Data processing: measuring – calibrating – or testing – Measurement system in a specific environment – Earth science
Reexamination Certificate
2000-11-13
2003-03-18
McElheny, Jr., Donald E. (Department: 2862)
Data processing: measuring, calibrating, or testing
Measurement system in a specific environment
Earth science
Reexamination Certificate
active
06535817
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to weather forecasts, and more specifically, to weather and seasonal forecasts generated from an assembly of forecast models.
BACKGROUND OF THE INVENTION
Because of the importance of the weather, forecasts are readily available via a wide variety of media, including the Internet, television, radio and print media. Images of the weather generated by satellite photographs and radar networks are familiar to almost everyone. Nevertheless, despite a long history of the study of the atmosphere and its phenomena, and enormous technological and scientific advances, local, regional and seasonal forecasts often are inaccurate.
Meteorology as an exact science is a relatively recent science. However, as an inexact science, meteorology has been around for a long time. It is widely agreed that the word ‘meteorology’ was coined by the Greek philosopher Aristotle, who wrote a book entitled Meteorologica circa 350 BC. In this work Aristotle attempted to explain atmospheric phenomena, such as clouds, wind, precipitation, lightning, thunder, and climatic changes. Although much of the work disclosed in Meteorologica was erroneous, it was not until the 17th century that his ideas were scientifically disproved.
The origins of meteorology as a natural science occurred in the late 16th century. At this time it had become evident that the speculations of philosophers regarding meteorology were inadequate and that better scientific knowledge was essential to understand the atmosphere. Therefore, it was realized that instruments were necessary to measure properties on Earth's atmosphere. As a result, instruments such as the hygrometer, thermometer, and barometer were developed. These instruments measured atmospheric data and helped identify changes in weather. However, the weather forecasting effectiveness of such instruments, combined with the understanding of atmospheric processes at the time, were minimal.
It was not until the twentieth century that more detailed scientific instruments and knowledge were cultivated to help predict daily and seasonal climate changes. For instance, in the 1940s measurements of upper level meteorological components, such as temperature, humidity, pressure, and wind speed and direction, became possible by placing instruments on balloons that were released into the atmosphere. Meteorological science took an additional step forward in the 1950's with the development of computers. Computers enabled models to be developed utilizing equations that approximated the physical processes of the atmosphere. These physical relationships are currently used in weather forecasting in an attempt to predict the future behavior of the atmosphere. To construct weather models computers use data collected from sophisticated instruments, such as RADAR and meteorological satellites, which provide monitoring of world weather events. Data from these instruments have been instrumental in improving our knowledge of all weather systems, including fronts, thunderstorms, hurricanes, and other weather events.
Weather and seasonal forecasting and prediction is a sophisticated art that utilizes measurements taken continuously from geographic areas around the globe. These measurements include temperature, wind speed, height of pressure gradient, humidity, precipitation, and the like, collected from weather balloons, weather stations, satellites, aircraft, buoys, and similar measurement equipment and/or facilities. Using these and other advancements in remote-sensing technologies to collect data, computer models for forecasting weather conditions have been developed.
Because of the collection and analysis of a vast amount of data from around the world and the numerical simulation of meteorological and climatological processes, supercomputers and the latest advanced mathematical techniques are an integral part of the science of the atmosphere. Using such equipment, one broad area of meteorological research encompasses the observation, numerical modeling, and prediction of weather systems such as hurricanes and severe storms. Today, sophisticated numerical models used in operational and research centers throughout the globe routinely make short-term (1 to 7 days in advance) weather and seasonal (one to several seasons in advance) climate forecasts. Models and projections are developed by the National Weather Service (the governmental entity in the United States charged with disseminating weather data to the public) and other private forecasting firms. Nevertheless, despite the vast scientific and technological improvements and advances in meteorology, including the modeling of weather using data accumulated by weather-monitoring instruments, weather prediction and models are often inaccurate, vague, broad, and lack regional or local specificity.
Because of the impact of weather on our daily lives, it is an understatement that it would be beneficial if we could predict both the short term and long term weather. Therefore, what is needed is a forecasting method and system that permits more accurate weather forecasts based upon the vast collection of data provided by scientific weather instruments. What is also needed is a forecasting method and system that can more accurately forecast climatological or seasonal weather changes.
SUMMARY OF THE INVENTION
Systems, methods and computer program products of the present invention collect historical forecast information generated from a plurality of weather models (or forecast models), where each model forecasted at least one predicted weather component. For example, a weather model may include a forecasted temperature (predicted weather component) for a specific geographical location for a certain past date or time period. Systems, methods and computer program products of the present invention compare the historical forecast information, and more particularly, the predicted weather components, generated by the plurality of weather models to observed weather data to determine the historical performance of the weather models. According to one aspect of the invention, the historical performance is the accuracy with which a weather model predicts a particular weather component. Thereafter, each model is weighted based upon the historical performance of that model in predicting a weather component at a particular geographic location or a range of geographical locations. The weighted weather models are then combined to generate a multi-model superensemble. The multi-model superensemble utilizes the historical performance of every weather model in forecasting weather components to generate a weather forecast for a future period of time.
More specifically, according to the present invention, a multi-model superensemble is developed using a plurality of forecasts from a variety of weather and climate models. Along with observed (or benchmark) analysis fields, these forecasts are used to derive statistics on the past behavior of the models. These statistics, combined with model forecasts, enables the construction of a superensemble forecast. More specifically, given a set of past model forecasts, the present invention uses a multiple regression technique to regress the model forecasts against observed (analysis) fields. Least-squares minimization of the difference between the model and the analysis field is used to determine the weights of each model component at any geographic location and vertical level.
According to one embodiment of the present invention, there is disclosed a method for generating an accurate weather forecast model. The method includes the steps of collecting historical forecast information from a plurality of weather models, wherein the historical forecast information includes at least one predicted weather component, and wherein the historical forecast information corresponds to a past period of time. The method also includes accumulating observed weather data, wherein the observed weather data corresponds to a plurality of known weather values, wherein at least one known weather
McElheny Jr. Donald E.
Sutherland & Asbill & Brennan LLP
The Florida State Research Foundation
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