AMS (American Meteorological Society). 2002. Enhancing weather information with probability forecasts. Bulletin of the American Meteorological Society 83:450-452. Available at http://www.ametsoc.org/POLICY/enhancingwxprob_final.html. Accessed April 26, 2006.
Anagnostou, E. N., and W. F. Krajewski. 1999. Real-time radar rainfall estimation. Part I: Algorithm formulation. Journal of Atmospheric and Oceanic Technology 16(2):189-197.
Anderson, E. A. 1996. Hydro 17—Snow Model. NWSRFS Users Manual, Part II.2. Silver Spring, MD: NOAA National Weather Service.
Baars, J. A., and C. F. Mass. 2005. Performance of National Weather Service forecasts compared to operational, consensus, and weighted model output statistics. Weather and Forecasting 20(6):1034-1047.
Bernoulli, D. 1738. Specimen Theoriae Novae de Mensura Sortis. Pp. 175-192 in Commentarii Academiae Scientarium Imperialis Petropolitanae, Tomus V (Papers of the Imperial Academy of Science in Petersburg, Vol. V). Translated by L. Sommer (1954) as Exposition of a new theory of the measurement of risk. Econometrica 22:23-26.
Beven, K. J. 1989. Changing ideas in hydrology—the case of physically-based models. Journal of Hydrology 105:157-172.
Broad, K., T. Leiserowitz, J. Weinkle, and M. Steketee. 2006. Media and public interpretation of hurricane forecasts: Evidence from Florida 2004. Bulletin of the American Meteorological Society (under review).
Brown, B. G., and A. H. Murphy. 1987. Quantification of uncertainty in fire-weather forecasts: Some results of operational and experimental forecasting programs. Weather and Forecasting 2:190-205.
Brown, B. G., R. W. Katz, and A. H. Murphy. 1986. On the economic value of seasonal-precipitation forecasts: The fallowing/planting problem. Bulletin of the American Meteorological Society 67:833-841.
Burnash, R. J. C. 1995. The NWS River Forecast System—Catchment Model. Chapter 10, pp. 311-365 in Computer Models of Watershed Hydrology, V.P. Singh, ed. Highlands Ranch, CO: Water Resources Publications.
Camerer, C., and M. Weber. 1992. Recent developments in modeling preferences: Uncertainty and ambiguity. Journal of Risk and Uncertainty 5:325-370.
Carpenter, T. M., and K. P. Georgakakos. 2004. Impacts of parametric and radar rainfall uncertainty on the ensemble streamflow simulations of a distributed hydrologic model. Journal of Hydrology 298:202-221.
Carpenter, T. M., J. A. Sperfslage, K. P. Georgakakos, T. Sweeney, and D. L. Fread. 1999. National threshold runoff estimation utilizing GIS in support of operational flash flood warning systems. Journal of Hydrology 224:21-44.
Chaiken, S., and Y. Trope. 1999. Dual process theories in social psychology. New York: Guilford Publications.
Changnon, D. 2000. Who used and benefited from the El Niño forecasts? Pp. 109-135 in El Niño 1997-1998: The Climate Event of the Century, S. A. Changnon, ed. New York: Oxford University Press.
Changnon, S. A. 2002. Impacts of the midwestern drought forecasts of 2000. Journal of Applied Meteorology 41(10):1042-1052.
Changnon, S. A. 2005. Applied climatology: The golden age has begun. Bulletin of the American Meteorological Society 86:915-919.
Changnon, S. A., J. M. Changnon, and D. Changnon. 1995. Uses and applications of climate forecasts for power utilities. Bulletin of the American Meteorological Society 76:711-720.
Charba, J. P. 1998. The LAMP QPF products. Part I: Model development. Weather and Forecasting 13:934-965.
Chatfield, C. 1995. Model Uncertainty, Data Mining and Statistical Inference. Journal of the Royal Statistical Society 158A:419-466.
