RCM Simulations Research Articles

Atmosphere-Cryosphere Coupled Model for Regional Climate Applications

There have been significant advances in our understanding of the climate system, but two major problems still exist in modeling atmospheric response during cold seasons: (a) lack of detailed physical description of snow and frozen soil in the land-surface schemes and (b) insufficient understanding of regional climate response from the cryosphere. A multilayer snow land-surface model based on the conservations of heat and water substance inside the soil and snow is coupled to an atmospheric RCM, to investigate the effect of snow, snowmelt, and soil frost on the atmosphere during cold seasons. The coupled RCM shows much improvement in moisture and temperature simulation for March-April of 1997 compared to simple parameterizations used in GCMs. The importance of such processes in RCM simulation is more pronounced in mid-to-high latitudes during the transition period (winter–spring) affected by changes in surface energy and the hydrological cycle. The effect of including cryosphere physics through snow-albedo feedback mechanism changes the meridional temperature gradients and in turn changes the location of weather systems passing over the region. The implications from our study suggest that, to reduce the uncertainties and better assess the impacts of climate change, RCM simulations should include the detailed snow and frozen soil processes.

Resolution dependence in simulating the African hydroclimate with the HadGEM3-RA regional climate model

This study documents the effect of horizontal resolution on the ability of the Met Office third-generation Global Atmosphere Regional Climate Model (HadGEM3-RA), a regional atmospheric configuration of the HadGEM3 model, to simulate rainfall variability over Africa. It is based on six 20-year long RCM simulations driven by ERA-Interim reanalysis and performed at 12, 25, 50, 70, 90, and 150 km over the CORDEX-Africa domain. To gain further insight into model errors, we also compared the HadGEM3-RA’s performance to that of the parent General Circulation Model using three different spatial resolutions (70, 100, and 150 km), and to HadRM3P—the current Met Office regional climate model. It is found that the 50 km resolution RCM reproduces reasonably the spatial and temporal features of rainfall variability across regions. These include the seasonal progression of the tropical rainbelt, its extent and location, the annual cycle and interannual variability. Although model biases vary across seasons and locations, a prominent feature is the over-prediction of rainfall totals over Central Africa, and underestimation of rainfall in coastal areas of the Guinea Gulf during boreal spring and autumn. HadGEM3-RA improves with increased horizontal resolution, but some model errors persist. Comparison with the parent global model simulations demonstrates generally a realistic and consistent behaviour over large scales—suggesting that the physical formulation is able to capture the key driving processes, but also confirms the benefit of increasing the model horizontal resolution. Despite the model errors, HadGEM3-RA rainfall shows superiority over that from HadRM3P, ERA-Interim and MERRA datasets—indicating that the associated dynamical features of HadGEM3-RA can complement the physical understanding gained from reanalyses. This article also highlights the challenges for evaluating climate models in data sparse regions where satellite derived rainfall and gridded observational datasets often diverge.

Application of a hydrometeorological model chain to investigate the effect of global boundaries and downscaling on simulated river discharge

In the current study, two regional climate models (MM5 and REMO) driven by different global boundary conditions (the ERA40 reanalysis and the ECHAM5 model) are one-way coupled to the uncalibrated hydrological process model PROMET to analyze the impact of global boundary conditions, dynamical regionalization and subsequent statistical downscaling (bilinear interpolation, correction of subgrid-scale variability and combined correction of subgrid-scale variability and bias) on river discharge simulation. The results of 12 one-way coupled model runs, set up for the catchment of the Upper Danube (Central Europe) over the historical period 1971–2000, prove the expectation that the global boundaries applied to force the RCMs strongly influence the accuracy of simulated river discharge. It is, however, noteworthy that all efficiency criteria in case of bias corrected MM5 simulations indicate better performance under ERA40 boundaries, whereas REMO-driven hydrological simulations better correspond to measured discharge under ECHAM5 boundaries. Comparing the hydrological results achievable with MM5 and REMO, the application of bias-corrected MM5 simulations turned out to allow for a more accurate simulation of discharge, while the variance in simulated discharge in most cases was better reflected in case of REMO forcings. The correction of subgrid-scale variability within the downscaling of RCM simulations compared to a bilinear interpolation allows for a more accurate simulation of discharge for all model configurations and all discharge criteria considered (mean monthly discharge, mean monthly low-flow and peak-flow discharge). Further improvements in the hydrological simulations could be achieved by eliminating the biases (in terms of deviations from observed meteorological conditions) inherent in the driving RCM simulations, regardless of the global boundary conditions or the RCM applied. In spite of all downscaling and bias correction efforts described, the RCM-driven hydrological simulations remain less accurate than those achievable with spatially distributed meteorological observations.

