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1.
In this study, we investigate the response of a Regional Climate Model (RCM) to errors in the atmospheric data used as lateral
boundary conditions (LBCs) using a perfect-model framework nick-named the “Big-Brother Experiment” (BBE). The BBE has been
designed to evaluate the errors due to the nesting process excluding other model errors. First, a high-resolution (45 km)
RCM simulation is made over a large domain. This simulation, called the Perfect Big Brother (PBB), is driven by the National
Centres for Environmental Prediction (NCEP) reanalyses; it serves as reference virtual-reality climate to which other RCM
runs will be compared. Next, errors of adjustable magnitude are introduced by performing RCM simulations with increasingly
larger domains at lower horizontal resolution (90 km mesh). Such simulations with errors typical of today’s Coupled General
Circulation Models (CGCM) are called the Imperfect Big-Brother (IBB) simulations. After removing small scales in order to
achieve low-resolution typical of today’s CGCMs, they are used as LBCs for driving smaller domain high-resolution RCM runs;
these small-domain high-resolution simulations are called Little-Brother (LB) simulations. The difference between the climate
statistics of the IBB and those of PBB simulations mimic errors of the driving model. The comparison of climate statistics
of the LB to those of the PBB provides an estimate of the errors resulting solely from nesting with imperfect LBCs. The simulations
are performed over the East Coast of North America using the Canadian RCM, for five consecutive February months (from 1990
to 1994). It is found that the errors contained in the large scales of the IBB driving data are transmitted to and reproduced
with little changes by the LB. In general, the LB restores a great part of the IBB small-scale errors, even if they do not
take part in the nesting process. The small scales are seen to improve slightly in regions with important orographic forcing
due to the finer resolution of the RCM. However, when the large scales of the driving model have errors, the small scales
developed by the LB have errors as well, suggesting that the large scales precondition the small scales. In order to obtain
correct small scales, it is necessary to provide the accurate large-scale circulation at the lateral boundary of the RCM. 相似文献
2.
The Big Brother Experiment methodology of Denis et al. (Clim Dyn 18:627-646, 2002) is applied to test the downscaling ability of a one-way nested regional climate model. This methodology consists of first obtaining a reference climate by performing a large domain, high resolution regional climate model simulation—the Big Brother. The small scales are then filtered out from the Big Brother’s output to produce a data set whose effective resolution is comparable to those of the data sets typically used to drive regional climate models. This filtered data set is then used to drive the same nested regional climate model, integrated over a smaller domain, but at the same high resolution as the Big Brother - the Little Brother. Any differences can only be attributed either to errors associated with the nesting strategy and downscaling technique, or to inherent unpredictability of the system, but not to model errors. This methodology was applied to the National Center for Environmental Prediction Regional Spectral Model over a tropical domain for a 1-month simulation period. The Little Brother reproduced most fields of the Big Brother quite well, with the important exception of the small-scale component of the precipitation field, which was poorly reproduced. Sensitivity experiments indicated that the poor agreement of the precipitation at these scales in a tropical domain was due primarily to the behavior of convective processes, and is specific to the Big Brother Experiment on the tropical domain. Much better agreement for the small-scale precipitation component was obtained in an extratropical winter case, suggesting that one factor explaining the tropical result is the importance of convective processes in controlling precipitation, versus the greater importance of large-scale dynamics in the winter extratropics. In the tropical case, results from two ensembles of five 3-month seasonal simulations forced by GCM output suggest a considerably greater predictability for the small-scale stationary component of tropical precipitation than did the Big Brother Experiment. 相似文献
3.
