model versions at the MH, whereas inconsistent responses are found between the two versions for the LGM. Part 2 of this paper examines whether these differences between IPSL_CM4 and IPSL_CM5A can be distinguished when comparing those results to palaeo-climatic reconstructions and investigates new approaches for model-data comparisons made possible by the inclusion of new components in IPSL_CM5A.     

Can ensembles of regional climate model simulations improve results from sensitivity studies?

Intrinsic variability (IV) in regional climate models (RCMs) is often assumed to be small because at climatological timescales, the model solutions tend to be dominated by the model??s lateral boundary conditions. Recent studies have indicated that this IV may actually be large in certain instances for some variables. Direct interpretation of anomalies from RCM sensitivity studies relies on the assumption that differences between model simulations are entirely due to a physical forcing. However, if IV is as large or larger than the physical signal, then this assumption is violated. Using a 20 member ensemble of RCM simulations, we verify that IV of precipitation within a RCM can be large enough to violate the sensitivity study assumption, and we show that generating ensembles of simulations can help reduce the level of IV. We also present two indicators that can rule out the influence of IV when it is ambiguous whether anomalies within a sensitivity study are due to the sensitivity perturbation or whether they are due to IV.     

A new building energy model coupled with an urban canopy parameterization for urban climate simulations—part I. formulation, verification, and sensitivity analysis of the model

The generation of heat in buildings, and the way this heat is exchanged with the exterior, plays an important role in urban climate. To analyze the impact on urban climate of a change in the urban structure, it is necessary to build and use a model capable of accounting for all the urban heat fluxes. In this contribution, a new building energy model (BEM) is developed and implemented in an urban canopy parameterization (UCP) for mesoscale models. The new model accounts for: the diffusion of heat through walls, roofs, and floors; natural ventilation; the radiation exchanged between indoor surfaces; the generation of heat due to occupants and equipments; and the consumption of energy due to air conditioning systems. The behavior of BEM is compared to other models used in the thermal analysis of buildings (CBS-MASS, BLAST, and TARP) and with another box-building model. Eventually, a sensitivity analysis of different parameters, as well as a study of the impact of BEM on the UCP is carried out. The validations indicate that BEM provides good estimates of the physical behavior of buildings and it is a step towards a modeling tool that can be an important support to urban planners.     

An atmosphere–ocean regional climate model for the Mediterranean area: assessment of a present climate simulation

We present an atmosphere–ocean regional climate model for the Mediterranean basin, called the PROTHEUS system, composed by the regional climate model RegCM3 as the atmospheric component and by a regional configuration of the MITgcm model as the oceanic component. The model is applied to an area encompassing the Mediterranean Sea and compared to a stand-alone version of its atmospheric component. An assessment of the model performances is done by using available observational datasets. Despite a persistent bias, the PROTHEUS system is able to capture the inter-annual variability of seasonal sea surface temperature (SST) and also the fine scale spatio-temporal evolution of observed SST anomalies, with spatial correlation as high as 0.7 during summer. The close inspection of a 10-day strong wind event during the summer of 2000 proves the capability of the PROTHEUS system to correctly describe the daily evolution of SST under strong air–sea interaction conditions. As a consequence of the model’s skill in reproducing observed SST and wind fields, we expect a reliable estimation of air–sea fluxes. The model skill in reproducing climatological land surface fields is in line with that of state of the art regional climate models.     

Does increasing the spatial resolution of a regional climate model improve the simulated daily precipitation?

Three different resolution (50, 12, and 1.5 km) regional climate model simulations are compared in terms of their ability to simulate moderate and high daily precipitation events over the southern United Kingdom. The convection-permitting 1.5-km simulation is carried out without convective parametrisation. As in previous studies, increasing resolution (especially from 50 to 12 km) is found to improve the representation of orographic precipitation. The 50-km simulation underestimates mean precipitation over the mountainous region of Wales, and event intensity tends to be too weak; this bias is reduced in both the 12- and 1.5-km simulations for both summer and winter. In south–east England lowlands where summer extremes are mostly convective, increasing resolution does not necessary lead to an improvement in the simulation. For the 12-km simulation, simulated daily extreme events are overly intense. Even though the average intensity of summer daily extremes is improved in the 1.5-km simulation, this simulation has a poorer mean bias with too many events exceeding high thresholds. Spatial density and clustering of summer extremes in south–east England are poorly simulated in both the 12- and 1.5-km simulations. In general, we have not found any clear evidence to show that the 1.5-km simulation is superior to the 12-km simulation, or vice versa at the daily level.     

