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1.
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
2.
Downscaling ability of one-way nested regional climate models: the Big-Brother Experiment 总被引：8，自引：4，他引：4
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
3.
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
4.
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
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.
A suite of high-resolution (10 km) simulations were performed with the International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM3) to study the effect of various lateral boundary conditions (LBCs), domain size, and intermediate domains on simulated precipitation over the Great Alpine Region. The boundary conditions used were ECMWF ERA-Interim Reanalysis with grid spacing 0.75°, the ECMWF ERA-40 Reanalysis with grid spacing 1.125 and 2.5°, and finally the 2.5° NCEP/DOE AMIP-II Reanalysis. The model was run in one-way nesting mode with direct nesting of the high-resolution RCM (horizontal grid spacing Δx = 10 km) with driving reanalysis, with one intermediate resolution nest (Δx = 30 km) between high-resolution RCM and reanalysis forcings, and also with two intermediate resolution nests (Δx = 90 km and Δx = 30 km) for simulations forced with LBC of resolution 2.5°. Additionally, the impact of domain size was investigated. The results of multiple simulations were evaluated using different analysis techniques, e.g., Taylor diagram and a newly defined useful statistical parameter, called Skill-Score, for evaluation of daily precipitation simulated by the model. It has been found that domain size has the major impact on the results, while different resolution and versions of LBCs, e.g., 1.125° ERA40 and 0.7° ERA-Interim, do not produce significantly different results. It is also noticed that direct nesting with reasonable domain size, seems to be the most adequate method for reproducing precipitation over complex terrain, while introducing intermediate resolution nests seems to deteriorate the results. 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.
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
9.
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
10.
High-resolution simulations of West African climate using regional climate model (RegCM3) with different lateral boundary conditions 总被引：3，自引：1，他引：2
M. B. Sylla A. T. Gaye J. S. Pal G. S. Jenkins X. Q. Bi 《Theoretical and Applied Climatology》2009,98(3-4):293-314
To downscale climate change scenarios, long-term regional climatologies employing global model forcing are needed for West Africa. As a first step, this work examines present-day integrations (1981–2000) with a regional climate model (RCM) over West Africa nested in both reanalysis data and output from a coupled atmospheric–ocean general circulation model (AOGCM). Precipitation and temperature from both simulations are compared to the Climate Research Unit observations. Their spatial distributions are shown to be realistic. Annual cycles are considerably correlated. Simulations are also evaluated with respect to the driving large-scale fields. RCM offers some improvements compared to the AOGCM driving field. Evaluation of seasonal precipitation biases reveals that RCM dry biases are highest on June–August around mountains. They are associated to cold biases in temperature which, in turn, are connected to wet biases in precipitation outside orographic zones. Biases brought through AOGCM forcing are relatively low. Despite these errors, the simulations produce encouraging results and show the ability of the AOGCM to drive the RCM for future projections. 相似文献
11.
Sources of systematic errors in the climatology of a regional climate model over Europe 总被引：2，自引：2，他引：0
Two ten-year simulations made with a European regional climate model (RCM) are compared. They are driven by the same observed
sea surface temperatures but use different lateral boundary forcing. For one simulation, RCM AMIP, this forcing is obtained
from a standard integration of a global general circulation model (GCM AMIP), whereas for the other simulation, RCM ASSIM,
it is derived from a time series of operational analyses. The archive of analysis fields (surface pressure plus winds and
temperatures on various pressure levels) is not sufficiently comprehensive to provide directly the full set of driving fields
required for the RCM (in particular, no moisture fields are present), so these are obtained via a GCM integration, GCM ASSIM,
in which the model is continuously relaxed towards the analysis fields using a data assimilation technique. Errors in RCM
AMIP can arise either from the internal RCM physics or from errors in the lateral boundary forcing inherited from GCM AMIP.
Errors in RCM ASSIM can arise from the internal RCM physics or the boundary moisture forcing but not from the driving circulation.
