Meteorology
In 1904, Norwegian scientist Vilhelm Bjerknes first postulated that prognostication of the weather is possible from calculations based upon natural laws.
Early in the 20th century, advances in the understanding of atmospheric physics led to the foundation of modern numerical weather prediction. In 1922, Lewis Fry Richardson published "Weather prediction by numerical process," which described how small terms in the fluid dynamics equations governing atmospheric flow could be neglected to allow numerical solutions to be found. However, the sheer number of calculations required was too large to be completed without the use of computers.
At this time in Norway a group of meteorologists led by Vilhelm Bjerknes developed the model that explains the generation, intensification and ultimate decay (the life cycle) of mid-latitude cyclones, introducing the idea of fronts, that is, sharply defined boundaries between air masses. The group included Carl-Gustaf Rossby (who was the first to explain the large scale atmospheric flow in terms of fluid dynamics), Tor Bergeron (who first determined the mechanism by which rain forms) and Jacob Bjerknes.
Starting in the 1950s, numerical experiments with computers became feasible. The first weather forecasts derived this way used barotropic (that means, single-vertical-level) models, and could successfully predict the large-scale movement of midlatitude Rossby waves, that is, the pattern of atmospheric lows and highs.
In the 1960s, the chaotic nature of the atmosphere was first observed and understood by Edward Lorenz, founding the field of chaos theory. These advances have led to the current use of ensemble forecasting in most major forecasting centers, to take into account uncertainty arising from the chaotic nature of the atmosphere.
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Equipment
Generally speaking, each science has its own unique sets of laboratory equipment. However, meteorology is a science which does not use much lab equipment but relies more on field-mode observation equipment. In some aspects this can make simple observations slide on the erroneous side.
In science, an observation, or observable, is an abstract idea that can be measured and data can be taken. In the atmosphere, there are many things or qualities of the atmosphere that can be measured. Rain, which can be observed, or seen anywhere and anytime was one of the first ones to be measured historically. Also, two other accurately measured qualities are wind and humidity. Neither of these can be seen but can be felt. The devices to measure these three sprang up in the mid-15th century and were respectively the rain gauge, the anemometer, and the hygrometer.[14]
Sets of surface measurements are important data to meteorologists. They give a snapshot of a variety of weather conditions at one single location and are usually at a weather station, a ship or a weather buoy. The measurements taken at a weather station can include any number of atmospheric observables. Usually, temperature, pressure, wind measurements, and humidity are the variables that are measured by a thermometer, barometer, anemometer, and hygrometer, respectively.
Upper air data are of crucial importance for weather forecasting. The most widely used technique is launches of radiosondes. Supplementing the radiosondes a network of aircraft collection is organized by the World Meteorological Organization.
Remote sensing, as used in meteorology, is the concept of collecting data from remote weather events and subsequently producing weather information. The common types of remote sensing are Radar, Lidar, and satellites (or photogrammetry). Each collects data about the atmosphere from a remote location and, usually, stores the data where the instrument is located. RADAR and LIDAR are not passive because both use EM radiation to illuminate a specific portion of the atmosphere.[15]
The 1960 launch of the first successful weather satellite, TIROS-1, marked the beginning of the age where weather information became available globally. Weather satellites along with more general-purpose Earth-observing satellites circling the earth at various altitudes have become an indispensable tool for studying a wide range of phenomena from forest fires to El Niño.
In recent years, climate models have been developed that feature a resolution comparable to older weather prediction models. These climate models are used to investigate long-term climate shifts, such as what effects might be caused by human emission of greenhouse gases.
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Weather forecasting
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Although meteorologists now rely heavily on computer models (numerical weather prediction), it is still relatively common to use techniques and conceptual models that were developed before computers were powerful enough to make predictions accurately or efficiently (generally speaking, prior to around 1980). Many of these methods are used to determine how much skill a forecaster has added to the forecast (for example, how much better than persistence or climatology did the forecast do?). Similarly, they could also be used to determine how much skill the industry as a whole has gained with emerging technologies and techniques.
- Persistence method
The persistence method assumes that conditions will not change. Often summarised as "Tomorrow equals today". This method works best over short periods of time in stagnant weather regimes.[16]
- Extrapolation method
The extrapolation method assumes that atmospheric systems will propagate at similar speeds in the near future to those seen in the past. This method achieves the best results when diurnal changes in the pressure and precipitation patterns are taken into account.
- Numerical forecasting method
The numerical weather prediction or NWP[17] method uses computers to take into account a large number of variables and creates a computer model of the atmosphere. This is most successful when used with the methods below, and when model biases and relative skill are taken into account.
- Consensus/ensemble methods of forecasting
Statistically, it is difficult to beat the mean solution, and the consensus and ensemble methods of forecasting take advantage of the situation by only favoring models that have the greatest support with their ensemble means or other pieces of global model guidance. A local Hydrometeorological Prediction Center study showed that using this method alone verifies 50-55% of the time.
