Robust Adaptation to Multiscale Climate Variability

[1]  Shaun Lovejoy,et al.  Low‐Frequency Weather and the Emergence of the Climate , 2013 .

[2]  Warren E. Walker,et al.  Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty , 2013 .

[3]  Jiqiang Guo,et al.  Stan: A Probabilistic Programming Language. , 2017, Journal of statistical software.

[4]  V. P. Dimri,et al.  Wavelet and rescaled range approach for the Hurst coefficient for short and long time series , 2007, Comput. Geosci..

[5]  C. Ropelewski,et al.  Global and Regional Scale Precipitation Patterns Associated with the El Niño/Southern Oscillation , 1987 .

[6]  Hisashi Nakamura,et al.  The Pacific Decadal Oscillation, Revisited , 2016 .

[7]  Bruno Merz,et al.  Floods and climate: emerging perspectives for flood risk assessment and management , 2014 .

[8]  Upmanu Lall,et al.  Regional Extreme Precipitation Events: Robust Inference From Credibly Simulated GCM Variables , 2018, Water Resources Research.

[9]  Demetris Koutsoyiannis,et al.  Climate change, the Hurst phenomenon, and hydrological statistics , 2003 .

[10]  J. Wallace,et al.  A Pacific Interdecadal Climate Oscillation with Impacts on Salmon Production , 1997 .

[11]  P. Bates,et al.  Hess Opinions: An interdisciplinary research agenda to explore the unintended consequences of structural flood protection , 2018, Hydrology and Earth System Sciences.

[12]  Michael Ghil,et al.  El Ni�o on the Devil's Staircase: Annual Subharmonic Steps to Chaos , 1994, Science.

[13]  Eric Jones,et al.  SciPy: Open Source Scientific Tools for Python , 2001 .

[14]  L. Rabiner,et al.  An introduction to hidden Markov models , 1986, IEEE ASSP Magazine.

[15]  C. Torrence,et al.  A Practical Guide to Wavelet Analysis. , 1998 .

[16]  Günter Blöschl,et al.  Flood frequency hydrology: 1. Temporal, spatial, and causal expansion of information , 2008 .

[17]  Upmanu Lall,et al.  Stochastic simulation model for nonstationary time series using an autoregressive wavelet decomposition: Applications to rainfall and temperature , 2007 .

[18]  Kyna Powers.  Benefit-Cost Analysis and the Discount Rate for the Corps of Engineers' Water Resource Projects: Theory and Practice , 2003 .

[19]  P. O'Gorman,et al.  The physical basis for increases in precipitation extremes in simulations of 21st-century climate change , 2009, Proceedings of the National Academy of Sciences.

[20]  Thiago G. Martins,et al.  Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors , 2014, 1403.4630.

[21]  K. Rypdal,et al.  ENSO dynamics: Low‐dimensional‐chaotic or stochastic? , 2012, 1206.5657.

[22]  Isaac M. Held,et al.  The Gap between Simulation and Understanding in Climate Modeling , 2005 .

[23]  Demetris Koutsoyiannis,et al.  The scientific legacy of Harold Edwin Hurst (1880–1978) , 2016 .

[24]  Edoardo Borgomeo,et al.  Risk, Robustness and Water Resources Planning Under Uncertainty , 2018 .

[25]  J. Aerts,et al.  Global exposure to river and coastal flooding - long term trends and changes , 2012 .

[26]  H. Madsen,et al.  Climate-driven variability in the occurrence of major floods across North America and Europe , 2017 .

[27]  Casey Brown,et al.  The End of Reliability , 2010 .

[28]  Björn Müller,et al.  Rethinking solar resource assessments in the context of global dimming and brightening , 2014 .

[29]  E. Barnes,et al.  Contrasting interannual and multidecadal NAO variability , 2015, Climate Dynamics.

[30]  F. Maruyama.  The Relation among the Solar Activity, the Total Ozone, QBO, NAO, and ENSO by Wavelet-Based Multifractal Analysis , 2018 .

[31]  Jaap Schellekens,et al.  Transient scenarios for robust climate change adaptation illustrated for water management in The Netherlands , 2015 .

[32]  C. Spence,et al.  Nonstationary decision model for flood risk decision scaling , 2016 .

[33]  Bruno Merz,et al.  Projecting flood hazard under climate change: an alternative approach to model chains , 2013 .

