Editorial Type:
Article
Article Type:
Research Article

The Skill of ECMWF Medium-Range Forecasts during the Year of Tropical Convection 2008

Arindam Chakraborty Divecha Centre for Climate Change, and Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore, India

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Print Publication:
01 Oct 2010
DOI:
https://doi.org/10.1175/2010MWR3217.1
Page(s):
3787–3805
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Abstract

This study uses the European Centre for Medium-Range Weather Forecasts (ECMWF) model-generated high-resolution 10-day-long predictions for the Year of Tropical Convection (YOTC) 2008. Precipitation forecast skills of the model over the tropics are evaluated against the Tropical Rainfall Measuring Mission (TRMM) estimates. It has been shown that the model was able to capture the monthly to seasonal mean features of tropical convection reasonably. Northward propagation of convective bands over the Bay of Bengal was also forecasted realistically up to 5 days in advance, including the onset phase of the monsoon during the first half of June 2008. However, large errors exist in the daily datasets especially for longer lead times over smaller domains.

For shorter lead times (less than 4–5 days), forecast errors are much smaller over the oceans than over land. Moreover, the rate of increase of errors with lead time is rapid over the oceans and is confined to the regions where observed precipitation shows large day-to-day variability. It has been shown that this rapid growth of errors over the oceans is related to the spatial pattern of near-surface air temperature. This is probably due to the one-way air–sea interaction in the atmosphere-only model used for forecasting. While the prescribed surface temperature over the oceans remain realistic at shorter lead times, the pattern and hence the gradient of the surface temperature is not altered with change in atmospheric parameters at longer lead times. It has also been shown that the ECMWF model had considerable difficulties in forecasting very low and very heavy intensity of precipitation over South Asia. The model has too few grids with “zero” precipitation and heavy (>40 mm day−1) precipitation. On the other hand, drizzle-like precipitation is too frequent in the model compared to that in the TRMM datasets.

Further analysis shows that a major source of error in the ECMWF precipitation forecasts is the diurnal cycle over the South Asian monsoon region. The peak intensity of precipitation in the model forecasts over land (ocean) appear about 6 (9) h earlier than that in the observations. Moreover, the amplitude of the diurnal cycle is much higher in the model forecasts compared to that in the TRMM estimates. It has been seen that the phase error of the diurnal cycle increases with forecast lead time. The error in monthly mean 3-hourly precipitation forecasts is about 2–4 times of the error in the daily mean datasets. Thus, effort should be given to improve the phase and amplitude forecast of the diurnal cycle of precipitation from the model.

Corresponding author address: Arindam Chakraborty, Divecha Centre for Climate Change and Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore, 560012, India. Email: arch@caos.iisc.ernet.in

Abstract

This study uses the European Centre for Medium-Range Weather Forecasts (ECMWF) model-generated high-resolution 10-day-long predictions for the Year of Tropical Convection (YOTC) 2008. Precipitation forecast skills of the model over the tropics are evaluated against the Tropical Rainfall Measuring Mission (TRMM) estimates. It has been shown that the model was able to capture the monthly to seasonal mean features of tropical convection reasonably. Northward propagation of convective bands over the Bay of Bengal was also forecasted realistically up to 5 days in advance, including the onset phase of the monsoon during the first half of June 2008. However, large errors exist in the daily datasets especially for longer lead times over smaller domains.

For shorter lead times (less than 4–5 days), forecast errors are much smaller over the oceans than over land. Moreover, the rate of increase of errors with lead time is rapid over the oceans and is confined to the regions where observed precipitation shows large day-to-day variability. It has been shown that this rapid growth of errors over the oceans is related to the spatial pattern of near-surface air temperature. This is probably due to the one-way air–sea interaction in the atmosphere-only model used for forecasting. While the prescribed surface temperature over the oceans remain realistic at shorter lead times, the pattern and hence the gradient of the surface temperature is not altered with change in atmospheric parameters at longer lead times. It has also been shown that the ECMWF model had considerable difficulties in forecasting very low and very heavy intensity of precipitation over South Asia. The model has too few grids with “zero” precipitation and heavy (>40 mm day−1) precipitation. On the other hand, drizzle-like precipitation is too frequent in the model compared to that in the TRMM datasets.

Further analysis shows that a major source of error in the ECMWF precipitation forecasts is the diurnal cycle over the South Asian monsoon region. The peak intensity of precipitation in the model forecasts over land (ocean) appear about 6 (9) h earlier than that in the observations. Moreover, the amplitude of the diurnal cycle is much higher in the model forecasts compared to that in the TRMM estimates. It has been seen that the phase error of the diurnal cycle increases with forecast lead time. The error in monthly mean 3-hourly precipitation forecasts is about 2–4 times of the error in the daily mean datasets. Thus, effort should be given to improve the phase and amplitude forecast of the diurnal cycle of precipitation from the model.