Cheng, W. Y. Y., and W. R. Cotton. 2004. Sensitivity of a cloud-resolving simulation of the genesis of a mesoscale convective system to horizontal heterogeneities in soil moisture initialization. Journal of Hydro-meteorology 5(5):934-958.
Colle, B. A., J. B. Olson, and J. S. Tongue. 2003a. Multiseason verification of the MM5. Part I: Comparison with the Eta model over the central and eastern United States and impact of MM5 resolution. Weather and Forecasting 18(3):431-457.
Colle, B. A., J. B. Olson, and J. S. Tongue. 2003b. Multiseason verification of the MM5. Part II: Evaluation of high-resolution precipitation forecasts over the northeastern United States. Weather and Forecasting 18(3):458-480.
Cooke, W. E. 1906. Weighting forecasts. Monthly Weather Review 34:274-275.
Damasio, A. R. 1994. Descartes’ Error: Emotion, Reason, and the Human Brain. New York: Putnam.
Day, G. N. 1985. Extended streamflow forecasting using the NWS-RFS. Journal of Water Resources Planning and Management 111(2):157-170.
De Elia, R., and R. Laprise. 2005a. Diversity in interpretations of probability: implications for weather forecasting. Monthly Weather Review 133:1129-1143.
De Elia, R., and R. Laprise. 2005b. The unbearable lightness of probabilities. Bulletin of the American Meteorological Society 86:1224-1225.
Draper, D. 1995. Assessment and propagation of model uncertainty. Journal of the Royal Statistical Society 57B:45-97.
Du, J., G. DiMego, M. S. Tracton, and B. Zhou. 2003. NCEP short-range ensemble forecasting (SREF) system: Multi-IC, multi-model and multi-physics approach. Research Activities in Atmospheric and Oceanic Modelling, J. Côté, ed. Report 33 CAS/JSC Working Group Numerical Experimentation (WGNE), WMO/TD-No. 1161, 5.09-5.10. Available at http://www.emc.ncep.noaa.gov/mmb/SREF/srefWMO_2003.pdf. Accessed April 28, 2006.
Duan, Q., J. Schaake, and V. Koren. 2001. A priori estimation of land surface model parameters. Pp. 77-94 in Land Surface Hydrology, Meteorology and Climate, Observations and Modeling, V. Lakshmi, J. Albertson, and J. Schaake, eds. AGU Water Science and Application 3. Washington, D.C.: American Geophysical Union.
Dutton, J. A. 2002. Opportunities and priorities in a new era for weather and climate services. Bulletin of the American Meteorological Society 83:1303-1311.
Ellsberg, D. 1961. Risk, ambiguity, and the Savage axioms. Quarterly Journal of Economics 75:643-669.
Epstein, E. S. 1962. A Bayesian approach to decision making in applied meteorology. Journal of Applied Meteorology 1(2):169-177.
Epstein, E. S. 1969. The role of uncertainties in prediction. Journal of Applied Meteorology 8:190-198.
Epstein, S. 1994. Integration of the cognitive and the psychodynamic unconscious. American Psychologist 49:709-724.
Evensen, G. 1994. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. Journal of Geophysical Research 99(C5):10,143-10,162.
Farnsworth, R. K., E. S. Thompson, and E. L. Peck. 1982. Evaporation Atlas for the Contiguous 48 United States. NOAA Technical Report NWS 33. Washington, D.C.: NOAA/National Weather Service.
Finnerty, B. D., M. B. Smith, D-J. Seo, V. Koren, and G. E. Moglen. 1997. Space-time scale sensitivity of the Sacramento model to radar-gage precipitation inputs. Journal of Hydrology 203:21-38.
Fischhoff, B. 1994. What forecasts (seem to) mean. International Journal of Forecasting 10:387-403.
Fox, C. R., and A. Tversky. 1995. Ambiguity aversion and comparative ignorance. Quarterly Journal of Economics 110:585-603.
