TY  - BOOK
AU  - Kropp,Jürgen
AU  - Schellnhuber,Hans-Joachim
ED  - SpringerLink (Online service)
TI  - In Extremis: Disruptive Events and Trends in Climate and Hydrology 
SN  - 9783642148637
AV  - GC1-1581 
U1  - 551.46 23
PY  - 2011///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Geography
KW  - Hydraulic engineering
KW  - Meteorology
KW  - Oceanography
KW  - Climatic changes
KW  - Physical geography
KW  - Earth Sciences
KW  - Climate Change
KW  - Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
KW  - Environmental Physics
KW  - Meteorology/Climatology
KW  - Hydrogeology
N1  - 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
N2  - 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
UR  - http://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-14863-7
ER  -