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Author:
Publisher:
ISBN:
Category : Agriculture
Languages : en
Pages : 98
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Book Description
Author:
Publisher:
ISBN:
Category : Agriculture
Languages : en
Pages : 98
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Book Description
Author: Ramesh Teegavarapu
Publisher: Elsevier
ISBN: 0128109866
Category : Science
Languages : en
Pages : 434
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Book Description
Trends and Changes in Hydroclimatic Variables: Links to Climate Variability and Change discusses the change detection and trend analysis methods used to assess hydroclimatic variables in a changing climate. Changes and trends in hydroclimatic variables are assessed using state-of-the-art methods, such as non-linear trend estimation (including spline smoothing and local regression) and handling persistence (or serial auto-correlation in data) for assessing trends in different hydroclimatic variables (e.g. pre-whitening methods). This book offers a variety of real-life case studies and problem-solving techniques for a field that is rapidly evolving. Users will find methods to evaluate points where time series characteristics change and non-homogeneity in time series. In addition, it covers the subject of climate variability and change in an immense level of detail, including changes on precipitation, streamflow and sea levels. - Examines statistical methods for trend analysis, providing an excellent reference book for scholars, scientists, students and professionals - Offers an exhaustive treatment of several hydroclimatic variables in one book, providing readers with a comprehensive understanding of changes in hydroclimatic variables over time and space - Presents case studies dealing with changes in hydroclimatic variables in different geographical regions of the world - Focuses on climate variability and change, including an extensive assessment of trends and their associated links to climate variability and change
Author: Taesam Lee
Publisher: CRC Press
ISBN: 0429861141
Category : Science
Languages : en
Pages : 195
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Book Description
Global climate change is typically understood and modeled using global climate models (GCMs), but the outputs of these models in terms of hydrological variables are only available on coarse or large spatial and time scales, while finer spatial and temporal resolutions are needed to reliably assess the hydro-environmental impacts of climate change. To reliably obtain the required resolutions of hydrological variables, statistical downscaling is typically employed. Statistical Downscaling for Hydrological and Environmental Applications presents statistical downscaling techniques in a practical manner so that both students and practitioners can readily utilize them. Numerous methods are presented, and all are illustrated with practical examples. The book is written so that no prior background in statistics is needed, and it will be useful to graduate students, college faculty, and researchers in hydrology, hydroclimatology, agricultural and environmental sciences, and watershed management. It will also be of interest to environmental policymakers at the local, state, and national levels, as well as readers interested in climate change and its related hydrologic impacts. Features: Examines how to model hydrological events such as extreme rainfall, floods, and droughts at the local, watershed level. Explains how to properly correct for significant biases with the observational data normally found in current Global Climate Models (GCMs). Presents temporal downscaling from daily to hourly with a nonparametric approach. Discusses the myriad effects of climate change on hydrological processes.
Author: Maria J. Santos
Publisher:
ISBN:
Category : Climatic changes
Languages : en
Pages : 146
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Book Description
Author: David Stoms
Publisher:
ISBN:
Category : Climatic changes
Languages : en
Pages : 46
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Book Description
Author: Muhammad Zia ur Rahman Hashmi
Publisher:
ISBN:
Category : Bayesian statistical decision theory
Languages : en
Pages : 536
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Book Description
Global Circulation Models (GCMs) are considered the most reliable source to provide the necessary data for climate change studies. At present, there is a wide variety of GCMs, which can be used for future projections of climate change using different emission scenarios. However, for assessing the hydrological impacts of climate change at the watershed and the regional scale, the GCM outputs cannot be used directly due to the mismatch in the spatial resolution between the GCMs and hydrological models. In order to use the output of a GCM for conducting hydrological impact studies, downscaling is used to convert the coarse spatial resolution of the GCM output into a fine resolution. In broad terms, downscaling techniques can be classified as dynamical downscaling and statistical downscaling. Statistical downscaling approaches are further classified into three broad categories, namely: (1) weather typing; (2) weather generators; and (3) multiple regression-based. For the assessment of hydrologic impacts of climate change at the watershed scale, statistical downscaling is usually preferred over dynamical downscaling as station scale information required for such studies may not be directly obtained through dynamical downscaling. Among the variables commonly downscaled, precipitation downscaling is still quite challenging, which has been recognised by many recent studies. Moreover, statistical