Analyzing a Multidecadal High Resolution Regional Climate Simulation over Complex Terrain (original) (raw)
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Regionalization of Climate Change Simulations over the Eastern Mediterranean
Journal of Climate, 2009
In this study, the potential role of global warming in modulating the future climate over the eastern Mediterranean (EM) region has been investigated. The primary vehicle of this investigation is the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 3 (ICTP-RegCM3), which was used to downscale the present and future climate scenario simulations generated by the NASA's finite-volume GCM (fvGCM). The present-day (1961-90; RF) simulations and the future climate change projections (2071-2100; A2) are based on the Intergovernmental Panel on Climate Change (IPCC) greenhouse gas (GHG) emissions. During the Northern Hemispheric winter season, the general increase in precipitation over the northern sector of the EM region is present both in the fvGCM and RegCM3 model simulations. The regional model simulations reveal a significant increase (10%-50%) in winter precipitation over the Carpathian Mountains and along the east coast of the Black Sea, over the Kackar Mountains, and over the Caucasus Mountains. The large decrease in precipitation over the southeastern Turkey region that recharges the Euphrates and Tigris River basins could become a major source of concern for the countries downstream of this region. The model results also indicate that the autumn rains, which are primarily confined over Turkey for the current climate, will expand into Syria and Iraq in the future, which is consistent with the corresponding changes in the circulation pattern. The climate change over EM tends to manifest itself in terms of the modulation of North Atlantic Oscillation. During summer, temperature increase is as large as 78C over the Balkan countries while changes for the rest of the region are in the range of 38-48C. Overall the temperature increase in summer is much greater than the corresponding changes during winter. Presentation of the climate change projections in terms of individual country averages is highly advantageous for the practical interpretation of the results. The consistence of the country averages for the RF RegCM3 projections with the corresponding averaged station data is compelling evidence of the added value of regional climate model downscaling.
Geophysical Research Letters, 2006
1] Results are presented from high resolution climate change simulations over the Mediterranean region using the ICTP Regional Climate Model, RegCM3. Two sets of multi-decadal simulations are performed at 20-km grid spacing for present day and future climate (IPCC A2 scenario). We analyze changes in precipitation mean and extremes and find that the change signal shows seasonally dependent fine scale structure in response to the topographic forcing and changes in circulation, especially over the Alpine region and the Iberian, Italian and Hellenic peninsulas. In winter, the mean precipitation change is positive in the Northern Mediterranean regions and negative in the Southern Mediterranean, while precipitation in the other seasons mostly decreases (especially in summer), except over some localized areas. Changes in extreme precipitation events and dry spells suggest not only shifts, but also a broadening, of the precipitation distribution, with an increased probability of occurrence of events conducive to both floods and droughts. Citation: Gao, X., J. S. Pal, and F. Giorgi (2006), Projected changes in mean and extreme precipitation over the Mediterranean region from a high resolution double nested RCM simulation, Geophys. Res. Lett., 33, L03706,
Advances in Geosciences, 2007
Two configurations of RegCM3 regional climate model (RCM) have been used to downscale results of two atmosphere-ocean global climate model (AOGCM) simulations of the current and future climates (2071-2100) over the eastern Mediterranean (EM) region. The RCM domain covering the EM region from northern Africa to central part of Asia Minor with grid spacing of 50 km was used. Three sets of RCM simulations were completed. Results of the RCM experiment support earlier projections of a temperature (annual precipitation) increase (decrease) to the end of 21st century over the EM. The roles of several major factors in controlling uncertainty of the climate change estimates are evaluated. The main uncertainty factors appear to be associated with possible inadequacies in RCM description of the EM-climate-controlling developments over remotely located areas as well as those in the simulations of the global climate and its trends by the AOGCMs.
Hydrology and Earth System Sciences, 2013
In the framework of the international CORDEX program, new regional climate model (RCM) simulations at high spatial resolutions are becoming available for the Mediterranean region (Med-CORDEX initiative). This study provides the first evaluation for hydrological impact studies of one of these high-resolution simulations in a 1800 km 2 catchment located in North Morocco. Different approaches are compared to analyze the climate change impacts on the hydrology of this catchment using a high-resolution RCM (ALADIN-Climate) from the Med-CORDEX initiative at two different spatial resolutions (50 and 12 km) and for two different Radiative Concentration Pathway scenarios (RCP4.5 and RCP8.5). The main issues addressed in the present study are: (i) what is the impact of increased RCM resolution on present-climate hydrological simulations and on future projections? (ii) Are the bias-correction of the RCM model and the parameters of the hydrological model stationary and transferable to different climatic conditions? (iii) What is the climate and hydrological change signal based on the new Radiative Concentration Pathways scenarios (RCP4.5 and RCP8.5)? Results indicate that high resolution simulations at 12 km better reproduce the seasonal patterns, the seasonal distributions and the extreme events of precipitation. The parameters of the hydrological model, calibrated to reproduce runoff at the monthly time step over the 1984-2010 period, do not show a strong variability between dry and wet calibration periods in a differential split-sample test. However the bias correction of precipitation by quantilematching does not give satisfactory results in validation using the same differential split-sample testing method. Therefore a quantile-perturbation method that does not rely on any stationarity assumption and produces ensembles of perturbed series of precipitation was introduced. The climate change signal under scenarios 4.5 and 8.5 indicates a decrease of respectively −30 to −57 % in surface runoff for the mid-term (2041-2062), when for the same period the projections for precipitation are ranging between −15 and −19 % and for temperature between +1.3 and +1.9 • C.