The downscaling ability of a one-way nested regional climate model (RCM) is evaluated over a region subjected to strong surface forcing: the west of North America. The sensitivity of the results to the horizontal resolution jump and updating frequency of the lateral boundary conditions are also evaluated. In order to accomplish this, a perfect-model approach nicknamed the Big-Brother Experiment (BBE) was followed. The experimental protocol consists of first establishing a virtual-reality reference climate over a fairly large area by using the Canadian RCM with grid spacing of 45 km nested within NCEP analyses. The resolution of the simulated climate is then degraded to resemble that of operational general circulation models (GCM) or observation analyses by removing small scales; the filtered fields are then used to drive the same regional model, but over a smaller sub-area. This set-up permits a comparison between two simulations of the same RCM over a common region. The Big-Brother Experiment has been carried out for four winter months over the west coast of North America. The results show that complex topography and coastline have a strong positive impact on the downscaling ability of the one-way nesting technique. These surface forcings, found to be responsible for a large part of small-scale climate features, act primarily locally and yield good climate reproducibility. Precipitation over the Rocky Mountains region is a field in which such effect is found and for which the nesting technique displays significant downscaling ability. The best downscaling ability is obtained when the ratio of spatial resolution between the nested model and the nesting fields is less than 12, and when the update frequency is more than twice a day. Decreasing the spatial resolution jump from a ratio of 12 to six has more benefits on the climate reproducibility than a reduction of spatial resolution jump from two to one. Also, it is found that an update frequency of four times a day leads to a better downscaling than twice a day when a ratio of spatial resolution of one is used. On the other hand, no improvement was found by using high-temporal resolution when the driving fields were degraded in terms of spatial resolution. 相似文献
4.
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
5.
The downscaling ability of a one-way nested regional climate model (RCM) is evaluated over a region subjected to strong surface
forcing: the west of North America. The sensitivity of the results to the horizontal resolution jump and updating frequency
of the lateral boundary conditions are also evaluated. In order to accomplish this, a perfect-model approach nicknamed the
Big-Brother Experiment (BBE) was followed. The experimental protocol consists of first establishing a virtual-reality reference
climate over a fairly large area by using the Canadian RCM with grid spacing of 45 km nested within NCEP analyses. The resolution
of the simulated climate is then degraded to resemble that of operational general circulation models (GCM) or observation
analyses by removing small scales; the filtered fields are then used to drive the same regional model, but over a smaller
sub-area. This set-up permits a comparison between two simulations of the same RCM over a common region. The Big-Brother Experiment
has been carried out for four winter months over the west coast of North America. The results show that complex topography
and coastline have a strong positive impact on the downscaling ability of the one-way nesting technique. These surface forcings,
found to be responsible for a large part of small-scale climate features, act primarily locally and yield good climate reproducibility.
Precipitation over the Rocky Mountains region is a field in which such effect is found and for which the nesting technique
displays significant downscaling ability. The best downscaling ability is obtained when the ratio of spatial resolution between
the nested model and the nesting fields is less than 12, and when the update frequency is more than twice a day. Decreasing
the spatial resolution jump from a ratio of 12 to six has more benefits on the climate reproducibility than a reduction of
spatial resolution jump from two to one. Also, it is found that an update frequency of four times a day leads to a better
downscaling than twice a day when a ratio of spatial resolution of one is used. On the other hand, no improvement was found
by using high-temporal resolution when the driving fields were degraded in terms of spatial resolution.
Figure legends were missing in original article. Climate Dynamics (2005) 23: 473-493. The complete article is given here.
DOI: 10.1007/s00382-004-0438-5 相似文献
6.
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
7.
The ability of a nested model to accurately simulate the subarctic climate is studied here. Two issues have been investigated: Model??s internal variability (IV) and the impact of domain size (DS). For this purpose we combine the ??perfect model?? approach, Big-Brother Experiment (BBE) (Denis et al. in Clim Dyn 18:627?C646, 2002) with the ensemble of simulations. The advantage of this framework is the possibility to study small-scale climate features that constitute the main added value of RCM. The effects of the DS on result were studied by employing two Little-Brother (LB) domain sizes. IV has been evaluated by introducing small differences in initial conditions in an ensemble of 20 simulations over each LB. Results confirm previous findings that the IV is more important over the larger domain of integration. The temporal evolution over two domain sizes is rather different and depends strongly on the synoptic situation. Small-scales solution over the larger domain diverges freely from the boundary forcing in some periods. Over the smaller domain, the amplitude of small-scale transient eddies is systematically underestimated, especially at higher altitude characterized by the strongest winds along the storm tracks. Over the larger domain, the amplitude of small-scale transient eddies is better represented. However, the weaker control by the lateral boundaries over the larger domain results in solutions with large internal variability. As a result, the ensemble average strongly underestimates the transient-eddy variance due to partial destructive interference of individual ensemble member solutions. 相似文献
8.