Evaluation of the twenty-first century RCM simulations driven by multiple GCMs over the Eastern Mediterranean–Black Sea region

In this study, human-induced climate change over the Eastern Mediterranean–Black Sea region has been analyzed for the twenty-first century by performing regional climate model simulations forced with large-scale fields from three different global circulation models (GCMs). Climate projections have been produced with Special Report on Emissions Scenarios A2, A1FI and B1 scenarios, which provide greater diversity in climate information for future period. The gradual increases for temperature are widely apparent during the twenty-first century for each scenario simulation, but ECHAM5-driven simulation generally has a weaker signal for all seasons compared to CCSM3 simulations except for the Fertile Crescent. The contrast in future temperature change between the winter and summer seasons is very strong for CCSM3-A2-driven and HadCM3-A2-driven simulations over Carpathians and Balkans, 4–5 °C. In addition, winter runoff over mountainous region of Turkey, which feeds many river systems including the Euphrates and Tigris, increases in second half of the century since the snowmelt process accelerates where the elevation is higher than 1,500 m. Moreover, analysis of daily temperature outputs reveals that the gradual decrease in daily minimum temperature variability for January during the twenty-first century is apparent over Carpathians and Balkans. Analysis of daily precipitation extremes shows that positive trend is clear during the last two decades of the twenty-first century over Carpathians for both CCSM3-driven and ECHAM5-driven simulations. Multiple-GCM driven regional climate simulations contribute to the quantification of the range of climate change over a region by performing detailed comparisons between the simulations.

Projecting future drought in Mediterranean forests: bias correction of climate models matters!

Global and regional climate models (GCM and RCM) are generally biased and cannot be used as forcing variables in ecological impact models without some form of prior bias correction. In this study, we investigated the influence of the bias correction method on drought projections in Mediterranean forests in southern France for the end of the twenty-first century (2071–2100). We used a water balance model with two different atmospheric climate forcings built from the same RCM simulations but using two different correction methods (quantile mapping or anomaly method). Drought, defined here as periods when vegetation functioning is affected by water deficit, was described in terms of intensity, duration and timing. Our results showed that the choice of the bias correction method had little effects on temperature and global radiation projections. However, although both methods led to similar predictions of precipitation amount, they induced strong differences in their temporal distribution, especially during summer. These differences were amplified when the climatic data were used to force the water balance model. On average, the choice of bias correction leads to 45 % uncertainty in the predicted anomalies in drought intensity along with discrepancies in the spatial pattern of the predicted changes and changes in the year-to-year variability in drought characteristics. We conclude that the choice of a bias correction method might have a significant impact on the projections of forest response to climate change.

Reply to “Comments on ‘The North American Regional Climate Change Assessment Program: Overview of Phase I Results'”

The authors of Mearns et al. (2012) are well aware of the role of driving RCMs with reanalyses and have written extensively on the roles of different types of RCM simulations (e.g., Giorgi and Mearns, 1999; Leung et al., 2003). Thus, we agree that the skill of dynamical downscaling in which global reanalysis is used to provide boundary conditions in general indicates an upper bound of skill compared to dynamical downscaling in which the boundary conditions come from global climate model simulations. This finding has long been established as global climate model simulations cannot outperform global reanalysis in providing boundary conditions since the latter is constrained by observations through data assimilation (that is unless the reanalyses themselves have been shown to have serious deficiences, e.g. Cerezo-Mota et al, 2011). The classification of different types of dynamical downscaling introduced by Castro et al. (2005) further adds clarity to this point.

