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1.
The fifth-generation Canadian Regional Climate Model (CRCM5) was used to dynamically downscale two Coupled Global Climate Model (CGCM) simulations of the transient climate change for the period 1950–2100, over North America, following the CORDEX protocol. The CRCM5 was driven by data from the CanESM2 and MPI-ESM-LR CGCM simulations, based on the historical (1850–2005) and future (2006–2100) RCP4.5 radiative forcing scenario. The results show that the CRCM5 simulations reproduce relatively well the current-climate North American regional climatic features, such as the temperature and precipitation multiannual means, annual cycles and temporal variability at daily scale. A cold bias was noted during the winter season over western and southern portions of the continent. CRCM5-simulated precipitation accumulations at daily temporal scale are much more realistic when compared with its driving CGCM simulations, especially in summer when small-scale driven convective precipitation has a large contribution over land. The CRCM5 climate projections imply a general warming over the continent in the 21st century, especially over the northern regions in winter. The winter warming is mostly contributed by the lower percentiles of daily temperatures, implying a reduction in the frequency and intensity of cold waves. A precipitation decrease is projected over Central America and an increase over the rest of the continent. For the average precipitation change in summer however there is little consensus between the simulations. Some of these differences can be attributed to the uncertainties in CGCM-projected changes in the position and strength of the Pacific Ocean subtropical high pressure.  相似文献   

2.
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.  相似文献   

3.
Results from a first-time employment of the WRF regional climate model to climatological simulations in Europe are presented. The ERA-40 reanalysis (resolution 1°) has been downscaled to a horizontal resolution of 30 and 10?km for the period of 1961?C1990. This model setup includes the whole North Atlantic in the 30?km domain and spectral nudging is used to keep the large scales consistent with the driving ERA-40 reanalysis. The model results are compared against an extensive observational network of surface variables in complex terrain in Norway. The comparison shows that the WRF model is able to add significant detail to the representation of precipitation and 2-m temperature of the ERA-40 reanalysis. Especially the geographical distribution, wet day frequency and extreme values of precipitation are highly improved due to the better representation of the orography. Refining the resolution from 30 to 10?km further increases the skill of the model, especially in case of precipitation. Our results indicate that the use of 10-km resolution is advantageous for producing regional future climate projections. Use of a large domain and spectral nudging seems to be useful in reproducing the extreme precipitation events due to the better resolved synoptic scale features over the North Atlantic, and also helps to reduce the large regional temperature biases over Norway. This study presents a high-resolution, high-quality climatological data set useful for reference climate impact studies.  相似文献   

4.
We present an analysis of a regional simulation of present-day climate (1981–1990) over southern South America. The regional model MM5 was nested within time-slice global atmospheric model experiments conducted by the HadAM3H model. We evaluate the capability of the model in simulating the observed climate with emphasis on low-level circulation patterns and surface variables, such as precipitation and surface air mean, maximum and minimum temperatures. The regional model performance was evaluated in terms of seasonal means, seasonal cycles, interannual variability and extreme events. Overall, the regional model is able to capture the main features of the observed mean surface climate over South America, its seasonal evolution and the regional detail due to topographic forcing. The observed regional patterns of surface air temperatures (mean, maxima and minima) are well reproduced. Biases are mostly within 3°C, temperature being overestimated over central Argentina and underestimated in mountainous regions during all seasons. Biases in northeastern Argentina and southeastern Brazil are positive during austral spring season and negative in other seasons. In general, maximum temperatures are better represented than minimum temperatures. Warm bias is larger during austral summer for maximum temperature and during austral winter for minimum temperature, mainly over central Argentina. The broad spatial pattern of precipitation and its seasonal evolution are well captured; however, the regional model overestimates the precipitation over the Andes region in all seasons and in southern Brazil during summer. Precipitation amounts are underestimated over the La Plata basin from fall to spring. Extremes of precipitation are better reproduced by the regional model compared with the driving model. Interannual variability is well reproduced too, but strongly regulated by boundary conditions, particularly during summer months. Overall, taking into account the quality of the simulation, we can conclude that the regional model is capable in reproducing the main regional patterns and seasonal cycle of surface variables. The present reference simulation constitutes the basis to examine the climate change simulations resulting from the A2 and B2 forcing scenarios which are being reported in a separate study.  相似文献   

