Meteorology

Jump to navigation Jump to search


Meteorology (from Greek: μετέωρον, metéōron, "high in the sky"; and λόγος, lógos, "knowledge") is the interdisciplinary scientific study of the atmosphere that focuses on weather processes and forecasting (in contrast with climatology). Meteorological phenomena are observable weather events which illuminate and are explained by the science of meteorology. Those events are bound by the variables that exist in Earth's atmosphere. They are temperature, pressure, water vapor, and the gradients and interactions of each variable, and how they change in time. The majority of Earth's observed weather is located in the troposphere. [1] [2]

Meteorology, climatology, atmospheric physics, and atmospheric chemistry are sub-disciplines of the atmospheric sciences. Meteorology and hydrology compose the interdisciplinary field of hydrometeorology.

Interactions between Earth's atmosphere and the oceans are part of coupled ocean-atmosphere studies. Meteorology has application in many diverse fields such as the military, energy production, transport, agriculture and construction.

Sub-classifications

In the study of the atmosphere, meteorology can be divided into distinct areas of emphasis depending on the temporal scope and spatial scope of interest. At one extreme of this scale is climatology. In the timescales of hours to days, meteorology separates into micro-, meso-, and synoptic scale meteorology. Respectively, the geospatial size of each of these three scales relates directly with the appropriate timescale.

Other subclassifications are available based on the need by humans, or by the unique, local or broad effects that are studied within that sub-class.

Boundary layer meteorology

Boundary layer meteorology is the study of processes in the air layer directly above Earth's surface, known as the atmospheric boundary layer (ABL) or peplosphere. The effects of the surface – heating, cooling, and friction – cause turbulent mixing within the air layer. Significant fluxes of heat, matter, or momentum on time scales of less than a day are advected by turbulent motions.[3] Boundary layer meteorology includes the study of all types of surface-atmosphere boundary, including ocean, lake, urban land and non-urban land.

Mesoscale meteorology

Mesoscale meteorology is the study of atmospheric phenomena that has horizontal scales ranging from microscale limits to synoptic scale limits and a vertical scale that starts at the Earth's surface and includes the atmospheric boundary layer, troposphere, tropopause, and the lower section of the stratosphere. Mesoscale timescales last from less than a day to the lifetime of the event, which in some cases can be weeks. The events typically of interest are thunderstorms, squall lines, fronts, precipitation bands in tropical and extratropical cyclones, and topographically generated weather systems such as mountain waves and sea and land breezes.[4]

File:Surface analysis.gif
NOAA: Synoptic scale weather analysis.
Synoptic scale

Synoptic scale meteorology is generally large area dynamics referred to in horizontal coordinates and with respect to time. The phenomena typically described by synoptic meteorology include events like extratropical cyclones, baroclinic troughs and ridges, frontal zones, and to some extent jets. All of these are typically given on weather maps for a specific time. The minimum horizontal scale of synoptic phenomena are limited to the spacing between surface observation stations. [5]

File:Wiki plot 03.png
Annual mean sea surface temperatures.
Global scale

Global scale meteorology is study of weather patterns related to the transport of heat from the tropics to the poles. Also, very large scale oscillations are of importance. Those oscillations have time periods typically longer than a full annual seasonal cycle, such as ENSO, PDO, MJO, etc. Global scale pushes the thresholds of the perception of meteorology into climatology. The traditional definition of climate is pushed in to larger timescales with the further understanding of how the global oscillations cause both climate and weather disturbances in the synoptic and mesoscale timescales.

Numerical Weather Prediction is a main focus in understanding air-sea interaction, tropical meteorology, atmospheric predictability, and tropospheric/stratospheric processes.[6]. Currently (2007) Naval Research Laboratory in Monterey produces the atmospheric model called NOGAPS, a global scale atmospheric model, this model is run operationally at Fleet Numerical Meteorology and Oceanography Center. There are several other global atmospheric models.

Dynamic meteorology

Dynamic meteorology generally focuses on the physics of the atmosphere. The idea of air parcel is used to define the smallest element of the atmosphere, while ignoring the discrete molecular and chemical nature of the atmosphere. An air parcel is defined as a point in the fluid continuum of the atmosphere. The fundamental laws of fluid dynamics, thermodynamics, and motion are used to study the atmosphere. The physical quantities that characterize the state of the atmosphere are temperature, density, pressure, etc. These variables have unique values in the continuum.[7]

Aviation meteorology

Aviation meteorology deals with the impact of weather on air traffic management. It is important for air crews to understand the implications of weather on their flight plan as well as their aircraft, as noted by the Aeronautical Information Manual[8]:

