How is weather forecasting a reliable method to take precaution against disasters
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Good predictions and warnings save lives. With only a few minutes' notice of a tornado or flash flood, people can act to protect themselves from injury and death. Predictions and warnings can also reduce damage and economic losses. When notice of an impending disaster can be issued well in advance, as it can for some riverine floods, wildfires, and hurricanes, property and natural resources can be protected.
Hurricane Hugo illustrates the benefits of an effective natural hazards warning system. Without successful prediction, warning, and evacuation, the loss of life could have reached the thousands, but actual deaths numbered 28. By contrast, when a hurricane struck Galveston, Texas — which had no warning system — on September 8, 1900, 6,000 people were killed and 5,000 injured.
Scientific and technological advances in recent decades have greatly improved the nation's capability to predict most natural hazards and disseminate warnings based on those predictions. However, prediction accuracy and lead times vary with the type of hazard. Prediction capabilities for atmospheric and hydrologic events are generally more advanced and specific than those for their geologic counterparts.
The federal government operates several systems to monitor natural hazards and make predictions. For example, an extensive weather monitoring and forecasting network covers the nation. Warnings are disseminated through a joint public-private partnership. Continuous radio and television broadcasts make both routine weather forecasts and severe weather warnings accessible to everyone. Televised weather programs have improved through the use of meteorologists and advanced presentation technology. Wildfire potential is closely monitored, and newspapers such as USA Today publish maps of daily and weekly fire danger. A system of observatories monitors volcanoes in Alaska, Hawaii, and Washington and issues warnings that have led to evacuation of surrounding areas, rerouting of air traffic, and other actions.
The technological capabilities for prediction are considerably better than social and organizational capabilities to disseminate warnings. For example, warnings of an impending natural hazard may not reach all potential victims. A concerted effort is needed to improve dissemination networks and the content of warning messages.
The Committee recommends that the nation expand and intensify its programs to improve prediction of significant natural hazard events and to ensure the effective and timely dissemination of warnings to all sectors of society.
To achieve this goal, the Committee proposes:
the upgrading of natural hazard prediction and warning systems through application of state-of-theart science and technology;
augmentation of research programs on the basic physical and biological processes of natural hazards, models to predict their occurrence, and technology to detect and monitor them and to disseminate warnings; and
expansion of research on the social aspects of effective warning messages.
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Weather forecasts are made by collecting as much data as possible about the current state of the atmosphere (particularly the temperature, humidity and wind) and using understanding of atmospheric processes (through meteorology) to determine how the atmosphere evolves in the future.
However, the chaotic nature of the atmosphere and incomplete understanding of the processes mean that forecasts become less accurate as the range of the forecast increases.
Traditional observations made at the surface of atmospheric pressure, temperature, wind speed, wind direction, humidity, precipitation are collected routinely from trained observers, automatic weather stations or buoys.
During the data assimilation process, information gained from the observations is used in conjunction with a numerical model's most recent forecast for the time that observations were made to produce the meteorological analysis.
Numerical weather prediction models are computer simulations of the atmosphere.
They take the analysis as the starting point and evolve the state of the atmosphere forward in time using understanding of physics and fluid dynamics.
The complicated equations which govern how the state of a fluid changes with time require supercomputers to solve them.
The output from the model provides the basis of the weather forecast.