Fread, D. L., R. C. Shedd, G. F. Smith, R. Farnsworth, C. N. Hoffeditz, L. A. Wenzel, S. M. Wiele, J. A. Smith, and G. N. Day. 1995. Modernization in the National Weather Service river and flood program. Weather and Forecasting 10(3):477-484.
Georgakakos, K. P. 2006. Analytical results for operational flash flood guidance. Journal of Hydrology 317:81-103.
Georgakakos, K. P., and T. M. Carpenter. 2005. Potential value of operationally available and spatially distributed ensemble soil water estimates for agriculture. Journal of Hydrology (in revision).
Georgakakos, K. P., and R. Krzysztofowicz, eds. 2001. Special Issue on Probabilistic and Ensemble Forecasting. Journal of Hydrology 249:1-196.
Georgakakos, K. P., N. E. Graham, T. M. Carpenter, A. P. Georgakakos, and H. Yao. 2005. Integrating climate-hydrology forecasts and multi-objective reservoir management for Northern California. Eos 86(12):122-127.
Gigerenzer, G., and U. Hoffrage. 1995. How to improve Bayesian reasoning without instruction: Frequency formats. Psychological Review 102:684-704.
Gigerenzer, G., R. Hertwig, E. van den Broek, B. Fasolo, and K. Katsikopoulos. 2005. “A 30% Chance of Rain Tomorrow”: How does the public understand probabilistic weather forecasts? Risk Analysis 25:1-7.
Glahn, H. R. 1964. Use of decision theory in meteorology. Monthly Weather Review 92:383-388.
Gneiting, T., A. E. Raftery, A. H. Westveld III, and T. Goldman. 2005. Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation. Monthly Weather Review 133:1098-1118.
Grimit, E. P., and C. F. Mass. 2002. Initial results of a mesoscale short-range ensemble forecasting system over the Pacific Northwest. Weather and Forecasting 17:192-205.
Hager, P. J., and H. J. Scheiber. 1997. Designing and Delivering Scientific, Technical, and Managerial Presentations. New York: John Wiley & Sons.
Hallenbeck, C. 1920. Forecasting precipitation in percentages of probability. Monthly Weather Review 48:645-647.
Hamill, T. M. 2001. Interpretation of rank histograms for verifying ensemble forecasts. Monthly Weather Review 129:550-560.
Hamill, T. M., J. S. Whitaker, and S. L. Mullen. 2006. Reforecasts: An important dataset for improving weather predictions. Bulletin of the American Meteorological Society 87:33-46.
Hansen, J., S. Marx, and E. U. Weber. 2004. The role of climate perceptions, expectations, and forecasts in farmer decision making: The Argentine Pampas and South Florida. Technical Report 04-01. Palisades, NY: International Research Institute for Climate Prediction.
Hart, K. A., W. J. Steenburgh, D. J. Onton, and A. J. Siffert. 2004. An evaluation of mesoscale-model-based model output statistics (MOS) during the 2002 Olympic and Paralympic winter games. Weather and Forecasting 19:200-218.
Heath, C., and A. Tversky. 1991. Preference and belief: Ambiguity and competence in choice under uncertainty. Journal of Risk and Uncertainty 4:5-28.
Hersbach, H. 2000. Decomposition of the continuous ranked probability score for ensemble prediction systems. Weather and Forecasting 15:559-570.
Hertwig, R., G. Barron, E. U. Weber, and I. Erev. 2004. Decisions from experience and the effect of rare events. Psychological Science 15:534-539.
Hertwig, R., G. Barron, E. U. Weber, and I. Erev. 2006. The role of information sampling in risky choice. Pp. 72-91 in Information Sampling and Adaptive Cognition, K. Fiedler and P. Juslin, eds. New York: Cambridge University Press.
Higgins, E. T. 1999. Persons and situations: Unique explanatory principles or variability in general principles? Pp. 61–93 in The coherence of personality: Social-cognitive bases of consistency, variability, and organization, D. Cervone and Y. Shoda, eds. New York: Guilford Press.
