Use of Decision Theory to Predict Dust Storms over New Delhi, India


The north and northwest parts of India experience dust/sandstorms during the pre-monsoon season (April to May). We studied dust storms occurring over New Delhi, India (2001 to 2012) to develop a probabilistic forecast method. A probabilistic forecast method is discussed in this paper as a decision making tool that can be used to meet the needs of the users. The application of decision theory to forecast an event is that the end user of the forecast takes a decision for action on the basis of each forecast. This study stems from an elementary decision theory based on three interlocking procedures to follow viz. 1) identification of meteorological parameters responsible for dust storms, 2) determining the impact of each meteorological parameter in the initiation of a dust storm and 3) finally using the first two steps an action is recommended. Among the meteorological parameters, temperature, wind speed, pressure, number of sunny hours and evaporation had a positive impact on dust storm occurrence as compared to other variables selected. Using the concept of utility, which is an integral part of decision theory, a decision matrix is constructed. This decision matrix contains the threshold value above which a dust storm has occurred followed by each state of weather and the course of action. Thus, in this paper, a different concept of forecasting is discussed and optional rules for decision making based on the availability of a limited amount of meteorological data are presented. This forecast is of the very short range (0 - 3 hours) based on the meteorological conditions just prior to the occurrence of a dust event. We validated our findings with the OMI Aerosol index obtained from AERONET.

Share and Cite:

Desouza, N. , Kurchania, R. and Qureshi, M. (2014) Use of Decision Theory to Predict Dust Storms over New Delhi, India. Natural Science, 6, 574-582. doi: 10.4236/ns.2014.68057.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Moorthy, K.K., Babu, S.S., Satheesh, S.K., Srinivasan, J. and Dutt, C.B.S. (2007) Dust Absorption over the “Great Indian Desert” Inferred Using Ground-Based and Satellite Remote Sensing. Journal of Geophysical Research, 112, D9.
[2] Sikka, D.R. (1997) Desert Climate and Its Dynamics. Current Science, 72, 35-46.
[3] Mishra, S.K. and Tripathi, S.N. (2008) Modelling Optical Properties of Mineral Dust over the Indian Desert. Journal of Geophysical Research, 113, D23201.
[4] Ramon, D.E. and Rene, L. (2004) Diversity in Interpretations of Probability: Implications for Weather Forecasting. Monthly Weather Review, 133, 1129-1143.
[5] Lindley, D.V. (1985) Making Decisions. 2nd Edition, John Wiley & Sons Ltd., London.
[6] Mylne, K.R. (2002) Decision Making from Probability from Probability Forecasts Based on Forecast Value. Meteorological Applications, 9, 307-315.
[7] Thomson, A.W.P. (2000) Evaluating Space Weather Forecast of Geomagnetic Activity from a User Perspective. Geophysical Research Letters, 27, 4049-4052.
[8] Richardson, D. (2000) Skill and Relative Economic Value of the ECMWF Ensemble Prediction System. Quarterly Journal of Royal Meteorological Society, 126, 649-667.
[9] Qiu, Y.J., Niu, S.J. and Zhao, X.Y. (2008) The Relationship between Dust Event Frequency and Meteorological Factors. Plateau Meteorology, 27, 637-643.
[10] Xiao, F.J., Zhou, C.P. and Liao, Y.M. (2008) Dust Storm Events Evolution in Taklimakan Desert and Its Correlation with Climatic Parameters. Journal of Geographic Science, 18, 415-424.
[11] Li, W.Y., Lu, S.H., Yu, Y., Dong, Z., Shen, Z. and Chen, Y. (2011) Evaluating the Impact and Significance of Meteorological Factors upon Dust Storm Occurrence. Science in Cold and Arid Regions, 3, 161-171.
[12] Torres, O., Ahn, C. and Chen, Z. (2013) Improvements to the OMI near-UV Aerosol Algorithm Using A-Train, CALIOP and AIRS Observations. Atmospheric Measurement Techniques, 6, 3257-3270.
[13] Rivera, N.I. (2006) Meteorological Conditions of Extreme Dust Events in the Chihuahuan Desert Region of the United States and Mexico. SOARS, 1-43.
[14] Morton, F.I. (1968) Evaporation and Climate: A Study in Cause and Effect. Scientific Series No. 4, Inland Water Branch, Department of Energy, Mines and Resources, Ottawa, 32.
[15] Monteith, J.L. (1964) Evaporation and Environment. Symposia of the Society for Experimental Biology, 19, 205-234.
[16] van Bavel, C.H.M. (1966) Potential Evaporation: The Combination Concept and Its Experimental Verification. Water Resources Research, 2, 455-467.
[17] Linacre, E.T. (1964) Calculations of the Transpiration Rate and Temperature of a Leaf. Archiv für Meteorologie, Geophysik und Bioklimatologie, B13, 391-399.
[18] Skidmore, E.L. and Hagen, L.J. (1970) Evaporation in Sheltered Areas as Influenced by Windbreak Porosity. Agricultural Meteorology, 7, 363-374.
[19] Dey, S., Tripathi, S.N. and Singh, R.P. (2004) Influence of Dust Storms on the Aerosol Optical Properties over the Indo-Gangetic Basin. Journal of Geophysical Research, 109, D20211.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.