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.     

Multiyear hindcast simulations of summer monsoon over South Asia using a nested regional climate model��BCC_RegCM1.0

Multiyear (1983?C2006) hindcast simulation of summer monsoon over South Asia has been carried out using the regional climate model of the Beijing Climate Centre (BCC_RegCM1.0). The regional climate model (hereafter BCC RCM) is nested into the global climate model of the Beijing Climate Centre BCC_CGCM1.0 (here after CGCM). The regional climate model is initialized on 01 May and integrated up to the end of the September for 24?years. Compared to the driving CGCM the BCC RCM reproduces reasonably well the intensity and magnitude of the large-scale features associated with the South Asia summer monsoon such as the upper level anticyclone at 200?hPa, the mid-tropospheric warming over the Tibetan plateau, the surface heat low and the 850?hPa moisture transport from ocean to the land. Both models, i.e., BCC RCM and the driving CGCM overestimates (underestimates) the 850?hPa southwesterly flow over the northern (southern) Arabian Sea. Moreover, both models overestimate the seasonal mean precipitation over much of the South Asia region compared to the observations. However, the precipitation biases are significantly reduced in the BCC RCM simulations. Furthermore, both models simulate reasonably the interannual variability of the summer monsoon over India. The precipitation index simulated by BCC RCM shows significant correlation (0.62) with the observed one. The BCC RCM simulates reasonably well the spatial and temporal variation of the precipitation and surface air temperature compared to the driving CGCM. Further, the temperature biases are significantly reduced (1?C4°C) in the BCC RCM simulations. The simulated vertical structure of the atmosphere show biases above the four sub-regions, however, these biases are significantly reduced in the BCC RCM simulations compared to the driving CGCM. Compared to the driving CGCM, the evolution processes of the onset of summer monsoon, e.g., the meridional temperature gradient and the vertical wind shear are well simulated by the BCC RCM. The 24-year simulations also show that with a little exception the BCC RCM is capable to reproduce the monsoon active and break phases and the intraseasonal precipitation variation over the Indian subcontinent.     

Multi-century simulations with the coupled GISS–HYCOM climate model: control experiments

Multi-century climate simulations obtained with the GISS atmospheric general circulation model coupled to the hybrid-isopycnic ocean model HYCOM are described. Greenhouse gas concentrations are held fixed in these experiments to investigate the coupled model’s ability to reproduce the major features of today’s climate with minimal drift. Emphasis is placed on the realism of the oceanic general circulation and its effect on air–sea exchange processes. Several model runs using different closures for turbulent vertical exchange as well as improvements to reduce vertical numerical diffusion are compared with climate observations. As in previous studies, the Southern Ocean emerges as the Achilles Heel of the ocean model; deficiencies in its physical representation had far-reaching consequences in early experiments with the coupled model and have provided the strongest impetus for model improvement. The overarching goal of this work is to add diversity to the pool of ocean models available for climate prediction and thereby reduce biases that may stand in the way of assessing climate prediction uncertainty.

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A new Building Energy Model coupled with an Urban Canopy Parameterization for urban climate simulations—part II. Validation with one dimension off-line simulations

Recent studies show that the fluxes exchanged between buildings and the atmosphere play an important role in the urban climate. These fluxes are taken into account in mesoscale models considering new and more complex Urban Canopy Parameterizations (UCP). A standard methodology to test an UCP is to use one-dimensional (1D) off-line simulations. In this contribution, an UCP with and without a Building Energy Model (BEM) is run 1D off-line and the results are compared against the experimental data obtained in the BUBBLE measuring campaign over Basel (Switzerland) in 2002. The advantage of BEM is that it computes the evolution of the indoor building temperature as a function of energy production and consumption in the building, the radiation coming through the windows, and the fluxes of heat exchanged through the walls and roofs as well as the impact of the air conditioning system. This evaluation exercise is particularly significant since, for the period simulated, indoor temperatures were recorded. Different statistical parameters have been calculated over the entire simulated episode in order to compare the two versions of the UCP against measurements. In conclusion, with this work, we want to study the effect of BEM on the different turbulent fluxes and exploit the new possibilities that the UCP–BEM offers us, like the impact of the air conditioning systems and the evaluation of their energy consumption.     

