The predictions from global or regional scale climate models are often too coarse for direct use at local scales. There is thus a need for tools to produce inputs at the scale of hydrologic models from climate reanalysis data. Scott rupp e a alaska center for climate assessment and policy, university of alaska, fairbanks, ak, usa b department of atmospheric sciences, geophysical. Title page abstract introduction conclusions references tables figures back close. Design and development of a prototype tool for integrated. Statistical downscaling is a method used to predict local climate variables such. This paper integrates perspectives from meteorologists, climatologists, statisticians, and hydrologists to identify generic end user in particular, impact modeler needs and to discuss.
In addition, gcms may not be able to adequately represent the climate of a specific region with a varied and complex climate. There is no single best way, it depends on the goal. Statistical downscaling and dynamical downscaling of. In common with weather typing methods, regression methods also assume validity of the model parameters under future climate conditions, and regressionbased downscaling is highly sensitive to the choice of predictor. Downscaling method typical global climate models are run with grid resolution of approximately 2. Sdsm statistical downscaling model is a decision support tool for assessing local climate change impacts using a robust statistical downscaling technique. The most severe limitation to empiricalstatistical downscaling is the requirement that. Downscaled modeling examines relatively small areas in detailin some cases down to 25 square kilometers, 3 a far higher resolution than that offered by global climate model simulations. Statistical downscaling delta method ccafs climate. The paper summarizes an endtoend activity connecting the global climate modeling enterprise with users of climate information in alaska. Littell c, matthew leonawicz d, michael lindgren d, thomas a. Keith dixon lucas harris tom knutson related areas of research. This includes raw climate model output, as well as model output that has been processed by bias correction removal of some known errors andor downscaling addition of finer spatial detail.
Prediction of climate variables by comparing the knearest neighbor method and miroc5 outputs in an arid environment. What software is easiestbest to downscaling future climate. Evaluation of the empiricalstatistical downscaling method. Regional scenarios constructed to assess climate change impacts require finer. The sd gcm statistical downscaling of general circulation models is a useful tool for downscaling cmip5 models under rcps representative concentration pathways scenarios. Global climate models gcms cannot simulate climate at the local to regional scale. May 26, 2018 a comprehensive performance assessment of the empiricalstatistical downscaling esd technique named episodes is presented. Pertaining evaluation analyses consist of multifarious validation experiments as well as various comparisons of episodes projections with those of three rcms and two esd methods based on the same gcm scenarios driven by two distinct representative concentration. What toolssoftware do you recommend for downscaling this models.
Pertaining evaluation analyses consist of multifarious validation experiments as well as various comparisons of episodes projections with those of three rcms and two esd methods based on the same gcm scenarios driven by two distinct representative. Downscaling climate modelling for highresolution climate information and impact. Statistical downscaling and dynamical downscaling of regional. Anomalies are interpolated between gcm cell centroids and are then applied to a baseline climate given by a high resolution surface worldclim 1. Climate model downscaling geophysical fluid dynamics. Simonovic, in trends and changes in hydroclimatic variables, 2019.
Two different classes of models have been used in the past to perform downscaling. Welcome to regional climate model evaluation system. Sep 27, 2012 we will examine the potential climate change effects on transitional coastal habitats with highquality local habitat data, downscaled climate models, and projected storm effects, and we will link habitat responses to wildlife using vulnerability assessments. Climate model downscaling geophysical fluid dynamics laboratory. The links below provide access to a growing body of data, generated by climate models, relevant to understanding potential future climate change. It is well known that downscaling comes in two flavorsthe dynamical, using regional climate models rcms, and the statistical, using empirical statistical techniques. It is also well known that both have their advantages and disadvantages, and often they are not even easy to compare because of their different target applications. Regional integrated sciences and assessments programs funded by the. Climate impacts weather and climate extremes global climate models gcms continue to yield important scientific insights into the dynamics and evolution of the climate system o.
