In Extremis Disruptive Events and Trends in Climate and Hydrology /

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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Kropp, Jürgen (Επιμελητής έκδοσης), Schellnhuber, Hans-Joachim (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.