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1.
Regional Climate Models (RCMs) have been developed in the last two decades in order to produce high-resolution climate information by downscaling Atmosphere-Ocean General Circulation Models (AOGCMs) simulations or analyses of observed data. A crucial evaluation of RCMs worth is given by the assessment of the value added compared to the driving data. This evaluation is usually very complex due to the manifold circumstances that can preclude a fair assessment. In order to circumvent these issues, here we limit ourselves to estimating the potential of RCMs to add value over coarse-resolution data. We do this by quantifying the importance of fine-scale RCM-resolved features in the near-surface temperature, but disregarding their skill. The Reynolds decomposition technique is used to separate the variance of the time-varying RCM-simulated temperature field according to the contribution of large and small spatial scales and of stationary and transient processes. The temperature variance is then approximated by the contribution of four terms, two of them associated with coarse-scales (e.g., corresponding to the scales that can be simulated by AOGCMs) and two of them describing the original contribution of RCM simulations. Results show that the potential added value (PAV) emerges almost exclusively in regions characterised by important surface forcings either due to the presence of fine-scale topography or land-water contrasts. Moreover, some of the processes leading to small-scale variability appear to be related with relatively simple mechanisms such as the distinct physical properties of the Earth surface and the general variation of temperature with altitude in the Earth atmosphere. Finally, the article includes some results of the application of the PAV framework to the future temperature change signal due to anthropogenic greenhouse gasses. Here, contrary to previous studies centred on precipitation, findings suggest for surface temperature a relatively low potential of RCMs to add value over coarser resolution models, with the greatest potential located in coastline regions due to the differential warming occurring in land and water surfaces.  相似文献   

2.
The scaled-decomposed atmospheric water budget over North America is investigated through the analysis of 25 years of simulation by the Canadian Regional Climate Model (CRCM) driven by the NCEP–NCAR reanalyses for the period 1975–1999. The time average and time variability of the atmospheric water budget for the winter and summer seasons are decomposed into their large-scale and small-scale components to identify the added value of the regional model. For the winter season, the intra-seasonal transient-eddy variance is the main temporal variability. The large- and small-scale terms are of the same order of magnitude, and are large over both coasts and weak over the continent. For the summer season, the time–mean atmospheric water budget is rather different to that of winter, with maximum values over the south-eastern part of the continent. The summer intra-seasonal variance is about twice stronger than in winter and also dominates the variability, but the inter-monthly variance is non-negligible and can be in part associated to North American Monsoon System. Over the continent, the intra-seasonal climatological variance is dominated by the variability of the small scales. The small scales, that is those scales that are only resolved in the regional model but not in the reanalyses, contribute to the added value in a regional climate simulation. In the winter season, the added value of the CRCM is large and dominated by oceanic forcing, while in summer, it is dominant (larger than the large scales) and controlled mainly by convective processes.  相似文献   

