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Author: Min Young Lee
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Min Young Lee
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Annie Cung
Publisher:
ISBN:
Category : Rainfall anomalies
Languages : en
Pages : 236
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Book Description
"Furthermore, a regional analysis was performed and homogenous regions of weather stations within Quebec were identified. A method for the estimation of missing data at ungauged sites based on regional NCMs was found to yield good estimates." --
Author: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309380979
Category : Science
Languages : en
Pages : 187
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Book Description
As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities.
Author: Manfred Mudelsee
Publisher: Cambridge University Press
ISBN: 1107033187
Category :
Languages : en
Pages : 213
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Book Description
The risks posed by climate change and its effect on climate extremes are an increasingly pressing societal problem. This book provides an accessible overview of the statistical analysis methods which can be used to investigate climate extremes and analyse potential risk. The statistical analysis methods are illustrated with case studies on extremes in the three major climate variables: temperature, precipitation, and wind speed. The book also provides datasets and access to appropriate analysis software, allowing the reader to replicate the case study calculations. Providing the necessary tools to analyse climate risk, this book is invaluable for students and researchers working in the climate sciences, as well as risk analysts interested in climate extremes.
Author: Ramesh S. V. Teegavarapu
Publisher: Cambridge University Press
ISBN: 1139851659
Category : Science
Languages : en
Pages : 289
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Book Description
Measurement, analysis and modeling of extreme precipitation events linked to floods is vital in understanding changing climate impacts and variability. This book provides methods for assessment of the trends in these events and their impacts. It also provides a basis to develop procedures and guidelines for climate-adaptive hydrologic engineering. Academic researchers in the fields of hydrology, climate change, meteorology, environmental policy and risk assessment, and professionals and policy-makers working in hazard mitigation, water resources engineering and climate adaptation will find this an invaluable resource. This volume is the first in a collection of four books on flood disaster management theory and practice within the context of anthropogenic climate change. The others are: Floods in a Changing Climate: Hydrological Modeling by P. P. Mujumdar and D. Nagesh Kumar, Floods in a Changing Climate: Inundation Modeling by Giuliano Di Baldassarre and Floods in a Changing Climate: Risk Management by Slodoban Simonović.
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: National Academies of Sciences, Engineering, and Medicine
Publisher: National Academies Press
ISBN: 0309380944
Category : Science
Languages : en
Pages : 187
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Book Description
As climate has warmed over recent years, a new pattern of more frequent and more intense weather events has unfolded across the globe. Climate models simulate such changes in extreme events, and some of the reasons for the changes are well understood. Warming increases the likelihood of extremely hot days and nights, favors increased atmospheric moisture that may result in more frequent heavy rainfall and snowfall, and leads to evaporation that can exacerbate droughts. Even with evidence of these broad trends, scientists cautioned in the past that individual weather events couldn't be attributed to climate change. Now, with advances in understanding the climate science behind extreme events and the science of extreme event attribution, such blanket statements may not be accurate. The relatively young science of extreme event attribution seeks to tease out the influence of human-cause climate change from other factors, such as natural sources of variability like El Niño, as contributors to individual extreme events. Event attribution can answer questions about how much climate change influenced the probability or intensity of a specific type of weather event. As event attribution capabilities improve, they could help inform choices about assessing and managing risk, and in guiding climate adaptation strategies. This report examines the current state of science of extreme weather attribution, and identifies ways to move the science forward to improve attribution capabilities.