Atmospheric science automated regressionbased statistical. We will examine the potential climate change effects on transitional coastal habitats with highquality local habitat data, downscaled climate models, and projected storm effects, and we will link habitat responses to wildlife using vulnerability assessments. I want to study the effect of climate change on hydrology. This study approaches the problem of downscaling global climate model simulations with an emphasis on validating and selecting global models. A daily weather generator for use in climate change studies. Differences between model and observed precipitation over three regions in us. They are physically based and their higher resolution allows to better. Dec 08, 2017 the predictions from global or regional scale climate models are often too coarse for direct use at local scales. What is the besteasiest computer software for gcm downscaling. There are numerous number of statistical downscaling sd methods. A climate model is a mathematical representation of the climate system. Essential software toolkit for mineral processing professionals for process research, development, and analysis. Rcmes utilizes the following statistical downscaling methods used in previous studies e.
The delta method decision and policy analysis working paper no. Here we apply a downscaling method based on thin plate spline spatial interpolation of anomalies deltas of original gcm outputs. Many impact studies require climate change information at a finer resolution than that provided by global climate models gcms. Statistical delta downscaling adds the difference delta between a historical period and a modeled value to a known historical climatology. Downscaling requires at least 30 years of observed data for the baseline period. The downscaling method makes minimal, physically based corrections to the global simulation while preserving much of the statistics of interannual variability in the climate model. Windows software for statistical downscaling of gcm models. Downscaling of climate model output for alaskan stakeholders. The regional climate model evaluation system rcmes is designed to facilitate regionalscale evaluations of climate and earth system models by providing standardized access to a vast and comprehensive set of observations e. A tool for downscaling weather data from largegrid. Dynamical downscaling with regional climate models have been demonstrated to have added value for downscaling global models.
Improving the downscaling of climate model for impacts. Video downscaling design example this example demonstrates an open computing language opencl implementation of a fixed ratio 23 video downscaler. Statistical downscaling encompasses the use of various statisticsbased techniques to determine relationships between largescale climate patterns resolved by global climate models and observed local climate responses. Gmdd 6, 25172549, 20 downscaling a global climate model m. Statistical downscaling regional climate model evaluation. Statistical downscaling using rcmes why do we need to downscale gcm outputs. Downscaling of climate model output for alaskan stakeholders john e. Downscaling a global climate model to simulate climate change impacts on us regional and urban air quality. Im currently working on predicting the climate change impacts with larswg statistical downscaling model. Units are mm for mean precipitation and mm2 for variance.
Downscaling of ipcc scenarios refers to a process of taking global information on climate response to changing atmospheric composition, and translating it to a finer spatial scale that is more meaningful in the context of local and regional impacts. A software tool allows users to evaluate skill 22 climate models for eight regions. In some situations, the spatial resolution of global climate model gcm outputs is too coarse for informing regional or local adaptation. Dynamical downscaling requires running highresolution climate models on a regional subdomain, using observational data or lowerresolution climate model output as a boundary condition. While it is possible to downscale all available gcm datasets, snap provides climate data for the top 5 models for the alaska and arctic regions from the coupled model intercomparison project cmip for.
Downscaling of global climate change estimates to regional scales. Downscaled regional climate models rcms provide grist for. Downscaled climate data for more than 4000 communities are viewable by users. Carry out thermodynamic and mineral processing calculations on a standard computer quickly and easily. Downscaling is performed to estimate higher resolution climatic projections from global climate odel modeled climate output. Downscaling climate models are an attempt to bridge the gap between global and local effects by layering locallevel data over largerscale climate models. Statistical downscaling and dynamical downscaling are two approaches to generate high. What software is easiestbest to downscaling future. In the last 10 years, downscaling techniques, both dynamical i. The downscaling models are calibrated using ncep reanalysis as largescale predictors, and predictors are also provided for a number of gcm climate change simulations, including hadcm3. May 2010 downscaling global circulation model outputs. Essential software toolkit for process research, development, design, and. For instance, empiricalstatistical downscaling has successfully been applied to multimodel ensembles consisting of different gcm scenarios from the intergovernmental panel on climate change ipcc in order to explore intermodel similarities and differences. Climate data is inherently geospatial in nature, with global climate models and their many scenarios and projections tied to 2degree grid cells.