3.
A. M. Duan  G. X. Wu 《Climate Dynamics》2005,24(7-8):793-807
The mechanism of the Tibetan Plateau (TP) thermal forcing in influencing the summer climate patterns over subtropical Asia is investigated by means of NCEP/NCAR reanalysis diagnosis. Results show that since the TP is a huge elevated heating source with the strongest heating in the surface layers in summer, the thermal adaptation results in a shallow cyclonic circulation near the surface and a deep anticyclonic circulation above it. According to the steady barotropic vorticity equation for large scales, airflow must converge in the lower layers and diverge in the higher layers over the eastern side of the TP. However, the western side of the TP is characterized by a reversed structure, i.e., divergence in lower layers but convergence in higher layers. Hence, pumping and sucking processes bring in upward and downward movement over the east and west sides of the TP, respectively. Such a circulation is embedded in the large-scale circulation that is forced by the Eurasian continental heating. Because the TP together with Iran Plateau are located at the central and eastern parts of the continent, and, because the orography-induced circulation is in phase with the continental scale circulation, the role of the TP thermal forcing is to intensify the East Asian monsoon to its east and the dry and hot desert climate in mid-Asia to its west. The summertime thermal forcing of the Rockies and Andes can generate similar circulations along the two subtopics as the TP does since they are located near the western coasts. But, the lower troposphere poleward flow that is induced by orographic thermal forcing does not coincide with the poleward flows over the eastern coastal region that is induced by continental heating and the monsoon rainfall in North and South America is not as strong as in East Asia. However, the equatorward flow and the associated subsidence induced by the two mountain ranges along the western coasts of both North and South America are in phase with those induced by continental heating. These contribute to the formation of the stable low stratus clouds and strong long-wave radiative cooling over the eastern subtropical Pacific regions just off the western coast of the continent.  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 Andes Cordillera acts as regional ??Water Towers?? for several countries and encompasses a wide range of ecosystems and climates. Several hydroclimatic changes have been described for portions of the Andes during recent years, including glacier retreat, negative precipitation trends, an elevation rise in the 0° isotherm, and changes in regional streamflow regimes. The Temperate-Mediterranean transition (TMT) zone of the Andes (35.5°?C39.5°S) is particularly at risk to climate change because it is a biodiversity hotspot with heavy human population pressure on water resources. In this paper we utilize a new tree-ring network of Austrocedrus chilensis to reconstruct past variations in regional moisture in the TMT of the Andes by means of the Palmer Drought Severity Index (PDSI). The reconstruction covers the past 657?years and captures interannual to decadal scales of variability in late spring?Cearly summer PDSI. These changes are related to the north?Csouth oscillations in moisture conditions between the Mediterranean and Temperate climates of the Andes as a consequence of the latitudinal position of the storm tracks forced by large-scale circulation modes. Kernel estimation of occurrence rates reveals an unprecedented increment of severe and extreme drought events during the last century in the context of the previous six centuries. Moisture conditions in our study region are linked to tropical and high-latitude ocean-atmospheric forcing, with PDSI positively related to Ni?o-3.4 SST during spring and strongly negatively correlated with the Antarctic Oscillation (AAO) during summer. Geopotential anomaly maps at 500-hPa show that extreme dry years are tightly associated with negative height anomalies in the Ross?CAmundsen Seas, in concordance with the strong negative relationship between PDSI and AAO. The twentieth century increase in extreme drought events in the TMT may not be related to ENSO but to the positive AAO trend during late-spring and summer resulting from a gradual poleward shift of the mid-latitude storm tracks. This first PDSI reconstruction for South America demonstrates the highly significant hindcast skill of A. chilensis as an aridity proxy.  相似文献   

6.
The 2m temperature (T2m) and precipitation from five regional climate models (RCMs), which participated in the ENSEMBLES project and were integrated at a 25-km horizontal resolution, are compared with observed climatological data from 13 stations located in the Croatian coastal zone. The twentieth century climate was simulated by forcing RCMs with identical boundary conditions from the ERA-40 reanalysis and the ECHAM5/MPI-OM global climate model (GCM); climate change in the twenty-first century is based on the A1B scenario and assessed from the GCM-forced RCMs’ integrations. When forced by ERA-40, most RCMs exhibit cold bias in winter which contributes to an overestimation of the T2m annual cycle amplitude and the errors in interannual variability are in all RCMs smaller than those in the climatological mean. All models underestimate observed warming trends in the period 1951–2010. The largest precipitation biases coincide with locations/seasons with small observed amounts but large precipitation amounts near high orography are relatively well reproduced. When forced by the same GCM all RCMs exhibit a warming in the cold half-year and a cooling (or weak warming) in the warm period, implying a strong impact of GCM boundary forcing. The future eastern Adriatic climate is characterised by a warming, up to +5 °C towards the end of the twenty-first century; for precipitation, no clear signal is evident in the first half of the twenty-first century, but a reduction in precipitation during summer prevails in the second half. It is argued that land-sea contrast and complex coastal configuration of the Croatian coast, i.e. multitude of island and well indented coastline, have a major impact on small-scale variability. Orography plays important role only at small number of coastal locations. We hypothesise that the parameterisations related to land surface processes and soil hydrology have relatively stronger impact on variability than orography at those locations that include a relatively large fraction of land (most coastal stations), but affecting less strongly locations at the Adriatic islands.  相似文献   