Holtgrave, D. R., and E. U. Weber. 1993. Dimensions of risk perception for financial and health risks. Risk Analysis 13:553-558.
Houtekamer, P. L., and H. L. Mitchell. 1998. Data assimilation using an ensemble Kalman filter technique. Monthly Weather Review 126:796-811.
Huberman, G. 2001. Familiarity breeds investment. Review of Financial Studies XIV:659-680.
Jardine, C. G., and S. E. Hrudey. 1997. Mixed messages in risk communication. Risk Analysis 17(4):489-498.
Johnson, E. J., and D. Goldstein. 2003. Do defaults save lives? Science 302:1338-1339.
Jolliffe, I. T., and D. B. Stephenson. 2003. Forecast Verification: A Prac-titioner’s Guide in Atmospheric Science. New York: Wiley and Sons.
Jordan, P. W., A. W. Seed, and P. E. Weinmann. 2003. A stochastic model of radar measurement errors in rainfall accumulations at catchment scale. Journal of Hydrometeorology 4(5):841-855.
Kahneman, D., and A. Tversky. 1979. Prospect theory: An analysis of decision under risk. Econometrica 47:263-292.
Katz, R. W., and A. H. Murphy. 1997. Economic Value of Weather and Climate Forecasts. New York: Cambridge University Press.
Katz, R. W., A. H. Murphy, and R. L. Winkler. 1982. Assessing the value of frost forecasts to orchardists: A dynamic decision-making approach. Journal of Applied Meteorology 21:518– 531.
Keeney, R. L., and H. Raiffa. 1976. Decision with Multiple Objectives: Preferences and Value Tradeoffs. New York: John Wiley and Sons.
Keith, R. 2003. Optimization of value of aerodrome forecasts. Weather and Forecasting 18:808-824.
Kitanidis, P. K., and R. L. Bras. 1980. Real-time forecasting with a conceptual hydrologic model. Part 1: Analysis of uncertainty. Water Resources Research 16(6):1025-1033.
Krzysztofowicz, R., W. J. Drzal, T. Rossi-Drake, J. C. Weyman, and L. A. Giordano. 1993. Probabilistic quantitative precipitation forecasts for river basins. Weather and Forecasting 8(4):424-439.
Kuligowski, R. J. 2002. A self-calibrating real-time GOES rainfall algorithm for short-term rainfall estimates. Journal of Hydrometeorology 3(2):112-130.
Larson, L. W., R. L. Ferral, E. T. Strem, A. J. Morin, B. Armstrong, T. R. Carroll, M. D. Hudlow, L. A. Wenzel, G. L. Schaefer, and D. E. Johnson. 1995. Operational responsibilities of the National Weather Service river and flood program. Weather and Forecasting 10(3):465-476.
Leith, C. E. 1974. Theoretical skill of Monte Carlo forecasts. Monthly Weather Review 102:409-418.
Liljas, E., and A. H. Murphy. 1994. Anders Ångström and his early papers on probability forecasting and the use/value of weather forecasts. Bulletin of the American Meteorological Society 75:1227-1236.
Lipkus, I. M., G. Samsa, and B. K. Rimer. 2001. General performance on a numeracy scale among highly educated samples. Medical Decision Making 21:37-44.
Loewenstein, G. F., E. U. Weber, C. K. Hsee, and E. Welch. 2001. Risk as feelings. Psychological Bulletin 127:267-286.
Lorenz, E. N. 1963. Deterministic nonperiodic flow. Journal of the Atmospheric Sciences 20:130-141.
Lorenz, E. N. 1965. A study of the predictability of a 28-variable atmospheric model. Tellus 17:321-333.
Lorenz, E. N. 1968. On the range of atmospheric predictability. Pp. 11-19 in Proceedings of the First Statistical Meteorology Conference. Hartford, CT: American Meteorological Society.