Although previous studies have considered RCM integrations driven either by output from standard GCM integrations or operational
analyses, our study is the first to compare parallel integrations of each type. This allows the total systematic error in
an RCM integration driven by standard GCM output to be partitioned into components arising from the driving circulation and
the internal RCM physics. These components indicate the scope for reducing regional simulation biases by improving either
the driving GCM or the RCM itself. The results relate mainly to elements of surface climate likely to be influenced by both
the driving circulation and regional physical processes operating in the RCM. For cloud cover, errors are found to arise largely
from the internal RCM physics. Values are too low despite a positive relative humidity bias, indicating shortcomings in the
parametrisation scheme used to calculate cloud cover. In summer, surface temperature and precipitation errors are also explained
principally by regional processes. For example excessive solar heating leads to anomalously high surface temperatures over
southern Europe and excessive drying of the soil reduces precipitation in the south eastern sector of the domain. The lateral
boundary forcing reduces precipitation in the south eastern sector of the domain. The lateral boundary forcing also exerts
some influence, mainly via a tropospheric cold bias which partially offsets the warming over southern Europe and also increases
precipitation. In other seasons the lateral boundary forcing and the regional physics both contribute significantly to the
errors in surface temperature and precipitation. In winter the boundary forcing (apart from moisture) is responsible for about
60% of the total error variance for temperature and about 40% for precipitation, due to the cold bias and circulation errors
such as a southward shift in the storm track. The remaining errors arise from the regional physics, although for precipitation
an excessive supply of moisture from the lateral boundaries also contributes. The skill of the mesoscale component of the
surface temperature and precipitation distributions exceeds previous estimates, due to more realistic observed climatology.
The mesoscale patterns are very similar in the two RCM simulations indicating that errors in the simulation of fine scale
detail arise mainly from inadequate representations of local forcings rather than errors in the large-scale circulation. Circulation
errors in RCM AMIP (e.g. cold bias, southward shift of storm track) are also present in GCM AMIP, but are largely absent in
RCM ASSIM except in summer. This confirms evidence from previous work that the key to reducing most circulation errors in
the RCM lies in improving the driving GCM. Regional processes only make a major contribution to circulation errors in summer,
when reduced advection from the boundaries allows errors in surface temperature to be transmitted more effectively into the
troposphere. Finally, we find evidence of error balances in the GCM which act to minimise biases in important climatological
variables. This reflects tuning of the model physics at GCM resolution. In order to achieve simultaneous optimisation of the
RCM and GCM at widely differing resolutions it may be necessary to introduce explicit scale dependences into some aspects
of the physics.
Received: 17 September 1997/Accepted: 10 March 1998 相似文献
12.
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
13.
M. Fulakeza L. M. Druyan T. N. Krishnamurti 《Meteorology and Atmospheric Physics》2002,79(1-2):105-126
Summary
A regional climate model (RCM) is described which incorporates an improved scheme for soil moisture availability (SMA) compared
to an earlier version. The improvement introduces a sensitivity of SMA to soil type, vegetation cover and ground albedo, making
the model more adaptable to divers regions. In addition, the interactive SMA depends on past precipitation, ground temperature
and terrain relief. Six RCM simulations of the monthly mean climate over southern Africa are performed at 0.5° grid spacing.
Improvements in the RCM climate simulations compared to control runs are attributed to the newer SMA scheme. Only a slight
improvement in skill results from driving the RCM with observational analyses as opposed to GCM “predicted” lateral boundary
conditions. The high spatial resolution of the RCM provides a distinct advantage in the simulated spatial distribution of
precipitation compared with a global model run at an effective grid spacing of 2.8°. The mesoscale precipitation signal in
the RCM simulations is more dominant during the rather dry December 1982 than during December 1988. The improved SMA scheme
contributed to a realistic partition between latent and sensible heat fluxes at the ground-atmosphere boundary and consequently
a realistic diurnal cycle of ground temperature. Simulated differences in the spatial distribution of rainfall between December
1982 and December 1988 are more realistic with the improved scheme.
Received June 28, 2001 Revised August 27, 2001 相似文献
14.