7.
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   

8.
A methodology is developed for testing the downscaling ability of nested regional climate models (RCMs). The proposed methodology, nick-named the Big-Brother Experiment (BBE), is based on a "perfect-prognosis" approach and hence does not suffer from model errors nor from limitations in observed climatologies. The BBE consists in first establishing a reference climate by performing a large-domain high-resolution RCM simulation: this simulation is called the Big Brother. This reference simulation is then degraded by filtering short scales that are unresolved in today's global objective analyses (OA) and/or global climate models (GCMs) when integrated for climate projections. This filtered reference is then used to drive the same nested RCM (called the Little Brother), integrated at the same high-resolution as the Big Brother, but over a smaller domain that is embedded in the Big-Brother domain. The climate statistics of the Little Brother are then compared with those of the Big Brother over the Little-Brother domain. Differences can thus be attributed unambiguously to errors associated with the nesting and downscaling technique, and not to model errors nor to observation limitations. The results of the BBE applied to a one-winter-month simulation over eastern North America at 45-km grid-spacing resolution show that the one-way nesting strategy has skill in downscaling large-scale information to the regional scales. The time mean and variability of fine-scale features in a number of fields, such as sea level pressure, 975-hPa temperature and precipitation are successfully reproduced, particularly over regions where small-scale surface forcings are strong. Over other regions such as the ocean and away from the surface, the small-scale reproducibility is more difficult to achieve.  相似文献   

9.
The study examines future scenarios of precipitation extremes over Central Europe in an ensemble of 12 regional climate model (RCM) simulations with the 25-km resolution, carried out within the European project ENSEMBLES. We apply the region-of-influence method as a pooling scheme when estimating distributions of extremes, which consists in incorporating data from a ‘region’ (set of gridboxes) when fitting an extreme value distribution in any single gridbox. The method reduces random variations in the estimates of parameters of the extreme value distribution that result from large spatial variability of heavy precipitation. Although spatial patterns differ among the models, most RCMs simulate increases in high quantiles of precipitation amounts when averaged over the area for the late-twenty-first century (2070–2099) climate in both winter and summer. The sign as well as the magnitude of the projected change vary only little for individual parts of the distribution of daily precipitation in winter. In summer, on the other hand, the projected changes increase with the quantile of the distribution in all RCMs, and they are negative (positive) for parts of the distribution below (above) the 98% quantile if averaged over the RCMs. The increases in precipitation extremes in summer are projected in spite of a pronounced drying in most RCMs. Although a rather general qualitative agreement of the models concerning the projected changes of precipitation extremes is found in both winter and summer, the uncertainties in climate change scenarios remain large and would likely further increase considerably if a more complete ensemble of RCM simulations driven by a larger suite of global models and with a range of possible scenarios of the radiative forcing is available.  相似文献   

