• Burpee, R. W., 1975: Some features of synoptic-scale waves based on a compositing analysis of GATE data. Mon. Wea. Rev., 103 , 921925.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Charba, J. P., 1979: Two to six hour severe local storm probabilities: An operational forecasting system. Mon. Wea. Rev., 107 , 269281.

    • Search Google Scholar
    • Export Citation
  • Curtis, R. C., and Panofsky H. A. , 1958: The relation between large scale vertical motion and weather in summer. Bull. Amer. Meteor. Soc., 39 , 521531.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • de Felice, P., Viltard A. , and Oubuih J. , 1993: A synoptic-scale wave of 6–9-day period in the Atlantic tropical troposphere during summer 1981. Mon. Wea. Rev., 121 , 12911298.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dhonneur, G., 1984: Traite de Meteorologie Tropicale. Vol. 1. Météo-France, 150 pp. [Available from Librairie, Météo-France, 2 Av. Rapp, F75007 Paris, France.].

    • Search Google Scholar
    • Export Citation
  • Dhonneur, G., Falque P. , and Schroeder L. , 1967: Etude de l'instabilite a Ndjamena. Rapport Tech. 8, ASECNA, 24 pp. [Available from Direction Generale, ASECNA, BP 3144, Dakar, Senegal.].

    • Search Google Scholar
    • Export Citation
  • Diedhiou, A., Janicot S. , Viltard A. , de Felice P. , and Laurent H. , 1999: Easterly wave regimes and associated convection over West Africa and tropical Atlantic: Results from the NCEP/NCAR and ECMWF reanalyses. Climate Dyn., 15 , 795822.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Doswell, C. A., 1986: Short range forecasting. Mesoscale Meteorology and Forecasting, P. S. Ray, Ed., Amer. Meteor. Soc., 689–719.

  • Draper, N. R., and Smith H. , 1998: Applied Regression Analysis. 3d ed. John Wiley and Sons, 706 pp.

  • Fortune, M., 1980: Properties of African squall lines inferred from time lapse satellite imagery. Mon. Wea. Rev., 108 , 153168.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gray, W. M., 1968: Global view of the origin of tropical disturbances and storms. Mon. Wea. Rev., 96 , 669700.

  • Houze, R. A., 1977: Structure and dynamics of a tropical squall line system. Mon. Wea. Rev., 105 , 15401567.

  • Laing, A. G., Fritschand J. M. , and Negri A. J. , 1999: Contribution of mesoscale convective complexes to rainfall in Sahelian Africa: Estimates from geostationnary infrared and passive microwave data. J. Appl. Meteor., 38 , 957964.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lamb, P. J., 1983: West African water vapor variations between recent contrasting Subsaharan rainy seasons. Tellus, 35A , 198212.

  • Laurent, H., D'Amato N. , and Lebel T. , 1998: How important is the contribution of the mesoscale convective complexes to the Sahelian rainfall? Phys. Chem. Earth, 23 , 629633.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lebel, T., and LeBarbé L. , 1997: Rainfall monitoring during HAPEX-Sahel. 2. Point and areal estimation at the event and seasonal scales. J. Hydrol., 188–189 , 97122.

    • Search Google Scholar
    • Export Citation
  • Lin, S-J., and Smith P. J. , 1985: Utilization of satellite-derived cloud cover to improve the estimation of latent heat release in a winter extratropical cyclone. Mon. Wea. Rev., 113 , 19421950.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moncrieff, M. W., and Miller M. J. , 1976: The dynamics and simulation of tropical cumulonimbus and squall lines. Quart. J. Roy. Meteor. Soc., 102 , 373394.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Peppler, R. A., and Lamb P. J. , 1989: Tropospheric static stability and central North American growing season rainfall. Mon. Wea. Rev., 117 , 11561180.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reed, R. J., Norquist D. C. , and Recker E. E. , 1977: The structure and properties of synoptic-scale wave disturbances as observed during phase III of GATE. Mon. Wea. Rev., 105 , 317342.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reeves, R. W., Ropelewski C. F. , and Hudlow M. D. , 1979: Relationships between large-scale motion and convective precipitation during GATE. Mon. Wea. Rev., 107 , 11541168.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Roux, F., and Sun J. , 1990: Single-Doppler observations of a West African squall line on 27–28 May 1981 during COPT 81: Kinematics, thermodynamics and water budget. Mon. Wea. Rev., 118 , 18261854.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Senesi, S., and Thepenier R. M. , 1997: Indices d'instabilite et occurences d'orages: Le cas de l'Ile de France. La Meteorologie, VIIIe Serie, No. 19, 18–33.