Atmospheric circulation in regional climate models over Central Europe: links to surface air temperature and the influence of driving data 总被引：1，自引：1，他引：0
The study examines simulation of atmospheric circulation, represented by circulation indices (flow direction, strength and vorticity), and links between circulation and daily surface air temperatures in regional climate models (RCMs) over Central Europe. We explore control simulations of five high-resolution RCMs from the ENSEMBLES project driven by re-analysis (ERA-40) and the same global climate model (ECHAM5 GCM) plus of one RCM (RCA) driven by different GCMs. The aims are to (1) identify errors in RCM-simulated distributions of circulation indices in individual seasons, (2) identify errors in simulated temperatures under particular circulation indices, and (3) compare performance of individual RCMs with respect to the driving data. Although most of the RCMs qualitatively reflect observed distributions of the airflow indices, each produces distributions significantly different from the observations. General biases include overestimation of the frequency of strong flow days and of strong cyclonic vorticity. Some circulation biases obviously propagate from the driving data. ECHAM5 and all simulations driven by ECHAM5 underestimate frequency of easterly flow, mainly in summer. Except for HIRHAM, however, all RCMs driven by ECHAM5 improve on the driving GCM in simulating atmospheric circulation. The influence on circulation characteristics in the nested RCM differs between GCMs, as demonstrated in a set of RCA simulations with different driving data. The driving data control on circulation in RCA is particularly weak for the BCM GCM, in which case RCA substantially modifies (but does not improve) the circulation from the driving data in both winter and summer. Those RCMs with the most distorted atmospheric circulation are HIRHAM driven by ECHAM5 and RCA driven by BCM. Relatively strong relationships between circulation indices and surface air temperatures were found in the observed data for Central Europe. The links differ by season and are usually stronger for daily maxima than minima. RCMs qualitatively reproduce these relationships. Effects of the driving model biases were found on RCMs’ performance in reproducing not only atmospheric circulation but also the links to surface temperature. However, the RCM formulation appears to be more important than the driving data in representing the latter. Differences of the circulation-to-temperature links among the RCA simulations are smaller and the links tend to be more realistic compared to the driving GCMs. 相似文献
15.
A numerical nesting system is developed to simulate wintertime climate of the eastern South Pacific-South America-western
South Atlantic region, and preliminary results are presented. The nesting system consists of a large-scale global atmospheric
general circulation model (GCM) and a regional climate model (RCM). The latter is driven at its boundaries by the GCM. The
particularity of this nesting system is that the GCM itself has a variable horizontal resolution (stretched grid). Our main
purpose is to assess the plausibility of such a technique to improve climate representation over South America. In order to
evaluate how this nesting system represents the main features of the regional circulation, several mean fields have been analyzed.
The global model, despite its relatively low resolution, could simulate reasonably well the more significant large-scale circulation
patterns. The use of the regional model often results in improvements, but not universally. Many of the systematic errors
of the global model are also present in the regional model, although the biases tend to be rectified. Our preliminary results
suggest that nesting technique is a computationally low-cost alternative for simulating regional climate features. However,
additional simulations, parametrizations tuning and further diagnosis are clearly needed to represent local patterns more
precisely.
Received: 18 February 1999 / Accepted: 31 May 2000 相似文献
16.