- Trends method
The trends method involves determining the change in fronts and high and low pressure centers in the model runs over various lengths of time. If the trend is seen over a long enough time frame (24 hours or so), it is more meaningful. The forecast models have been known to overtrend however, so use of this method verifies 55-60% the time, more so in the surface pattern than aloft.[18]
- Climatology/Analog method
The climatology or analog method involves using historical weather data collected over long periods of time (years) to predict conditions on a given date. A variation on this theme is the use of teleconnections, which rely upon the date and the expected position of other positive or negative 500 hPa height anomalies to give someone an impression of what the overall pattern would look like with this anomaly in place, and is of more significant help than a model trend since it verifies roughly 75 percent of the time, when used properly and with a stable anomaly center. Another variation is the use of standard deviations from climatology in various meteorological fields. Once the pattern deviates more than 4-5 sigmas from climatology, it becomes an improbable solution.[19]
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See also
- American Practical Navigator
- Atmospheric circulation
- Atmospheric dynamics
- Atmospheric layers
- Atmospheric models
- Atmospheric thermodynamics
- ENSO (El Niño-Southern Oscillation)
- List of weather instruments
- List of meteorology institutions
- List of meteorology topics
- Madden-Julian oscillation
- Space weather
- Walker circulation
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References
- ^ "Meteorology." The Encyclopedia Brintannica.15th Ed. 2005.
- ^ Byers, Horace. General Meteorology. New York: McGraw-Hill, 1994.
- ^ Garratt, J.R., The atmospheric boundary layer, Cambridge University Press, 1992; ISBN 0-521-38052-9.
- ^ Online Glossary of Meteorology, American Meteorological Society [1] ,2nd Ed., 2000, Allen Press.
- ^ Bluestein, H., Synoptic-Dynamic Meteorology in Midlatitudes: Principles of Kinematics and Dynamics, Vol. 1, Oxford University Press, 1992; ISBN 0-19-506267-1
- ^ Global Modelling, US Naval Research Laboratory, Monterrey, Ca.
- ^ Holton, J.R. [2004]. An Introduction to Dynamic Meteorology, 4th Ed., Burlington, Md: Elsevier Inc.. ISBN 0-12-354015-1.
- ^ An international version called the Aeronautical Information Publication contains parallel information, as well as specific information on the international airports for use by the international community.
- ^ "7-1-22. PIREPs Relating to Airframe Icing", [February 16, 2006], Aeronautical Information Manual, FAA AIM Online
- ^ Agricultural and Forest Meteorology, Elsevier, ISSN: 0168-1923.
- ^ Encyclopedia Britannica, 2007.
- ^ About the HPC, NOAA/ National Weather Service, National Centers for Environmental Prediction, Hydrometeorological Prediction Center, Camp Springs, Maryland, 2007.
- ^ Smithsonian Institution Archives
- ^ Many attempts had been made prior to the 15th century to construct adequate equipment to measure the many atmospheric variables. Many were faulty in some way or were simply not reliable. Even Aristotle notes this in some of his work; as the difficulty to measure the air.
- ^ Peebles, Peyton, [1998], Radar Principles, John Wiley & Sons, Inc., New York, ISBN 0-471-25205-0.
- ^ The Online Meteorology Guide, Module:Weather Forecasting; Department of Atmospheric Sciences (DAS) at the University of Illinois at Urbana-Champaign.
- ^ The Online Meteorology Guide
- ^ The Online Meteorology Guide
- ^ The Online Meteorology Guide
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Further reading
- Byers, Horace. General Meteorology. New York: McGraw-Hill, 1994.
- Garret, J.R. [1992]. The atmospheric boundary layer. Cambridge University Press. ISBN 0-521-38052-9.
- [2000] Glossary of Meteorology, American Meteorological Society, 2nd Ed., Allen Press.
- Bluestein, H [1992]. Synoptic-Dynamic Meteorology in Midlatitudes: Principles of Kinematics and Dynamics, Vol. 1. Oxford University Press. ISBN 0-19-506267-1.
- Bluestein, H [1993]. Synoptic-Dynamic Meteorology in Midlatitudes: Volume II: Observations and Theory of Weather Systems. Oxford University Press. ISBN 0-19-506268-X.
- Reynolds, R [2005]. Guide to Weather. Buffalo, New York: Firefly Books Inc, 208. ISBN 1-55407-110-0.
- Holton, J.R. [2004]. An Introduction to Dynamic Meteorology, 4th Ed., Burlington, Md: Elsevier Inc.. ISBN 0-12-354015-1.
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External links
Please see weather forecasting for weather forecast sites.
- Air Quality Meteorology - Online course that introduces the basic concepts of meteorology and air quality necessary to understand meteorological computer models. Written at a bachelor's degree level.
- The GLOBE Program - (Global Learning and Observations to Benefit the Environment) An international environmental science and education program that links students, teachers, and the scientific research community in an effort to learn more about the environment through student data collection and observation.
- Glossary of Meteorology - From the American Meteorological Society, an excellent reference of nomenclature, equations, and concepts for the more advanced reader.
- JetStream - An Online School for Weather - National Weather Service
- Learn About Meteorology - Australian Bureau of Meteorology
- Meteorology Education and Training (MetEd) - The COMET Program
- NOAA Central Library - National Oceanic & Atmospheric Administration
- The World Weather 2010 Project The University of Illinois at Urbana-Champaign
- NOAA Weather Navigator Plot and download archived data from thousands of worldwide weather stations
- Ogimet - online data from meteorological stations of the world, obtained through NOAA free services
Satellite imagery:
- Geostationary Satellite Imagery - NOAA National Environmental Satellite, Data, and Information Service
- Satellite Imagery - UK Met Office
Base Reflectivity (Radar):
Meteorology during Solar Eclipse
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