Historical and future changes in maximum and minimum temperature records over Europe

Recent studies examining changes in temperature record frequency over the continental United States have reported that the number of Tmax records has been increasing over the past 50 years and occurring at twice the frequency of Tmin records. In a stationary climate, the number of records should decrease with time as 1/n, where n is the number of years of record-keeping. Here we seek to understand how European temperature records have changed during the late 20th century and how they are expected to change as greenhouse gases increase during the 21st century, using a new ensemble method to filter out the effect of the starting year in the calculation of the records. We find that until 1980, the ratio of Tmax to Tmin records remains close to one, indicating that the climate was relatively stationary. After 1980, there is a distinct positive trend where the observed ratio averages around four during the early part of the 21st century, indicative of a warming trend. We note considerable spatial variability in the observations. Further, the ratio of Tmax to Tmin records set by the year 2100 as simulated by five RCM simulations reaches values of up to several hundred by the end of the 21st century. However, the changes in record frequency vary spatially over Europe. The models project the highest numbers of Tmax records over the Mediterranean during summer, and Scandinavia during the spring and fall. Tmin records decrease most substantially over eastern Europe and western Russia, and the Mediterranean. Our analysis confirms the value of the use of maximum and minimum temperature records in regional climate change studies.

Canadian RCM projected changes to short‐ and long‐term drought characteristics over the Canadian Prairies

AbstractThe Canadian Prairies have experienced severe and extended droughts that have had significant impacts on agriculture, energy and other socio‐economic sectors; it is therefore desirable to assess future changes to drought characteristics in this drought prone region, in the context of a changing climate. This study addresses validation and projected changes to short‐ and long‐term drought characteristics, i.e. severity, frequency and duration, over the Canadian Prairies, using an ensemble of ten Canadian RCM (CRCM) simulations, of which five correspond to the current 1971–2000 period and the other five are the matching simulations for the future 2041–2070 period. These five pairs of current and future CRCM simulations were driven by five different members of a Canadian Global Climate Model ensemble. Validation of CRCM simulated precipitation suggests that the model reproduces the observed precipitation distribution for all seasons, except summer, across a large portion of the Canadian Prairies. However, comparison of CRCM simulated drought characteristics with those observed suggests that the model has difficulties in reproducing observed severity, frequency and duration of drought events, particularly those associated with longer events, possibly due to the overestimation of summer precipitation by the model. Analysis of projected changes to precipitation and drought characteristics between the 1971–2000 and 2041–2070 periods suggests a decrease in mean precipitation in summer and an increase for the other seasons, while the severity, frequency and maximum duration of both short‐ and long‐term droughts are projected to increase over the southern Prairies, with the largest projected changes associated with longer drought events. Classification of the watersheds spanning the southern Prairies based on changes to both severity and frequency further reveal the vulnerability of this region in a changing climate. Copyright © 2012 Royal Meteorological Society

Internal Variability of the Canadian RCM’s Hydrological Variables at the Basin Scale in Quebec and Labrador

Abstract The effect of a regional climate model’s (RCM’s) internal variability (IV) on climate statistics of annual series of hydrological variables is investigated at the scale of 21 eastern Canada watersheds in Quebec and Labrador. The analysis is carried out on 30-yr pairs of simulations (twins), performed with the Canadian Regional Climate Model (CRCM) for present (reanalysis and global climate model driven) and future (global climate model driven) climates. The twins differ only by the starting date of the regional simulation—a standard procedure used to trigger internal variability in RCMs. Two different domain sizes are considered: one comparable to domains used for RCM simulations over Europe and the other comparable to domains used for North America. Results for the larger North American domain indicate that mean relative differences between twin pairs of 30-yr climates reach ±5% when spectral nudging is used. Larger differences are found for extreme annual events, reaching about ±10% for 10% and 90% quantiles (Q10 and Q90). IV is smaller by about one order of magnitude in the smaller domain. Internal variability is unaffected by the period (past versus future climate) and by the type of driving data (reanalysis versus global climate model simulation) but shows a dependence on watershed size. When spectral nudging is deactivated in the large domain, the relative difference between pairs of 30-yr climate means almost doubles and approaches the magnitude of a global climate model’s internal variability. This IV at the level of the natural climate variability has a profound impact on the interpretation, analysis, and validation of RCM simulations over large domains.