5.
The objective of this work is to gain a general insight into the key mechanisms involved in the impact of nudging on the large scales and the small scales of a regional climate simulation. A “Big Brother experiment” (BBE) approach is used where a “reference atmosphere” is known, unlike when regional climate models are used in practice. The main focus is on the sensitivity to nudging time, but the BBE approach allows to go beyond a pure sensitivity study by providing a reference which model outputs try to approach, defining an optimal nudging time. Elaborating upon previous idealized studies, this work introduces key novel points. The BBE approach to optimal nudging is used with a realistic model, here the weather research and forecasting model over the European and Mediterranean regions. A winter simulation (1 December 1989–28 February 1990) and a summer simulation (1 June 1999–31 August 1999) with a 50 km horizontal mesh grid have been performed with initial and boundary conditions provided by the ERA-interim reanalysis of the European Center for Medium-range Weather Forecast to produce the “reference atmosphere”. The impacts of spectral and indiscriminate nudging are compared all others things being equal and as a function of nudging time. The impact of other numerical parameters, specifically the domain size and update frequency of the large-scale driving fields, on the sensitivity of the optimal nudging time is investigated. The nudged simulations are also compared to non-nudged simulations. Similarity between the reference and the simulations is evaluated for the surface temperature, surface wind and for rainfall, key variables for climate variability analysis and impact studies. These variables are located in the planetary boundary layer, which is not subject to nudging. Regarding the determination of a possible optimal nudging time, the conclusion is not the same for indiscriminate nudging (IN) and spectral nudging and depends on the update frequency of the driving large-scale fields τ a . For IN, the optimal nudging time is around τ = 3 h for almost all cases. For spectral nudging, the best results are for the smallest value of τ used for the simulations (τ = 1 h) for frequent update of the driving large-scale fields (3 and 6 h). The optimal nudging time is 3 for 12 h interval between two consecutive driving large-scale fields due to time sampling errors. In terms of resemblance to the reference fields, the differences between the simulations performed with IN and spectral nudging are small. A possible reason for this very similar performance is that nudging is active only above the planetary boundary layer where small-scale features are less energetic. As expected from previous studies, the impact of nudging is weaker for a smaller domain size. However the optimal nudging time itself is not sensitive to domain size. The proposed strategy ensures a dynamical consistency between the driving field and the simulated small-scale field but it does not ensure the best “observed” fine scale field because of the possible impact of incorrect driving large-scale field. This type of downscaling provides an upper bound on the skill possible for recent historical past and twenty-first century projections. The optimal nudging strategy with respect to dynamic downscaling could add skill whenever the parent global model has some level of skill.  相似文献   

6.
Central America has high biodiversity, it harbors high-value ecosystems and it??s important to provide regional climate change information to assist in adaptation and mitigation work in the region. Here we study climate change projections for Central America and Mexico using a regional climate model. The model evaluation shows its success in simulating spatial and temporal variability of temperature and precipitation and also in capturing regional climate features such as the bimodal annual cycle of precipitation and the Caribbean low-level jet. A variety of climate regimes within the model domain are also better identified in the regional model simulation due to improved resolution of topographic features. Although, the model suffers from large precipitation biases, it shows improvements over the coarse-resolution driving model in simulating precipitation amounts. The model shows a dry bias in the wet season and a wet bias in the dry season suggesting that it??s unable to capture the full range of precipitation variability. Projected warming under the A2 scenario is higher in the wet season than that in the dry season with the Yucatan Peninsula experiencing highest warming. A large reduction in precipitation in the wet season is projected for the region, whereas parts of Central America that receive a considerable amount of moisture in the form of orographic precipitation show significant decreases in precipitation in the dry season. Projected climatic changes can have detrimental impacts on biodiversity as they are spatially similar, but far greater in magnitude, than those observed during the El Ni?o events in recent decades that adversely affected species in the region.  相似文献   