[34]  D. Schertzer,et al.  What Is Climate , 2013 .

[35]  Warren E. Walker,et al.  Dynamic adaptive policy pathways: A method for crafting robust decisions for a deeply uncertain world , 2013 .

[36]  K. Winemiller,et al.  Fish Migration, Dams, and Loss of Ecosystem Services in the Mekong Basin , 2010, AMBIO.

[37]  Achim Brauer,et al.  A 1600 yr seasonally resolved record of decadal-scale flood variability from the Austrian Pre-Alps , 2012 .

[38]  J. Geweke,et al.  THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS , 1983 .

[39]  John D. Hunter,et al.  Matplotlib: A 2D Graphics Environment , 2007, Computing in Science & Engineering.

[40]  Günter Blöschl,et al.  Climate change impacts—throwing the dice? , 2009 .

[41]  Balaji Rajagopalan,et al.  A Bayesian hierarchical nonhomogeneous hidden Markov model for multisite streamflow reconstructions , 2016 .

[42]  Upmanu Lall,et al.  A hierarchical Bayesian GEV model for improving local and regional flood quantile estimates , 2016 .

[43]  R. Seager,et al.  Megadroughts in North America: placing IPCC projections of hydroclimatic change in a long‐term palaeoclimate context , 2010 .

[44]  Tim N. Palmer,et al.  A nonlinear dynamical perspective on climate change , 1993 .

[45]  Upmanu Lall,et al.  Floods in a changing climate: Does the past represent the future? , 2001, Water Resources Research.

[46]  J. R. Wallis,et al.  Robustness of the rescaled range R/S in the measurement of noncyclic long run statistical dependence , 1969 .

[47]  A. Ångström.  Teleconnections of Climatic Changes in Present Time , 1935 .

[48]  Andrew Gelman,et al.  The Prior Can Often Only Be Understood in the Context of the Likelihood , 2017, Entropy.

[49]  P. Peduzzi,et al.  Global trends in tropical cyclone risk , 2012 .

[50]  B. Mandelbrot.  Self-Affine Fractals and Fractal Dimension , 1985 .

[51]  Francesco Serinaldi,et al.  Stationarity is undead: Uncertainty dominates the distribution of extremes , 2015 .

[52]  Shaun Lovejoy,et al.  The Weather and Climate: Emergent Laws and Multifractal Cascades , 2013 .

[53]  J. Salas,et al.  Techniques for assessing water infrastructure for nonstationary extreme events: a review , 2018 .

[54]  K. Trenberth,et al.  The changing character of precipitation , 2003 .

[55]  E. Barnes,et al.  Storm track processes and the opposing influences of climate change , 2016 .

[56]  Myles T. Collins,et al.  Managing the Risk of Uncertain Threshold Responses: Comparison of Robust, Optimum, and Precautionary Approaches , 2007, Risk analysis : an official publication of the Society for Risk Analysis.

[57]  Demetris Koutsoyiannis,et al.  Modeling and mitigating natural hazards: Stationarity is immortal! , 2014 .

[58]  I. Simonsen,et al.  Determination of the Hurst exponent by use of wavelet transforms , 1997, cond-mat/9707153.

[59]  Wes McKinney,et al.  Data Structures for Statistical Computing in Python , 2010, SciPy.

[60]  Christopher B. Field,et al.  Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: List of Major IPCC Reports , 2012 .

[61]  T A Carpenter,et al.  Colored noise and computational inference in neurophysiological (fMRI) time series analysis: Resampling methods in time and wavelet domains , 2001, Human brain mapping.

[62]  M. Kummu,et al.  Strong influence of El Niño Southern Oscillation on flood risk around the world , 2014, Proceedings of the National Academy of Sciences.

[63]  Dong Eun Lee,et al.  Predictability and prediction of persistent cool states of the Tropical Pacific Ocean , 2017, Climate Dynamics.

[64]  T. Willemain,et al.  Wavelet-Based Bootstrap for Time Series Analysis , 2005 .

[65]  Demetris Koutsoyiannis,et al.  Climatic Variability Over Time Scales Spanning Nine Orders of Magnitude: Connecting Milankovitch Cycles with Hurst–Kolmogorov Dynamics , 2013, Surveys in Geophysics.

[66]  A. Selvam.  Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall , 2010, Pure and Applied Geophysics.