Impact of Ensemble Size on TIGGE Precipitation Forecasts: An End-User Perspective
Publication: Journal of Hydrologic Engineering
Volume 20, Issue 2
Abstract
Precipitation forecasts play a key role in decision making for the water resource sector. The use of an ensemble numerical weather prediction model known as the ensemble prediction system to account for the uncertainties in weather forecasting has become common practice at various meteorological centers around the world. The current ensemble prediction systems operational at different forecasting centers vary in their parameters, including but not limited to spatial and temporal resolution, ensemble size, model physics, and initial perturbation strategy. This paper presents a comparison of six ensemble systems of varying characteristics, evaluating the quantitative precipitation forecasts issued for the Waikato River catchment in New Zealand. Three derivative products of the ensemble forecasts were used, most likely precipitation event, probability of above average rain, and ensemble mean precipitation, to test the potential application of the ensembles for resource allocation, hazard management, and catchment modeling. The forecasts of three-day cumulative precipitation, issued seven days in advance at different forecasting centers and connected through the Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE) network, were compared with the corresponding areal average precipitation observed in the selected catchment over a one-year period. The research investigated the effect of ensemble size on its performance and provides users an insight into the performance of various operational EPSs of different sizes in different situations of interest. The research presented in this paper also provides a preliminary framework of the evaluation of ensembles based on their intended use by different sectors. The results of the study indicate that an increased ensemble size is not always related to better performance. It was further inferred from the results that a slight gain in accuracy may be achieved by employing larger ensembles for their intended use in hazard management than the other two applications. Additionally, the grand ensemble, constructed by combining forecasts from all other ensembles tested in the study, adds no more value to an ensemble precipitation forecast if used in the context of the three scenarios adopted in this study.
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References
Addor, N., Jaun, S., Fundel, F., and Zappa, M. (2011). “An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): Skill, case studies and scenarios.” Hydrol. Earth Syst. Sci., 15(7), 2327–2347.
Atger, F. (2001). “Verification of intense precipitation forecasts from single models and ensemble prediction systems.” Nonlinear Processes Geophys., 8, 401–417.
Bao, H., and Zhao, L. (2012). “Development and application of an atmospheric-hydrologic-hydraulic flood forecasting model driven by TIGGE ensemble forecasts.” Acta Meteorol. Sin., 26(1), 93–102.
Bougeault, P., et al. (2010). “The THORPEX interactive grand global ensemble.” Bull Am. Meteorol. Soc., 91(8), 1059–1072.
Brier, G. W. (1950). “Verification of forecasts expressed in terms of probability.” Mon. Weather Rev., 78(1), 1–3.
Buizza, R. (2008). “The value of probabilistic prediction.” Atmos. Sci. Lett., 9, 36–42.
Buizza, R., Milleer, M., and Palmer, T. N. (1999). “Stochastic representation of model uncertainties in the ECMWF ensemble prediction system.” Q. J. R. Meteorol. Soc., 125(560), 2887–2908.
Cloke, H. L., and Pappenberger, F. (2009). “Ensemble flood forecasting: A review.” J. Hydrol., 375(3–4), 613–626.
Demeritt, D., Cloke, H., Pappenberger, F., Thielen, J., Bartholmes, J., and Ramos, M. H. (2007). “Ensemble predictions and perceptions of risk, uncertainty, and error in flood forecasting.” Environ. Hazard., 7, 115–127.
Ducrocq, V., Ricard, D., Lafore, J. P., and Orain, F. (2002). “Storm-scale numerical rainfall prediction for five precipitating events over France: On the importance of the initial humidity field.” Weather Forecast., 17(6), 1236–1256.
Hartmann, H. C., Pagano, T. C., Sorooshiam, S., and Bales, R. (2002). “Evaluating seasonal climate forecasts from user perspectives.” Bull Am. Meteorol. Soc., 83, 683–698.
He, Y., et al. (2009). “Tracking the uncertainty in flood alerts driven by grand ensemble weather predictions.” Meteorol. Appl., 16(1), 91–101.
Hopson, T. M., and Webster, P. J. (2010). “A 1–10 day ensemble forecasting scheme for the major river basins of Bangladesh: Forecasting severe floods of 2003–07.” J. Hydrometeorol., 11(3), 618–641.
