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Weather forecasting is the application of current technology and science to predict the state of the atmosphere for a future time and a given location. The history of weather forecasting goes back millennia, however the techniques used have changed significantly since then. Today, 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. History of weather forecasting Many people's livelihoods and indeed lives are strongly influenced by the weather. For millennia people have tried to predict what the weather would be like a day or a season in advance. In 650 BC, the Babylonians predicted the weather from cloud patterns. In about 340 BC, Aristotle described weather patterns in Meteorologica. The Chinese were predicting weather at least as far back as 300 BC. Ancient methods of weather forecasting usually relied on experience to spot patterns of events. For example, they noticed that if the sunset gave a particularly red sky, then the following day brought fair weather. This experience accumulated over the generations to produce weather lore. However, not all of these predictions prove reliable and many of them have since been found not to stand up to rigorous statistical testing. It was not until the invention of the telegraph in 1837 that the modern age of weather forecasting began. Before this time, it had not been possible to transport information about the current state of the weather any faster than a steam train, however the telegraph allowed reports of weather conditions from a wide area to be received almost instantaneously. This allowed forecasts to be made by knowing what the weather conditions were like further upwind. The two men most credited with the birth of forecasting as a science were Francis Beaufort (remembered chiefly for the Beaufort scale) and his protégé Robert Fitzroy (developer of the Fitzroy Barometer). Both were influential men in British Naval and Governmental circles, and though ridiculed in the press at the time, their work gained scientific credence, was accepted by the British Navy and formed the basis for all of today's weather forecasting knowledge. Great progress was made in the science of meteorology during the 20th century which allowed understanding of atmospheric processes. The idea of numerical weather prediction (NWP) was presented by Lewis Fry Richardson in 1922. However, computers fast enough to complete the vast number of calculations required to produce a forecast before the event had occurred did not exist at that time. It was not until the 1970’s that NWP became operational in forecasting agencies across the world. Modern day weather forecasting system A modern day weather forecasting system consists of five components: Data collection 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. The World Meteorological Organization acts to standardize the instrumentation, observing practices and timing of these observations worldwide. Stations either report hourly in METAR reports, or every six hours in SYNOP reports. Additionally, information about the temperature, humidity and wind above the surface are found by launching a radiosonde (weather balloon). Data up to the tropopause are usually transmitted to the surface. Increasingly, data from weather satellites are being used due to their (almost) global coverage. Although their visible light images are very useful for forecasters to see development of clouds, little of this information can be used by numerical weather prediction models. The infra-red (IR) data however can be used as it gives information on the temperature at the surface and cloud tops. Individual clouds can also be tracked from one time to the next to provide information on wind direction and strength at the clouds steering level. Polar orbiting satellites provide soundings of temperature and moisture throughout the depth of the atmosphere. Compared with similar data from radiosondes, the satellite data has the advantage that coverage is global, however the accuracy and resolution is not as good. Meteorological radar provide information on precipitation location and intensity. Additionally, if doppler radar are used then wind speed and direction can be determined. Data assimilation Main article Data assimilation 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 (since this contains information from previous observations) to produce the meteorological analysis. This is the best estimate of the current state of the atmosphere. It is a three dimensional representation of the distribution of temperature, moisture and wind. Numerical weather prediction (NWP) 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. Model output post processing The raw output is often modified before being presented as the forecast. This can be in the form of statistical techniques to remove known biases in the model, or of adjustment to take into account consensus among other numerical weather forecasts.. In the past, the human forecaster used to be responsible for generating the entire weather forecast from the observations. However today, for forecasts beyond 24hrs human input is generally confined to post-processing of model data to add value to the forecast. Humans are required to interpret the model data into weather forecasts that are understandable to the end user. Additionally, humans can use knowledge of local effects which may be too small in size to be resolved by the model to add information to the forecast. Increasing accuracy of forecast models continues to decrease the need for post-processing and human input, mostly in areas with a low variation in terrain. Presentation of weather forecasts The final stage in the forecasting process is perhaps the most important. Knowledge of what the end user needs from a weather forecast must be taken into account to present the information in a useful and understandable way. Public information
