Journal of Earth System Science

, Volume 113, Issue 2, pp 151–166 | Cite as

Tropical systematic and random error energetics based on NCEP (MRF) analysis-forecast system — A barotropic approach

Part I: In physical domain
  • S. De
  • D. R. Chakraborty


Deterministic predictability in the perspective of systematic and random error and their growth rates and different components of growth rate budgets like flux, pure generation, mixed generation and conversion in energy/variance form are investigated in physical domain for medium range tropical (30‡S-30‡N) weather forecast using daily horizontal wind field at 850 hPa up to 5-day forecast for the month of June, 2000 of NCEP (MRF) model. The study reveals the following:
  • •The Indian peninsula, the Indonesian region and their adjoining areas over 10‡N-20‡N latitudinal belt show a large amount of forecast error variance indicating that cumulus parameterization process may play a major role in the generation of tropical systematic error.

  • •Sparse observational networks over the tropical region are attributed to the uniform spread of random error over the continental as well as oceanic area. The results suggest that generation of random error in some geographical locations is perhaps due to the inefficient description of sensible heating process in the model.

  • •As far as growth rates are concerned, systematic error growth rate increases at initial forecast time and attains maximum value at 2-day forecast then it remains unchanged for rest of the forecast days. Whereas, the growth rate of random error is nearly invariant at 1 and 2-day forecasts and then it increases slowly at subsequent forecast time.

  • •Analyzing the flux, pure generation, mixed generation and conversion terms involved with the components of systematic and random error growth rate budget, it is shown that the components have their large variance in those regions where the respective error predominates.


Systematic error random error error energy and predictability 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Budyko M I 1974Climate and Life; New York: Academy Press, pp. 497Google Scholar
  2. Boer G J 1984 A spectral analysis of predictability and error in an operational forecast system;Mon. Weather Rev. 112 1183–1197CrossRefGoogle Scholar
  3. Boer G J 1993 Systematic and random error in an extended range forecasting experiment;Mon. Weather Rev. 121 173–188CrossRefGoogle Scholar
  4. Boer G J 1994 Predictability regimes in atmospheric flow;Mon. Weather Rev. 122 2285–2295CrossRefGoogle Scholar
  5. Dalcher A and Kalaney E 1987 Error growth and predictability in operational ECMWF forecasts;Tellus 39A 474–491Google Scholar
  6. Heckley W A 1985 Systematic errors of the ECMWF operational forecast model in tropical regions;Q. J. R. Meteorol Soc. 111 709–738CrossRefGoogle Scholar
  7. Kanamitsu M 1985 A study of predictability of ECMWF Operational Forecast Model in the tropics;J. Meteor. Soc. Japan 63 779–804Google Scholar
  8. Kamga A F, Fongang S and Viltard A 2000 Systematic errors of the ECMWF operational model over tropical Africa;Mon. Weather Rev. 128 1949–1959CrossRefGoogle Scholar
  9. Lorenz E N 1963 Deterministic nonperiodic flow;J. Atmos. Sci. 20 130–141CrossRefGoogle Scholar
  10. Lorenz E N 1969 Three approaches to atmospheric predictability;Bull. Amer. Meteorol Soc. 50 345–349Google Scholar
  11. Lorenz E N 1982 Atmospheric predictability experiments with large numerical model;Tellus 34 505–513Google Scholar
  12. Richardson L F 1922Weather prediction by numerical process; London: Cambridge Univ. Press, (Reprinted Dover, 1965), pp 236Google Scholar
  13. Roy Bhowmik S K 2004 Systematic errors of IMD operational NWP model; Mausam 55(1), (to appear)Google Scholar
  14. Surgi N 1989 Systematic errors of the FSU global spectral model;Mon. Weather Rev. 117 1751–1766CrossRefGoogle Scholar
  15. Thompson P D 1957 Uncertainity of the initial state as a factor in the predictability of large scale atmospheric flow pattern;Tellus 9 275–295CrossRefGoogle Scholar

Copyright information

© Indian Academy of Sciences 2004

Authors and Affiliations

  • S. De
    • 1
  • D. R. Chakraborty
    • 1
  1. 1.Indian Institute of Tropical MeteorologyPashan, PuneIndia

Personalised recommendations