Uncertainties in monsoon precipitation projections over China: results from two high-resolution RCM simulations

Uncertainties in monsoon precipitation projections over China: results from two high-resolution RCM simulations

The uncertainty of UTCI due to uncertainties in the determination of radiation fluxes derived from numerical weather prediction and regional climate model simulations

In this study we examine the determination accuracy of both the mean radiant temperature (Tmrt) and the Universal Thermal Climate Index (UTCI) within the scope of numerical weather prediction (NWP), and global (GCM) and regional (RCM) climate model simulations. First, Tmrt is determined and the so-called UTCI-Fiala model is then used for the calculation of UTCI. Taking into account the uncertainties of NWP model (among others the HIgh Resolution Limited Area Model HIRLAM) output (temperature, downwelling short-wave and long-wave radiation) stated in the literature, we simulate and discuss the uncertainties of Tmrt and UTCI at three stations in different climatic regions of Europe. The results show that highest negative (positive) differences to reference cases (under assumed clear-sky conditions) of up to -21°C (9°C) for Tmrt and up to -6°C (3.5°C) for UTCI occur in summer (winter) due to cloudiness. In a second step, the uncertainties of RCM simulations are analyzed: three RCMs, namely ALADIN (Aire Limitée Adaptation dynamique Développement InterNational), RegCM (REGional Climate Model) and REMO (REgional MOdel) are nested into GCMs and used for the prediction of temperature and radiation fluxes in order to estimate Tmrt and UTCI. The inter-comparison of RCM output for the three selected locations shows that biases between 0.0 and ±17.7°C (between 0.0 and ±13.3°C) for Tmrt (UTCI), and RMSE between ±0.5 and ±17.8°C (between ±0.8 and ±13.4°C) for Tmrt (UTCI) may be expected. In general the study shows that uncertainties of UTCI, due to uncertainties arising from calculations of radiation fluxes (based on NWP models) required for the prediction of Tmrt, are well below ±2°C for clear-sky cases. However, significant higher uncertainties in UTCI of up to ±6°C are found, especially when prediction of cloudiness is wrong.

Projection of Water Availability in the Miyun Watershed from an RCM Simulation

AbstractBased on a high-resolution regional climate model (RegCM3) simulation over East Asia, future climate changes over the Miyun Reservoir in the 21st century under the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario are analyzed. The model simulation extends from 1951 to 2100 at a grid spacing of 25 km and is one-way nested within a global model of MIROC3.2_ hires (the Model for Interdisciplinary Research on Climate). The focus of the analysis is on the Watershed of Miyun Reservoir, the main water supply for Beijing in northern China. The results show that RegCM3 reproduces the observed temperature well but it overestimates precipitation over the region. Significant warming in the 21st century is simulated in the annual mean, December-January-February (DJF) and June-July-August (JJA), although with differences concerning the spatial distribution and magnitude. Changes in precipitation for the annual mean, DJF, and JJA also show differences. A ...

ANALYSIS OF PROJECTED CLIMATE CHANGE FOR HUNGARY USING ENSEMBLES SIMULATIONS

In order to estimate the future regional climate change for the Carpathian Basin located in Central/Eastern Europe, outputs from several RCMs (from the completed European project ENSEMBLES) are summarized and analyzed using the SRES A1B scenario. Composite maps of the projected annual and seasonal temperature and precipitation changes are generated using RCM simulations (with 25 km spatial resolution) for the reference period 1961-1990, and the target periods 2021-2050, 2071-2100. Overall, the results suggest significant warming in Hungary. Projected seasonal warming is 1-3 °C, and 2-6 °C for 2021-2050, and 2071-2100, respectively. The largest temperature increase is likely to occur in summer. In case of precipitation, the annual sum is not likely to change significantly in the region. However, the summer precipitation is projected to decrease significantly during the 21st century, autumn and winter precipitation amounts are projected to increase.