Author: Sun Hee Lim
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
"Millions of people are still exposed to unanticipated extreme rainfall events, and their devastating effects extend from communities to the surrounding environment. The impact extends across borders, to both developed and developing nations, causing massive casualties and financial loss. Accurate estimation of such events, however, requires an elaborated investigation covering different parameters, since precipitation patterns can be so diverse depending on the regional Topographical condition and even more so with progressive climate change. Prediction of extreme precipitations has been extensively studied and improved in recent years by various specialists from science and engineering. In particular, in current engineering practices for the estimation of extreme rainfall for design purposes, many probability models have been proposed for describing the distribution of this random variable. However, there is no general agreement as to which distribution should be used to provide the most accurate and most reliable design rainfall estimate. In view of the above-mentioned issues, the overall objective of the present research is therefore to propose a general procedure for assessing the descriptive and predictive abilities of ten probability distributions that have been used in extreme rainfall frequency analyses. The feasibility of the proposed procedure was tested using available 5-minute, 1-hour, and 24-hour annual maximum rainfall data from a network of 11 raingage stations located in the British Columbia region in Canada. Two commonly used methods, the maximum likelihood and L-moment methods, were used for estimating the parameters of the selected probability models. On the basis of the assessment of the descriptive and predictive abilities of each model, the GNO, PE3 and GEV models were found the best choice for the selected daily and sub-daily annual maximum rainfalls. Despite the popular use of GEV in Canada, the GNO distribution was found to have more robust and accurate descriptive and predictive ability from this study. However, no one distribution consistently outperformed the others among those distributions, and it is impossible to choose one distribution as the best to represent the versatile rainfall pattern of BC. The performance of the distribution models was not consistent with either the topographical or climatological condition of study stations. Yet it was evident that most distributions performed poorly with data sets with high skewness. However, it was difficult to define a pattern of skewness in data, as skewness can vary without relation to rainfall durations and climatological or Topographical condition. Using the proposed procedure for selecting the best distribution, the GNO, GEV and PE3 were found the best overall choice for its descriptive and predictive ability with annual maximum rainfall data in British Columbia." --
Author: Myeong-Ho Yeo
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
"Understanding the variations of precipitation process in time and in space is essential for the planning, design, and management of various water resources systems. Recently, climate change impacts on precipitation have been recognized as one of the most critical issues for water management in many regions around the world. The present study was therefore carried out in order to develop better methods for improving the accuracy of rainfall estimation at a gauged or ungauged local site in the context of a changing climate. This study can be divided into five main parts.The first part of the present research deals with the development of a Statistical Downscaling model for Rainfall (SDRain) for describing accurately the linkage between large-scale climate predictors and observed daily rainfall characteristics at a local gauged site using a logistic regression model and a nonlinear model. The feasibility of the suggested SD was tested using the NCEP re-analysis data and the observed daily precipitation data available from a group of 26 raingages located in South Korea and in Canada. It was found that it is feasible to link large-scale climate predictors given by General Circulation Model (GCM) simulation outputs with daily precipitation characteristics at these stations.The second part proposed a statistical downscaling approach to describe the linkage between large-scale climate variables to Annual Maximum Precipitations (AMPs) for daily and sub-daily scales at a local site. The feasibility of the proposed downscaling method has been tested based on climate simulation outputs from CGCM3 and HadCM3 and using available AMPs for durations ranging from 5 minutes to 1 day at 9 raingage stations in Quebec (Canada). Results of the application has indicated that it is feasible to link large-scale climate predictors given by GCM simulation outputs with daily and sub-daily AMPs at a local site.The third part was concerned with the development of a new statistical regionalization method using the Ordinal Factor Analysis (OFA) and the daily precipitation occurrence data. The feasibility and accuracy of the proposed method has been assessed using the daily precipitation data available from a network of 63 raingage stations in South Korea. Results of the numerical application have indicated that the suggested method was more accurate and more robust than the Principal Component Analysis (PCA). The identified homogeneous precipitation regions were found physically consistent to the particular climatic features of South Korea.The fourth part proposed a stochastic estimation procedure for estimating the missing daily precipitation series at an ungauged site. The feasibility and accuracy of the proposed estimation approach have been assessed using the daily precipitation data available at 63 raingage stations in South Korea. Results have indicated that the proposed procedure could provide an accurate estimate of the daily precipitation series for ungauged locations.Finally, a statistical downscaling procedure was proposed for the downscaling of the daily precipitation process at an ungauged location. More specifically, the suggested approach consists of two components: a spatial-link function and a spatial downscaling. The feasibility and accuracy of the proposed SD procedure was assessed based on the NCEP re-analysis data and the observed and reconstructed daily precipitation series at the same raingage station. Results have indicated that the proposed procedure could provide comparable results as those given by the downscaling using real observed precipitation data at the local site." --
Author: John Abbot
Publisher: BoD – Books on Demand
ISBN: 1789847346
Category : Science
Languages : en
Pages : 122
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Book Description
This book describes aspects of rainfall including the extremes, distribution and properties. The introductory chapter focusses on drought and flooding rains over Australia, placing extreme rainfall events from recent decades into a historical context using reconstructions from proxy data. The next three chapters focus on distribution and impacts of rainfall. The first of these chapters presents a statistical analysis of rainfall patterns for Jeddah City and considers future impacts. The second examines rainfall in the context of impacts, vulnerability and climate change in eastern Africa. The third examines extreme rainfall and drought in the Asia-Pacific, through application of monitoring from space. The final chapters focus on properties of rain, one examining aerosol-cloud-precipitation interactions, while another considers the chemical nature of individual size-resolved raindrops.