The effects of ice on aircraft are cumulative-thrust is reduced, drag increases, lift lessens, and weight increases. The results are a decrease in stall speed and a deterioration of aircraft performance. In extreme cases, 2 to 3 inches of ice can form on the leading edge of the airfoil in less than 5 minutes. It takes but 1/2 inch of ice to reduce the lifting power of some aircraft by 50 percent and increases the frictional drag by an equal percentage.[9]

Agricultural meteorology

Meteorologists, soil scientists, agricultural hydrologists, and agronomists are persons concerned with studying the effects of weather and climate on plant distribution, crop yield, water-use efficiency, phenology of plant and animal development, and the energy balance of managed and natural ecosystems. Conversely, they are interested in the role of vegetation on climate and weather.[10]

Hydrometeorology

Hydrometeorology is the branch of meteorology that deals with the hydrologic cycle, the water budget, and the rainfall statistics of storms.[11] A hydrometeorologist prepares and issues forecasts of accumulating (quantitative) precipitation, heavy rain, heavy snow, and highlights areas with the potential for flash flooding. Typically the range of knowledge that is required overlaps with climatology, mesoscale and synoptic meteorology, and other geosciences.[12]

History

Observation networks and weather forecasting

The arrival of the electrical telegraph in 1837 afforded, for the first time, a practical method for quickly gathering surface weather observations from a wide area. This data could be used to produce maps of the state of the atmosphere for a region near the Earth's surface and to study how these states evolved through time. To make frequent weather forecasts based on these data required a reliable network of observations, but it was not until 1849 that the Smithsonian Institution began to establish an observation network across the United States under the leadership of Joseph Henry [13]. Similar observation networks were established in Europe at this time. In 1854, the United Kingdom government appointed Robert FitzRoy to the new office of Meteorological Statist to the Board of Trade with the role of gathering weather observations at sea. FitzRoy's office became the United Kingdom Meteorological Office in 1854, the first national meteorological service in the world. The first daily weather forecasts made by FitzRoy's Office were published in The Times newspaper in 1860. The following year a system was introduced of hoisting storm warning cones at principal ports when a gale was expected.

Over the next 50 years many countries established national meteorological services: Finnish Meteorological Central Office (1881) was formed from part of Magnetic Observatory of Helsinki University; India Meteorological Department (1889) established following tropical cyclone and monsoon related famines in the previous decades; United States Weather Bureau (1890) was established under the United States Department of Agriculture; Australian Bureau of Meteorology (1905) established by a Meteorology Act to unify existing state meteorological services.

Coriolis effect

Understanding the kinematics of how exactly the rotation of the Earth affects airflow was partial at first. Late in the 19th century the full extent of the large scale interaction of pressure gradient force and deflecting force that in the end causes air masses to move along isobars was understood. Early in the 20th century this deflecting force was named the Coriolis effect after Gaspard-Gustave Coriolis, who had published in 1835 on the energy yield of machines with rotating parts, such as waterwheels. In 1856, William Ferrel proposed the existence of a circulation cell in the mid-latitudes with air being deflected by the Coriolis force to create the prevailing westerly winds.

Numerical weather prediction

File:Weather Bureau 1965.jpg
A meteorologist at the console of the IBM 7090 in the Joint Numerical Weather Prediction Unit. c. 1965

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.

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.

File:Huracán Hugo.jpg
Satellite image of Hurricane Hugo with a polar low visible at the top of the image.

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.

Weather forecasting

File:Norman OK meteorologist.jpg
An NWS meteorologist communicates with storm spotters during a severe weather event.


Template:Weather nav 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]

See also

Template:WeatherPortal

References

  1. "Meteorology." The Encyclopedia Brintannica.15th Ed. 2005.
  2. Byers, Horace. General Meteorology. New York: McGraw-Hill, 1994.
  3. Garratt, J.R., The atmospheric boundary layer, Cambridge University Press, 1992; ISBN 0-521-38052-9.
  4. Online Glossary of Meteorology, American Meteorological Society [1] ,2nd Ed., 2000, Allen Press.
  5. Bluestein, H., Synoptic-Dynamic Meteorology in Midlatitudes: Principles of Kinematics and Dynamics, Vol. 1, Oxford University Press, 1992; ISBN 0-19-506267-1
  6. Global Modelling, US Naval Research Laboratory, Monterrey, Ca.
  7. Holton, J.R. [2004]. An Introduction to Dynamic Meteorology, 4th Ed., Burlington, Md: Elsevier Inc.. ISBN 0-12-354015-1.
  8. 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.
  9. "7-1-22. PIREPs Relating to Airframe Icing", [February 16, 2006], Aeronautical Information Manual, FAA AIM Online
  10. Agricultural and Forest Meteorology, Elsevier, ISSN: 0168-1923.
  11. Encyclopedia Britannica, 2007.
  12. About the HPC, NOAA/ National Weather Service, National Centers for Environmental Prediction, Hydrometeorological Prediction Center, Camp Springs, Maryland, 2007.
  13. Smithsonian Institution Archives
  14. 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.
  15. Peebles, Peyton, [1998], Radar Principles, John Wiley & Sons, Inc., New York, ISBN 0-471-25205-0.
  16. The Online Meteorology Guide, Module:Weather Forecasting; Department of Atmospheric Sciences (DAS) at the University of Illinois at Urbana-Champaign.
  17. The Online Meteorology Guide
  18. The Online Meteorology Guide
  19. The Online Meteorology Guide

