HIRLAM

HIRLAM, the High Resolution Limited Area Model, is a weather forecast computer model used and developed by a few European countries.

External links

- [http://hirlam.knmi.nl/ HIRLAM homepage]

Weather forecast

Weatherman redirects here. If you're looking for the Weather Underground Organization, see Weatherman (organization). Weather forecasting is the science (or as some argue, the art) of predicting the state of the atmosphere for a future time and 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 peoples livelihoods and indeed lives are strongly influenced by the weather. In the past, this was probably more true than it is today. 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 protegé 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, 1970’s that NWP became operational in forecasting agencies across the world. Lewis Fry Richardson presenting a weather report.]] =Modern day weather forecasting system= A modern day weather forecasting system consists of five components:
- Data collection
- Data assimilation
- Numerical weather prediction
- Model output post-processing
- Forecast presentation to end-user

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 is 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

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. However, the increasing accuracy of forecast models continues to decrease the need for post-processing and human input. Examples of weather model data can be found on Vigilant Weather's Model Pulse.

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

One of the main end users of a forecast is the general public. Thunderstorms can cause strong winds, dangerous lightning strikes leading to power outages, and widespread hail damage. Heavy snow or rain can bring transportation and commerce to a stand-still, as well as cause flooding in low-lying areas. Excessive heat or cold waves can kill or sicken those without adequate utilities. The National Weather Service provides forecasts and watches/warnings/advisories for all areas of the United States to protect life and property and maintain commercial interests. Traditionally, television and radio weather presenters have been the main method of informing the public, however increasingly the internet is being used due to the vast amount of information that can be found.

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.

Utility companies

Electricity 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.

Private sector

Increasingly, private companies pay for weather forecasts tailored to their needs so that they can increase their profits. For example, supermarket chains may change the stocks on their shelves in anticipation of different consumer spending habits in different weather conditions. =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 forecasted 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. $$ =Grammar= Weather forecasting uses an esoteric grammatic style, employing heavy use of 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. =Websites providing forecasts=

Meteorological agencies

- [http://www.noaa.gov/wx.html NOAA weather page]
- :[http://www.goes.noaa.gov/ NOAA satellite images]
- :[http://www.nws.noaa.gov/ National Weather Service]
- [http://www.metoffice.gov.uk/ The Met Office of the UK]
- :[http://www.bbc.co.uk/weather BBC Weather Centre]
- [http://www.ecmwf.int/ European Centre for Medium Range Weather Forecasting (ECMWF)]
- [http://weatheroffice.ec.gc.ca/canada_e.html Environment Canada Weather Office]
- [http://www.bom.gov.au Australian Bureau of Meteorology]
- [http://www.metservice.com New Zealand MetService]
- [http://www.meteoswiss.ch/en/index.shtml Meteo Suisse (Swiss Weather Agency, in English]
- Afghanistan Meteorological Authority
- [http://www.fmi.fi Finnish Meteorological Institute]
- [http://www.inm.es/ Instituto Nacional de Meteorología. INM]

Commercial organisations

- [http://www.weather.com/ Weather Channel]
- [http://www.weather.co.uk/ Weather Channel UK]
- [http://www.weather.com.au/ Australian Weather]
- [http://www.wunderground.com/ Weather Underground] =See also=
- Meteorology
- Weather
- Weather control
- TV Nova
- National Collegiate Weather Forecasting Competition
- AccuWeather Category:Meteorology Category:Weather Category:Broadcasting ja:天気予報

Brownsboro Farm, Kentucky

Brownsboro Farm esas urbo en Jefferson Komtio, Kentucky. Segun la 2000 kontado, la urbo havis tota populo di 676.

Geografio

Brownsboro Farm jacas a . Segun la Usana Kontado Ministerio, la urbo havas tota areo di 0.4 km² (0.2 mi²). 0.4 km² (0.2 mi²) di qua esas lando e nulo kovresas per aquo.

Demografio

Segun la kontado di 2000 esas 676 homi, 235 hemanari, e 211 familii qui rezidas en la urbo. La lojanto-denseso esas 1,535.3/km² (3,944.6/mi²). Esas 240 domi kun mezala denseso di 545.1/km² (1,400.5/mi²). La rasi en la urbo inkludas 96.30% Blanka, 0.59% Black or African American, 0.44% Indijena amerikana, 1.04% Aziana, 0.00% Pacifika Insulana, 0.59% de altra rasi, e 1.04% de du o plu rasi. 0.89% de la populo esas Hispana o Latina de irga raso. Esas 235 heminari di qua 37.9% havas pueri sub la evo di 18 en la domo, 79.6% esas mariajita e habitas kune, 8.9% havas homina domo-maestro sen spozulo, e 10.2% esas ne-familii. 8.5% de omna hemanari facesas ek individui e 6.4% havas ulu qua habitas sole qua evas 65 yari o plu evoza. La mezala grandeso di hemanari esas 2.88 e la mezala grandeso di familii esas 3.03. La nombro di lojanti e lia evi esas: 27.7% sub la evo di 18, 4.6% de 18 til 24, 21.3% de 25 til 44, 30.5% de 45 til 64, e 16.0% qui evas 65 yari o plus. La mezala evo esas 43 yari. Po 100 homini esas 93.1 homuli. Po 100 homini 18 yari o plus esas 88.1 homuli. La mezala revenuo di hemanaro en la urbo esas $76,445, e la mezala revenuo por familio esas $80,000. Homuli havas mezala revenuo di $52,396 kontre $37,143 por homini. La revenuo per capita por la urbo esas $30,807. 0.6% de la populo e 0.0% de familii esas sub la povreso-lineo. Ek la tota populo, 0.0% di qui sub la evo di 18 e 0.0% de ti qui evas 65 o plus habitas sub la povreso-lineo. Category:Urbi en Kentucky Category:Jefferson Komtio, Kentucky

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