Climate Dynamics, 2012
The outputs of three GCMs, ECHAM5, CCSM3 and HadCM3, are downscaled for the eastern Mediterranean-Black Sea region for the period 1961-1990 using a regional climate model, RegCM3, to assess the capability of these models in simulating the climatology of the region. In addition, the NCEP/NCAR Reanalysis data are also downscaled for the same period to display the performance of the regional climate model for the same region, which constitutes a relatively complex terrain and rich variety of climates. The gridded observational dataset of CRU is primarily used in the evaluation of the models, however, a regional dataset, which is based on a relatively dense gauging network, is also used to see how it affects the performance measures of the models. The reanalysis simulation indicates that RegCM3 is able to simulate the precipitation and surface temperature as well as the upper level fields reasonably well. However, it tends to overestimate the precipitation over the mountainous areas. All three GCM models are found to be highly skilled in simulating the winter precipitation and temperature in the region. The two models, ECHAM5 and HadCM3, are also good at simulating the summer precipitation and temperature, but the CCSM3 simulation generates dryer and warmer conditions than the observations for the whole region, which are most likely a result of the dryness in the upper levels of the original outputs. The use of the regional observational dataset does not necessarily improve the pattern correlations, but it yields better match between the modeled and observed precipitation in terms of variability and root-mean-square difference. It could be said that the outputs of these GCMs can be used in the climate change downscaling and impact assessment studies for the region, given that their strengths and weaknesses that are displayed in the present study are considered.
Many recent studies indicate climate change as a phenomenon that significantly alters the water cycle in different regions worldwide, also implying new challenges in water resources management and drought risk assessment. To this end, it is of key importance to ascertain the quality of Regional Climate Models (RCMs), which are commonly used for assessing at proper spatial resolutions future impacts of climate change on hydrological events. In this study, we propose a statistical methodological framework to assess the quality of the EURO-CORDEX RCMs concerning their ability to simulate historic climate (temperature and precipitation) and drought characteristics (duration, accumulated deficit, and intensity) determined by the theory of runs, at seasonal and annual time scales, by comparison with high-density and high-quality ground-based observational datasets. In particular, the proposed methodology is applied to Sicily and Calabria regions (Southern Italy), where long historical precipitation and temperature series were recorded by the ground-based monitoring networks operated by the formerly Regional Hydrographic Offices, whose density is considerably greater than observational gridded datasets available at the European level, such as E-OBS. Results show that the more skilful models, able to reproduce, overall, precipitation and temperature variability, as well as drought characteristics, are based on the COSMO-CLM RCM, with the significant exception of the combination based on the HadGEM2-ES GCM and the RACMO RCM. Nevertheless, the choice of the most appropriate model depends on the specific variable analysed, as well as the temporal and spatial scale of interest. From this point of view, the proposed methodology highlights the skills and weaknesses of the different configurations, supporting a proper model selection for climate projections depending on the examined hydrologic processes. as one of the major hot spots of climate change due to future projections of temperature increase and annual precipitation decrease (Giorgi, 2006; Kjellström et al., 2013). Global Circulation and Regional Climate Models (GCMs and RCMs) can play a crucial role in understanding the potential spatiotemporal evolution of climate change in the future, thus improving current monitoring and planning tools (e.g., Mendicino and Versace, 2007; Hart and Halden, 2019) and supporting decision-makers to choose and implement the best solutions to minimize the impact of climate change on human systems and the environment at the regional scale. While GCMs' simulations describe climate evolution at large scale, by using coarse resolution information, RCMs simulations, derived through climate-downscaling techniques, aim at representing regional and local scale weather conditions with grid resolutions lower than 50 km down to about 10 km (Kotlarski et al., 2014; Peres et al., 2019). Several studies, focused on the use of climate models to simulate future climate scenarios for hydrological analyses, have shown that changes in temperature and precipitation vary in space depending on the future climate scenario, type, and resolution of the models, as well as on spatial heterogeneity of climatic features. This is particularly evident in the Mediterranean region where, for instance, precipitation is partially controlled by orography, shows strong seasonality and large interannual fluctuations, and is characterized by the occurrence of extremes, such as prolonged droughts and high-intensity storms leading to floods. Recently, there is a growing interest in the implementation of RCMs derived by dynamical downscaling of GCM outputs for climate change impact studies at small spatial scales. These are high-resolution models able to provide a more realistic representation of important surface heterogeneities (such as topography, coastlines, and land surface characteristics) and mesoscale atmospheric processes. The Coordinated Regional Climate Downscaling Experiment (CORDEX) initiative is the first international program providing a common framework to simulate both historical and future climate at the regional level, under different Representative Concentration Pathways (RCPs) (van Vuuren et al., 2011), and over different domains which cover all the land areas. More specifically, it provides climate data simulated by an ensemble of RCMs developed by several research