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Meteorology, is the study of the atmosphere that focuses on weather
processes and forecasting. 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.

Meteorology, climatology, and atmospheric physics are subsets of the
atmospheric sciences.

History of meteorology

Also refer to the timeline of meteorology

The term meteorology goes back to the book Meteorologica (about 340 BC) by
Aristotle, who combined observations with speculation as to the origin of
celestial phenomena. The greek word meteoron refers to things "high in the
sky", that is between Earth and the realm of the stars, while logos means
"study". A similar work, called "Book of Signs", was published by
Theophrastus, a pupil of Aristotle. It was centered more on predicting the
weather by interpreting established celestial phenomena, such as a halo
around the moon, without asking for explanations.

Further progress in the meteorological field had to wait until accurate
instruments were available. Galileo constructed a thermometer in the 1500s,
followed by Torricelli's invention of the barometer in 1643. The dependence
of atmospheric pressure on height was first shown by Blaise Pascal and Ren
Descartes. The anemometer for measuring wind speed was constructed in 1667
by Robert Hooke, while Horace de Saussure completed this list of the most
important meteorological instruments in 1780 with the hair hygrometer, which
measures humidity.

Other advances that are usually thought of as part of the progression of
physics were Robert Boyle's investigation of the dependence of gas volume on
pressure which lead to thermodynamics and Benjamin Franklin's kite
experiments with lightning.

The first essentially correct explanation of global circulation was the 1735
study by George Hadley about the trade winds, which gave rise to calling the
tropical cell of zonal mean atmospheric circulation "Hadley cell". In 1835,
Gaspard de Coriolis recognized that the rotation of Earth causes a
velocity-dependent force on bodies in the reference frame of a nonrotating Earth.

Synoptic weather observations were still hindered by the difficulty of
establishing certain weather characteristics such as clouds or wind. These
were solved when Luke Howard and Francis Beaufort introduced their systems
for classifying clouds (1803) and wind speeds (1806), respectively. The real
turning point however was the invention of the telegraph in 1843 that
allowed exchange of weather information with unprecedented speed.

Early in the 20th century, theoretical studies of atmospheric phenomena
usually were performed analytically, that is by taking the fluid-dynamical
equations that govern atmosperic flow, simplifying them by neglecting lesser
terms, and looking for solutions to these equations. For example, Vilhelm
Bjerknes developed the model that explains the generation, intensification
and ultimate decay (the lifecycle) of midlatitude cyclones, introducing the
idea of fronts, that is, sharply defined boundaries between air masses.

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
atmosperic lows and highs.

In the 1960s, the chaotic nature of the atmosphere was first understood by
Edward Lorenz, founding the field of chaos theory. The mathematical advances
achieved here later filtered back to meteorology and made it possible to
describe the limits of predictability inherent in atmospheric modelling.
This is known as the butterfly effect, because the growth of disturbances
over time means that even one as minute as the flapping of a butterfly's
wings could much later cause a large disturbance to form somewhere else.

In 1960, the launch of Tiros 1, the first weather satellite marked the
beginning of the age where weather information is availabe 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 Nio.

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 the effects of long-term climate shifts such
as the one caused by human emission of greenhouse gases.

Meteorology and climatology: Some challenges for this century

With the development of powerful new supercomputers like the Earth Simulator
in Japan, numerical modelling of the atmosphere can reach unprecedented
accuracy. This is not only due to the enhanced spatial and temporal
resolution of the grids employed, but also because these more powerful
machines can model the Earth as an integrated climate system, where
atmosphere, ocean, vegetation, and man-made influences depend on each other
realistically. The goal in global meteorological modelling can thus
currently be termed Earth System Modelling, with a growing number of
submodels of various processes coupled to each other. Predictions for global
effects like Global Warming and El Nio are expected to benefit
substantially from these advancements.

Regional models are also becoming more interesting as the resolution of
global models increases and with the observed increase in regional weather
disasters such as the Elbe flooding in 2002 and the European heat wave in
2003. Decisionmakers expect from these models accurate assessments about the
possible increase of these natural hazards in specific regions and
countermeasures (such as dikes or areas that are flooded by purpose to
decrease the flooding somewhere else) that might be effective in preventing
or at least attenuating them.

For models at all scales, increased model resolution means less reliance on
parameterizations , which are empirically derived expressions for processes
that cannot be resolved on the model grid. For example, in mesoscale models
individual clouds can now be resolved removing the need for formulations
that average over a grid box. In global modelling, atmospheric waves such as
gravity waves with short temporal and spatial scales can be represented
without resorting to often overly simplified parameterizations.

With model output approaching oberservational data (e.g. from satellite
soundings) in resolution, the sheer size of the datasets means that data
mining and data management will become equally important considerations in
meteorological computing. In light of the decrease in density of surface and
rawinsonde observations, new algorithms have to be developed to extract
similarly accurate information from satellite data, for example about cloud
type and distribution. Data management will become more global in nature,
with some central archives storing a large number of numerical experiments
from various institutions. This data needs to have a sufficient amount of
metadata attached and can then be conveniently retrieved by a WWW interface
from anywhere. These new archives will alleviate the important task of
comparing experiments conducted with different models, which is instrumental
for their further improvement. Also, grid computing may be a interesting way
to harness the power of meteorological supercomputers more effectively. Of
course, international cooperation is nothing unusual in modelling, but grid
computing might automate the process of running a model where the right
amount of computing resources are currently available and leave scientists
more time for analyzing the results.

Meteorological instrumentation that is used at the surface or in airplanes
also has room for improvement. Radar and Lidar show precipitation and clouds
by their effects on emitted monospectral electromagnetic waves. If radar
measurements can be used to accurately determine the amount of precipitation
(which as of now is only possible with rain gauges), this would be
beneficial for numerical weather prediction. Lidar can be used to study
clouds that are so thin that they cannot be seen by the naked eye such as
certain types of cirrus filaments. The high-altitude clouds that can form
from contrails may well be the key to understanding the effect of the
increasing amount of air travel on global warming.

Aside from weather and climate prediction, weather modification has been
(often covertly) attempted sinces the 1950s---often by the military, but
also at airports. But even without consideration of anecdotal evidence of
trying to use weather modification as a "weapon" (such as the supposed cloud
seeding by US troops during the Vietnam conflict), it is clear that
unilateral weather modification may lead to political tensions. Especially
in the Middle East, the possibility of wars about water supply looms for
this century. While many of the proposed systems for modification of the
water cycle belong more to the domain of engineering than to meteorology, it
is clear that meteorology may take on additional political dimensions beyond
the battle between Europe and the US over the throttling of greenhouse gas emission.

Finally, meteorologists must educate the public more about weather and
climate in general. Scientifically accurate and understandable information
about topics like the ozone hole, global warming, the effects of rainforest
deforestation, or sea level rise must be disseminated and misinformation by
industry lobbyists be countered. Particularly in Europe, which may see an
increase in extreme weather events as it already has in the 1990s, the
population must be educated to pay closer attention to severe weather
warnings or information about other detrimental health factors such as high
tropospheric ozone concentration or high levels of UV radiation. Similarly,
a better infrastructure to deal with natural desasters must be developed
akin to similar services in the US. It is clear that political
decisionmakers in Europe will rely on scientific assessment to validate the
necessity for such spending.
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