Lorenz, E. N. 1969. Atmospheric predictability as revealed by naturally occurring analogues. Journal of Atmospheric Science 26:636-646.
Loucks, D. P., ed. 1989. Systems Analysis for Water Resources Management: Closing the Gap Between Theory and Practice. IAHS Publication No. 180. Wallingford, UK: IAHS Press, Institute of Hydrology, 303 pp.
Maloney, J. C. 2002. Eta-based MOS probability of precipitation (PoP) and quantitative precipitation forecast (QPF) guidance for the continental United States. NWS Technical Procedures Bulletin No. 487. Silver Spring, MD: National Oceanic and Atmospheric Administration.
Marx, S., E. U. Weber, D. Krantz, B. Orlove, A. Leiserowitz, C. Roncoli, and J. Phillips. 2006. Affective and statistical strategies in communicating climate uncertainty to individuals and groups. Global Environmental Change (under review).
Mason, I. 1982. A model for assessment of weather forecasts. Australian Meteorological Magazine 30:291-303.
McEnery, J., J. Ingram, Q. Duan, T. Adams, and L. Anderson. 2005. NOAA’s Advanced Hydrologic Prediction Service: Building pathways for better science in water forecasting. Bulletin of the American Meteorological Society 86(3):375-385.
McQueen, J., J. Du, B. Zhou, G. Manikin, B. Ferrier, H.-Y. Chuang, G. DiMego, and Z. Toth. 2005. Recent upgrades to the NCEP Short Range Ensemble Forecasting System (SREF) and future plans. In Preprints, 7th Conference on Numerical Weather Prediction/21st Conference on Weather Analysis and Forecasting, Washington, D.C., Aug. 1-5. Wash-ington, D.C.: American Meteorological Society.
Mellers, B., R. Hertwig, and D. Kahneman. 2001. Do frequency representations eliminate conjunction effects? An exercise in antagonistic collaboration. Psychological Science 12:269-275.
Morgan, M. G., and M. Henrion. 1990. Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis. New York: Cambridge University Press.
Morgan, M. G., B. Fischhoff, A. Bostrom, and C. Atman. 2002. Risk Communication: A Mental Models Approach. New York: Cambridge University Press, 351pp.
Morss, R. E., O. V. Wilhelmi, M. W. Downton, and E. Gruntfest. 2005. Flood risk, uncertainty, and scientific information for decision-making: Lessons from an interdisciplinary project. Bulletin of the American Meteorological Society 86:1593-1601.
Moss, R. H., and S. H. Schneider. 2000. Uncertainties in the IPCC TAR: Recommendations to Lead Authors for More Consistent Assessment and Reporting. Pp. 33-51 in Guidance Papers on the Cross Cutting Issues of the Third Assessment Report of the IPCC, R. Pachauri, T. Taniguchi, and K. Tanaka, eds. Geneva: World Meteorological Organization.
Murphy, A. H. 1976. Decision-making models in the cost-loss ratio situation and measures of the value of probability forecasts. Monthly Weather Review 104(8):1058-1065.
Murphy, A. H. 1977. The value of climatological, categorical and probabilistic forecasts in the cost-loss ratio situation. Monthly Weather Review 105:803-816.
Murphy, A. H. 1993. What is a good forecast? An essay on the nature of goodness in weather forecasting. Weather and Forecasting 8:281-293.
Murphy, A. H., and R. L. Winkler. 1982. Subjective probabilistic tor-nado forecasts: Some experimental results. Monthly Weather Review 110:1288-1297.
Murphy, A. H., and Q. Ye. 1990. Comparison of objective and subjective precipitation probability forecasts: The sufficiency relation. Monthly Weather Review 118(9):1783-1792.
Murphy, A., S. Lichtenstein, B. Fischhoff, and R. L. Winkler. 1980. Misinterpretation of precipitation probability forecasts. Bulletin of the American Meteorological Society 61:695-701.
