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A GIS application for weather analysis and forecasting

Saseendran S. A., Harenduprakash L., Rathore L. S. and Singh S. V.
National Centre for Medium Range Weather Forecasting,
Department of Science and Technology, New Delhi -3

With technological progresses and associated need for more and more human comfort, the demands for accurate weather forecasts for different spatial and temporal scales are also increasing. In this context, application of emerging technologies for increasing accuracy and skill of the weather forecast calls for special attention. Use of Geographical Information Systems (GIS) software viz. Arc View to develop an application, for plotting, analysis, visualization, and interpretation of weather data, to serve as an aid in the prognostication of weather is attempted in this paper. The application developed can help the meteorologists in instantaneous plotting of synoptic weather data from different locations at various isobaric levels of the atmosphere. Analysis of this data, for visualization and interpretation of weather systems over wide geographic areas become possible with less effort and error. Facilities available include, provision for superimposition of synoptic weather maps of the past with the present for tracking of movement of weather systems, computation of their persistence, tendencies and trends. Weather maps at different levels, or different days (past, present and future) can be superimposed and removed with the click of the mouse for analysis and visualization of weather developments. Advancing the weather systems forward or backward geographically for visualization of past and future (as forecasted) movement of weather systems across geographical areas becomes easier. Climatological data can also be plotted, departures from normals, tendencies, etc. calculated and presented as charts. Satellite pictures, topographical information, etc. can also be plotted and superimposed with other weather parameters for assistance in weather forecasting.

Introduction Atmosphere is the gaseous envelope of the earth in which all its flora and fauna survive. As weather is the statement of its physical conditions at an instant, its forecasting is of concern to one and all living over the earth. As such, since time immemorial weather forecasting was a subject of grave concern for the physical scientists. But, due to extremely complex nature of various physical processes of the atmosphere, which lead to weather, these endeavors have always been met with limited success.

Various methods were developed and used by meteorologists for weather forecasting. The most important methods in vogue currently are the conventional Synoptic, and Numerical Weather Prediction (NWP) methods. The former method is human subjective, and the latter is objective and deterministic. Skill of these forecasts can be enhanced through use of GIS by relating different features of the atmosphere and their proper visualization.

Conventional synoptic method
In this subjective method, conventional forecasting tools like, trend, persistence, Climatology, and analogue of weather systems, are popularly employed. Each of these methods makes use of some basic assumptions for extrapolating the weather into the future. The forecaster blends these extrapolations with his own experience and the location specific weather quirks like topography, land sea distributions etc.

None of these methods seems perfect, as the weather sometimes manifest differently, deviating considerably from the basic concepts on which these methods are founded. The inadequate human understanding of the various complex atmospheric processes leading to the weather development itself is one of the major problems associated with this method.

NWP method
To forecast weather, the NWP method makes use of numerical solutions (high speed super computers are generally required for this task) of complex system of mathematical prognostic equations/models representing both the physical and dynamical processes occurring in the atmosphere. These models are commonly known as Global Circulation Models (GCMs). In order to integrate the GCM forward in time, the model equations need initialization with precise knowledge of the current state or initial conditions of the atmosphere. To achieve this task, global observations of various atmospheric parameters e.g. temperature, wind speed and direction and humidity, made routinely at standard synoptic hours are usually assimilated into the model using a process known as Variation Analysis. The model integrations into the future automatically produce charts of important parameters such as surface pressure, wind circulations, etc. The forecaster interprets these charts for weather forecasting at the locations of his interest.

Medium Range Weather Forecasting in India
The National Centre for Medium Range Weather Forecasting (NCMRWF) was established in India under the Department of Science and Technology for issuing weather forecasts in the medium range i.e. 3 to 10 days in advance. The GCM used in the Medium-range Analysis Forecast System (MAFS) of the NCMRWF is an adapted version from NCEP (NMC, 1988). It is a Global Spectral Model having T80 horizontal resolution (about 150 km) and 18 layers in the vertical. The model uses climatological boundary conditions for the sea surface temperature, albedo, ice, snow, soil moisture, soil temperature, and roughness length and plant resistance. The MAFS operational at NCMRWF consists of (1) data processing and quality control, (ii) utilization of non-conventional data, (iii) data assimilation, (iv) model integration, (v) post processing and diagnostic studies, and (vi) preparation of location specific forecasts.

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