Conceptual study on incorporating user information into forecasting systems

Abstract

The purpose of improving weather forecast is to enhance the accuracy in weather prediction. An ideal forecasting system would incorporate user-end information. In recent years, the meteorological community has begun to realize that while general improvements to the physical characteristics of weather forecasting systems are becoming asymptotically limited, the improvement from the user end still has potential. The weather forecasting system should include user interaction because user needs may change with different weather. A study was conducted on the conceptual forecasting system that included a dynamic, user-oriented interactive component. This research took advantage of the recently implemented TIGGE (THORPEX interactive grand global ensemble) project in China, a case study that was conducted to test the new forecasting system with reservoir managers in Linyi City, Shandong Province, a region rich in rivers and reservoirs in eastern China. A self-improving forecast system was developed involving user feedback throughout a flood season, changing thresholds for flood-inducing rainfall that were responsive to previous weather and hydrological conditions, and dynamic user-oriented assessments of the skill and uncertainty inherent in weather prediction. This paper discusses ideas for developing interactive, user-oriented forecast systems.

Keywords

user-end information / user-oriented / interactive forecasting system / TIGGE (THORPEX interactive grand global ensemble)

References

[1] Stewart T R. Forecast value: Descriptive decision studies. In: Katz R W, Murphy A H, eds. Economic Value of Weather and Climate Forecasts. United Kingdom: Cambridge University Press, 1997, 147–181

[2] Pielke R Jr, Carbone R E. Weather impacts, forecasts, and policy - An integrated perspective. Bulletin of the American Meteorological Society, 2002, 83(3): 393–403

[3] Stone R C, Meinke H. Weather, climate, and farmers: An overview. Meteorological Applications, 2006, 13(Suppl 1): 7–20

[4] Hu Q, Zillig L M P, Lynne G D, Tomkins A J, Waltman W J, Hayes M J, Hubbard K G, Artikov I, Hoffman S J, Wilhite D A. Understanding farmers’ forecast use from their beliefs, values, social norms, and perceived obstacles. Journal of Applied Meteorology and Climatology, 2006, 45(9): 1190–1201

[5] Mass C. The uncoordinated giant - Why US weather research and prediction are not achieving their potential. Bulletin of the American Meteorological Society, 2006, 87(5): 573–584

[6] Morss R E, Wilhelmi O V, Downton M W, Gruntfest E. Flood risk, uncertainty, and scientific information for decision making - Lessons from an interdisciplinary project. Bulletin of the American Meteorological Society, 2005, 86(11): 1593–1601

[7] Ye D Z, Yan Z W, Dai X H, Qian W H, Ye Q. A discussion of future system of weather and climate prediction. Meteorological Monthly, 2006, 32(4): 3–8 (in Chinese)

[8] Demuth J L, Gruntfest E, Morss R E, Drobot S, Lazo J K. Building a community for integrating meteorology and social science. Bulletin of the American Meteorological Society, 2007, 88(11): 1729–1737

[9] Perry J S. Atmospheric sciences and problems of society. Bulletin of the American Meteorological Society, 1976, 57(2): 199–212

[10] Sarewitz D R, Pielke R A. Prediction in science and policy. In: Sarewitz D R, Pielke R A, Byerly R(eds). Prediction: Science, Decision Making, and the Future of Nature. USA: Island Press, 2000, 11–22

[11] Shapiro M A, Thorpe A J. THORPEX International Science Plan. WMO, WWRP Document, 2004, 1–51

[12] David R, Buizza R, Hagedorn R. First workshop on the THORPEX interactive grand global ensemble (TIGGE). WMO, WWRP Document, 2005, 1–39

[13] Rabier F, Gauthier P, Cardinali C, Langland R, Tsyrulnikov M, Lorenc A, Steinle P, Gelaro R, Koizumi K. An update on THORPEX related research in data assimilation and observing strategies. Nonlinear Processes in Geophysics, 2008, 15(1): 81–94

[14] Casati B, Wilson L J, Stephenson D B, Nurmi P, Ghelli A, Pocernich M, Damrath U, Ebert E, Brown B G, Mason S. Forecast verification: current status and future directions. Meteorological Applications, 2008, 15(1): 3–18

[15] Morgan M C, Houghton D D, Keller L M. The future of medium-extended-range weather prediction—Challenges and a vision. Bulletin of the American Meteorological Society, 2007, 88(5): 631–634