Does the model regional bias affect the projected regional climate change? An analysis of global model projections

An analysis is presented of the dependence of the regional temperature and precipitation change signal on systematic regional biases in global climate change projections. The CMIP3 multi-model ensemble is analyzed over 26 land regions and for the A1B greenhouse gas emission scenario. For temperature, the model regional bias has a negligible effect on the projected regional change. For precipitation, a significant correlation between change and bias is found in about 30% of the seasonal/regional cases analyzed, covering a wide range of different climate regimes. For these cases, a performance-based selection of models in producing climate change scenarios can affect the resulting change estimate, and it is noted that a minimum of four to five models is needed to obtain robust precipitation change estimates. In a number of cases, models with largely different precipitation biases can still produce changes of consistent sign. Overall, it is assessed that in the present generation of models the regional bias does not appear to be a dominant factor in determining the simulated regional change in the majority of cases.     

Validating a regional climate model’s downscaling ability for East Asian summer monsoonal interannual variability

Performance of a regional climate model (RCM), WRF, for downscaling East Asian summer season climate is investigated based on 11-summer integrations associated with different climate conditions with reanalysis data as the lateral boundary conditions. It is found that while the RCM is essentially unable to improve large-scale circulation patterns in the upper troposphere for most years, it is able to simulate better lower-level meridional moisture transport in the East Asian summer monsoon. For precipitation downscaling, the RCM produces more realistic magnitude of the interannual variation in most areas of East Asia than that in the reanalysis. Furthermore, the RCM significantly improves the spatial pattern of summer rainfall over dry inland areas and mountainous areas, such as Mongolia and the Tibetan Plateau. Meanwhile, it reduces the wet bias over southeast China. Over Mongolia, however, the performance of precipitation downscaling strongly depends on the year: the WRF is skillful for normal and wet years, but not for dry years, which suggests that land surface processes play an important role in downscaling ability. Over the dry area of North China, the WRF shows the worst performance. Additional sensitivity experiments testing land effects in downscaling suggest the initial soil moisture condition and representation of land surface processes with different schemes are sources of uncertainty for precipitation downscaling. Correction of initial soil moisture using the climatology dataset from GSWP-2 is a useful approach to robustly reducing wet bias in inland areas as well as to improve spatial distribution of precipitation. Despite the improvement on RCM downscaling, regional analyses reveal that accurate simulation of precipitation over East China, where the precipitation pattern is strongly influenced by the activity of the Meiyu/Baiu rainfall band, is difficult. Since the location of the rainfall band is closely associated with both lower-level meridional moisture transport and upper-level circulation structures, it is necessary to have realistic upper-air circulation patterns in the RCM as well as lower-level moisture transport in order to improve the circulation-associated convective rainfall band in East Asia.     

COSMO-CLM (CCLM) climate simulations over CORDEX-Africa domain: analysis of the ERA-Interim driven simulations at 0.44° and 0.22° resolution

We present the results of the application of the COSMO-CLM Regional Climate Model (CCLM) over the CORDEX-Africa domain. Two simulations were performed driven by the ERA-Interim reanalysis (1989–2008): the first one with the standard CORDEX spatial resolution (0.44°), and the second one with an unprecedented high resolution (0.22°). Low-level circulation and its vertical structure, the geographical and temporal evolution of temperature and precipitation are critically evaluated, together with the radiation budget and surface energy fluxes. CCLM is generally able to reproduce the overall features of the African climate, although some deficiencies are evident. Flow circulation is generally well simulated, but an excessive pressure gradient is present between the Gulf of Guinea and the Sahara, related to a marked warm bias over the Sahara and a cold bias over southern Sahel. CCLM underestimates the rainfall peak in the regions affected by the passage of the monsoon. This dry bias may be a consequence of two factors, the misplacement of the monsoon centre and the underestimation of its intensity. The former is related to the northern shift of the West African Heat Low. On the other hand, the underestimation of precipitation intensity may be related to the underestimation of the surface short-wave radiation and latent heat flux. The increase of the model resolution does not bring evident improvements to the results for monthly means statistics. As a result, it appears that 0.44° is a suitable compromise between model performances and computational constrains.     