10.
Runs of three regional climate models (RCMs) dynamically downscaling the outputs of atmosphere?Cocean coupling general circulation models (AOGCMs) are studied. These RCMs are NCAR-MM5, NCEP-RSM (Regional Spectral Model), and Purdue-PRM (Purdue Regional Model). A useful approach is developed to compare the variability, error, and spatial distribution of model-simulated results with respect to the Climatic Research Unit (CRU) datasets over East Asia and seven sub-regions during the 1990s. The results show that NCEP-RSM outperforms the other two in meeting criteria selected on evaluating the model performance. Furthermore, three super-ensemble approaches are tested on merging RCMs?? outputs. The inverse of the square error summation (ISES) method is selected as a suitable method with a generally good performance during the verification period. The projected future climate changes by ISES indicate larger temperature increases over high-latitude continent and smaller over low-latitude maritime areas. Rainfall will increase in summer over the central simulation domain, i.e. the eastern China, but decrease in winter, which are clearly linked to the variation in the synoptic airflows. Also, a more frequent occurrence of extreme rainfall events than what happened in the 1990s is projected. The projection over Taiwan suggests strong warming in summer, followed by autumn, winter, and spring. The interaction between the synoptic flow and the local terrain affects significantly the changes in precipitation. In general, larger change of the variability of rainfall will be over areas with lesser rainfall in the future, while lesser change will be over areas with more projected rainfall.  相似文献   

11.
Europe has been warming over the past 30?years. In particular all seasonal temperature records have been broken since 2003, which altered socio-economic and environmental systems. Since we expect this trend in both mean and extreme temperatures to continue along the twenty first century under enhanced radiative forcing, it is crucial to understand the underlying mechanisms of such climate variations to help in considering adaptation or mitigation strategies to reduce the impacts of a warmer climate. From a statistical analysis we show that the inter-annual variability of European seasonal temperatures can be reconstructed from North-Atlantic atmospheric circulation only, but not their recent trends and extreme seasons. Adding North-Atlantic sea-surface temperature (SST) as a predictor helps improving the reconstruction, especially in autumn and winter. Sensitivity experiments with the MM5 regional model over 2003?C2007 suggest that the anomalous SST enhance European land temperatures through the upper-air advection of heat and water vapor, interacting with radiative fluxes over the continent. This mechanism is pronounced in autumn and winter, where estimates of SST influence as obtained from MM5 are in agreement with those obtained from statistical regressions. We find a lesser SST influence in spring and summer, where local surface and radiative feedbacks are the main amplifiers of recent extremes.  相似文献   

12.
不同区域气候模式对中国地区温度和降水的长期模拟比较   总被引：19，自引：9，他引：19  
冯锦明  符淙斌 《大气科学》2007,31(5):805-814
利用亚洲区域模式比较计划RMIP第二阶段五个区域模式和一个变网格全球模式，对中国地区1988年12月～1998年11月十年模拟的平均温度和降水结果，分析比较了不同区域气候模式对中国地区温度和降水的模拟能力。研究结果表明:几乎所有模式都能模拟出中国地区多年平均温度和降水的基本空间分布形态，但模式模拟的温度普遍偏低，在大部分区域，大多数模式模拟的降水偏多，而且不同模式之间存在较大差别。模式能较好地反映出中国地区温度的年际变化，对夏季降水的年际变化模拟较差，对冬季模拟较好。  相似文献   

13.
We investigate how well the variability of extreme daily precipitation events across the United Kingdom is represented in a set of regional climate models and the E-OBS gridded data set. Instead of simply evaluating the climatologies of extreme precipitation measures, we develop an approach to validate the representation of physical mechanisms controlling extreme precipitation variability. In part I of this study we applied a statistical model to investigate the influence of the synoptic scale atmospheric circulation on extreme precipitation using observational rain gauge data. More specifically, airflow strength, direction and vorticity are used as predictors for the parameters of the generalised extreme value (GEV) distribution of local precipitation extremes. Here we employ this statistical model for our validation study. In a first step, the statistical model is calibrated against a gridded precipitation data set provided by the UK Met Office. In a second step, the same statistical model is calibrated against 14 ERA40 driven 25?km resolution RCMs from the ENSEMBLES project and the E-OBS gridded data set. Validation indices describing relevant physical mechanisms are derived from the statistical models for observations and RCMs and are compared using pattern standard deviation, pattern correlation and centered pattern root mean squared error as validation measures. The results for the different RCMs and E-OBS are visualised using Taylor diagrams. We show that the RCMs adequately simulate moderately extreme precipitation and the influence of airflow strength and vorticity on precipitation extremes, but show deficits in representing the influence of airflow direction. Also very rare extremes are misrepresented, but this result is afflicted with a high uncertainty. E-OBS shows considerable biases, in particular in regions of sparse data. The proposed approach might be used to validate other physical relationships in regional as well as global climate models.  相似文献   