Arctic RCM simulations of temperature and precipitation derived indices relevant to future frozen ground conditions

A regional climate model with high horizontal resolution (25 km) is used to downscale 20-year-long time slices of present-day (1980–1999) and future (2046–2065, 2080–2099) Arctic climate, as simulated by the ECHAM5/MPI-OM general circulation model under the A1B emission scenario. Changes in simulated air temperature and derived indices at the end of the century indicate that significant impacts on permafrost conditions should be expected. But the magnitude of the change is regionally conditioned beyond what is obvious: Warm permafrost in the sporadic to discontinuous zone is threatened and may degrade or even complete thaw before the end of the century. A decrease in freezing and increase in thawing degree-days is interpreted as potential decrease in seasonal freeze depth and increase in active layer thickness (ALT). We show that for some regions increasing maximum summer temperature is associated with an increase of interannual temperature variability in summer, while in other regions decreased maximum summer temperatures are related to decreased variability. The occurrence of warm/cold summers and spells changes significantly in the future time slices using the present-day criteria for classification. Taken together this implies a regionally varying exposure to significant change in permafrost conditions. In addition to these aspects of the general warming trend that would promote an increase in ALT and a northward shift of the southern permafrost boundary, an analysis of the occurrence of warm summers and spells highlight some particularly vulnerable regions for permafrost degradation (e.g. West Siberian Plain, Laptev Sea coast, Canadian Archipelago), but also some less vulnerable regions (e.g. Mackenzie Mountains).

The future of dry and wet spells in Europe: a comprehensive study based on the ENSEMBLES regional climate models

AbstractUnder the aspect of future climate change, it is important for decision makers to know how drought conditions might change on the regional scale in order to map out adequate adaptation and mitigation strategies. Recent RCM simulations provided by the ENSEMBLES project are used to analyse changes in dry and wet conditions in Europe by the mid of the 21st century under the A1B emission scenario. Eight RCMs are selected to capture the uncertainties of the projected changes. An empirical statistical error correction approach is applied to modelled daily mean air temperature and precipitation amount to account for RCM errors, and commonly used drought indices—the Standardized Precipitation Index (SPI), the self calibrated Palmer Z‐Index (scZI) and Palmer Drought Severity Index (scPDSI)—are calculated. Changes in the mean, in interannual variability, and in frequency, length, distance, magnitude, and area of dry and wet events are investigated. The statistical significance of the projected multi‐model mean changes and the according uncertainties are analysed for nine European subregions. Furthermore, distributional changes of the dry and wet spell characteristics are assessed. Changes in the mean, and in dry and wet event characteristics show the most pronounced changes towards drier and wetter conditions in the southern‐ and northernmost European subregions, respectively. Here, the changes are highly significant and confident, while the projected changes are more dissonant for the other subregions. Severe changes in the extremes of event length, distance, magnitude, and area particularly arise in the southern‐ and northernmost European subregions. The projected changes in interannual variability are less significant and confident. However, significantly increasing interannual variability is projected in regions with pronounced changes in the mean towards wetter as well as towards drier conditions. Copyright © 2011 Royal Meteorological Society

Copula-based statistical refinement of precipitation in RCM simulations over complex terrain

Abstract. This paper presents a new Copula-based method for further downscaling regional climate simulations. It is developed, applied and evaluated for selected stations in the alpine region of Germany. Apart from the common way to use Copulas to model the extreme values, a strategy is proposed which allows to model continuous time series. As the concept of Copulas requires independent and identically distributed (iid) random variables, meteorological fields are transformed using an ARMA-GARCH time series model. In this paper, we focus on the positive pairs of observed and modelled (RCM) precipitation. According to the empirical copulas, significant upper and lower tail dependence between observed and modelled precipitation can be observed. These dependence structures are further conditioned on the prevailing large-scale weather situation. Based on the derived theoretical Copula models, stochastic rainfall simulations are performed, finally allowing for bias corrected and locally refined RCM simulations.