Nested Limited-Area Models require driving data to define their lateral boundary conditions (LBC). The optimal choice of domain size and the repercussions of LBC errors on Regional Climate Model (RCM) simulations are important issues in dynamical downscaling work. The main objective of this paper is to investigate the effect of domain size, particularly on the larger scales, and to question whether an RCM, when run over very large domains, can actually improve the large scales compared to those of the driving data. This study is performed with a detailed atmospheric model in its global and regional configurations, using the “Imperfect Big-Brother” (IBB) protocol. The ERA-Interim reanalyses and five global simulations are used to drive RCM simulations for five winter seasons, on four domain sizes centred over the North American continent. Three variables are investigated: precipitation, specific humidity and zonal wind component. The results following the IBB protocol show that, when an RCM is driven by perfect LBC, its skill at reproducing the large scales decreases with increasing the domain of integration, but the errors remain small even for very large domains. On the other hand, when driven by LBC that contain errors, RCMs can bring some reduction of errors in large scales when very large domains are used. The improvement is found especially in the amplitude of patterns of both the stationary and the intra-seasonal transient components. When large errors are present in the LBC, however, these are only partly corrected by the RCM. Although results showed that an RCM can have some skill at improving imperfect large scales supplied as driving LBC, the main added value of an RCM is provided by its small scales and its skill to simulate extreme events, particularly for precipitation. Under the IBB protocol all RCM simulations were fairly skilful at reproducing small scales statistics, although the skill decreased with increasing LBC errors. Coarse-resolution model simulations have difficulties in simulating heavy precipitation events, and as a result their precipitation distributions are systematically shifted toward smaller intensity. Under the IBB protocol, all RCM simulations have distributions very similar to the reference field, being little affected by LBC errors, and no significant differences were found between the small scales statistics and the precipitation distributions obtained over different RCM domains. 相似文献
9.
嵌套域大小对区域气候模式模拟效果的影响 总被引：3，自引：3，他引：3
This paper presents a numerical study on the 1998 summer rainfall over the Yangtze River valley in central and eastern China, addressing effect of a nested area size on simulations in terms of the technique of nesting a regional climate model (RCM) upon a general circulation model (GCM). Evidence suggests that the size exerts greater impacts upon regional climate of the country, revealing that a larger nested size is su perior to a small one for simulation in mitigating errors of GCM-provided lateral boundary forcing. Also,simulations show that the RCM should incorporate regions of climate systems of great importance into study and a low-resolution GCM yields more pronounced errors as a rule when used in the research of the Tibetan Plateau, and, in contrast, our PσRCM can do a good job in describing the plateau′s role in a more realistic and accurate way. It is for this reason that the tableland should be included in the nested area when the RCM is employed to investigate the regional climate. Our PσRCM nesting upon a GCM reaches morerealistic results compared to a single GCM used. 相似文献
10.