centres all over the world which are forced by Global Circulation Models (GCMs) from the Coupled Model Intercomparison Project phase 5 (CMIP5) (Taylor et al., 2012). In the present study, we refer to the CORDEX domain centred on the Euro-Mediterranean area, known as EURO-CORDEX (Jacob et al., 2014) (www.euro-cordex.net). In particular, EURO-CORDEX provides simulations for a historic reference period (baseline) and future projections up to 2100, with a 12.5 km grid resolution, available for four RCPs defined at the international level within the Coupled Model Intercomparison Project-Phase 5 (CMIP 5). The reliability of individual RCMs in representing climate effects on the hydrological cycle depends on the quality of simulations and must be evaluated before using their output for impact assessment. Assessing RCMs performance is essential to either select single models for further applications (e.g., Senatore et al., 2011; Peres et al., 2017; Smiatek and Kunstmann, 2019) or properly weight individual RCMs in multi-model ensembles to predict future impacts of climate change on hydrological processes (e.g., Christensen et al., 2010; Coppola et al., 2010). Indeed, intercomparison and validation studies to evaluate RCMs' performances and to provide a ranking based on some hydrological measures, have demonstrated that no
Introduction to special section: Regional Climate Modeling Revisited
Journal of Geophysical Research, 1999
This paper provides an introduction to the special issue of the Journal of Geophysical Research on "New Developments and Applications With the NCAR Regional Climate Model (RegCM)." In the first part of the paper we revisit and discuss outstanding issues in regional climate modeling in view of the progress achieved in this area of research during the last decade. We discuss issues of simulation length, spin-up, model physics, domain and resolution, lateral boundary conditions, multiple and two way nesting, and variable resolution approaches. In the second part we introduce the papers included in this issue. Among the primary model developments that occurred in the last few years are inclusions of the radiative transfer package and cumulus convection scheme from the National Center for Atmospheric Research (NCAR) global model CCM3, a simplified explicit moisture scheme including direct interaction with cloud radiation, testing of a variable resolution model configuration, improvements in the coupled lake model, and interactive coupling with radiatively active atmospheric aerosols. The papers in the issue illustrate a wide range of applications over different regions, such as the United States, East Asia, central Asia, eastern Africa. The main model limitations and areas in need of improvement are indicated.
Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40% at 12 km to ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.
On the role of domain size and resolution in the simulations with the HIRHAM region climate model
Climate Dynamics, 2013
We investigate the simulated temperature and precipitation of the HIRHAM regional climate model using systematic variations in domain size, resolution and detailed location in a total of eight simulations. HIRHAM was forced by ERA-Interim boundary data and the simulations focused on higher resolutions in the range of 5.5-12 km. HIRHAM outputs of seasonal precipitation and temperature were assessed by calculating distributed model errors against a higher resolution data set covering Denmark and a 0.25°resolution data set covering Europe. Furthermore the simulations were statistically tested against the Danish data set using bootstrap statistics. The results from the distributed validation of precipitation showed lower errors for the winter (DJF) season compared to the spring (MAM), fall (SON) and, in particular, summer (JJA) seasons for both validation data sets. For temperature, the pattern was in the opposite direction, with the lowest errors occurring for the JJA season. These seasonal patterns between precipitation and temperature are seen in the bootstrap analysis. It also showed that using a 4,000 9 2,800 km simulation with an 11 km resolution produced the highest significance levels. Also, the temperature errors were more highly significant than precipitation. In similarly sized domains, 12 of 16 combinations of variables, observation validation data and seasons showed better results for the highest resolution domain, but generally the most significant improvements were seen when varying the domain size.
Climate Dynamics, 2011
Regional Climate Models (RCMs) constitute the most often used method to perform affordable highresolution regional climate simulations. The key issue in the evaluation of nested regional models is to determine whether RCM simulations improve the representation of climatic statistics compared to the driving data, that is, whether RCMs add value. In this study we examine a necessary condition that some climate statistics derived from the precipitation field must satisfy in order that the RCM technique can generate some added value: we focus on whether the climate statistics of interest contain some fine spatial-scale variability that would be absent on a coarser grid. The presence and magnitude of fine-scale precipitation variance required to adequately describe a given climate statistics will then be used to quantify the potential added value (PAV) of RCMs. Our results show that the PAV of RCMs is much higher for short temporal scales (e.g., 3-hourly data) than for long temporal scales (16-day average data) due to the filtering resulting from the time-averaging process. PAV is higher in warm season compared to cold season due to the higher proportion of precipitation falling from small-scale weather systems in the warm season. In regions of complex topography, the orographic forcing induces an extra component of PAV, no matter the season or the temporal scale considered. The PAV is also estimated using high-resolution datasets based on observations allowing the evaluation of the sensitivity of changing resolution in the real climate system. The results show that RCMs tend to reproduce relatively well the PAV compared to observations although showing an overestimation of the PAV in warm season and mountainous regions.