Future changes in European winter storm losses and extreme wind speeds inferred from GCM and RCM multi-model simulations

Abstract. Extreme wind speeds and related storm loss potential in Europe have been investigated using multi-model simulations from global (GCM) and regional (RCM) climate models. Potential future changes due to anthropogenic climate change have been analysed from these simulations following the IPCC SRES A1B scenario. The large number of available simulations allows an estimation of the robustness of detected future changes. All the climate models reproduced the observed spatial patterns of wind speeds, although some models displayed systematic biases. A storm loss model was applied to the GCM and RCM simulated wind speeds, resulting in realistic mean loss amounts calculated from 20th century climate simulations, although the inter-annual variability of losses is generally underestimated. In future climate simulations, enhanced extreme wind speeds were found over northern parts of Central and Western Europe in most simulations and in the ensemble mean (up to 5%). As a consequence, the loss potential is also higher in these regions, particularly in Central Europe. Conversely, a decrease in extreme wind speeds was found in Southern Europe, as was an associated reduction in loss potential. There was considerable spread in the projected changes of individual ensemble members, with some indicating an opposite signature to the ensemble mean. Downscaling of the large-scale simulations with RCMs has been shown to be an important source of uncertainty. Even RCMs with identical boundary forcings can show a wide range of potential changes. The robustness of the projected changes was estimated using two different measures. First, the inter-model standard deviation was calculated; however, it is sensitive to outliers and thus displayed large uncertainty ranges. Second, a multi-model combinatorics approach considered all possible sub-ensembles from GCMs and RCMs, hence taking into account the arbitrariness of model selection for multi-model studies. Based on all available GCM and RCM simulations, for example, a 25% mean increase in risk of loss for Germany has been estimated for the end of the 21st century, with a 90% confidence range of +15 to +35%.

Diagnostic study of the influence of lateral boundary conditions for the REMO RCM simulations over the Carpathian Basin

Abstract. At the Hungarian Meteorological Service, two experiments were accomplished with the REMO5.0 regional climate model: (1) a simulation of a past period from 1961 to 2000, driven by the ECMWF ERA40 re-analysis data, and (2) a transient run from 1951 to 2100 driven by the ECHAM5/MPI-OM global coupled atmosphere-ocean model using SRES A1B forcing. The integration domain covers continental Europe with 25 km horizontal resolution in both experiments. Present article is dedicated to the investigation of the simulation results for the past period. The results for 1961–1990 were compared on the one hand with observations, and on the other hand, with each other and the corresponding global fields in order to assess the impact of the different lateral boundary conditions on the results focusing on the area of our interest, i.e., Hungary. The evaluation indicated that the re-analysis driven experiment provides warm and in summer dry past climate over the Carpathian Basin, whereas lower temperature and higher precipitation values are obtained when the lateral boundary information is derived from a global climate model. Based on the validation, it is concluded that the temperature characteristics in the simulation-driven case outperformed the experiment forced by quasi-perfect (i.e., re-analysis) data, however, similar apparent conclusion cannot be drawn for precipitation. This paper is undertaking to give deeper insight into the details and possible reasons for these outcomes.

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

Multiyear (1983–2006) 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 (1–4°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.

Hydroclimatological response to dynamically downscaled climate change simulations for Korean basins

We investigated the hydrological response to climate change simulations for three basins in South Korea. To provide fine-scale climate information to the PRMS hydrological model, an ECHO-G B2 simulation was dynamically downscaled using the RegCM3 double-nested system implementing two different convection schemes, namely, the Grell and the MIT-Emanuel (EMU) schemes. The daily minimum and maximum temperatures and precipitation from the nested domain for a grid spacing of 20 km are used as the input for the PRMS run. Two sets of multi-decadal simulations are performed over a reference period (1971–2000) and a future period (2021–2050). We focus on the differences of hydrological impacts in response to both simulations with different performances. Based on the validation of the reference simulations, the EMU simulation shows considerable improvement compared to the Grell simulation, indicating a reduction in the cold and dry biases during summer. This improvement is directly reflected in the hydrological simulation of evapotranspiration and runoff. However, using the RCM simulations without bias-correction showed the limitations of hydrologic simulation, especially snowmelt. Despite large differences in both reference simulations, the change signals of temperature and precipitation derived from the differences between the reference and future simulations show a similar pattern and sign. However, the differences in monthly change in precipitation and temperature between Grell and EMU caused the relatively large differences in runoff changes in the study areas.