Accuracy of early GFS and ECMWF Sandy (2012) track forecasts: Evidence for a dependence on cumulus parameterization

Geophysical Research Letters

Volumn 41, Issue 9, 2014, Pages 3274-3281

  Bassill, Nick P ^a  

^a UNIVERSITY OF UTAH   (United States)

Author keywords

ensemble; forecast; parameterization; Sandy; track; WRF

Indexed keywords

CLOUDS; COMPUTER SIMULATION; FORECASTING; HURRICANES; PARAMETERIZATION;

CUMULUS PARAMETERIZATION; ENSEMBLE; GLOBAL FORECAST SYSTEMS; INITIAL CONDITIONS; SANDY; TRACK; WEATHER RESEARCH AND FORECASTING MODELS; WRF;

WEATHER FORECASTING;

ACCURACY ASSESSMENT; CUMULUS; ENSEMBLE FORECASTING; HURRICANE SANDY 2012; PARAMETERIZATION; TRACKING;

ATLANTIC OCEAN; ATLANTIC OCEAN (CENTRAL); ATLANTIC OCEAN (NORTH);

EID: 84901946659     PISSN: 00948276     EISSN: 19448007     Source Type: Journal    
DOI: 10.1002/2014GL059839     Document Type: Article

References (12)

1. Blake, E. S., T. B. Kimberlain, R. J. Berg, J. P. Cangialosi, and, J. L. Beven III, (2013), Tropical cyclone report: Hurricane Sandy (AL182012), Tech. Rep. AL182012, NOAA/National Hurricane Center, 157 pp. [Available at http://www.nhc.noaa.gov/data/tcr/AL182012-Sandy.pdf.]
2. Bougeault, P., et al. (2010), THORPEX Interactive Grand Global Ensemble (TIGGE), Bull. Am. Meteorol. Soc., 91, 1059-1072.
3. Buizza, R., M. Miller, and, T. N. Palmer, (1999), Stochastic representation of model uncertainties in the ECMWF ensemble prediction system, Q. J. R. Meteorol. Soc., 125, 2887-2908, doi: 10.1002/qj.49712556006.
4. Galarneau, T. J., C. A. Davis, and, M. A. Shapiro, (2013), Intensification of Hurricane Sandy (2012) through extratropical warm core seclusion, Mon. Weather Rev., 141, 4296-4321, doi: 10.1175/MWR-D-13-00181.1.
5. Hall, T. M., and, A. H. Sobel, (2013), On the impact angle of Hurricane Sandy's New Jersey landfall, Geophys. Res. Lett., 40, 2312-2315, doi: 10.1002/grl.50395.
6. Magnusson, L., J.-R. Bidlot, S. T. K. Lang, A. Thorpe, N. Wedi, and, M. Yamaguchi, (2014), Evaluation of Medium-Range Forecasts for Hurricane Sandy, Mon. Wea. Rev., 142, 1962-1981.
7. McNally, T., M. Bonavita, and, J. Thépaut, (2014), The role of satellite data in the forecasting of Hurricane Sandy, Mon. Weather Rev., 142, 634-646, doi: 10.1175/MWR-D-13-00170.1.
8. Nordeng, T. E., (1994), Extended versions of the convective parameterization scheme at ECMWF and their impact on the mean and transient activity of the model in the Tropics, ECMWF Research Department Tech. Memo. 206, 41 pp., European Centre for Medium Range Weather Forecasts, Shinfield Park, Reading, U. K.
9. Puri, K., and, M. J. Miller, (1990), Sensitivity of ECMWF analyses-forecasts of tropical cyclones to cumulus parameterization, Mon. Weather Rev., 118, 1709-1742, doi: 10.1175/1520-0493(1990)118<1709: SOEAFO>2.0.CO;2.
10. Skamarock, W. C., J. B. Klemp, J. Dudhia, D. O. Gill, D. M. Barker, W. Wang, and, J. G. Powers, (2008), A description of the advanced research WRF version 3. NCAR Technical Note NCAR/TN-475+STR, 113 pp., Natl. Cent. for Atmos. Res., Boulder, Colo.
11. Zhang, C., Y. Wang, and, K. Hamilton, (2011), Improved representation of boundary layer clouds over the Southeast Pacific in ARW-WRF using a modified Tiedtke cumulus parameterization scheme, Mon. Weather Rev., 139, 3489-3513, doi: 10.1175/MWR-D-10-05091.1.
12. Zhu, Y., D. Hou, X. Zhou, R. Wobus, M. Pena, and, J. Peng, (2014), The development of Global Ensemble Forecast System (GEFS). Poster, 26th Conference on Weather Analysis and Forecasting / 22nd Conference on Numerical Weather Prediction, Atlanta, GA, Amer. Meteor. Soc. [Available at https://ams.confex. com/ams/94Annual/webprogram/Paper236915.html.]