Further reading

  • Byers, Horace. General Meteorology. New York: McGraw-Hill, 1994.
  • Garret, J.R. The atmospheric boundary layer. Cambridge University Press. ISBN 0-521-38052-9. Unknown parameter |origdate= ignored (|orig-year= suggested) (help)
  • Glossary of Meteorology. American Meteorological Society (2nd Ed. ed.). Allen Press. Unknown parameter |origdate= ignored (|orig-year= suggested) (help)
  • Bluestein, H. Synoptic-Dynamic Meteorology in Midlatitudes: Principles of Kinematics and Dynamics, Vol. 1. Oxford University Press. ISBN 0-19-506267-1. Unknown parameter |origdate= ignored (|orig-year= suggested) (help)
  • Bluestein, H. Synoptic-Dynamic Meteorology in Midlatitudes: Volume II: Observations and Theory of Weather Systems. Oxford University Press. ISBN 0-19-506268-X. Unknown parameter |origdate= ignored (|orig-year= suggested) (help)
  • Reynolds, R. Guide to Weather. Buffalo, New York: Firefly Books Inc. p. 208. ISBN 1-55407-110-0. Unknown parameter |origdate= ignored (|orig-year= suggested) (help)


Links to other keywords in meteorology

Atmospheric conditions: Absolute stable air | Temperature inversion | Dine's compensation | precipitation | Cyclone | anticyclone | Thermal | Tropical cyclone (hurricane or typhoon) | Vertical draft | Extratropical cyclone

Weather forecasting: atmospheric pressure | Low pressure area | High pressure area | dew point | weather front | jet stream | windchill | heat index | Theta-e | primitive equations | Pilot Reports

Storm: thunderstorm | lightning | thunder | hail | tornado | convection | blizzard | supercell

Climate: El Niño | monsoon | flood | drought | Global warming | Effect of sun angle on climate.

Air Pollution: Air pollution dispersion modeling | Compilation of atmospheric dispersion models | Smog

Other phenomena: deposition | dust devil | fog | tide | wind | cloud | air mass | evaporation | sublimation | ice | crepuscular rays | anticrepuscular rays

Weather-related disasters: weather disasters | extreme weather

Climatic or Atmospheric Patterns: Alberta clipper | El Niño | Derecho | Gulf Stream | La Niña | Jet stream | North Atlantic Oscillation | Madden-Julian oscillation | Pacific decadal oscillation | Pineapple Express | Sirocco | Siberian Express | Walker circulation

External links

Please see weather forecasting for weather forecast sites.

Satellite imagery:

Base Reflectivity (Radar):

Meteorology during Solar Eclipse

Template:Meteorological variables Template:Meteorological equipment Template:Met stat Template:Met rem

af:Meteorologie ar:علم الطقس an:Metiorolochía bar:Meteorologie bs:Meteorologija bg:Метеорология ca:Meteorologia cs:Meteorologie cy:Meteoroleg da:Meteorologi de:Meteorologie et:Meteoroloogia el:Μετεωρολογία eo:Meteologio fa:هواشناسی fy:Waarkunde gl:Meteoroloxía ko:기상학 hr:Meteorologija io:Meteorologio id:Meteorologi ia:Meteorologia ie:Meteorologie is:Veðurfræði it:Meteorologia he:מטאורולוגיה lad:Meteorolojiya la:Meteorologia lv:Meteoroloģija lb:Meteorologie lt:Meteorologija li:Meteorologie jbo:timske hu:Meteorológia ms:Meteorologi nl:Meteorologie no:Meteorologi nn:Meteorologi sq:Meteorologjia sk:Meteorológia sl:Meteorologija fi:Meteorologia sv:Meteorologi th:อุตุนิยมวิทยา uk:Метеорологія vec:Meteorołogia wa:Meteyorolodjeye

Template:WS