Comparison of a very-fine-resolution GCM with RCM dynamical downscaling in simulating climate in China 总被引：2，自引：0，他引：2
Regional climate simulation can generally be improved by using an RCM nested within a coarser-resolution GCM. However, whether or not it can also be improved by the direct use of a state-of-the-art GCM with very fine resolution, close to that of an RCM, and, if so, which is the better approach, are open questions. These questions are important for understanding and using these two kinds of simulation approaches, but have not yet been investigated. Accordingly, the present reported work compared simulation results over China from a very-fine-resolution GCM (VFRGCM) and from RCM dynamical downscaling. The results showed that: (1) The VFRGCM reproduces the climatologies and trends of both air temperature and precipitation, as well as inter-monthly variations of air temperature in terms of spatial pattern and amount, closer to observations than the coarse-resolution version of the GCM. This is not the case, however, for the inter-monthly variations of precipitation. (2) The VFRGCM captures the climatology, trend, and inter-monthly variation of air temperature, as well as the trend in precipitation, more reasonably than the RCM dynamical downscaling method. (3) The RCM dynamical downscaling method performs better than the VFRGCM in terms of the climatology and inter-monthly variation of precipitation. Overall, the results suggest that VFRGCMs possess great potential with regard to their application in climate simulation in the future, and the RCM dynamical downscaling method is still dominant in terms of regional precipitation simulation. 相似文献
11.
Sensitivity to domain size of mid-latitude summer simulations with a regional climate model 总被引：1，自引：1，他引：0
Martin Leduc René Laprise Mathieu Moretti-Poisson Jean-Philippe Morin 《Climate Dynamics》2011,37(1-2):343-356
The issue of Regional Climate Model (RCM) domain size is studied here by using a perfect-model approach, also known as the Big-Brother experiment. It is known that the control exerted by the lateral boundary conditions (LBC) on nested simulations increases when reducing the domain size. The large-scale component of the simulation that is forced by the LBC influences the small-scale features that develop along the large-scale flow. Small-scale transient eddies need space and time to develop sufficiently however, and small domains can impede their development. Our tests performed over eastern North America in summer reveal that the small-scale features are systematically underestimated over the entire domain, even for domain as large as 140 by 140 grid points. This result differs from that obtained in winter where the small scales were mainly underestimated on the west (inflow) side of the domain. This difference is due to the circulation regime over Eastern Canada, which is characterized by weak and variable flow in summer, but strong and westerly flow in winter. For both seasons, the small-scale transient-eddy amplitudes are systematically underestimated at higher levels, but this problem is less severe in summer. Overall the model is more skilful in regenerating the small scales in summer than in winter for comparable domain sizes, which can be related to the weaker summer flow and stronger physical processes occurring in this season. 相似文献
12.
Dynamical downscaling: Fundamental issues from an NWP point of view and recommendations 总被引：4，自引：0，他引：4
Dynamical downscaling has been recognized as a useful tool not only for the climate community, but also for associated application communities such as the environmental and hydrological societies. Although climate projection data are available in lower-resolution general circulation models (GCMs), higher-resolution climate projections using regional climate models (RCMs) have been obtained over various regions of the globe. Various model outputs from RCMs with a high resolution of even as high as a few km have become available with heavy weight on applications. However, from a scientific point of view in numerical atmospheric modeling, it is not clear how to objectively judge the degree of added value in the RCM output against the corresponding GCM results. A key factor responsible for skepticism is based on the fundamental limitations in the nesting approach between GCMs and RCMs. In this article, we review the current status of the dynamical downscaling for climate prediction, focusing on basic assumptions that are scrutinized from a numerical weather prediction (NWP) point of view. Uncertainties in downscaling due to the inconsistencies in the physics packages between GCMs and RCMs were revealed. Recommendations on how to tackle the ultimate goal of dynamical downscaling were also described. 相似文献
13.
