Decision support experiments and evaluations using seasonal to ...

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The U.S. Climate Change Science Program Chapter 1 22 Study or Experiment Chapter Long-Term Municipal Water Management Planning— New York City (NYC) 4, Experiment 2 Type of Decision Support Information Needed, Used or Delivered NYC is adapting strategic and capital planning to include the potential effects of climate change (i.e., sea- level rise, higher temperatures, increases in extreme events, and changing precipitation patterns) on the City’s water systems. NYC Department of Environmental Protection, in partnership with local universities and private sector consultants, is evaluating climate change projections, impacts, indicators, and adaptation and mitigation strategies to support agency decision making. most Successful Feature(s) or lesson(s) learned from Case Study This case illustrates (1) plans for regional capital improvements can include measures that reduce vulnerability to sea level rise; (2) the meteorological and hydrology communities need to define and communicate current and increasing risks, with explicit discussion of the inherent uncertainties; (3) more research is needed (e.g., to further reduce uncertainties associated with sea-level rise, provide more reliable predictions of changes in frequency/intensity of tropical and extra-tropical storms, etc.); (4) regional climate model simulations and statistical techniques used to predict long-term climate change impacts could be down-scaled to help manage projected SI climate variability; and (5) decision makers need to build support for adaptive action despite uncertainties. The extent and effectiveness of this action will depend on building awareness of these issues among decision makers, fostering processes of interagency interaction and collaboration, and developing common standards.
Study or Experiment Chapter Integrated Forecast and Reservoir Management (INFORM)—Northern California How Seattle Public Utility (SPU) District Uses Climate Information to Manage Reservoirs 4, Experiment 3 4, Experiment 4 Decision-Support Experiments and Evaluations using Seasonal to Interannual Forecasts and Observational Data: A Focus on Water Resources Type of Decision Support Information Needed, Used or Delivered INFORM aims to demonstrate the value of climate, weather, and hydrology forecasts in reservoir operations. Specific objectives are to: (1) implement a prototype integrated forecastmanagement system for the Northern California river and reservoir system in close collaboration with operational forecasting and management agencies, and (2) demonstrate the utility of meteorological/climate and hydrologic forecasts through near-real-time tests of the integrated system with actual data and management input. Over the past several years SPU has taken steps to improve incorporation of climate, weather, and hydrologic information into the real-time and SI management of its mountain water supply system. They are receptive to new management approaches due to public pressure and the risk of legal challenges related to the protection of fish populations most Successful Feature(s) or lesson(s) learned from Case Study INFORM demonstrated key aspects of integrated forecastdecision systems, i.e., (1) seasonal climate and hydrologic forecasts benefit reservoir management, provided that they are used in connection with adaptive dynamic decision methods that can explicitly account for and manage forecast uncertainty; (2) ignoring forecast uncertainty in reservoir regulation and water management decisions leads to costly failures; and (3) static decision rules cannot take full advantage of and handle forecast uncertainty information. The extent that forecasts help depends on their reliability, range, and lead time, in relation to the management systems’ ability to regulate flow, water allocation, etc. The SPU case shows: (1) access to skillful SI forecasts enhances credibility of using climate information in the region; (2) monitoring of snowpack moisture storage and mountain precipitation is essential for effective decision making and for detecting long-term trends that can affect water supply reliability; and (3) SPU has significant capacity to conduct in-house investigations/assessments. This provides confidence in the use of information. 23
Page 1 and 2: Decision-Support Experiments and Ev
Page 5 and 6: TABLE OF CONTENTS Abstract ........
Page 7 and 8: TABLE OF CONTENTS 5................
