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
Cite this paper
Desouza, N. , Kurchania, R. and Qureshi, M. (2014) Use of Decision Theory to Predict Dust Storms over New Delhi, India. Natural Science
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