May 04, 2016 statistical downscaling methods sdsm 5. Environmental modelling software, 17, 145157 and the automated. The statistical downscaling model sdsm is a freely available software tool that facilitates the rapid development of multiple, lowcost. Statistical downscaling of global climate models using. Downscaling simulations of future global climate with. In this study, these two downscaling methods are used to simulate the surface climate of china and compared. Downscaling global climate models gcms are our best tools for providing climate projections. Projected warming and wetting are largest in winter and summer, respectively. What software is easiestbest to downscaling future climate models. Climate impacts weather and climate extremes global climate models gcms continue to yield important scientific insights into the. In this study, we developed a spatial downscaling tool for generating 3hourly grid.
Downscaling is the process of relocating coarse resolution gcm to fine spatial scale ground station data murphy, 1999. The material in this chapter of the workshop report was assembled initially as a letter report of the meeting to the national climate assessment development and. Empiricalstatistical downscaling in climate modeling. Many researchers and users need a software package it can easily use statistical downscaling models. Regional climate models and downscaling rccap regional. Additionally, the software performs ancillary tasks of predictor variable prescreening, model calibration, basic diagnostic testing, statistical analyses and graphing of climate data. Daily rainfall statistics from the ukmo 5 km data set. Dynamical downscaling provides physically consistent projections of many variables, and therefore suf. Downscaling extremesan intercomparison of multiple. Wilby c a school of civil engineering and geosciences, university of newcastle upon tyne, claremont road, newcastle upon tyne ne1 7ru, uk b climatic research unit cru, school of environmental sciences, university of. Dynamical downscaling requires running highresolution climate models on a regional subdomain, using observational data or lower. The downscaling phase involves the use of the output of largescale fields which we want to downscale generally data from a climate model.
Automated regressionbased statistical downscaling tool. Climate model downscaling contacts, for more information. A comprehensive performance assessment of the empiricalstatistical downscaling esd technique named episodes is presented. Global climate models gcms are our best tools for providing climate projections. Statistical downscaling model sdsm tutorial youtube.
Sdsm facilitates the rapid development of multiple, lowcost, singlesite scenarios of daily surface weather variables under current and future regional climate forcing. Conservation of momentum fma for pressure differences and the coriolis force 2. I am not that much familiar with the climate models work. Apr 18, 20 essential software toolkit for mineral processing professionals for process research, development, and analysis. The two main approaches to downscaling climate information are dynamical and statistical. These models use physical principles to reproduce local climates, but are computationally intensive. Regional climate model and statistical methods, have been developed to. Acrossmodel uncertainties often exceed changes of temperature and precipitation. This project evaluated local projected changes in climate across, as well as drives highresolution hydrologic and ecological models for, the lake champlain basin. A daily weather generator for use in climate change studies c.
Preprint downscaling climate change salathe 02022005 ii. The effort included retrieval of the requisite observational datasets and model output, a model evaluation and selection procedure, the actual downscaling by the delta method with its inherent biasadjustment, and the provision of products to a range of. As with the other resources provided through climate. Downscaling is the general name for a procedure to take information known at large scales to make predictions at local scales. This course trains on the use and application of this decision support tool for assessing local climate change impacts, taught by professionals currently using this technique in their own research. The downscaling method makes minimal, physically based corrections to the global simulation while preserving much. A number of federal agencies, including reclamation, have developed and applied downscaling methodologies resulting. This paper integrates perspectives from meteorologists, climatologists, statisticians, and hydrologists to identify generic end user in. Met office hadley centres regional climate model version 3. Downscaling definition of downscaling by the free dictionary. Help of sd gcm statistical downscaling general circulation models.
Statistical downscaling of global climate models using sdsm 5. Regional climate model and statistical methods, have been developed to obtain fine resolution climate change scenarios. Its purpose was to bring the gcm model data in closer agreement with the station level data maraun et al. Comparing the performance of dynamical and statistical downscaling on historical run precipitation data over a semiarid region. Hydrostatic equation how pressure varies with height gravitational force balanced by pressure gradient force.
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