downscaling methods are usually considered to be not very effective for simulation of precipitation, especially extreme precipitation events. On the other hand, the frequency and intensity of extreme precipitation events are very likely to be impacted by envisaged climate change in most parts of the world, thus posing the risk of increased floods and droughts. In this situation, hydrologists should only rely on those statistical downscaling tools that are equally efficient for simulating mean precipitation as well as extreme precipitation events. There is a wide variety of statistical downscaling methods available under the three categories mentioned above, and each method has its strengths and weaknesses. Therefore, no single method has been developed which is considered universal for all kinds of conditions and all variables. In this situation there is a need for multi-model downscaling studies to produce probabilistic climate change projections rather than a point estimate of a projected change. In order to address some of the key issues in the field of statistical downscaling research, this thesis study includes the evaluation of two well established and popular downscaling models, i.e. the Statistical DownScaling Model (SDSM) and Long Ashton Research Station Weather Generator (LARS-WG), in terms of their ability to downscale precipitation, with its mean and extreme characteristics, for the Clutha River watershed in New Zealand. It also presents the development of a novel statistical downscaling tool using Gene Expression Programming (GEP) and compares its performance with the SDSM-a widely used tool of similar nature. The GEP downscaling model proves to be a simpler and more efficient solution for precipitation downscaling than the SDSM model. Also, a major part of this study comprises of an evaluation of all the three downscaling models i.e. the SDSM, the LARS-WG and the GEP, in terms of their ability to simulate and downscale the frequency of extreme precipitation events, by fitting a Generalised Extreme Value (GEV) distribution to the annual maximum data obtained from the three models. Out of the three models, the GEP model appears to be the least efficient in simulating the frequency of extreme precipitation events while the other two models show reasonable capability in this regard. Furthermore, the research conducted for this thesis explores the development of a novel probabilistic multi-model ensemble of the three downscaling models, involved in the thesis study, using a Bayesian statistical framework and presents probabilistic projections of precipitation change for the Clutha watershed. In this way, the thesis endeavoured to contribute in the ongoing research related to statistical downscaling by addressing some of the key modern day issues highlighted by other leading researchers.
Author:
Publisher:
ISBN:
Category : Agriculture
Languages : en
Pages : 220
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Book Description
Author: Patrick A. Ray
Publisher: World Bank Publications
ISBN: 1464804788
Category : Business & Economics
Languages : en
Pages : 149
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Book Description
Confronting Climate Uncertainty in Water Resources Planning and Project Design describes an approach to facing two fundamental and unavoidable issues brought about by climate change uncertainty in water resources planning and project design. The first is a risk assessment problem. The second relates to risk management. This book provides background on the risks relevant in water systems planning, the different approaches to scenario definition in water system planning, and an introduction to the decision-scaling methodology upon which the decision tree is based. The decision tree is described as a scientifically defensible, repeatable, direct and clear method for demonstrating the robustness of a project to climate change. While applicable to all water resources projects, it allocates effort to projects in a way that is consistent with their potential sensitivity to climate risk. The process was designed to be hierarchical, with different stages or phases of analysis triggered based on the findings of the previous phase. An application example is provided followed by a descriptions of some of the tools available for decision making under uncertainty and methods available for climate risk management. The tool was designed for the World Bank but can be applicable in other scenarios where similar challenges arise.
Author: Mathieu Choux
Publisher:
ISBN:
Category :
Languages : en
Pages : 138
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Book Description
"Finally, the influence of the calibration period length on the new downscaling scheme performance was carried out by comparing the simulation results obtained from two calibration runs of 15 and 30 years of length: for the 1961-1975 period and for the 1961-1990 one. It was found that doubling the calibration period length could lead to significant improvements in the reproduction of the local precipitation characteristics." --
Author: Rasmus E. Benestad
Publisher: World Scientific
ISBN: 9812819126
Category : Science
Languages : en
Pages : 228
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Book Description
Empirical-statistical downscaling (ESD) is a method for estimating how local climatic variables are affected by large-scale climatic conditions. ESD has been applied to local climate/weather studies for years, but there are few ? if any ? textbooks on the subject. It is also anticipated that ESD will become more important and commonplace in the future, as anthropogenic global warming proceeds. Thus, a textbook on ESD will be important for next-generation climate scientists.