Corresponding author address: Arindam Chakraborty, Divecha Centre for Climate Change and Centre for Atmospheric and Oceanic Sciences, Indian Institute of Science, Bangalore, 560012, India. Email: arch@caos.iisc.ernet.in

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  • Anthes, R. A., 1983: Regional models of the atmosphere in middle latitudes. Mon. Wea. Rev., 111 , 1306–1330.

  • Bengtsson, L., and A. J. Simmons, 1983: Medium range weather prediction: Operational experience at ECMWF. Large Scale Dynamical Process in the Atmosphere, B. J. Hoskins and R. D. Pearce, Eds., Academic Press, 337–363.

    • Search Google Scholar
    • Export Citation

  • Bergman, J. W., 1997: A numerical investigation of cloud diurnal variations. J. Climate, 10 , 2330–2350.

  • Bergman, J. W., and M. L. Salby, 1997: The role of cloud diurnal variations in the time-mean energy budget. J. Climate, 10 , 1114–1124.

    • Search Google Scholar
    • Export Citation

  • Chakraborty, A., and T. N. Krishnamurti, 2006: Improved seasonal climate forecasts of the South Asian summer monsoon using a suite of 13 coupled ocean–atmosphere models. Mon. Wea. Rev., 134 , 1697–1721.

    • Search Google Scholar
    • Export Citation

  • Chakraborty, A., and T. N. Krishnamurti, 2008: Improved forecasts of the diurnal cycle in the tropics using multiple global models. Part II: Asian summer monsoon. J. Climate, 21 , 4045–4067.

    • Search Google Scholar
    • Export Citation

  • Chakraborty, A., and T. N. Krishnamurti, 2009: Improving global model precipitation forecasts over India using downscaling and the FSU superensemble. Part II: Seasonal climate. Mon. Wea. Rev., 137 , 2736–2757.

    • Search Google Scholar
    • Export Citation

  • Chakraborty, A., T. N. Krishnamurti, and C. Gnanaseelan, 2007: Prediction of the diurnal cycle using a multimodel superensemble. Part II: Clouds. Mon. Wea. Rev., 135 , 4097–4116.

    • Search Google Scholar
    • Export Citation

  • Charles, M. E., and B. A. Colle, 2009: Verification of extratropical cyclones within the NCEP operational models. Part I: Analysis errors and short-term NAM and GFS forecasts. Wea. Forecasting, 24 , 1173–1190.

    • Search Google Scholar
    • Export Citation

  • Colle, B. A., C. F. Mass, and D. Ovens, 2001: Evaluation of the timing and strength of MM5 and Eta surface trough passages over the eastern Pacific. Wea. Forecasting, 16 , 553–572.

    • Search Google Scholar
    • Export Citation

  • Dai, A., 2001: Global precipitation and thunderstorm frequencies. Part II: Diurnal variations. J. Climate, 14 , 1112–1128.

  • Dai, A., and C. Deser, 1999: Diurnal and semidiurnal variations in global surface wind and divergence fields. J. Geophys. Res., 104 , 31109–31126.

    • Search Google Scholar
    • Export Citation

  • Dai, A., F. Giorgi, and K. E. Trenberth, 1999: Observed and model-simulated precipitation diurnal cycle over the contiguous United States. J. Geophys. Res., 104 , 6377–6402.

    • Search Google Scholar
    • Export Citation

  • Druyan, L. M., M. Fulakeza, and L. Patric, 2002: Dynamical downscaling of seasonal climate predictions over Brazil. J. Climate, 15 , 84–117.

    • Search Google Scholar
    • Export Citation

  • Harper, K., L. W. Uccellini, E. Kalnay, K. Carey, and L. Morone, 2007: 50th anniversary of numerical weather prediction. Bull. Amer. Meteor. Soc., 88 , 639–650.

    • Search Google Scholar
    • Export Citation

  • Huth, R., 2002: Statistical downscaling of daily temperature in central Europe. J. Climate, 15 , 1731–1742.

  • Janowiak, J. E., V. E. Kousky, and R. J. Joyce, 2005: Diurnal cycle of precipitation determined from the cmorph high spatial and temporal resolution global precipitation analysis. J. Geophys. Res., 110 , D23105. doi:10.1029/2005JD006156.