7.
This study presents the evaluation of simulations from two new Canadian regional climate models (RCMs), CanRCM4 and CRCM5, with a focus on the models’ skill in simulating daily precipitation indices and the Standardized Precipitation Index (SPI). The evaluation was carried out over the past two decades using several sets of gridded observations that partially cover North America. The new Canadian RCMs were also compared with four reanalysis products and six other RCMs. The different configurations of the Canadian RCM simulations also permit evaluation of the impact of different spatial resolutions, atmospheric drivers, and nudging conditions. The results from the new Canadian models show some improvement in precipitation characteristics over the previous Canadian RCM (CRCM4), but these differ with the seasons. For winter, CanRCM4 and CRCM5 have better skill than most other models over all of North America. For the summer, CRCM5 0.44° performs best over the United States, while CRCM4 has the best skill over Canada. Good skill is exhibited by CanRCM4 and CRCM4 in simulating the 6-month SPI over the Prairies and the western US Corn Belt. In general, differences are small between runs with or without large-scale spectral nudging; differences are small when different boundary conditions are used.  相似文献   

8.
This study aims to analyse the interannual variability simulated by several regional climate models (RCMs), and its potential for disguising the effect of seasonal temperature increases due to greenhouse gases. In order to accomplish this, we used an ensemble of regional climate change projections over North America belonging to the North American Regional Climate Change Program, with an additional pair of 140-year continuous runs from the Canadian RCM. We find that RCM-simulated interannual variability shows important departures from observed one in some cases, and also from the driving models’ variability, while the expected climate change signal coincides with estimations presented in previous studies. The continuous runs from the Canadian RCM were used to illustrate the effect of interannual variability in trend estimation for horizons of a decade or more. As expected, it can contribute to the existence of transitory cooling trends over a few decades, embedded within the expected long-term warming trends. A new index related to signal-to-noise ratio was developed to evaluate the expected number of years it takes for the warming trend to emerge from interannual variability. Our results suggest that detection of the climate change signal is expected to occur earlier in summer than in winter almost everywhere, despite the fact that winter temperature generally has a much stronger climate change signal. In particular, we find that the province of Quebec and northwestern Mexico may possibly feel climate change in winter earlier than elsewhere in North America. Finally, we show that the spatial and temporal scales of interest are fundamental for our capacity of discriminating climate change from interannual variability.  相似文献   

9.
The analysis of possible regional climate changes over Europe as simulated by 10 regional climate models within the context of PRUDENCE requires a careful investigation of possible systematic biases in the models. The purpose of this paper is to identify how the main model systematic biases vary across the different models. Two fundamental aspects of model validation are addressed here: the ability to simulate (1) the long-term (30 or 40 years) mean climate and (2) the inter-annual variability. The analysis concentrates on near-surface air temperature and precipitation over land and focuses mainly on winter and summer. In general, there is a warm bias with respect to the CRU data set in these extreme seasons and a tendency to cold biases in the transition seasons. In winter the typical spread (standard deviation) between the models is 1 K. During summer there is generally a better agreement between observed and simulated values of inter-annual variability although there is a relatively clear signal that the modeled temperature variability is larger than suggested by observations, while precipitation variability is closer to observations. The areas with warm (cold) bias in winter generally exhibit wet (dry) biases, whereas the relationship is the reverse during summer (though much less clear, coupling warm (cold) biases with dry (wet) ones). When comparing the RCMs with their driving GCM, they generally reproduce the large-scale circulation of the GCM though in some cases there are substantial differences between regional biases in surface temperature and precipitation.  相似文献   

10.
A high resolution regional climate model (RCM) is used to simulate climate of the recent past and to project future climate change across the northeastern US. Different types of uncertainties in climate simulations are examined by driving the RCM with different boundary data, applying different emissions scenarios, and running an ensemble of simulations with different initial conditions. Empirical orthogonal functions analysis and K-means clustering analysis are applied to divide the northeastern US region into four climatologically different zones based on the surface air temperature (SAT) and precipitation variability. The RCM simulations tend to overestimate SAT, especially over the northern part of the domain in winter and over the western part in summer. Statistically significant increases in seasonal SAT under both higher and lower emissions scenarios over the whole RCM domain suggest the robustness of future warming. Most parts of the northeastern US region will experience increasing winter precipitation and decreasing summer precipitation, though the changes are not statistically significant. The greater magnitude of the projected temperature increase by the end of the twenty-first century under the higher emissions scenario emphasizes the essential role of emissions choices in determining the potential future climate change.  相似文献   

