sdsm — a decision support tool for the assessment of regional climate change impacts

Wilby, Robert L.; Dawson, Christian W.; Barrow, Elaine

doi:10.1016/s1364-8152(01)00060-3

Cited by 1,220 publications

(1,105 citation statements)

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“…Although appropriate for global-scale studies, this resolution is inadequate for areas with complex terrain, urban areas (which produce highly-localized effects), or impact studies (Wilby et al, 2002;Leung et al, 2004). The use of regional information will be necessary for this study, which examines climate change impacts on air quality in an urban area characterized by complex terrain.…”

Section: Extreme Value Methodsmentioning

confidence: 99%

“…RCMs are similar to GCMs but have a finer output resolution and are focussed on a specific region. Like GCMs, they are computationally demanding and are highly sensitive to input boundary conditions (Wilby et al, 2002).…”

Section: Extreme Value Methodsmentioning

confidence: 99%

“…However, there are a number of uncertainties with downscaled information that stem both from the original GCM and the downscaling process. As with RCMs, SD depends on the validity of the GCM output, and any GCM uncertainties are compounded by the SD process (Wilby et al, 2002). Input data uncertainty from the historical data used in downscaling is another potential source of error (Chen et al, 2006).…”

Section: Extreme Value Methodsmentioning

confidence: 99%

“…The SD method must also assume stationarity between predictor and predictand relationships (i.e. that current statistical relationships will be the same under future climate conditions) (Wilby et al, 2002), a weakness that has been shown to underestimate future changes (Christensen et al, 2007). SD methods are likely to underestimate future variance, also leading to conservative predictions (Fowler et al, 2007).…”

Section: Extreme Value Methodsmentioning

confidence: 99%

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Climate‐based sensitivity of air quality to climate change scenarios for the southwestern United States

Wise

2008

Intl Journal of Climatology

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ABSTRACT:The need to understand future trends in air quality is an issue that is frequently raised by air quality planners and managers. The potential for extreme events is of particular interest, but forecasts are difficult using traditional methods and further complicated by predictions of future climate change. This study aims to address this research need through a climate-based sensitivity study of ground-level ozone and particulate matter (PM) in the U.S. Southwest. Extreme value methods were used to examine ozone and PM in Tucson, Arizona, over the time period 1990-2001. A Statistical DownScaling Model (SDSM) was employed to build regression-based models between gridded meteorological data and point time series of ozone and PM. Following model calibration and verification, future climate-based ozone and PM scenarios were created for 2002-2050 and 2051-2099. Daily output of projected ozone and PM were then subjected to extreme value methods in order to estimate climate-based changes in ozone and PM extremes over the next century. Results indicate that monthly mean and extreme ozone values are sensitive to predicted increases in temperature, particularly in the summer months. PM results are less certain but suggest that PM may be sensitive to changing moisture conditions.

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Section: Extreme Value Methodsmentioning

confidence: 99%

Section: Extreme Value Methodsmentioning

confidence: 99%

Section: Extreme Value Methodsmentioning

confidence: 99%

Section: Extreme Value Methodsmentioning

confidence: 99%

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Climate‐based sensitivity of air quality to climate change scenarios for the southwestern United States

Wise

2008

Intl Journal of Climatology

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“…Essa redução de escala dinâmica inclui o aninhamento de um modelo de circulação regional a uma resolução mais grosseira de um modelo de circulação global. O modelo de circulação regional utiliza o modelo de circulação global para defi nir as condições de contorno atmosféricas, variáveis com o tempo, em torno de um domínio fi nito (Wilby et al, 2002). Schlenker et al (2007), ao analisar o impacto da mudança climática na agricultura irrigada na Califórnia, concluíram que, com aplicação de uma escala geográfi ca menor, o escoamento superfi cial durante a maior parte da estação de cultivo sofre decréscimo, com a possibilidade de modesto aumento na precipitação, o que resulta em redução na disponibilidade de água quando ela é mais necessária, aumento da demanda para irrigação, aumento da pressão sobre os rios e sobre os sistemas de água subterrânea.…”