    • Search Google Scholar
    • Export Citation
  • Stansky, R. H., Wilson L. J. , and Burrows W. R. , 1989: Survey of common verification methods in meteorology. World Weather Watch, Tech. Rep. 8, WMO/TD 358, WMO, 113 pp.

    • Search Google Scholar
    • Export Citation
  • Viltard, A., Oubuih J. , de Felice P. , and Laurent H. , 1998: Rainfall and 6–9 day wave-like disturbance in West Africa during summer 1989. Meteor. Atmos. Phys., 66 , 229234.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wandishin, M. S., Mullen S. L. , Stensrud D. J. , and Brooks H. E. , 2001: Evaluation of a short-range multimodel ensemble system. Mon. Wea. Rev., 129 , 729747.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • WMO/ACMAD, 1998: Prevision climatique en Afrique. African Centre of Meteorological Applications for Development Rapport Tech. 927, 210 pp. [Available from ACMAD, B.P. 13184, Niamey, Niger.].

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1 1 1
PDF Downloads 1 1 1

Daily Precipitation Forecasting in Dakar Using the NCEP–NCAR Reanalyses

View More View Less
  • 1 Laboratoire de Météorologie Dynamique, Palaiseau, France
Restricted access

Abstract

In order to predict the daily rain amount at Dakar at 1–5-day lead times, 65 thermodynamical and dynamical indices are computed at each grid point for the area 15°S–30°N, 30°W–30°E. The data used are NCEP–NCAR reanalyses and daily rainfall obtained by averaging over 21 rain gauges near Dakar, for 23 Augusts (1968–90). At each lead time and each grid point, a Pearson product–moment correlation coefficient r is computed between each index and the rainfall over 17 Augusts (1968–84). Predictive regression equations are developed including the 65 indices taken at the grid points where their r value is at a maximum. The prediction skill is tested over six Augusts (1985–90). The variance (R2) explained is 42% for the 1-day lead time, it decreases slowly up to the 4-day lead time (35%), and it is 28% at the 5-day lead time. The skill is better than when climatological data are used to predict rain amount. Among the predictors that appear most frequently in the predicting equations are lifting condensation level, vorticity at 700 hPa, humidity at 925 hPa, the total water vapor flux in the monsoon layer, and water vapor meridional flux in the 600–300-hPa layer.

Corresponding author address: Dr. Abdoulaye Deme, LMD, Ecole Polytechnique, F91128 Palaiseau Cedex, France. Email: defelice@lmd.polytechnique.fr

Abstract

In order to predict the daily rain amount at Dakar at 1–5-day lead times, 65 thermodynamical and dynamical indices are computed at each grid point for the area 15°S–30°N, 30°W–30°E. The data used are NCEP–NCAR reanalyses and daily rainfall obtained by averaging over 21 rain gauges near Dakar, for 23 Augusts (1968–90). At each lead time and each grid point, a Pearson product–moment correlation coefficient r is computed between each index and the rainfall over 17 Augusts (1968–84). Predictive regression equations are developed including the 65 indices taken at the grid points where their r value is at a maximum. The prediction skill is tested over six Augusts (1985–90). The variance (R2) explained is 42% for the 1-day lead time, it decreases slowly up to the 4-day lead time (35%), and it is 28% at the 5-day lead time. The skill is better than when climatological data are used to predict rain amount. Among the predictors that appear most frequently in the predicting equations are lifting condensation level, vorticity at 700 hPa, humidity at 925 hPa, the total water vapor flux in the monsoon layer, and water vapor meridional flux in the 600–300-hPa layer.

Corresponding author address: Dr. Abdoulaye Deme, LMD, Ecole Polytechnique, F91128 Palaiseau Cedex, France. Email: defelice@lmd.polytechnique.fr

Save