Neter, J., W. Wasserman, and M. H. Kutner. 1996. Applied Linear Statistical Models. New York: McGraw-Hill, 1408 pp.
Nicholls, N. 1999. Cognitive Illusions, Heuristics, and Climate Prediction. Bulletin of the American Meteorological Society 80:1385-1397.
NOAA (National Oceanic and Atmospheric Administration). 1999. NOAA’s Coastal Assessment and Data Synthesis System: Physical and Hydro-logic Characteristics of Coastal Watersheds. Silver Spring, MD: NOAA. Available at http://spo.nos.noaa.gov/projects/cads/data_references/pandh/P_and_H_doc.pdf. Accessed July 30, 2006.
NRC (National Research Council). 1995. Flood Risk Management and the American River Basin: An Evaluation. Washington, DC: National Academy Press.
NRC. 1999a. Improving American River Flood Frequency Analyses. Wash-ington, DC: National Academy Press.
NRC. 1999b. A Vision for the National Weather Service: Road Map for the Future. Washington, DC: National Academy Press.
NRC. 1999c. Making Climate Forecasts Matter. Washington, DC: National Academy Press.
NRC. 2000. From Research to Operations in Weather Satellites and Numerical Weather Prediction: Crossing the Valley of Death. Washing-ton, DC: National Academy Press.
NRC. 2003a. Fair Weather: Effective Partnerships in Weather and Climate Services. Washington, DC: The National Academies Press.
NRC. 2003b. Communicating Uncertainties in Weather and Climate Information. Washington, DC: The National Academies Press.
Ntelekos, A. A., W. F. Krajewski, and K. P. Georgakakos. 2006. On the uncertainties of flash flood guidance: Towards probabilistic forecasting of flash floods. Journal of Hydrometeorology (in press).
NWS (National Weather Service). 2003. Building Pathways for Better Science and Technology in Water Forecasts. Office of Hydrologic Development Strategic Plan for FY 2003-2008 Version 1.1. Great Falls, VA: Varone Consulting Group, Inc.
Olson, D. A., N. W. Junker, and B. Korty. 1995. Evaluation of 33 years of quantitative precipitation forecasting at the NMC. Weather Forecasting 10:498-511.
Pielke, R. A., Jr. 1999. Who decides? Forecasts and responsibilities in the 1997 Red River floods. Applied Behavioral Science Review 7:83-101.
Power, S., B. Sadler, and N. Nicholls. 2005. The influence of climate science on water management in Western Australia: Lessons for climate scientists. Bulletin of the American Meteorological Society 86(6):839-844.
Raftery, A. E., T. Gneiting, F. Balabdaoui, and M. Polakowski. 2005. Using Bayesian model averaging to calibrate forecast ensembles. Monthly Weather Review 133:1155-1174.
Reed, S., D. Johnson, and T. Sweeney. 2002. Application and national geographic information system database to support two-year flood and threshold runoff estimates. Journal of Hydrologic Engineering 7(3):209-219.
Richardson, D. S. 2001. Ensembles using multiple models and analyses. Quarterly Journal of the Royal Meteorological Society 172:1847-1664.
Roulston, M. S., and L. A. Smith. 2002. Evaluating probabilistic forecasts using information theory. Monthly Weather Review 130:1653-1660.
Roulston, M. S., and L. A. Smith. 2003. Combining dynamical and statistical ensembles. Tellus 55A:16-30.
Saha, S., S. Nadiga, C. Thiaw, J. Wang, W. Wang, Q. Zhang, H. M. van den Dool, H.-L. Pan, S. Moorthi, D. Behringer, D. Stokes, M. Pena, S. Lord, G. White, W. Ebisuzaki, P. Peng, and P. Xie. 2006. The NCEP Climate Forecast System. Journal of Climate (accepted). Available at http://www.emc.ncep.noaa.gov/gmb/ssaha/cfs_data/cfs_paper_revised.pdf. Accessed April 28, 2006.