Potential for added value to downscaled climate extremes over Korea by increased resolution of a regional climate model 总被引：1，自引：0，他引：1
This study estimates the potential for added value in dynamical downscaling by increasing the spatial resolution of the regional climate model (RCM) over Korea. The Global/Regional Integrated Model System—Regional Model Program with two different resolutions is employed as the RCM. Large-scale forcing is given by a historical simulation of a global climate model, namely the Hadley Center Global Environmental Model version 2. As a standard procedure, the reproducibility of the RCM results for the present climate is evaluated against the reanalysis and observation datasets. It is confirmed that the RCM adequately reproduces the major characteristics of the observed atmospheric conditions and the increased resolution of the RCM contributes to the improvement of simulated surface variables including precipitation and temperature. For the added-value assessment, the interannual and daily variabilities of precipitation, temperature are compared between the different resolution RCM experiments. It is distinctly shown that variabilities are additionally described as the spatial resolution becomes higher. The increased resolution also contributes to capture the extreme weather conditions, such as heavy rainfall events and sweltering days. The enhanced added value is more evident for the precipitation than for the temperature, which stands for a usefulness of the high-resolution RCM especially for diagnosing potential hazard related to heavy rainfall. The results of this study assure the effectiveness of increasing spatial resolution of the RCM for detecting climate extremes and also provide credibility to the current climate simulation for future projection studies. 相似文献
14.
Performance of a regional climate model (RCM), WRF, for downscaling East Asian summer season climate is investigated based on 11-summer integrations associated with different climate conditions with reanalysis data as the lateral boundary conditions. It is found that while the RCM is essentially unable to improve large-scale circulation patterns in the upper troposphere for most years, it is able to simulate better lower-level meridional moisture transport in the East Asian summer monsoon. For precipitation downscaling, the RCM produces more realistic magnitude of the interannual variation in most areas of East Asia than that in the reanalysis. Furthermore, the RCM significantly improves the spatial pattern of summer rainfall over dry inland areas and mountainous areas, such as Mongolia and the Tibetan Plateau. Meanwhile, it reduces the wet bias over southeast China. Over Mongolia, however, the performance of precipitation downscaling strongly depends on the year: the WRF is skillful for normal and wet years, but not for dry years, which suggests that land surface processes play an important role in downscaling ability. Over the dry area of North China, the WRF shows the worst performance. Additional sensitivity experiments testing land effects in downscaling suggest the initial soil moisture condition and representation of land surface processes with different schemes are sources of uncertainty for precipitation downscaling. Correction of initial soil moisture using the climatology dataset from GSWP-2 is a useful approach to robustly reducing wet bias in inland areas as well as to improve spatial distribution of precipitation. Despite the improvement on RCM downscaling, regional analyses reveal that accurate simulation of precipitation over East China, where the precipitation pattern is strongly influenced by the activity of the Meiyu/Baiu rainfall band, is difficult. Since the location of the rainfall band is closely associated with both lower-level meridional moisture transport and upper-level circulation structures, it is necessary to have realistic upper-air circulation patterns in the RCM as well as lower-level moisture transport in order to improve the circulation-associated convective rainfall band in East Asia. 相似文献
15.
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
16.
Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs 总被引：6，自引：3，他引：6
Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel ClimateModel (PCM), and the implications of the comparison for a future(2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregation (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly(at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at 1/2-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology. 相似文献
17.
Regional climate model sensitivity to domain size 总被引：3，自引：1，他引：2
Regional climate models are increasingly used to add small-scale features that are not present in their lateral boundary conditions
(LBC). It is well known that the limited area over which a model is integrated must be large enough to allow the full development
of small-scale features. On the other hand, integrations on very large domains have shown important departures from the driving
data, unless large scale nudging is applied. The issue of domain size is studied here by using the “perfect model” approach.
This method consists first of generating a high-resolution climatic simulation, nicknamed big brother (BB), over a large domain
of integration. The next step is to degrade this dataset with a low-pass filter emulating the usual coarse-resolution LBC.
The filtered nesting data (FBB) are hence used to drive a set of four simulations (LBs for Little Brothers), with the same
model, but on progressively smaller domain sizes. The LB statistics for a climate sample of four winter months are compared
with BB over a common region. The time average (stationary) and transient-eddy standard deviation patterns of the LB atmospheric
fields generally improve in terms of spatial correlation with the reference (BB) when domain gets smaller. The extraction
of the small-scale features by using a spectral filter allows detecting important underestimations of the transient-eddy variability
in the vicinity of the inflow boundary, which can penalize the use of small domains (less than 100 × 100 grid points). The
permanent “spatial spin-up” corresponds to the characteristic distance that the large-scale flow needs to travel before developing
small-scale features. The spin-up distance tends to grow in size at higher levels in the atmosphere. 相似文献
18.
