A synoptic-climatology approach to increase the skill of numerical weather predictions over Iran

Document Type : Scientific and Research


1 Professor, Tarbiat Modares University, Iran

2 Assistant Professor, Kermanshah Meteorological Office, Iran


Simplifications used in regional climate models decrease the accuracy of the regional climate models. To overcome this deficiency, usually a statistical technique of MOS is used to improve the skill of gridded outputs of the Numerical Weather Prediction (NWP) models. In this paper, an experimental synoptic-climatology based method has been used to calibrate, and decrease amount of errors in GFS numerical weather prediction model. Usually, physiographic characteristics, climatic behavior and synoptic climatology of the region are not included in MOS techniques. In this regard, an experimental model for Precipitation potential using Synoptic-climatology and Physiographic characteristics (PSP) of the region has been developed for statistical downscaling of the NWP outputs over the study region under study. A Climatic and Physiographic Index for surface weather stations is defined to represent their climatic and physiographic characteristics in MOS technique. CPI covers monthly mean precipitation, temperature, monthly number of wet and dry days, and latitude and height of station.  CPI index which is defined in this paper can be used as climate classification index. In this study daily gridded outputs from Global Forecast System (GFS) has been used for calibration and running the PSP experimental model. Inputs of the model are gridded meteorological parameters in 500 hpa and surface layer from GFS model. Data from more than 85 daily weather systems have been used to find synoptic climatology characteristics, and coefficients needed as input for PSP equations in the period of 2002-2007. Coefficients are computed by using regression equation between observed and computed precipitation over each station with. 85. 


  1. Asakereh, H. ( Hossin, 2006). T, the modeling of spatial precipitation of climatic factors of Iran; case study: Esfahan annually precipitation, . Geographical research Research journalJournal, No. 74, P: 25-36.
  2. Asakereh, Hossin,.; Seyfipoor, Zohreh,. (2014). S, spatial modeling of Iran annually precipitation, . Geography and Development Journal, No. 29, P: 15-30.

Babaeian I., Jamali1 J.B., Ahmadi M., Won-tae Kwon, Ean-Soon Im. Synoptic climatology of heavy summer rainfall over northeast of I.R. of Iran: 2001-2003. CRI/Iranian meteorological org., Mashhad, I.R.IRAN;

Climate Research Lab, METRI/KMA, Seoul. R. of Korea.

BARRY, D. KEIM, Climate Change Research Center, Institute for the Study of Earth, Oceans, and Space, and Department of Geography, University of New Hampshire, and New Hampshire State Climatologist, Durham, New Hampshire.

  1. Brunet, N.;, Verret, R.; and Yacowar, N, . (1988)., An objective comparison of model output statistics and prefect progress systems in producing numerical weather element forecasts, . Techniques Development x, Canadian met. Office, Atmospheric Environment Service, Dorval, Quebec, Canada.

BRADBURY ,JAMES A,2002, Climate System Research Center, Department of GeoCPIences, University of Massachusetts, Amherst, Massachusetts.

Colby, Frank P, Jr. Professor of Meteorology, University of Massachusetts Lowell, (http://www.wxdude.com/proverb.html),Meteorology, Weather and Climate, Weather Forecasting 1, Ruth Doherty.

  1. Cline Joel, W,.; Keeter Kermt, k,K. (1991)., National Hurricane hurricane Centercenter, Coral Gables, Florida, National weather service forecast office , Raleigh-Durban, North Carolina, The objective use of observed and forecast thickness value to predict precipitation type in North Carolina.

Davies M.  .Jonatha N, 2004."Estimation of CIN and LFC Associated with Tornadic and Non tornadic Supercells" Wiehita, Kansas, volume 14 of weather and forecasting.

Glhan H R, Lowry D A, 1972, the use of model output statistics (MOS) in objective weather forecasting, Techniques Development Laboratory, National Weather Service, NOAA, Silver Spring, and Md.2010

Gordon A H, 1982,Principal of dynamic meteorology, translated by Qasem Qasemi.

Klein Willaim H, Glahn Harry R, 1974, Forecasting local weather by means of model output statistics, Technique Development Lab., National Weather Service NOAA.

Kiefer, peter, 2001, Michigan Technology University, Houghton, MI49931, from The PUMAS Collection. http://pumas.jpl.nasa.gov California Institute of Technology.

Lester, Peter, Aviation Weather, Englewood USA.

Marks D Frank, Jr, Austin M Pauline, 1978, Effects of the New England coastal front on the distribution of precipitation, Dept. of meteorology, Massachusetts institute of technology, Cambridge 02139.

McCann, D.W, Windex, 1994, A new index for forecasting microburst potential, Wec and forecasting, p: 9,532-541.

Nasrallah H A, Balling R C,Selover N J,Vose R S, 2001,Development of seasonal forecast model for Kuwait winter precipitation, College of health CPIence, Dept. of environmental CPIence, Public authority of applied education and training, State of Kuwait, Office of climatology, Arizona state University, Tempe, Arizona, USA.

Retallack, B.J., 1981, compounding of meteorology, Vol 1, Part 2, Physical

meteorology, Geneva, WMO.

Wakimoto. R. M, Forecasting Dry Microburst Activity over the High Plain, Monthly Weather Review, p: 113, 1131, 1143.1985.

Saidan Mostafa sall, Henri Seuvageot, Amadou Thiermo Gage, Aloain Viltard,De Felce Piere,2002,"A cyclogenesis index for tropical Atlantic off the African coasts.

  1. Sari Saraf, B. Behroz,; Rajaey AbdolhamidA.;, Mesri Alamdari, P. (Parichehr, 2010). T, the study of relation between precipitation and topography in eastern and western hillside of Talesh mountains zone, . Geography and Environmental Planning journalJournal, No. 35, P. : 36-45.
  2. Tapp, R R.G, .; Woodcock, G.; and Mills, G G.A, . (1985). T, the application of model output statistical to precipitation prediction in Australia, Bureau of meteorology, . Dept. of CPIence, Melbourne, Australia.
  3. Vislocky, Robert R.L.,; Young George, S, . (1989). T, the use of prefect progress forecast to improve model output statistics forecast of precipitation probability, . Dept. of meteorologyMeteorology, The Pennsylvania State University, University of Pak Pennsylvania.

Watts Jill D and Klkstein Laurence S, 2003, The development of a warm-weather relative heat stress index for environment application, University of Delaware, Newark.

BYerz Robert  , Hariss. 1998, General Meteorology, first edition, translated by Tajdedin Bnihashem, Behruz Hajebi, Alireza Behruziyan, Tehran university publication.


Yokuver Alexander,1975, An analohu-based method to downscale surface precipitation, climat dynamic, 17,No. 2,  947-963.


Krueizing peter, 1983, An analog method for real-time forecasting of summer Monson rainfall, Atmospheric research, 24, 7, 64-78.