Biases existing in the lateral boundary conditions (LBCs) influence climate simulations in regional climate models (RCMs). Correcting the biases in global climate model (GCM)-produced LBCs before running RCMs was proposed in previous studies as a possible way to reduce the GCM-related model dependence of future climate projections using RCMs. In this study the ICTP Regional Climate Model Version 4 (RegCM4) is used to investigate the impact of LBC bias correction on projected future changes of regional climate in West Africa. To accomplish this, two types of present versus future simulations are conducted using RegCM4: a control type where both the present and future LBCs are derived directly from the GCM output (as is done in most regional climate downscaling studies); an experiment type where the present-day LBCs are from reanalysis data and future LBCs are derived by combining the reanalysis data and the GCM-projected LBC changes. For each type of simulations, three different sets of LBCs are experimented on: 6-hourly synoptic forcing directly from the reanalysis or GCM, 6-hourly data interpolated from monthly climatology (without diurnal cycle), and 6-hourly data interpolated from the month-specific climatology of diurnal cycles. It is found that the simulations using different LBCs produce similar present-day summer rainfall patterns, but the predicted future changes differ significantly depending on how the LBC bias correction is treated. Specifically, both the bias correction applied at the synoptic scale and the bias correction applied to the monthly interpolated LBCs without diurnal cycle produce a spurious drying signal caused by physical inconsistency in the corrected future LBCs. Interpolated monthly LBCs with diurnal cycle alleviate the problem to a large extent. These results suggest that using bias-corrected LBCs to drive regional climate models may not guarantee reliable future projections although reasonable present climate can be simulated. Physical inconsistencies may be contained in the bias-corrected LBCs, increasing the uncertainties of RCM-produced future projections. 相似文献
17.
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
18.
Simulations of the Indian summer monsoon using a nested regional climate model: domain size experiments 总被引：2，自引：0，他引：2
Seasonal simulations of the Indian summer monsoon using a 50-km regional climate model (RCM) are described. Results from three versions of the RCM distinguished by different domain sizes are compared against those of the driving global general circulation model (AGCM). Precipitation over land is 20% larger in the RCMs due to stronger vertical motions arising from finer horizontal resolution. The resulting increase in condensational heating helps to intensify the monsoon trough relative to the AGCM. The RCM precipitation distributions show a strong orographically forced mesoscale component (similar in each version). This component is not present in the AGCM. The RCMs produce two qualitatively realistic intraseasonal oscillations (ISOs) associated respectively with monsoon depressions which propagate northwestward from the Bay of Bengal and repeated northward migrations of the regional tropical convergence zone. The RCM simulations are relatively insensitive to domain size in several respects: (1) the mean bias relative to the AGCM is similar for all three domains; (2) the variability simulated by the RCM is strongly correlated with that of the driving AGCM on both daily and seasonal time scales, even for the largest domain; (3) the mesoscale features and ISOs are not damped by the relative proximity of the lateral boundaries in the version with the smallest domain. Results (1) and (2) contrast strongly with a previous study for Europe carried out with the same model, probably due to inherent differences between mid-latitude and tropical dynamics. 相似文献
19.
Climate scenarios for the Netherlands are constructed by combining information from global and regional climate models employing
a simplified, conceptual framework of three sources (levels) of uncertainty impacting on predictions of the local climate.
In this framework, the first level of uncertainty is determined by the global radiation balance, resulting in a range of the
projected changes in the global mean temperature. On the regional (1,000–5,000 km) scale, the response of the atmospheric
circulation determines the second important level of uncertainty. The third level of uncertainty, acting mainly on a local
scale of 10 (and less) to 1,000 km, is related to the small-scale processes, like for example those acting in atmospheric
convection, clouds and atmospheric meso-scale circulations—processes that play an important role in extreme events which are
highly relevant for society. Global climate models (GCMs) are the main tools to quantify the first two levels of uncertainty,
while high resolution regional climate models (RCMs) are more suitable to quantify the third level.
Along these lines, results of an ensemble of RCMs, driven by only two GCM boundaries and therefore spanning only a rather
narrow range in future climate predictions, are rescaled to obtain a broader uncertainty range. The rescaling is done by first
disentangling the climate change response in the RCM simulations into a part related to the circulation, and a residual part
which is related to the global temperature rise. Second, these responses are rescaled using the range of the predictions of
global temperature change and circulation change from five GCMs. These GCMs have been selected on their ability to simulate
the present-day circulation, in particular over Europe. For the seasonal means, the rescaled RCM results obey the range in
the GCM ensemble using a high and low emission scenario. Thus, the rescaled RCM results are consistent with the GCM results
for the means, while adding information on the small scales and the extremes. The method can be interpreted as a combined
statistical–dynamical downscaling approach, with the statistical relations based on regional model output. 相似文献
20.
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