Abstract
Summer-time short- to medium-range predictability of precipitation, 500-hPa geopotential height, and wind fields over East Asia are investigated by comparing three ensemble forecast configurations: multi-analysis, multi-convection, and multi-model. These three systems are used in this study in order to assess initial condition uncertainties, model uncertainties, and a combination of initial condition and model uncertainties in an ensemble forecast approach. Each system has a set of six members. Ensemble forecast skill is verified in both deterministic and probabilistic senses using the European Center for Medium-range Weather Forecasting analyses and the Tropical Rainfall Measuring Mission Microwave Imager 2A12 rain estimates. The multi-model configuration, which considers both the initial condition and model uncertainties to predict weather phenomena over East Asia, is an optimal set of ensemble members. The bias-corrected ensemble and the superensemble (SE) show similar predictability, but slightly better skill is obtained from the SE forecasts.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Arribas A, Robertson KB, Mylne KR (2005) Test of a poor man’s ensemble prediction system for short-range probability forecasting. Mon Weather Rev 133:1825–1839
Bougeault P et al (2010) The THORPEX interactive grand global ensemble. Bull Am Meteor Soc 91:1059–1072
Cocke S, LaRow TE (2000) Seasonal predictions using a regional spectral model embedded within a coupled ocean-atmosphere model. Mon Weather Rev 128:689–708
Emanuel KA, Zivkovic-Rothman M (1999) Development and evaluation of a convection scheme for use in climate models. J Atm Sci 56:1766–1782
Ferraro RR, Marks GF (1995) The development of SSM/I rain-rate retrieval algorithms using ground-based radar measurements. J Atm Ocean Technol 12:755–770
Hamill TM, Juras J (2006) Measuring forecast skill: is it real skill or is it the varying climatology? Q J Roy Meteor Soc 132:2905–2923
Johnson C, Swinbank R (2009) Medium-range multimodel ensemble combination and calibration. Q J R Meteorol Soc 135:777–794
Krishnamurti TN, Low-Nam S, Pasch R (1983) Cumulus parameterization and rainfall rates II. Mon Weather Rev 111:815–828
Krishnamurti TN et al (2003) Improved skill for the anomaly correlation of geopotential heights at 500 hPa. Mon Weather Rev 131:1082–1102
Kummerow C, Olson WS, Giglio L (1996) A simplified sche\me for obtaining precipitation and vertical hydrometeor profiles from passive microwave sensors. IEEE Trans Geosci Remote Sens 34:1213–1232
Moorthi S, Suarez MJ (1992) Relaxed Arakawa-Schubert: a parameterization of moist convection for general circulation models. Mon Weather Rev 120:978–1002
Mutemi JN, Ogallo LA, Krishnamurti TN, Mishra AK, Kumar TSVV (2007) Multimodel based superensemble forecasts for short and medium range NWP over various regions of Africa. Meteorol Atm Phys 95:87–113
Olson WS, LaFontaine FJ, Smith WL, Achtor RH (1990) Recommended algorithms for the retrieval of rainfall rates in the tropics using SSM/I (DMSP-F8). (Available at University of Wisconsin, 10 pp)
Palmer TN, Molteni F, Mureau R, Buizza R, Chapelet P, Tribbia J (1992) Ensemble prediction. ECMWF Tech Memo 188
Pan HL, Wu WS (1994) Implementing a mass flux convection parameterization scheme for the NMC Medium-Range Forecast model. In: Tenth Conference on Numerical Weather Prediction, American Meteorological Society, Portland, OR, pp 96–98
Rosmond TE (1992) The design and testing of the Navy operational global atmospheric prediction system. Weather Forecast 7:262–272
Shin DW, Krishnamurti TN (2003a) Short- to medium-range superensemble precipitation forecasts using satellite products. Part I: deterministic forecasting. J Geophys Res 108:8383. doi:10.1029/201JD001510
Shin DW, Krishnamurti TN (2003b) Short- to medium-range superensemble precipitation forecasts using satellite products. Part II: probabilistic forecasting. J Geophys Res 108:8384. doi:10.1029/201JD001511
Shin DW, Cocke S, LaRow TE (2003) Ensemble configurations for typhoon precipitation forecasts. J Meteor Soc Jpn 81:679–696
Stensrud DJ, Brooks HE, Du J, Tracton MS, Rogers E (1999) Using ensembles for short-range forecasting. Mon Weather Rev 127:433–446
Toth Z, Kalnay E (1997) Ensemble forecasting at NCEP and the breeding method. Mon Weather Rev 125:3297–3319
Toth Z, Zhu YJ, Marchok T (2001) The use of ensembles to identify forecasts with small and large uncertainty. Weather Forecast 16:463–477
Turk FJ, Qui S, Hawkins J, Smith EA, Marzano FS, Mugnai A (2001) Blending coincident SSM/I, TRMM and Infrared geostationary satellite data for an operational rainfall analysis, Part I: technique description. (Draft)
Zhang Z, Krishnamurti TN (1997) Ensemble forecasting on hurricane tracks. Bull Am Meteorol Soc 78:2785–2795
Zhang GJ, McFarlane NA (1995) Sensitivity of climate simulations to the parameterization of cumulus convection in the Canadian Climate Centre general circulation model. Atm Ocean 33:407–446
Zhou BB, Du J (2010) Fog prediction from a multimodel mesoscale ensemble prediction system. Weather Forecast 25:303–322
Ziehmann C (2000) Comparison of a single-model EPS with a multi-model ensemble consisting of a few operational models. Tellus 52:280–299
Acknowledgments
This work was funded by Korea Meteorological Administration Research and Development Program under grant CATER (Center for Atmospheric Sciences and Earthquake Research) 2010-75.
Author information
Authors and Affiliations
Corresponding author
Additional information
Responisble editor: B. Ahrens.
Rights and permissions
About this article
Cite this article
Kang, SD., Shin, D.W., Cocke, S. et al. Comparison of ensemble methods for summer-time numerical weather prediction over East Asia. Meteorol Atmos Phys 113, 27–38 (2011). https://doi.org/10.1007/s00703-011-0148-6
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00703-011-0148-6