Section: Introductionunclassified

Mudanças climáticas e impactos na necessidade hídrica das culturas perenes na Bacia do Jaguaribe, no Estado do Ceará

Gondim

Castro

Evangelista

et al. 2008

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi avaliar os impactos das mudanças climáticas na demanda de água para irrigação de culturas perenes, na Bacia do Jaguaribe, no Estado do Ceará. Foi empregado o sistema integrado de modelagem regional PRECIS ("Providing Regional Climates for Impact Studies"), e aplicado o método de redução de escala de bacia hidrográfi ca, com as condições de contorno do modelo climático regional (HadRM3P). Foi utilizado um conjunto de climatologia de base do modelo de 1961 a 1990 e de projeções climáticas futuras. As coordenadas geográfi cas da região em estudo foram consideradas para interpolação num sistema de informação geográfi ca. A evapotranspiração de referência foi estimada por meio de dados da temperatura média mensal. As mudanças climáticas projetadas aumentaram a demanda projetada de água para irrigação, porque a evapotranspiração foi estimada para aumentos de 3,1 a 2,2% e a precipitação pluvial foi estimada para diminuições de 30,9 a 37,3%. O aumento da necessidade hídrica foi estimada em 32,9% a 43,9%, para o ano de 2040, conforme o cenário analisado.Termos para indexação: evapotranspiração, irrigação, SIG. Climate change and impacts on water requirement of permanent crops in the Jaguaribe Basin, Ceará, BrazilAbstract -The aim of this study was to estimate climate change impacts on irrigation water demand for permanent crops. The PRECIS (Providing Regional Climates for Impact Studies) system was applied, and downscaling techniques were used at the river basin level, with the boundary conditions of the regional climate model (HadRM3P). A climate data set was generated for 1961 to 1990 (baseline) and for future climate projections. The regional geographical coordinates were considered for interpolation in a georeferenced coordinated system. The reference evapotranspiration was estimated through data of monthly average temperature. Projected climate change increased projected irrigation water demand, because evapotranspiration was estimated to increase by 3.1 to 2.2% and rainfall was estimated to decrease by 30.9 to 37.3%. The 2040 water need was estimated to increase by 32.9% to 43.9%, according to the analyzed scenario.

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Statistical framework to simulate daily rainfall series conditional on upper-air predictor variables

Langousis

Kaleris

2014

Water Resour. Res.

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We propose a statistical framework to generate synthetic rainfall time series at daily resolution, conditional on predictor variables indicative of the atmospheric circulation at the mesoscale. We do so by first introducing a dimensionless measure to assess the relative influence of upper-air variables at different pressure levels on ground-level rainfall statistics, and then simulating rainfall occurrence and amount by proper conditioning on the selected atmospheric predictors. The proposed scheme for conditional rainfall simulation operates at a daily time step (avoiding discrete approaches for identification of weather states), can incorporate any possible number and combination of predictor variables, while it is capable of reproducing rainfall seasonality directly from the variation of upper-air variables, without any type of seasonal analysis or modeling. The suggested downscaling approach is tested using atmospheric data from the ERAInterim archive and daily rainfall measurements from western Greece. The model is found to accurately reproduce several statistics of actual rainfall time series, at both annual and seasonal levels, including wet day fractions, the alternation of wet and dry intervals, the distributions of dry and wet spell lengths, the distribution of rainfall intensities in wet days, short-range dependencies present in historical rainfall records, the distribution of yearly rainfall maxima, dependencies of rainfall statistics on the observation scale, and long-term climatic features present in historical rainfall records. The suggested approach is expected to serve as a useful tool for stochastic rainfall simulation conditional on climate model outputs at a regional level, where climate change impacts and risks are assessed.

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sdsm — a decision support tool for the assessment of regional climate change impacts

Cited by 1,220 publications

References 44 publications

Climate‐based sensitivity of air quality to climate change scenarios for the southwestern United States

Climate‐based sensitivity of air quality to climate change scenarios for the southwestern United States

Mudanças climáticas e impactos na necessidade hídrica das culturas perenes na Bacia do Jaguaribe, no Estado do Ceará

Statistical framework to simulate daily rainfall series conditional on upper-air predictor variables

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