Air traffic The aviation industry is especially sensitive to the weather. Fog and/or exceptionally low ceilings can prevent many aircraft landing and taking off. Similarly, turbulence and icing can be hazards whilst in flight. Thunderstorms are a problem for all aircraft, due to severe turbulence and icing, as well as large hail, strong winds, and lightning, all of which can cause fatal damage to an aircraft in flight. On a day to day basis airliners are routed to take advantage of the jet stream tailwind to improve fuel efficiency. Air crews are briefed prior to take off on the conditions to expect en route and at their destination. Marine Commercial and recreational use of waterways can be limited significantly by weather in that wind direction and speed, wave periodicity and heights, tides, and precipitation can each influence the safety of marine transit. Consequently, a variety of codes have been established to efficiently transmit detailed marine weather forecasts to vessel pilots via radio, for example the MAFOR (marine forecast). Utility companies Electricity and gas companies rely on weather forecasts to anticipate demand which can be strongly affected by the weather. In winter, severe cold weather can cause a surge in demand as people turn up their heating. Similarly, in summer a surge in demand can be linked with the increased use of air conditioning systems in hot weather. By anticipating a surge in demand, utility companies can purchase additional supplies of power or natural gas before the price increases, or in some circumstances, supplies are restricted. Private sector Increasingly, private companies pay for weather forecasts tailored to their needs so that they can increase their profits or to avoid large losses. For example, supermarket chains may change the stocks on their shelves in anticipation of different consumer spending habits in different weather conditions. State Deptartments of Transportation and private road maintenance companies also use their forecasts to demonstrate a 'best effort' in defending against lawsuits as a result of traffic accidents. Military applications Similarly to the private sector, Military weather forecasters present weather conditions to the war fighter community. Equally provide pre-flight weather briefs and flight weather briefs from take off to terminal location. Including updates throughout the flight path. Also, military weather forecasters provide real time resource protection services for military installations, not covered by the National Weather Service. Three military branches have independent weather forecasting techniques tailored for their specific needs. For example, Naval Forecasters cover the waters and ship weather forecasts; Air Force Forecasters cover air operations in both wartime and peacetime operations and provide Army support; Coast Guard Forecasters provide ship forecasts for ice breakers and other various operations within their realm; And Marine Forecasters forecast for their troops and local aviation assets. There is a silent cooperative agreement between civilian forecasters and military forecasters, both working in unison for the improvement of weather forecasting in general. Ensemble forecasting Although a forecast model will predict realistic looking weather features evolving realistically into the distant future, the errors in a forecast will inevitably grow with time due to the chaotic nature of the atmosphere. The detail that can be given in a forecast therefore decreases with time as these errors increase. There becomes a point when the errors are so large that the forecast is completely wrong and the forecast atmospheric state has no correlation with the actual state of the atmosphere. However, looking at a single forecast gives no indication of how likely that forecast is to be correct. Ensemble forecasting uses lots of forecasts produced to reflect the uncertainty in the initial state of the atmosphere (due to errors in the observations and insufficient sampling). The uncertainty in the forecast can then be assessed by the range of different forecasts produced. They have been shown to be better at detecting the possibility of extreme events at long range. Ensemble forecasts are increasingly being used for operational weather forecasting (for example at ECMWF, NCEP, and the Canadian forecasting center). Nowcasting The forecasting of the weather in the 0-6 hour timeframe is often referred to as nowcasting. It is in this range that the human forecaster still has an advantage over computer NWP models. In this time range it is possible to forecast smaller features such as individual shower clouds with reasonable accuracy, however these are often too small to be resolved by a computer model. A human given the latest radar, satellite and observational data will be able to make a better analysis of the small scale features present and so will be able to make a more accurate forecast for the following few hours. Below is a sample nowcast, issued by the National Weather Service in Mount Holly, New Jersey: 000 FPUS71 KPHI 240805 NOWPHI SHORT TERM FORECAST NATIONAL WEATHER SERVICE MOUNT HOLLY NJ 405 AM EDT FRI JUN 24 2005 DEZ002>004-MDZ015-019-020-NJZ013-014-020-022>027-241200- ATLANTIC NJ-ATLANTIC COASTAL CAPE MAY NJ-CAPE MAY NJ-CAROLINE MD- COASTAL ATLANTIC NJ-COASTAL OCEAN NJ-DELAWARE BEACHES DE- EASTERN MONMOUTH NJ-INLAND SUSSEX DE-KENT DE-OCEAN NJ- QUEEN ANNE'S MD-SOUTHEASTERN BURLINGTON NJ-TALBOT MD- WESTERN MONMOUTH NJ- INCLUDING THE CITIES OF...ATLANTIC CITY AND DOVER 405 AM EDT FRI JUN 24 2005 .NOW... AREAS OF FOG AND LOW CLOUDS WILL BE OVER SOUTHERN DELAWARE AND PORTIONS OF THE NORTHEASTERN MARYLAND SHORE EARLY THIS MORNING, AS WELL AS ALONG THE NEW JERSEY COAST. THE PATCHY DENSE FOG MAY REDUCE THE VISIBILITY TO A QUARTER MILE OR LESS AT TIMES. IF YOU WILL BE DRIVING THIS MORNING, BE SURE TO LEAVE PLENTY OF ROOM BETWEEN YOUR VEHICLE AND THE ONE AHEAD OF YOU. YOUR VISIBILITY COULD DROP QUICKLY IF YOU DRIVE INTO A DENSE PATCH OF FOG. WATCH ESPECIALLY FOR PEDESTRIANS. THE FOG SHOULD DISSIPATE AN HOUR OR TWO AFTER SUNRISE. $$ Punctuation Written weather forecasts use an idiosyncratic punctuation style, employing heavy use of three-dot ellipses (e.g.: "light rain...strengthening through the night"). It takes the place of a comma and is derived from legacy computer systems (some of which are still active), which did not include a comma in their character sets. Meteorological agencies These are academic or governmental meteorology organizations. Most provide at least a limited forecast for their area of interest on their website. Commercial organisations These are high profile commercial sites of varying quality. Most of these companies get their forecasts from the same source, namely the NOAA's GFS model. See also | |||||||||
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