The simulation of hydrological consequences of climate change has received increasing attention from the hydrology and land-surface modelling communities. There have been many studies of climate-change effects on hydrology and water resources which usually consist of three steps： （1） use of general circulation models （GCMs） to provide future global climate scenarios under the effect of increasing greenhouse gases, （2） use of downscaling techniques （both nested regional climate models, RCMs, and statistical methods） for ＂downscaling＂ the GCM output to the scales compatible with hydrological models, and （3） use of hydrologic models to simulate the effects of climate change on hydrological regimes at various scales. Great progress has been achieved in all three steps during the past few years, however, large uncertainties still exist in every stage of such study. This paper first reviews the present achievements in this field and then discusses the challenges for future studies of the hydrological impacts of climate change. 相似文献
19.
区域和全球模式的嵌套技术
及其长期积分试验 总被引：7，自引：0，他引：7
将区域模式嵌入澳大利亚CSIRO (Commonwealth Scientific and Industrial Research Organization）的全球模式中,并将其应用于区域模式的长期气候积分试验。模拟结果表明,当区域与全球模式嵌套时,边界吸收问题十分重要,由区域模式得到的高分辨率大尺度环流形式在边界上必须与全球模式提供的强迫一致,同时区域模式必须给出基于模式内部物理过程产生的高分辨信息。因此,在嵌套过程中,必须仔细考虑缓冲区的设置,使大尺度强迫与中尺度特征充分混合,既保持区域模式内外的一致性,又使区域内部中尺度强迫物理过程得到充分发展。将区域模式与澳大利亚CSIRO的9层21波三角形截断谱模式嵌套后,完成了连续3年的区域气候模式积分。模拟结果表明,由于区域模式较好地刻划了区域尺度的地形、下垫面和海岸线分布等的细节特征,模拟的区域气候特征比全球模式有较大的改进,尤其是对季风降水的模拟,区域模式明显改进了全球模式的模拟结果。 相似文献
20.
Ida Bülow Gregersen Hjalte Jomo Danielsen Sørup Henrik Madsen Dan Rosbjerg Peter Steen Mikkelsen Karsten Arnbjerg-Nielsen 《Climatic change》2013,118(3-4):783-797
Climate change is expected to influence the occurrence and magnitude of rainfall extremes and hence the flood risks in cities. Major impacts of an increased pluvial flood risk are expected to occur at hourly and sub-hourly resolutions. This makes convective storms the dominant rainfall type in relation to urban flooding. The present study focuses on high-resolution regional climate model (RCM) skill in simulating sub-daily rainfall extremes. Temporal and spatial characteristics of output from three different RCM simulations with 25 km resolution are compared to point rainfall extremes estimated from observed data. The applied RCM data sets represent two different models and two different types of forcing. Temporal changes in observed extreme point rainfall are partly reproduced by the RCM RACMO when forced by ERA40 re-analysis data. Two ECHAM forced simulations show similar increases in the occurrence of rainfall extremes of over a 150-year period, but significantly different changes in the magnitudes. The physical processes behind convective rainfall extremes generate a distinctive spatial inter-site correlation structure for extreme events. All analysed RCM rainfall extremes, however, show a clear deviation from this correlation structure for sub-daily rainfalls, partly because RCM output represents areal rainfall intensities and partly due to well-known inadequacies in the convective parameterization of RCMs. The results highlight the problem urban designers are facing when using RCM output. The paper takes the first step towards a methodology by which RCM performance and other downscaling methods can be assessed in relation to the simulation of short-duration rainfall extremes. 相似文献