In Extremis [electronic resource] : Disruptive Events and Trends in Climate and Hydrology /
Kropp, Jürgen.editor.
Schellnhuber, Hans-Joachim.editor.
The book addresses a weakness of current methodologies used in extreme value assessment, i.e. the assumption of stationarity, which is not given in reality. With respect to this issue a lot of new developed technologies are presented, i.e. influence of trends vs. internal correlations, quantitative uncertainty assessments, etc. The book not only focuses on artificial time series data, but has a close link to empirical measurements, in order to make the suggested methodologies applicable for practitioners in water management and meteorology.
Description based upon print version of record.
Includes bibliographical references and index.
Part I. General -- The Threat of Climate Extremes: The Need of New Assessment Methodologies -- Intense Precipitation and High Floods - Observations and Projections -- Wavelet Spectral and Cross Spectral Analysis -- Part II. Extremes and Trend Detection -- Trend Detection in River Floods -- Extreme Value Analysis Considering Trends -- Extreme Value and Trend Analysis based on Statistical Modelling of Precipitation Time Series -- Part III. Extremes and Correlations -- The statistics of Return Intervals, Maxima and Centennial Events under the Influence of Long-Term Correlations -- Detrended Fluctuation Studies of Long-Term Persistence and Multifractality of Precipitation and River Runoff Records -- Extraction of Long-term Structures from Southern German Runoff Data by Means of Linear and Nonlinear Dimensionality Reduction -- Part IV. Assessing Uncertainty -- The Bootstrap in Climate Risk Analysis -- Flood Level Confidence Intervals -- A Review on the Pettitt-Test -- Seasonality Effects on Nonlinear Properties of Hydrometeorological Records -- Part V. Spatial Issues -- Regional Determination of Historical Heavy Rain for Reconstruction of Extreme Flood Events -- Development of Regional Flood Frequency Relationships for Gauged and Ungauged Catchments Using L-Moments -- Spatial Correlations of River Runoffs in a Catchment.
The book addresses a weakness of current methodologies used in extreme value assessment, i.e. the assumption of stationarity, which is not given in reality. With respect to this issue a lot of new developed technologies are presented, i.e. influence of trends vs. internal correlations, quantitative uncertainty assessments, etc. The book not only focuses on artificial time series data, but has a close link to empirical measurements, in order to make the suggested methodologies applicable for practitioners in water management and meteorology.
Oceanography.
Climate change.
Statistics .
Environmental sciences.
Atmospheric sciences.
Hydrogeology.
Oceanography.
Climate Change/Climate Change Impacts.
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Environmental Physics.
Atmospheric Sciences.
Hydrogeology.