    • Search Google Scholar
    • Export Citation

  • Kalnay, E., S. J. Lord, and R. D. McPherson, 1998: Maturity of operational numerical weather prediction: Medium range. Bull. Amer. Meteor. Soc., 79 , 2753–2769.

    • Search Google Scholar
    • Export Citation

  • Krishnamurti, T. N., and C. M. Kishtawal, 2000: A pronounced continental-scale diurnal mode of the Asian summer monsoon. Mon. Wea. Rev., 128 , 462–472.

    • Search Google Scholar
    • Export Citation

  • Krishnamurti, T. N., C. Gnanaseelan, and A. Chakraborty, 2007: Prediction of the diurnal cycle using a multimodel superensemble. Part I: Precipitation. Mon. Wea. Rev., 135 , 3613–3632.

    • Search Google Scholar
    • Export Citation

  • Krishnamurti, T. N., A. K. Mishra, A. Chakraborty, and M. Rajeevan, 2009: Improving global model precipitation forecasts over India using downscaling and the FSU superensemble. Part I: 1–5-day forecasts. Mon. Wea. Rev., 137 , 2713–2735.

    • Search Google Scholar
    • Export Citation

  • Mass, C. F., D. Ovens, K. Westrick, and B. A. Colle, 2002: Does increasing horizontal resolution produce more skillful forecasts? Bull. Amer. Meteor. Soc., 83 , 407–430.

    • Search Google Scholar
    • Export Citation

  • McMurdie, L., and C. Mass, 2004: Major numerical forecast failures over the northeast Pacific. Wea. Forecasting, 19 , 338–356.

  • Murakami, M., 1983: Analysis of the deep convective activity over the tropical western Pacific. J. Meteor. Soc. Japan, 61 , 60–77.

  • Palmer, T. N., and Coauthors, 2004: Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction (DEMETER). Bull. Amer. Meteor. Soc., 85 , 853–872.

    • Search Google Scholar
    • Export Citation

  • Pandey, G. R., D. R. Cayan, M. D. Dettinger, and K. P. Georgakakos, 2000: A hybrid orographic plus statistical model for downscaling daily precipitation in northern California. J. Hydrometeor., 1 , 491–506.

    • Search Google Scholar
    • Export Citation

  • Randall, D. A., Harshvardhan, and D. A. Dazlich, 1991: Diurnal variability of the hydrologic cycle in a general circulation model. J. Atmos. Sci., 48 , 40–62.

    • Search Google Scholar
    • Export Citation

  • Shin, K-S., G. R. North, Y-S. Ahn, and P. A. Arkin, 1990: Time scales and variability of area-averaged tropical oceanic rainfall. Mon. Wea. Rev., 118 , 1507–1516.

    • Search Google Scholar
    • Export Citation

  • Simmons, A. J., and A. Hollingsworth, 2002: Some aspects of the improvement in skill of numerical weather prediction. Quart. J. Roy. Meteor. Soc., 128 , 647–677.

    • Search Google Scholar
    • Export Citation

  • Slingo, J. M., P. Inness, R. Neale, S. Woolnough, and G-Y. Yang, 2003: Scale interactions on diurnal to seasonal timescales and their relevance to model systematic errors. Ann. Geophys., 46 , 139–155.

    • Search Google Scholar
    • Export Citation

  • Storch, H. V., H. Langenberg, and F. Feser, 2000: A spectral nudging technique for dynamical downscaling purposes. Mon. Wea. Rev., 128 , 3664–3673.

    • Search Google Scholar
    • Export Citation

  • Trenberth, K. E., A. Dai, R. M. Rasmussen, and D. B. Parsons, 2003: The changing character of precipitation. Bull. Amer. Meteor. Soc., 84 , 1205–1217.

    • Search Google Scholar
    • Export Citation

  • Wallace, J. M., 1975: Diurnal variations in precipitation and thunderstorm frequency over the conterminous United States. Mon. Wea. Rev., 103 , 403–419.

    • Search Google Scholar
    • Export Citation

  • Wedam, G. B., L. A. McMurdie, and C. F. Mass, 2009: Comparison of model forecast skill of sea level pressure along the east and west coasts of the United States. Wea. Forecasting, 24 , 843–854.

    • Search Google Scholar
    • Export Citation

  • Yang, G-Y., and J. Slingo, 2001: The diurnal cycle in the tropics. Mon. Wea. Rev., 129 , 784–801.

  • Yang, S., and E. A. Smith, 2006: Mechanisms for diurnal variability of global tropical rainfall observed from TRMM. J. Climate, 19 , 5190–5226.

    • Search Google Scholar
    • Export Citation
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