[16] Palmer T N. The economic value of ensemble forecasts as a tool for risk assessment: From days to decades. Quarterly Journal of the Royal Meteorological Society, 2002, 128(581): 747–774

[17] Dutton J A. Opportunities and priorities in a new era for weather and climate services. Bulletin of the American Meteorological Society, 2002, 83(9): 1303–1311

[18] Ritchie J W, Zammit C, Beal D. Can seasonal climate forecasting assist in catchment water management decision-making? A case study of the border rivers catchment in Australia. Agriculture Ecosystems & Environment, 2004, 104(3): 553–565

[19] Stewart T R, Pielke R, Nath R. Understanding user decision making and the value of improved precipitation forecasts—Lessons from a case study. Bulletin of the American Meteorological Society, 2004, 85(2): 223–235

[20] Cunderlik J M, Simonovic S P. Inverse flood risk modelling under changing climatic conditions. Hydrological Processes, 2007, 21(5): 563–577

[21] Han J R. Study on Public Needs and the Role of Media in Weather Services. Dissertation for the Master Degree. Beijing: Chinese Academy of Meteorological Sciences, 2007, 18–32(in Chinese)

[22] Dessai S, Hulme M, Lempert R, Pielke R Jr. Do we need better predictions to adapt to a changing climate. Eos, Transactions, American Geophysical Union, 2009, 90(13): 111–112

[23] Mylne K R. Decision-making from probability forecasts based on forecast value. Meteorological Applications, 2002, 9(3): 307–315

[24] Casati B, Wilson L J, Stephenson D B, Nurmi P, Ghelli A, Pocernich M, Damrath U, Ebert E E, Brown B G, Mason S. Forecast verification: Current status and future directions. Meteorological Applications, 2008, 15(1): 3–18

[25] Zhang Q Y, Tao S Y, Peng J B. The studies of meteorological disasters over China. Chinese Journal of Atmospheric Sciences, 2008, 32(4): 815–825 (in Chinese)

[26] Liu J T, Zhang J B. Effect of antecedent soil water content on the uncertainty of hydrological simulation. Journal of Glaciology and Geocryology, 2006, 28(4): 519–525 (in Chinese)

[27] Li X Y, Gong J D, Gao Q Z. The experimental research of runoff yielding rainfall threshold in artificial catchments. Journal of Soil and Water Conservation, 2001, 12(4): 516–522 (in Chinese)

[28] Wang H, Lei X H, Qin D Y, Wang J H, Zhou Z H. Basin runoff yielding model construction based on human activities. Resources Science, 2003, 25(6): 11–18 (in Chinese)

[29] Jan van Andel S, Price R K, Lobbrecht A H, Van Kruiningen F, Mureau R. Ensemble precipitation and water level forecasts for anticipatory water-system control. Journal of Hydrometeorology, 2008, 9(4): 776–788

[30] Gneiting T, Raftery A E. Atmospheric science. Weather forecasting with ensemble methods. Science, 2005, 310(5746): 248–249

[31] Pappenberger F, Bartholmes J, Thielen J, Cloke H L, Buizza R, de Roo A. New dimensions in early flood warning across the globe using grand-ensemble weather predictions. Geophysical Research Letters, 2008, 35(10): L10404–L10407

[32] He Y, Wetterhall F, Cloke H L, Pappenberger F, Wilson M, Freer J, Mcgregor G. Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions. Meteorological Applications, 2009, 132: 1–11

[33] Johnson C, Swinbank R. Medium-range multimodel ensemble combination and calibration. Quarterly Journal of the Royal Meteorological Society, 2009, 135(640): 777–794

[34] Komma J, Reszler C, Bloschl G, Haiden T. Ensemble prediction of floods-catchment non-linearity and forecast probabilities. Natural Hazards and Earth System Sciences, 2007, 7(4): 431–444

[35] Park Y Y, Buizza R, Leutbecher M. TIGGE: preliminary results on comparing and combining ensembles. Quarterly Journal of the Royal Meteorological Society, 2008, 134(637): 2029–2050

[36] Martina M L V, Todini E, Libralon A. Rainfall thresholds for flood warning systems: a Bayesian decision approach. Hydrol. Modelling Water Cycle, 2008, 6(3): 203–227

Acknowledgement

This work was supported by the National Department Public Benefit Research Foundation of China (GYHY200706001 and GYHY200906007). The authors would like to acknowledge the generous support and help of this study provided by Linyi hydrology bureau, Linyi water conservancy bureau and Linyi meteorology bureau.

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg