Downscaling ability of one-way nested regional climate models: the Big-Brother Experiment

Denis, B.; Laprise, René; Caya, Daniel; Côté, Jean

doi:10.1007/s00382-001-0201-0

Cited by 258 publications

(45 citation statements)

References 33 publications

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“…Current GCMs have spatial resolution on the order of 100-250 km and have the potential to simulate the main characteristics of general circulation at the range of this scale (Shongwe et al 2009). Although GCMs can satisfactorily simulate the atmospheric general circulation at the continental scale, they are not necessarily capable of capturing the detailed processes associated with regionallocal climate variability and changes that are required for regional and national climate change assessments (Giorgi and Mearns 1999;Denis et al 2002;Wang et al 2004;Giorgi et al 2009;Rummukainen 2010). This is particularly true for heterogeneous regions such as eastern Africa, where sub-GCM gridscale variations in topography, vegetation, soils, and coastlines have a significant effect on the climate.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Performance of CORDEX Regional Climate Models in Simulating East African Rainfall

et al. 2013

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This study evaluates the ability of 10 regional climate models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating the characteristics of rainfall patterns over eastern Africa. The seasonal climatology, annual rainfall cycles, and interannual variability of RCM output have been assessed over three homogeneous subregions against a number of observational datasets. The ability of the RCMs in simulating large-scale global climate forcing signals is further assessed by compositing the El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events. It is found that most RCMs reasonably simulate the main features of the rainfall climatology over the three subregions and also reproduce the majority of the documented regional responses to ENSO and IOD forcings. At the same time the analysis shows significant biases in individual models depending on subregion and season; however, the ensemble mean has better agreement with observation than individual models. In general, the analysis herein demonstrates that the multimodel ensemble mean simulates eastern Africa rainfall adequately and can therefore be used for the assessment of future climate projections for the region.

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Section: Introductionmentioning

confidence: 99%

Assessment of the Performance of CORDEX Regional Climate Models in Simulating East African Rainfall

et al. 2013

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“…Here we adopt a commonly used dynamical downscaling technique in which a high-resolution regional climate model (RCM) is driven by time series of lateral boundary conditions (atmospheric surface pressure, wind, temperature and moisture plus chemical species required for the calculation of sulphate aerosol concentrations) and surface boundary conditions (sea surface temperatures and sea ice extents) saved from a previous GCM simulation. Nested RCMs have been shown to generate skilful fine-scale information in idealized predictability studies (Denis et al 2002), and in verification of simulations driven by observed or GCM boundary conditions, for both time averaged climate means (e.g. Christensen et al 1998;Noguer et al 1998) and extreme events (e.g.…”

Section: (I ) Downscaling Transient Changes For Impact Assessments (Bmentioning

confidence: 99%

A methodology for probabilistic predictions of regional climate change from perturbed physics ensembles

Murphy

Booth

Collins

et al. 2007

Phil. Trans. R. Soc. A.

289

254

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A methodology is described for probabilistic predictions of future climate. This is based on a set of ensemble simulations of equilibrium and time-dependent changes, carried out by perturbing poorly constrained parameters controlling key physical and biogeochemical processes in the HadCM3 coupled ocean-atmosphere global climate model. These (ongoing) experiments allow quantification of the effects of earth system modelling uncertainties and internal climate variability on feedbacks likely to exert a significant influence on twenty-first century climate at large regional scales. A further ensemble of regional climate simulations at 25 km resolution is being produced for Europe, allowing the specification of probabilistic predictions at spatial scales required for studies of climate impacts. The ensemble simulations are processed using a set of statistical procedures, the centrepiece of which is a Bayesian statistical framework designed for use with complex but imperfect models. This supports the generation of probabilities constrained by a wide range of observational metrics, and also by expert-specified prior distributions defining the model parameter space. The Bayesian framework also accounts for additional uncertainty introduced by structural modelling errors, which are estimated using our ensembles to predict the results of alternative climate models containing different structural assumptions. This facilitates the generation of probabilistic predictions combining information from perturbed physics and multi-model ensemble simulations. The methodology makes extensive use of emulation and scaling techniques trained on climate model results. These are used to sample the equilibrium response to doubled carbon dioxide at any required point in the parameter space of surface and atmospheric processes, to sample time-dependent changes by combining this information with ensembles sampling uncertainties in the transient response of a wider set of earth system processes, and to sample changes at local scales.The methodology is necessarily dependent on a number of expert choices, which are highlighted throughout the paper.

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“…The first category is the dynamical downscaling. This is based on nesting a high resolution regional climate model (RCM) within GCM and drives it using boundary condition from GCM (Danis et al, 2002). The second category is statistical downscaling.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Use of Moist Potential Vorticity and Moist Potential Vorticity Vector in Describing Annual Cycles of Rainfall over Different Regions in Tanzania

Luhunga

Djolov

2017

Front. Earth Sci.

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Downscaling ability of one-way nested regional climate models: the Big-Brother Experiment

Cited by 258 publications

References 33 publications

Assessment of the Performance of CORDEX Regional Climate Models in Simulating East African Rainfall

Assessment of the Performance of CORDEX Regional Climate Models in Simulating East African Rainfall

A methodology for probabilistic predictions of regional climate change from perturbed physics ensembles

Evaluation of the Use of Moist Potential Vorticity and Moist Potential Vorticity Vector in Describing Annual Cycles of Rainfall over Different Regions in Tanzania

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