Page 9 and 10: ACKNOWLEDGEMENTS The authors would
Page 11 and 12: ABSTRACT Faced with mounting pressu
Page 15 and 16: PREFACE Report Motivation and Guida
Page 17 and 18: EXECUTIVE SUMMARY ES.1 WHAT IS DECI
Page 19 and 20: • Improved bias corrections in ex
Page 21 and 22: • • ness with customized produc
Page 23 and 24: CHAPTER 1 1.1 INTRODUCTION Increasi
Page 25 and 26: western United States and is the ba
Page 29 and 30: Study or Experiment Chapter CPC Sea
Page 31: Study or Experiment Chapter Interpr
Page 35 and 36: Study or Experiment Chapter Regiona
Page 37 and 38: Study or Experiment Chapter Murray-
Page 39 and 40: Study or Experiment Chapter Integra
Page 41 and 42: Study or Experiment Chapter Regiona
Page 43 and 44: Study or Experiment Chapter Murray-
Page 45 and 46: CHAPTER 2 KEY FINDINGS Decision-Sup
Page 47 and 48: 2.1 INTRODUCTION In the past, water
Page 49 and 50: data and forecast products that sup
Page 51 and 52: BOX 2.2: Forecast Approaches Decisi
Page 53 and 54: cal elements, including models, dat
Page 55 and 56: a sub-seasonal lead time, the singl
Page 57 and 58: The hydrologic and water resources
Page 59 and 60: forecasts link to CPC drought produ
Page 61 and 62: losses of snowpack and the tendenci
Page 63 and 64: At NCEP, the dynamical tool, CFS, i
Page 67 and 68: 2.4.1 Improving Seasonal-to- Intera
Page 69 and 70: climate variations. The rationale f
Page 71 and 72: 2.4.2.2 improvementS in hydrologic
Page 73 and 74: BOX 2.3: The CPC Seasonal Drought O
Page 75 and 76: Koch’s research to operational pr
Page 77 and 78: BOX 2.4: What Role Can a "Testbed"
Page 79 and 80: satisfy all users. The Advanced Hyd
Page 81 and 82: CHAPTER 3 KEY FINDINGS Decision-Sup
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discuss impediments to forecast inf
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Commission (SRBC) to pave the way f
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BOX 3.1: Georgia Drought Decision-S
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Figure 3.1 Water resources decision
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frameworks for decision making are
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Adaptive capacity is the least expl
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tions, discussion, feedback, and re
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water quality in downstream reservo
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25 years, as predicted by the Energ
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forecasting, however, is hampered b
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3.2.5 Reliability and Trustworthine
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mental conditions (e.g., demands fo
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it must involve an extended group o
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egional population and economic gro
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Decision-Support Experiments and Ev
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to the gravity of its consequences.
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Decision-Support Experiments and Ev
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CHAPTER 4 KEY FINDINGS Decision-Sup
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including ecological restoration, r
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For example, observed global sea-le
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into the Pacific Ocean. The Norther
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leaders in considering climate chan
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and communities vulnerable to wildf
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tion patterns. There are concerns t
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forecasts in the region also enhanc
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knowledge, as well as development o
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obust communication in which each s
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Organizational measures to hasten,
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and, thus, able to span the domains
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in climate and weather (Garfin and
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local water supply sector: the grow
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investment” efforts and their eff
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time by the interest of groups to c
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Case Study F: Southeast Climate Con
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ect application of climate science
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a receptive audience for new tools
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strength offered by the case study
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CHAPTER 5 5.1 INTRODUCTION The futu
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poverty, and resources are required
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Fostering inclusive, equitable acce
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effective in managing problems, or
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5.3.1 A Better Understanding of Vul
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on climate variability and water re
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apid development of better decision
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APPENDIX A Decision-Support Experim
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APPENDIX B Decision-Support Experim
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GLOSSARY AND ACRONYMS adaptive capa
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ACRONYMS AND ABBREVIATIONS ACCAP Al
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REFERENCES References marked with (
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Atger, F., 2003: Spatial and intera
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Hughes, M.K. and P.M. Brown, 1992:
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of seasonal forecasts. Bulletin of
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Brandon, D., B. Udall, and J. Lowre
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Georgia Forestry Commission, 2007:
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Leatherman, S.P. and G. White, 2005
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Pringle, C.M., 2000: Threats to U.S
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Yarnal, B., A.L. Heasley, R.E. O’
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Gallaher, B.M. and R.J. Koch, 2004:
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McNie, E.C., 2007: Reconciling the
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* Trimble, P.J., E.R. Santee, and C
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Hartmann, H., 2001: Stakeholder Dri
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PHOTGRAPHY CREDITS Cover/Title Page
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Global Change Research Information
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