11.
Summary An assessment is made of a regional climate model's skill in simulating the mean climatology and the interannual variability experienced in a specific region. To this end two ensembles comprising three realizations of month-long January and July simulations are undertaken with a limited are a operational NWP model. The modelling suite is driven at its lateral boundaries by analysed meteorological fields and the computational domain covers Europe and the North-western Atlantic with a horizontal resolution of 56 km.Validation is performed against both operational ECMWF analyses and objectively analysed precipitation fields from a network of ~ 1400 SYNOP rain gauge stations. Analysis of the simulated ensemble-mean climatology indicates that the model successfully reproduces both the winter and summer distributions of the primary dynamical and thermodynamical field, and also provides a reasonable representation of the measured precipitation over most of Europe. Typically the domain averaged model-biases are below 0.5 K for temperature and 0.1 g/kg for specific humidity. Analysis of the interannual variability reveals that the model captures the wintertime changes including that of the precipitation distribution, but in contrast the summertime precipitation totals for the individual years is not simulated satisfactorily and only partially reproduces the observed regional interannual variability.The latter shortcomings are related to the following factors. Firstly the model bias in the dynamical fields is somewhat larger for summer than winter, while at the same time summertime interannual variability is associated with weaker effects in the dynamical fields. Secondly the summertime precipitation distribution is more substantially affected by small-scale moist convection and surface hydrological processes. Together these two factors suggest that summertime precipitation over continental extratropical land masses might be intrinsically less predictable than wintertime synoptic scale precipitation.With 17 Figures  相似文献   

12.
This work focuses on the evaluation of different sources of uncertainty affecting regional climate simulations over South America at the seasonal scale, using the MM5 model. The simulations cover a 3-month period for the austral spring season. Several four-member ensembles were performed in order to quantify the uncertainty due to: the internal variability; the definition of the regional model domain; the choice of physical parameterizations and the selection of physical parameters within a particular cumulus scheme. The uncertainty was measured by means of the spread among individual members of each ensemble during the integration period. Results show that the internal variability, triggered by differences in the initial conditions, represents the lowest level of uncertainty for every variable analyzed. The geographic distribution of the spread among ensemble members depends on the variable: for precipitation and temperature the largest spread is found over tropical South America while for the mean sea level pressure the largest spread is located over the southeastern Atlantic Ocean, where large synoptic-scale activity occurs. Using nudging techniques to ingest the boundary conditions reduces dramatically the internal variability. The uncertainty due to the domain choice displays a similar spatial pattern compared with the internal variability, except for the mean sea level pressure field, though its magnitude is larger all over the model domain for every variable. The largest spread among ensemble members is found for the ensemble in which different combinations of physical parameterizations are selected. The perturbed physics ensemble produces a level of uncertainty slightly larger than the internal variability. This study suggests that no matter what the source of uncertainty is, the geographical distribution of the spread among members of the ensembles is invariant, particularly for precipitation and temperature.  相似文献   

13.
Observations as well as most climate model simulations are generally in accord with the hypothesis that the hydrologic cycle should intensify and become highly volatile with the greenhouse-gas-induced climate change, although uncertainties of these projections as well as the spatial and seasonal variability of the changes are much larger than for temperature extremes. In this study, we examine scenarios of changes in extreme precipitation events in 24 future climate runs of ten regional climate models, focusing on a specific area of the Czech Republic (central Europe) where complex orography and an interaction of other factors governing the occurrence of heavy precipitation events result in patterns that cannot be captured by global models. The peaks-over-threshold analysis with increasing threshold censoring is applied to estimate multi-year return levels of daily rainfall amounts. Uncertainties in scenarios of changes for the late 21st century related to the inter-model and within-ensemble variability and the use of the SRES-A2 and SRES-B2 greenhouse gas emission scenarios are evaluated. The results show that heavy precipitation events are likely to increase in severity in winter and (with less agreement among models) also in summer. The inter-model and intra-model variability and related uncertainties in the pattern and magnitude of the change is large, but the scenarios tend to agree with precipitation trends recently observed in the area, which may strengthen their credibility. In most scenario runs, the projected change in extreme precipitation in summer is of the opposite sign than a change in mean seasonal totals, the latter pointing towards generally drier conditions in summer. A combination of enhanced heavy precipitation amounts and reduced water infiltration capabilities of a dry soil may severely increase peak river discharges and flood-related risks in this region.  相似文献   