14.
Summary This study investigates the capabilities of two regional models (the ICTP RegCM3 and the climate version of the CPTEC Eta model – EtaClim) in simulating the mean climatological features of the summer quasi-stationary circulations over South America. Comparing the results with the NCEP/DOE reanalysis II data it is seen that the RegCM3 simulates a weaker and southward shifted Bolivian high (BH). But, the Nordeste low (NL) is located close to its climatological position. In the EtaClim the position of the BH is reproduced well, but the NL is shifted towards the interior of the continent. To the east of Andes, the RegCM3 simulates a weaker low level jet and a weaker basic flow from the tropical Atlantic to Amazonia while they are stronger in the EtaClim. In general, the RegCM3 and EtaClim show, respectively a negative and positive bias in the surface temperature in almost all regions of South America. For both models, the correlation coefficients between the simulated precipitation and the GPCP data are high over most of South America. Although the RegCM3 and EtaClim overestimate the precipitation in the Andes region they show a negative bias in general over the entire South America. The simulations of upper and lower level circulations and precipitation fields in EtaClim were better than that of the RegCM3. In central Amazonia both models were unable to simulate the precipitation correctly. The results showed that although the RegCM3 and EtaClim are capable of simulating the main climatological features of the summer climate over South America, there are areas which need improvement. This indicates that the models must be more adequately tuned in order to give reliable predictions in the different regions of South America.  相似文献   

15.
Changes in indices related to frost and snow in Europe by the end of the twenty-first century were analyzed based on experiments performed with seven regional climate models (RCMs). All the RCMs regionalized information from the same general circulation model (GCM), applying the IPCC-SRES A2 radiative forcing scenario. In addition, some simulations used SRES B2 radiative forcing and/or boundary conditions provided by an alternative GCM. Ice cover over the Baltic Sea was examined using a statistical model that related the annual maximum extent of ice to wintertime coastal temperatures. Fewer days with frost and snow, shorter frost seasons, a smaller liquid water equivalent of snow, and milder sea ice conditions were produced by all model simulations, irrespective of the forcing scenario and the driving GCM. The projected changes have implications across a diverse range of human activities. Details of the projections were subject to differences in RCM design, deviations between the boundary conditions of the driving GCMs, uncertainties in future emissions and random effects due to internal climate variability. A larger number of GCMs as drivers of the RCMs would most likely have resulted in somewhat wider ranges in the frost, snow and sea ice estimates than those presented in this paper.  相似文献   

16.
The aim of this paper is to investigate different aspects of the seasonal-to-interannual temperature variability in Eastern Patagonia, the southernmost area of South America, east of the Andes Cordillera. Homogenous regions of seasonal variability and the atmospheric circulation patterns associated with warm and cold conditions in each of them are described in this study. Relationships between temperature in Eastern Patagonia and that registered in other areas of southern South America are also addressed. Results show that the northern and southern areas of Eastern Patagonia have different temperature variability in summer and autumn whereas the temperature variability tends to be more homogeneous within the region during winter and spring. Warm (cold) conditions in the northern areas are associated with reinforced (weakened) westerlies in summer, winter and spring whereas northerly (southerly) advections of warm (cold) air toward the region produce such conditions in autumn. Temperature in the southern portion of Eastern Patagonia is affected by anticyclonic (cyclonic) anomalies that enhance (reduce) the incoming solar radiation and induce reinforced (weakened) westerlies promoting warm (cold) conditions in the region. Furthermore, cyclonic (anticyclonic) anomalies at subpolar latitudes hinder (favor) outbreaks of cold air increasing (decreasing) the temperature over areas of Eastern Patagonia. The circulation anomalies associated with warm (cold) conditions in Eastern Patagonia also promote cold (warm) conditions over areas of northern Argentina, Paraguay and southern Brazil. Consequently, a dipole of temperature is detected in southern South America with centers of opposite sign over these regions.  相似文献   