Samuelson, W., and R. Zeckhauser. 1988. Status quo bias in decision making. Journal of Risk and Uncertainty 1(1):7-59.
Seo, D. J., V. Koren, and N. Cajina. 2003. Real-time variational assimilation of hydrologic and hydrometeorological data into operational hydrologic forecasting. Journal of Hydrometeorology 4(3):627-641.
Simpson, J. J., M. D. Dettinger, F. Gehrke, T. J. McIntire, and G. L. Hufford. 2004. Hydrologic scales, cloud variability, remote sensing, and models: Implications for forecasting snowmelt and streamflow. Weather and Forecasting 19(2):251-276.
Sinaceur, M., and C. Heath. 2005. Emotional and deliberative reactions to a public crisis: Mad cow disease in France. Psychological Science 16:247-254.
Sloman, S. A. 1996. The empirical case for two systems of reasoning. Psychological Bulletin 1(119):3-22.
Smith, J. A., G. N. Day, and M. D. Kane. 1991. A Nonparametric Framework for Long-Range Streamflow Forecasting. WMO/TD-428. Geneva: World Meteorological Organization.
Smith, M. B., K.P. Georgakakos, and X. Liang, eds. 2004. Special Issue on the Distributed Model Intercomparison Project (DMIP). Journal of Hydrology 298:1-334.
Smith, P. J., and J. T. Snow. 1997. Tenth meeting of heads and chairs of departments of atmospheric, oceanic, hydrologic, and related sciences: A summary. Bulletin of the American Meteorological Society 78:1165-1175.
Sokol, Z. 2003. MOS-based precipitation forecasts for river basins. Weather and Forecasting 18:769-781.
Stensrud, D. J., and N. Yussouf. 2003. Short-range ensemble predictions of 2-m temperature and dewpoint temperature over New England. Monthly Weather Review 131(10): 2510-2524.
Sweeney, T. L. 1992. Modernized Areal Flash Flood Guidance. NOAA Technical report NWS HYDRO 44. Silver Spring, MD: NOAA/NWS Hydrology Laboratory.
Talagrand, O., R. Vautard, and B. Strauss. 1997. Evaluation of probabilistic prediction systems. Pp. 1-25 in Proceedings of ECMWF Workshop on Predictability, Shinfield Park, Reading, UK, October 20-22.
Taylor, A. A., and L. M. Leslie. 2005. A single-station approach to model output statistics temperature forecast error assessment. Weather and Forecasting 20:1006-1020.
Thompson, J. C. 1962. Economic gains from scientific advances and operational improvements in meteorological prediction. Journal of Applied Meteorology 1:13-17.
Thompson, J. C., and G. W. Brier. 1955. The economic utility of weather forecasts. Monthly Weather Review 83:249-253.
Torn, R., and G. J. Hakim. 2005. Real-Time Ensemble Data Assimilation at the University of Washington. Presented at the American Meteorological Society 21st Conference on Weather Analysis and Forecasting/17th Conference on Numerical Weather Prediction, Washington, D.C., August 5.
Toth, Z., and E. Kalnay. 1993. Ensemble forecasting at NMC: The generation of perturbations. Bulletin of the American Meteorological Society 74:2317-2330
Tufte, E. R. 2001. The Visual Display of Quantitative Information. 2nd ed. Cheshire, CT: Graphics Press.
Tversky, A., and D. Kahneman. 1974. Judgment under uncertainty: Heuristics and biases. Science 185:1124-1130.
Tversky, A., and D. Kahneman. 1992. Cumulative prospect theory: An analysis of decision under uncertainty. Journal of Risk and Uncertainty 5:297-323.
USACE (U.S. Army Corps of Engineers). 2002. Forecast-Based Advance Release at Folsom Dam, Effectiveness and Risks, Phase I. HEC Report PR-48. Davis, CA: Hydrologic Engineering Center, USACE, 93 pp.