14.
General circulation models still show deficiencies in simulating the basic features of the West African Monsoon at intraseasonal, seasonal and interannual timescales. It is however, difficult to disentangle the remote versus regional factors that contribute to such deficiencies, and to diagnose their possible consequences for the simulation of the global atmospheric variability. The aim of the present study is to address these questions using the so-called grid point nudging technique, where prognostic atmospheric fields are relaxed either inside or outside the West African Monsoon region toward the ERA40 reanalysis. This regional or quasi-global nudging is tested in ensembles of boreal summer simulations. The impact is evaluated first on the model climatology, then on intraseasonal timescales with an emphasis on North Atlantic/Europe weather regimes, and finally on interannual timescales. Results show that systematic biases in the model climatology over West Africa are mostly of regional origin and have a limited impact outside the domain. A clear impact is found however on the eddy component of the extratropical circulation, in particular over the North Atlantic/European sector. At intraseasonal timescale, the main regional biases also resist to the quasi-global nudging though their magnitude is reduced. Conversely, nudging the model over West Africa exerts a strong impact on the frequency of the two North Atlantic weather regimes that favor the occurrence of heat waves over Europe. Significant impacts are also found at interannual timescale. Not surprisingly, the quasi-global nudging allows the model to capture the variability of large-scale dynamical monsoon indices, but exerts a weaker control on rainfall variability suggesting the additional contribution of regional processes. Conversely, nudging the model toward West Africa suppresses the spurious ENSO teleconnection that is simulated over Europe in the control experiment, thereby emphasizing the relevance of a realistic West African monsoon simulation for seasonal prediction in the extratropics. Further experiments will be devoted to case studies aiming at a better understanding of regional processes governing the monsoon variability and of the possible monsoon teleconnections, especially over Europe.  相似文献   

15.
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.  相似文献   

16.
The ability of a regional climate model (RCM) to successfully reproduce the fine-scale features of a regional climate during summer is evaluated using an approach nick-named the “Big-Brother Experiment” (BBE). The BBE establishes a reference virtual-reality climate with a RCM applied on a large and high-resolution domain: this simulation is called the Big-Brother (BB) simulation. This reference simulation is then downgraded by filtering small-scale features that are unresolved in today’s global objective analyses. The resulting fields are then used as nesting data to drive the same RCM, which is integrated, at the same high resolution as the BB, only over a sub-area of the larger BB domain, hence, producing the Little-Brother simulation (LB). With the BBE approach, differences between the two simulated climates (BB and LB) can be unambiguously attributed to errors associated with the dynamical downscaling technique, and not to model errors or observational limitations. The current study focuses on the summer over the West Coast of North America. Results of the stationary and transient parts of the fields, decomposed by horizontal scales, are presented for the month of July, for 5 consecutive years (1990–1994). Three degrees of spatial filtering (roughly equivalent to the global spectral resolution of T30, T60 and T360) as well as two update intervals (3 and 6 h) of the lateral boundary conditions (LBC) have been employed. This study establishes that the maximum acceptable resolution of driving data for summer is T30, with improved results employing the T60 resolution of LBC. There is little improvement by reducing the time interval from 6 h to 3 h. These results are generally in agreement with previous studies carried out for winter. The good correlation between LB and BB simulations is more difficult to achieve during the summer season, mostly due to weaker control exerted by LBC. Poor correlations are more pronounced for the transient parts than they are for the stationary parts of the fields. This is especially true for the precipitation field, where differences can be attributed to higher temporal variability during the summer due to the presence of convection.  相似文献   