17.
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   

18.
To enable downscaling of seasonal prediction and climate change scenarios, long-term baseline regional climatologies which employ global model forcing are needed for South America. As a first step in this process, this work examines climatological integrations with a regional climate model using a continental scale domain nested in both reanalysis data and multiple realizations of an atmospheric general circulation model (GCM). The analysis presents an evaluation of the nested model simulated large scale circulation, mean annual cycle and interannual variability which is compared against observational estimates and also with the driving GCM for the Northeast, Amazon, Monsoon and Southeast regions of South America. Results indicate that the regional climate model simulates the annual cycle of precipitation well in the Northeast region and Monsoon regions; it exhibits a dry bias during winter (July–September) in the Southeast, and simulates a semi-annual cycle with a dry bias in summer (December–February) in the Amazon region. There is little difference in the annual cycle between the GCM and renalyses driven simulations, however, substantial differences are seen in the interannual variability. Despite the biases in the annual cycle, the regional model captures much of the interannual variability observed in the Northeast, Southeast and Amazon regions. In the Monsoon region, where remote influences are weak, the regional model improves upon the GCM, though neither show substantial predictability. We conclude that in regions where remote influences are strong and the global model performs well it is difficult for the regional model to improve the large scale climatological features, indeed the regional model may degrade the simulation. Where remote forcing is weak and local processes dominate, there is some potential for the regional model to add value. This, however, will require improvments in physical parameterizations for high resolution tropical simulations.  相似文献   

19.
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20.
In recent decades, the need of future climate information at local scales have pushed the climate modelling community to perform increasingly higher resolution simulations and to develop alternative approaches to obtain fine-scale climatic information. In this article, various nested regional climate model (RCM) simulations have been used to try to identify regions across North America where high-resolution downscaling generates fine-scale details in the climate projection derived using the “delta method”. Two necessary conditions were identified for an RCM to produce added value (AV) over lower resolution atmosphere-ocean general circulation models in the fine-scale component of the climate change (CC) signal. First, the RCM-derived CC signal must contain some non-negligible fine-scale information—independently of the RCM ability to produce AV in the present climate. Second, the uncertainty related with the estimation of this fine-scale information should be relatively small compared with the information itself in order to suggest that RCMs are able to simulate robust fine-scale features in the CC signal. Clearly, considering necessary (but not sufficient) conditions means that we are studying the “potential” of RCMs to add value instead of the AV, which preempts and avoids any discussion of the actual skill and hence the need for hindcast comparisons. The analysis concentrates on the CC signal obtained from the seasonal-averaged temperature and precipitation fields and shows that the fine-scale variability of the CC signal is generally small compared to its large-scale component, suggesting that little AV can be expected for the time-averaged fields. For the temperature variable, the largest potential for fine-scale added value appears in coastal regions mainly related with differential warming in land and oceanic surfaces. Fine-scale features can account for nearly 60 % of the total CC signal in some coastal regions although for most regions the fine scale contributions to the total CC signal are of around ～5 %. For the precipitation variable, fine scales contribute to a change of generally less than 15 % of the seasonal-averaged precipitation in present climate with a continental North American average of ～5 % in both summer and winter seasons. In the case of precipitation, uncertainty due to sampling issues may further dilute the information present in the downscaled fine scales. These results suggest that users of RCM simulations for climate change studies in a delta method framework have little high-resolution information to gain from RCMs at least if they limit themselves to the study of first-order statistical moments. Other possible benefits arising from the use of RCMs—such as in the large scale of the downscaled fields– were not explored in this research.  相似文献   

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