Jaun, S., Ahrens, B., Walser, A., Ewen, T., and Schär, C. (2008). “A probabilistic view on the August 2005 floods in the upper Rhine catchment.” Nat. Hazard. Earth Syst. Sci., 8(2), 281–291.
Khan, M. M., Shamseldin, A. Y., and Melville, B. W. (2014). “Impact of ensemble size on forecasting occurrence of rainfall using TIGGE precipitation forecasts.” J. Hydrol. Eng., 19(4), 732–738.
Khummongkol, R., Sutivong, D., and Kuntanakulwong, S. (2007). “Water resource management using multi-objective optimization and rainfall forecast.” Proc., Convergence Information Technology, IEEE, New York.
Komma, J., Reszler, C., Bloschl, G., and Haiden, T. (2007). “Ensemble prediction of floods—Catchment non-linearity and forecast probability.” Nat. Hazard. Earth Syst. Sci., 7, 431–444.
Mason, I. (1982). “A model for assessment of weather forecasts.” Aust. Meteorol. Mag., 30, 291–303.
Molteni, F., Buizza, R., Palmer, T. N., and Petroliagis, T. (1996). “The ECMWF ensemble prediction system: Methodology and validation.” Q. J. R. Meteorol. Soc., 122, 73–119.
Montani, A., Marsigli, C., Nerozzi, F., Paccagnella, T., Tibaldi, S., and Buizza, R. (1999). “The Soverato flood in southern Italy: Performance of global and limited-area ensemble forecasts.” Nonlinear Processes Geophys., 10(3), 261–274.
Morss, R. E. (2003). “Assessing the needs of users warm season of quantitative precipitation forecasts in Colorado.” Joint session 17th Conf. on Hydrology and the Symp. on Impacts of Water Variability: Benefits and Challenges, American Meteorological Society, Boston, MA.
Morss, R. E., Lazo, J. K., and Demuth, J. L. (2010). “Examining the use of weather forecasts in decision scenarios: results from a US survey with implications for uncertainty communication.” Meteorol. Appl., 17(2), 149–162.
Palmer, T. N., and Raisanen, J. (2002). “Quantifying the risk of extreme seasonal precipitation events in a changing climate.” Nature, 415(6871), 512–514.
Pappenberger, F., Bartholmes, J., Thielen, J., Cloke, H. L., Buizza, R., and de Roo, A. (2008). “New dimensions in early flood warning across the globe using grand-ensemble weather predictions.” Geophys. Res. Lett., 35(10), L10404.
Saetra, Ø., Hersbach, H., Bidlot, J. R., and Richardson, D. S. (2004). “Effects of observation errors on the statistics for ensemble spread and reliability.” Mon. Weather Rev., 132(6), 1487–1501.
Sattler, K., and Feddersen, H. (2005). “Limited-area short-range ensemble predictions targeted for heavy rain in Europe.” Hydrol. Earth Syst. Sci., 9, 300–312.
Schumacher, R. S., and Davis, C. A. (2010). “Ensemble-based forecast uncertainty analysis of diverse heavy rainfall events.” Weather Forecast., 25(4), 1103–1122.
Thiessen, A. H. (1991). “Precipitation averages for large areas.” Mon. Weather Rev., 39(7), 1082–1084.
Toth, Z., and Kalnay, E. (1993). “Ensemble forecasting at the NMC: The generation of perturbations.” Bull. Am. Meteorol. Soc., 74, 2317–2330.
Verbunt, M., Walser, A., Gurtz, J., Montani, A., and Schär, C. (2007). “Probabilistic flood forecasting with a limited-area ensemble prediction system: Selected case studies.” J. Hydrometeorol., 8(4), 897–909.
Weesakul, U., and Lowanichchai, S. (2005). “Rainfall forecast for agricultural water allocation planning in Thailand.” Thammasat Int. J. Sci. Technol., 10(3), 18–27.
Wilks, D. S. (1995). Statistical methods in the atmospheric sciences, Vol. 59, International Geophysics Series, Academic Press, MA, 260.
Ziehmann, C. (2000). “Comparison of a single model EPS with a multi-model ensemble consisting of a few operational models.” Tellus, 52A, 280–299.
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Published In
Journal of Hydrologic Engineering
Volume 20 • Issue 2 • February 2015
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Oct 28, 2013
Accepted: May 7, 2014
Published online: Aug 1, 2014
Discussion open until: Jan 1, 2015
Published in print: Feb 1, 2015
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