Application of a “Big-Tree” model to regional climate modeling: a sensitivity study

Summary ¶In order to better understand land-atmosphere interactions and increase the predictability of climate models, it is important to investigate the role of forest representation in climate modeling. Corresponding to the big-leaf model commonly employed in land surface schemes to represent the effects of a forest, a so called big-tree model, which uses multi-layer vegetation to represent the vertical canopy heterogeneity, was introduced and incorporated into the National Center for Atmospheric Research (NCAR) regional climate model RegCM2, to make the vegetation model more physically based. Using this augmented RegCM2 and station data for China during 1991 Meiyu season, we performed 10 experiments to investigate the effects of the application of the big-tree model on the summer monsoon climate.With the big-tree model incorporated into the regional climate model, some climate characteristics, e.g. the 3-month-mean surface temperature, circulation, and precipitation, are significantly and systematically changed over the model domain, and the change of the characteristics differs depending on the area. Due to the better representation of the shading effect in the big-tree model, the temperature of the lower layer atmosphere above the plant canopy is increased, which further influences the 850hPa temperature. In addition, there are significant decreases in the mean latent heat fluxes (within 20–30W/m²) in the three areas of the model domain.The application of the big-tree model influences not only the simulated climate of the forested area, but also that of the whole model domain, and its impact is greater on the lower atmosphere than on the upper atmosphere. The simulated rainfall and surface temperature deviate from the originally simulated result and are (or seem to be) closer to the observations, which implies that an appropriate representation of the big-tree model may improve the simulation of the summer monsoon climate.We also find that the simulated climate is sensitive to some big-tree parameter values and schemes, such as the shape, height, zero-plane displacement height and mixing-length scheme. The simulated local/grid differences may be very large although the simulated areal-average differences may be much lower. The area-average differences in the monthly-mean surface temperature and heat fluxes can amount to 0.5°C and 4W/m², respectively, which correspond to maximum local/grid differences of 3.0°C and 40W/m² respectively. It seems that the simulated climate is most sensitive to the parameter of the zero-plane displacement among the parameters studied.     

Impact of soil moisture�Catmosphere coupling on European climate extremes and trends in a regional climate model

Processes acting at the interface between the land surface and the atmosphere have a strong impact on the European summer climate, particularly during extreme years. These processes are to a large extent associated with soil moisture (SM). This study investigates the role of soil moisture?Catmosphere coupling for the European summer climate over the period 1959?C2006 using simulations with a regional climate model. The focus of this study is set on temperature and precipitation extremes and trends. The analysis is based on simulations performed with the regional climate model CLM, driven with ECMWF reanalysis and operational analysis data. The set of experiments consists of a control simulation (CTL) with interactive SM, and sensitivity experiments with prescribed SM: a dry and a wet run to determine the impact of extreme values of SM, as well as experiments with lowpass-filtered SM from CTL to quantify the impact of the temporal variability of SM on different time scales. Soil moisture?Cclimate interactions are found to have significant effects on temperature extremes in the experiments, and impacts on precipitation extremes are also identified. Case studies of selected major summer heat waves reveal that the intraseasonal and interannual variability of SM account for 5?C30% and 10?C40% of the simulated heat wave anomaly, respectively. For extreme precipitation events on the other hand, only the wet-day frequency is impacted in the experiments with prescribed soil moisture. Simulated trends for the past decades, which appear consistent with projected changes for the 21st century, are identified to be at least partly linked to SM-atmosphere feedbacks.     

A scaling analysis of soil moisture–precipitation interactions in a regional climate model

The University of Oklahoma’s Advanced Regional Prediction System (ARPS) was used to examine the impacts of varying mean soil moisture and model resolution on the magnitude and frequency of precipitation events in the U.S. Central Plains and to determine whether modeled soil moisture and precipitation fields exhibit scale invariance using the statistical moments. It was found that high soil moisture resulted in greater precipitation amounts and a higher frequency of events, suggesting the occurrence of a positive soil moisture–precipitation feedback. The scaling analysis performed on cumulative precipitation determined that these fields did not exhibit signs of self-similarity and, therefore, statistical properties cannot be predicted at other resolutions. The scaling properties of soil moisture were highly variable in time which has important implications for the use of remotely sensed data, as scaling properties from 1 day cannot necessarily be applied to subsequent days.     

Comment on “application of the Canadian regional climate model to the Laurentian Great Lakes region: Implementation of a lake model”

Abstract

A recently published slab model formulation of lake thermodynamics (Goyette et al., 2000), including an empirical factor to adjust the incoming heat flux so that the modelled lake surface temperature agrees with observed climatology, leads to a distinct lack of energy conservation. The empirical adjustment conceptually represents an exchange of heat between the mixed‐layer water (the slab that is explicitly simulated in the model) and deeper layers of water. It ensures a realistic temporal progression of temperature in the mixed layer, but the thermodynamic balance of the deeper water is not considered. When the deeper water is considered, it is found that the empirical adjustment accounts for the entire heat input to the deeper water, and on an annual mean basis, it is considerably unbalanced. This reveals a flaw in this model concept and, although not entirely invalidating the model, it needs to be included as a caveat in its use.     

Projected climate change scenario over California by a regional ocean–atmosphere coupled model system

This study examines a future climate change scenario over California in a 10-km coupled regional downscaling system of the Regional Spectral Model for the atmosphere and the Regional Ocean Modeling System for the ocean forced by the global Community Climate System Model version 3.0 (CCSM3). In summer, the coupled and uncoupled downscaled experiments capture the warming trend of surface air temperature, consistent with the driving CCSM3 forcing. However, the surface warming change along the California coast is weaker in the coupled downscaled experiment than it is in the uncoupled downscaling. Atmospheric cooling due to upwelling along the coast commonly appears in both the present and future climates, but the effect of upwelling is not fully compensated for by the projected large-scale warming in the coupled downscaling experiment. The projected change of extreme warm events is quite different between the coupled and uncoupled downscaling experiments, with the former projecting a more moderate change. The projected future change in precipitation is not significantly different between coupled and uncoupled downscaling. Both the coupled and uncoupled downscaling integrations predict increased onshore sea breeze change in summer daytime and reduced offshore land breeze change in summer nighttime along the coast from the Bay area to Point Conception. Compared to the simulation of present climate, the coupled and uncoupled downscaling experiments predict 17.5 % and 27.5 % fewer Catalina eddy hours in future climate respectively.     

Evaluation of a climate simulation in Europe based on the WRF–NOAH model system: precipitation in Germany

The Weather Research and Forecast (WRF) model with its land surface model NOAH was set up and applied as regional climate model over Europe. It was forced with the latest ERA-interim reanalysis data from 1989 to 2008 and operated with 0.33° and 0.11° resolution. This study focuses on the verification of monthly and seasonal mean precipitation over Germany, where a high quality precipitation dataset of the German Weather Service is available. In particular, the precipitation is studied in the orographic terrain of southwestern Germany and the dry lowlands of northeastern Germany. In both regions precipitation data is very important for end users such as hydrologists and farmers. Both WRF simulations show a systematic positive precipitation bias not apparent in ERA-interim and an overestimation of wet day frequency. The downscaling experiment improved the annual cycle of the precipitation intensity, which is underestimated by ERA-interim. Normalized Taylor diagrams, i.e., those discarding the systematic bias by normalizing the quantities, demonstrate that downscaling with WRF provides a better spatial distribution than the ERA interim precipitation analyses in southwestern Germany and most of the whole of Germany but degrades the results for northeastern Germany. At the applied model resolution of 0.11°, WRF shows typical systematic errors of RCMs in orographic terrain such as the windward–lee effect. A convection permitting case study set up for summer 2007 improved the precipitation simulations with respect to the location of precipitation maxima in the mountainous regions and the spatial correlation of precipitation. This result indicates the high value of regional climate simulations on the convection-permitting scale.     

Multi-decadal scenario simulation over Korea using a one-way double-nested regional climate model system. Part 2: future climate projection (2021–2050)

An analysis of simulated future surface climate change over the southern half of Korean Peninsula using a RegCM3-based high-resolution one-way double-nested system is presented. Changes in mean climate as well as the frequency and intensity of extreme climate events are discussed for the 30-year-period of 2021–2050 with respect to the reference period of 1971–2000 based on the IPCC SRES B2 emission scenario. Warming in the range of 1–4°C is found throughout the analysis region and in all seasons. The warming is maximum in the higher latitudes of the South Korean Peninsula and in the cold season. A large reduction in snow depth is projected in response to the increase of winter minimum temperature induced by the greenhouse warming. The change in precipitation shows a distinct seasonal variation and a substantial regional variability. In particular, we find a large increase of wintertime precipitation over Korea, especially in the upslope side of major mountain systems. Summer precipitation increases over the northern part of South Korea and decreases over the southern regions, indicating regional diversity. The precipitation change also shows marked intraseasonal variations throughout the monsoon season. The temperature change shows a positive trend throughout 2021–2050 while the precipitation change is characterized by pronounced interdecadal variations. The PDF of the daily temperature is shifted towards higher values and is somewhat narrower in the scenario run than the reference one. The number of frost days decreases markedly and the number of hot days increases. The regional distribution of heavy precipitation (over 80 mm/day) changes considerably, indicating changes in flood vulnerable regions. The climate change signal shows pronounced fine scale signal over Korea, indicating the need of high-resolution climate simulations