Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 29 for “"Statistical Downscaling"”.
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On the use of Statistical Downscaling for the Study of Coastal Hazards in the Pacific
… compound events are impossible to characterize. Statistical downscaling is a computationally efficient and reliable technique for obtaining hydrodynamic components based on the relationship between large scale predictors and local predictands. Firstly, based on the relationship between sea level …
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Extreme value theory: Applications to estimation of stochastic traffic capacity and statistical downscaling of precipitation extremes
… improve fitted results.</p><p>Next, we perform a statistical downscaling by applying a CDF transformation function to local-level daily precipitation extremes (from NCDC station data) and corresponding NARCCAP regional climate model (RCM) output to derive local-scale projections. These …
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Forecasting of rainfall using statistical downscaling model (SDSM) – general circulation model (GCM) for future estimation of rainwater harvesting
Changes in the spatial and temporal rainfall pattern affected by the climate change need to be investigated as its significant characteristics are often used for managing water resources. In this study, the impacts of climate change on rainfall variability in Johor was investigated by using General …
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Interactive effects of n fertilization rate, cultivars and planting date under climate change on maize (zea mays l.) yield using crop simulation and statistical downscaling of climate models
… potentials under which farmers operate. Statistical downscaling models such as stochastic weather generator (Long Ashton Research Station Weather Generator [LARS-WG]) and delta-based methods (Agricultural Model Intercomparison and Improvement Project (AgMIP) protocols) have not been …
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Development of a correction approach for future precipitation changes simulated by General Circulation Models
… important challenge in climate change science. Statistical downscaling methods are often utilised to bridge the gap between the coarse resolution of General Circulation Models (GCMs) and the higher-resolutions at which information is required by the majority of end users. However, the skill of …
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Bias Correction and Downscaling of Climate Model Outputs Required for Impact Assessments of Climate Change in the U.S. Northeast
… impact analysis of climate change. Although downscaling of GCM outputs can be performed by dynamical downscaling using Regional Climate Models (RCMs), it requires large computational capacity. When daily climate data from multiple GCMs are required to be downscaled, dynamical downscaling may …
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Catchment Scale Downscaling of Hydroclimatic Variables from General Circulation Model Outputs
… scale studies. Therefore either dynamic or statistical downscaling techniques are used for linking GCM outputs to catchment scale hydroclimatic variables.
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Development of a quantile-based approach to statistically downscale global climate models
… this weakness I here introduce a novel method of statistical downscaling, which bridges the gap between the low-resolution output provided by climate models and the high-resolution data needed to perform local or regional climate assessments. The statistical downscaling method developed here, …
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Predicting Climate Change in Big Bend National Park, Texas
This study uses statistical downscaling to improve the resolution of global climate model predictions of temperature and precipitation over the next 100 years in Big Bend National Park, Texas. The method is an adaptation of climate prediction by model statistics. I use historical data from 12 …
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Assessment of Future Impact of Climate Change on Structural Protections and Hydrological Extremes – Floods
… Circulation Models (GCMs). The study created a statistical downscaling model called SDCRR, using the Volterra series realization, principal components, and ridge regression. The model was applied at four stations in the Manawatu catchment to downscale daily rainfall. The performance of the SDCRR …
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STATISTICAL MODELLING AND ANALYSIS FOR REGIONAL CLIMATE CHANGE
… due to their coarse spatial resolutions, downscaling approaches are often relied to transit the coarser-scale GCM outputs to higher resolutions. Multivariate multisite weather generators (MMWGs) are appealing tools, as they allow for simulations of multiple realizations of climate change …
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How Climate Change Could Affect The Water Supply of Potash of Potash Solution Mining in Southern Saskatchewan
… (Budyko, Ol’dekop, Schreiber and Turc) and statistical downscaling, in order to identify the best two estimators of observed runoff. Based on the quantile indicators of goodness of fit, total runoff (mrro) and the statistical downscaling based on the standardized precipitation …
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Quantification of climate change impacts on urban catchment hydrology and water sensitive design devices
… a single Global Climate Model (GCM) or a single downscaling method. This study has assessed the capabilities of dynamical and statistical downscaling methods in climate impact studies by using twelve GCMs at the Lucas Creek catchment located in Auckland, New Zealand. For downscaling, a Regional …
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The evaluation of NARCCAP regional climate models using the North American Regional Reanalysis
… and rate of change. More recently, dynamic downscaling has been employed with the use of regional climate models (RCMs) as an alternative to statistical downscaling. However, while RCMs provide a much finer resolution, they have still been shown to exhibit bias within their simulations. In …
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Weighted ensemble analysis of extreme precipitation under climate change
… daily precipitation data are calculated from 13 statistical downscaling general circulation models under 3 CMIP3 emission scenarios: A1B, A2 and B1, as well as from 17 stations in NCDC and CCPN rain gage network. Then precipitation events of different recurrence intervals are calculated through …
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An Analysis of Hydrological Model Uncertainty at the Local Stage of a Climate Change Impact Assessment in the Suir Catchment
… to synoptic station level by empirical statistical downscaling (Fealy and Sweeney, 2007). In the analysis of changes to catchment hydrology for the 2050s and the 2080s, GCM uncertainty is the greatest source of uncertainty. However, by the 2080s, uncertainty due to equifinality of …
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Projecting Future Local Hydroclimatology: A Framework for Local Water Resource Planners in the Animas River Basin at Durango, Colorado
… analysis of basinwide hydroclimatology, statistical downscaling increased the resolution of, and built a linear relationship between, historical upper atmospheric reanalysis data to surface level mean air temperature and precipitation for several climate stations located across the basin. …
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Statistical inference for dependent data
… of high-resolution climate projections through statistical downscaling, we consider the change point problem and the two sample problem for temporally dependent functional data. Specifically, in Chapter 1, we develop a self-normalization based test to test the structural stability of temporally …
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Integrated Model-Based Impact Assessment of Climate Change and Land Use Change on the Occoquan Watershed
… General Circulation Models (GCMs) by using two statistical downscaling methods, were applied to drive the Hydrological Simulation Program - Fortran (HSPF) and CE-QUAL-W2 (W2) in two future time periods (2046-2065 and 2081-2100). Incorporation of these factors yielded 68 simulation models which …
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Methodological Developments for an Improved Evaluation of Climate Change Impact on Flow Hydrodynamics in Estuaries
… the flow in estuaries, gulfs, etc. It includes downscaling methods to project the required climate variables through the next decades. Here, two statistical downscaling methods, namely, Nearest Neighbouring and Quantile-Quantile techniques, are developed and implemented in order to predict the …
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