17.
The uncertainties in the regional climate models (RCMs) are evaluated by analyzing the driving global data of ERA40 reanalysis and ECHAM5 general circulation models, and the downscaled data of two RCMs (RegCM4 and PRECIS) over South-Asia for the present day simulation (1971–2000) of South-Asian summer monsoon. The differences between the observational datasets over South-Asia are also analyzed. The spatial and the quantitative analysis over the selected climatic regions of South-Asia for the mean climate and the inter-annual variability of temperature, precipitation and circulation show that the RCMs have systematic biases which are independent from different driving datasets and seems to come from the physics parameterization of the RCMs. The spatial gradients and topographically-induced structure of climate are generally captured and simulated values are within a few degrees of the observed values. The biases in the RCMs are not consistent with the biases in the driving fields and the models show similar spatial patterns after downscaling different global datasets. The annual cycle of temperature and rainfall is well simulated by the RCMs, however the RCMs are not able to capture the inter-annual variability. ECHAM5 is also downscaled for the future (2071–2100) climate under A1B emission scenario. The climate change signal is consistent between ECHAM5 and RCMs. There is warming over all the regions of South-Asia associated with increasing greenhouse gas concentrations and the increase in summer mean surface air temperature by the end of the century ranges from 2.5 to 5 °C, with maximum warming over north western parts of the domain and 30 % increase in rainfall over north eastern India, Bangladesh and Myanmar.  相似文献   

18.
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.  相似文献   

19.
We investigate major results of the NARCCAP multiple regional climate model (RCM) experiments driven by multiple global climate models (GCMs) regarding climate change for seasonal temperature and precipitation over North America. We focus on two major questions: How do the RCM simulated climate changes differ from those of the parent GCMs and thus affect our perception of climate change over North America, and how important are the relative contributions of RCMs and GCMs to the uncertainty (variance explained) for different seasons and variables? The RCMs tend to produce stronger climate changes for precipitation: larger increases in the northern part of the domain in winter and greater decreases across a swath of the central part in summer, compared to the four GCMs driving the regional models as well as to the full set of CMIP3 GCM results. We pose some possible process-level mechanisms for the difference in intensity of change, particularly for summer. Detailed process-level studies will be necessary to establish mechanisms and credibility of these results. The GCMs explain more variance for winter temperature and the RCMs for summer temperature. The same is true for precipitation patterns. Thus, we recommend that future RCM-GCM experiments over this region include a balanced number of GCMs and RCMs.  相似文献   

20.
Present and future climatologies in the phase I CREMA experiment   总被引：1，自引：0，他引：1  
We provide an overall assessment of the surface air temperature and precipitation present day (1976–2005) and future (2070–2099) ensemble climatologies in the Phase I CREMA experiment. This consists of simulations performed with different configurations (physics schemes) of the ICTP regional model RegCM4 over five CORDEX domains (Africa, Mediterranean, Central America, South America, South Asia), driven by different combinations of three global climate models (GCMs) and two greenhouse gas (GHG) representative concentration pathways (RCP8.5 and RCP4.5). The biases (1976–2005) in the driving and nested model ensembles compared to observations show a high degree of spatial variability and, when comparing GCMs and RegCM4, similar magnitudes and more similarity for precipitation than for temperature. The large scale patterns of change (2070–2099 minus 1976–2005) are broadly consistent across the GCM and RegCM4 ensembles and with previous analyses of GCM projections, indicating that the GCMs selected in the CREMA experiment are representative of the more general behavior of current GCMs. The RegCM4, however, shows a lower climate sensitivity (reduced warming) than the driving GCMs, especially when using the CLM land surface scheme. While the broad patterns of precipitation change are consistent across the GCM and RegCM4 ensembles, greater differences are found at sub-regional scales over the various domains, evidently tied to the representation of local processes. This paper serves to provide a reference view of the behavior of the CREMA ensemble, while more detailed and process-based analysis of individual domains is left to companion papers of this special issue.  相似文献   

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