Statistical downscaling (SDSM)
Assessment of future temperature change scenario by statistical downscaling model (canesm2) in abaya chamo sub basin, Ethiopia
... using statistical downscaling model (SDSM) and the second generation Canadian Earth System Model (CanESM2) General Circulation Model (GCM) output, which is significant for assessment of temperature change ...
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Analyzing the future climate change of Upper Blue Nile River basin using statistical downscaling techniques
... Generally, downscaling methods are classified into dy- namic and statistical downscaling (Fowler et ...Dynamic downscaling nests higher- resolution regional climate models (RCMs) into coarse- ...
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STUDY THE IMPACT OF CLIMATE CHANGE ON MAXIMUM AND MINIMUM TEMPERATURE OVER ALEXANDRIA, EGYPT USING STATISTICAL DOWNSCALING MODEL (SDSM)
... Babel and Turyatunga (2015), using Statistical Downscaling Model (SDSM) v4.2 to downscale low-resolution future climate data obtained from general circulation model HadCM3 for two SRES scenarios, A2 and B2. ...
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Evaluation of a statistical downscaling procedure for the estimation of climate change impacts on droughts
... a statistical downscaling method for precipitation using a global circulation ...the downscaling method for present and future climate con- ditions and the use of the downscaling method on ...
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Hydrologic extremes – an intercomparison of multiple gridded statistical downscaling methods
... when downscaling NCEP1 and 20CR, which, as shown earlier, exhibit inhomogeneities between calibration and validation ...when downscaling ERA40 or ERAInt to VIC Forcings or ANUSPLIN for all three hydrologic ...
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Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0)
... Differences between LI+BA and BA+SD in their ability to adjust biases at 2 ◦ spatial resolution reflect structural dif- ferences between the ISIMIP2b and ISIMIP3 approaches to statistical downscaling. Bias ...
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Present and LGM permafrost from climate simulations: contribution of statistical downscaling
... the statistical downscaling methods (SDMs) are less resource-intensive and represent an alternative to quickly obtain high-resolution fields from several different climate ...using statistical re- ...
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Chaotic Statistical Downscaling (CSD): Application and Comparison in the Bogotá River Basin
... Chaotic Statistical Downscaling model (CSD) evaluate the presence of deterministic chaos for different rainfall accumulation intervals for both of the time series (rainfall gauge stations and the global ...
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Statistical Downscaling Precipitation Forecast for Hydropower Industry and Its Calibration Using Frequency Matching Method
... a statistical downscaling method based on the linear regression of the categorized daily precipitation forecasts taken from the European Centre for Medium-Range Weather Forecasts (ECMWF), Japan ...
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Climate change assessment for Mediterranean agricultural areas by statistical downscaling
... developed statistical downscaling tech- niques for climatic predictions in order to provide scenar- ios for selected small regions or complement the results of dynamical ...models. Statistical ...
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Statistical downscaling for future extreme wave heights in the North Sea
... existing statistical transfer function downscaling techniques using a combination of generalised Pareto tails, covariate models, and two possible extensions to overcome their major ...
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Quantile Regression in Statistical Downscaling to Estimate Extreme Monthly Rainfall
... statistical downscaling. This paper concerns with developing model of statistical downscaling using quantile regression to estimate extreme monthly ...rainfall. Statistical ...
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Inter comparison of statistical downscaling methods for projection of extreme precipitation in Europe
... Comparison of the results of the SDMs with EPI obtained from the uncorrected RCMs shows that in the case of NO2 all the SDMs clearly agree better with the observations. But for the other two catchments, the results ...
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Sensitivity analysis of runoff modeling to statistical downscaling models in the western Mediterranean
... dynamical downscaling techniques, statistical downscaling models (SDMs) are also used in antic- ipated hydrologic impact studies under climate change sce- narios (for a review, see, ...determining ...
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Projections of future extreme rainfall events using statistical downscaling in Malaysia
... earlier, downscaling is used to match the scale between the GCM and the station scale since the GCM scale is much coarser compared to station ...of downscaling known as dynamical and statistical are ...
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BUASCSDSEC — Uncertainty Assessment of Coupled Classification and Statistical Downscaling Using Gaussian Process Error Coupling
... and statistical downscaling models in a way that the dependency among modelling errors will impact the result of stochastic classification and statistical downscaling model calibration and ...
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Statistical Downscaling of Extreme Temperature Events in Greenland
... for statistical downscaling. Many of these focusing on downscaling the mean behaviour of the climate ...in downscaling the extremes, we list only methods which have been developed specifically ...
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Statistical downscaling of precipitation projections in Southeast Queensland Catchments
... and Statistical techniques are the two primary methods used for downscaling data from coarse resolution ...Dynamical downscaling involves nesting a high resolution Regional Climate Model (RCM) in a ...
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Statistical downscaling of precipitation projections in Southeast Queensland Catchments
... level. Statistical downscaling by linear regression of projected climate predictor variables on a monthly basis is used in this thesis to conduct an analysis of future rainfall at three stations in ...
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Statistical Downscaling Modeling Through K-means Clustering
... Statistical downscaling (SD) is a technique used to describe the relationship between data on a global grid (predictor) with data on a local scale grid (response) to translate global-scale anomalies into ...
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