Wallsten, T. S. 1990. Measuring vague uncertainties and understanding their use in decision making. Pp. 377-399 in Acting Under Uncertainty: Multidisciplinary Conceptions, G. F. Furstenberg, ed. Boston: Kluwer Academic Publishers.
Wallsten, T. S., D. V. Budescu, A. Rapoport, R. Zwick, and B. Forsyth. 1986. Measuring the vague meanings of probability terms. Journal of Experimental Psychology 115:348-365.
Wallsten, T. S., D. V. Budescu, R. Zwick, and S. M. Kemp. 1993. Preferences and reasons for communicating probabilistic information in verbal or numerical terms. Bulletin of the Psychonomic Society 31:135-138.
Wallsten, T. S., D. V. Budescu, I. Erev, and A. Diederich. 1997. Evaluating and combining subjective probability estimates. Journal of Behavioral Decision Making 10:243-268.
Wang, X., and C. H. Bishop. 2005. Improvement of ensemble reliability with a new dressing kernel. Quarterly Journal of the Royal Meteorological Society 131:965-986.
Warner, T. T., E. A. Brandes, J. Sun, D. N. Yates, and C. K. Mueller. 2000. Prediction of a flash flood in complex terrain. Part I: A comparison of rainfall estimates from radar, and very short range rainfall simulations from a dynamic model and an automated algorithmic system. Journal of Applied Meteorology 39(6):797-814.
Weber, E. U. 1994. From subjective probabilities to decision weights: The effect of asymmetric loss functions on the evaluation of uncertain outcomes and events. Psychological Bulletin 115:228-242.
Weber, E. U., and D. J. Hilton. 1990. Contextual effects in the interpretations of probability words: Perceived base rate and severity of events. Journal of Experimental Psychology: Human Perception and Performance 16:781-789.
Weber, E. U., U. Böckenholt, D. J. Hilton, and B. Wallace. 2000. Confidence judgments as expressions of experienced decision conflict. Risk Decision and Policy 5:1-32.
Weber, E. U., S. Shafir, and A.-R. Blais. 2004. Predicting risk sensitivity in humans and lower animals: Risk as variance or coefficient of variation. Psychological Review 111:430-445.
Weber, E. U., N. Siebenmorgen, and M. Weber. 2005. Communicating asset risk: How name recognition and the format of historic volatility information affect risk perception and investment decisions. Risk Analysis 25:597-609.
Wilks, D. S. 2004. The minimum spanning tree histogram as a verification tool for multidimensional ensemble forecasts. Monthly Weather Review 132:1329-1340.
Wilks, D. S. 2006. Statistical Methods in the Atmospheric Sciences. San Diego, CA: Academic Press.
Wilks, D. S., and T. M. Hamill. 1995. Potential economic value of ensemble-based surface-weather forecasts. Monthly Weather Review 123:3565-3575.
WSAT (Water Sector Assessment Team). 2000. Water: The Potential Consequences of Climate Variability and Change for the Water Resources of the United States. Report of the Water Sector Assessment Team of the National Assessment of the Potential Consequences of Climate Variability and Change for the U.S. Global Change Research Program. Reston, VA: United States Geological Survey.
Yao, H., and A. Georgakakos. 2001. Assessment of Folsom Lake response to historical and potential future climate scenarios. Journal of Hydrology 249:176-196.
Yates, D. N., T. T. Warner, and G. H. Leavesley. 2000. Prediction of a flash flood in complex terrain. Part II: A comparison of flood discharge simulations using rainfall input from radar, a dynamic model, and an automated algorithmic system. Journal of Applied Meteorology 39(6):815-825.
Zhang, F., Z. Meng, and Z. Aksoy. 2006. Test of an ensemble Kalman filter for mesoscale and regional-scale data assimilation. Part I: Perfect model experiments. Monthly Weather Review 134:722-736.