Prognostic chart

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A prognostic chart is a map displaying the likely weather forecast for a future time. Such charts generated by atmospheric models as output from numerical weather prediction and contain a variety of information such as temperature, wind, precipitation and weather fronts. They can also indicate derived atmospheric fields such as vorticity, stability indices,[ clarification needed ] or frontogenesis. Forecast errors need to be taken into account and can be determined either via absolute error, or by considering persistence and absolute error combined.[ clarification needed ]

Contents

Definition

The forecast map showing the state of the atmosphere at a future time is called a prognostic chart. Prognostic charts generated by computer models are sometimes referred to as machine-made forecasts. [1]

Variety

Surface weather prognostic charts for mariners indicate the positions of high and low pressure areas, as well as frontal zones, up to five days into the future. Surface wind direction and speed is also forecast on this type of chart. Wave prognostic charts show the expected sea state at some future time. [2] Low-level prognostic charts used by aviators show the forecast between the Earth's surface and 24,000 feet (7,300 m) above sea level over the next two days. They show areas where visual flight rules are in effect, instrument flight rules are in effect, the height of the freezing level, the location of weather features, and areas of moderate to severe turbulence. [3] Prognostic charts can be made of isentropic surfaces (along a certain potential temperature surface determined in kelvins) in regards to moisture advection, mean temperatures at the surface, mean sea level pressures, and precipitation either for a single day or multiple days. [4] For purposes of severe weather, prognostic charts can be issued to depict current weather watches, convective outlooks for thunderstorms multiple days into the future, and fire weather outlooks. [5]

Manual

A manual prognostic chart of the weather in the United States 36 hours into the future Manualfcst36hrs.gif
A manual prognostic chart of the weather in the United States 36 hours into the future

Manual prognostic charts depict tropical cyclones, turbulence, weather fronts, rain and snow areas, precipitation type and coverage indicators, as well as centers of high and low pressure. [6] Within the United States, these type of maps are generated by the Hydrometeorological Prediction Center, [7] the Storm Prediction Center, [5] the Ocean Prediction Center, [8] and the National Hurricane Center. The Aviation Weather Center re-sends these maps, and also generates specialized maps for aviation. [9]

Automated

An automated prognostic chart of the 96-hour forecast of 850 mbar geopotential height and temperature from the Global Forecast System GFS 850 MB.PNG
An automated prognostic chart of the 96-hour forecast of 850 mbar geopotential height and temperature from the Global Forecast System

Atmospheric models are computer programs that produce meteorological information, including prognostic charts, for future times at given locations and altitudes. [10] Within any modern model is a set of equations, known as the primitive equations, used to predict the future state of the atmosphere. [11] These equations—along with the ideal gas law—are used to evolve the density, pressure, and potential temperature scalar fields and the velocity vector field of the atmosphere through time. Additional transport equations for pollutants and other aerosols are included in some primitive-equation mesoscale models as well. [12] These equations are initialized from the analysis data and rates of change are determined. These rates of change predict the state of the atmosphere a short time into the future; the time increment for this prediction is called a time step. This time stepping is repeated until the solution reaches the desired forecast time. [13] Time steps for global models are on the order of tens of minutes, [14] while time steps for regional models are between one and four minutes. [15] The global models are run outwards to varying times into the future. The UKMET Unified Model is run six days into the future, [16] the European Centre for Medium-Range Weather Forecasts model is run out to 10 days into the future, [17] while the Global Forecast System model run by the Environmental Modeling Center is run 16 days into the future. [18]

Verification

Around 1950, a good surface prognostic chart was considered to be one whose isobars were in the correct location. [19] By 1957, it was proposed when isobars or height lines at the 500 hectopascals (15 inHg) pressure level in the atmosphere were being verified, that the degree of persistence should be considered so as to avoid getting bad forecasts for slow moving systems too much credit. [20]

See also

Related Research Articles

<span class="mw-page-title-main">Meteorology</span> Interdisciplinary scientific study of the atmosphere focusing on weather forecasting

Meteorology is a branch of the atmospheric sciences with a major focus on weather forecasting. The study of meteorology dates back millennia, though significant progress in meteorology did not begin until the 18th century. The 19th century saw modest progress in the field after weather observation networks were formed across broad regions. Prior attempts at prediction of weather depended on historical data. It was not until after the elucidation of the laws of physics and more particularly, the development of the computer, allowing for the automated solution of a great many equations that model the weather, in the latter half of the 20th century that significant breakthroughs in weather forecasting were achieved. An important branch of weather forecasting is marine weather forecasting as it relates to maritime and coastal safety, in which weather effects also include atmospheric interactions with large bodies of water.

Weather Short-term state of the atmosphere

Weather is the state of the atmosphere, describing for example the degree to which it is hot or cold, wet or dry, calm or stormy, clear or cloudy. On Earth, most weather phenomena occur in the lowest layer of the planet's atmosphere, the troposphere, just below the stratosphere. Weather refers to day-to-day temperature, precipitation, and other atmospheric conditions, whereas climate is the term for the averaging of atmospheric conditions over longer periods of time. When used without qualification, "weather" is generally understood to mean the weather of Earth.

Weather forecasting Science and technology application

Weather forecasting is the application of science and technology to predict the conditions of the atmosphere for a given location and time. People have attempted to predict the weather informally for millennia and formally since the 19th century. Weather forecasts are made by collecting quantitative data about the current state of the atmosphere, land, and ocean and using meteorology to project how the atmosphere will change at a given place.

General circulation model Type of climate model

A general circulation model (GCM) is a type of climate model. It employs a mathematical model of the general circulation of a planetary atmosphere or ocean. It uses the Navier–Stokes equations on a rotating sphere with thermodynamic terms for various energy sources. These equations are the basis for computer programs used to simulate the Earth's atmosphere or oceans. Atmospheric and oceanic GCMs are key components along with sea ice and land-surface components.

Weather map Table of weather elements

A weather map, also known as synoptic weather chart, displays various meteorological features across a particular area at a particular point in time and has various symbols which all have specific meanings. Such maps have been in use since the mid-19th century and are used for research and weather forecasting purposes. Maps using isotherms show temperature gradients, which can help locate weather fronts. Isotach maps, analyzing lines of equal wind speed, on a constant pressure surface of 300 or 250 hPa show where the jet stream is located. Use of constant pressure charts at the 700 and 500 hPa level can indicate tropical cyclone motion. Two-dimensional streamlines based on wind speeds at various levels show areas of convergence and divergence in the wind field, which are helpful in determining the location of features within the wind pattern. A popular type of surface weather map is the surface weather analysis, which plots isobars to depict areas of high pressure and low pressure. Cloud codes are translated into symbols and plotted on these maps along with other meteorological data that are included in synoptic reports sent by professionally trained observers.

Weather Prediction Center United States weather agency

The Weather Prediction Center (WPC), located in College Park, Maryland, is one of nine service centers under the umbrella of the National Centers for Environmental Prediction (NCEP), a part of the National Weather Service (NWS), which in turn is part of the National Oceanic and Atmospheric Administration (NOAA) of the U.S. Government. Until March 5, 2013 the Weather Prediction Center was known as the Hydrometeorological Prediction Center (HPC). The Weather Prediction Center serves as a center for quantitative precipitation forecasting, medium range forecasting, and the interpretation of numerical weather prediction computer models.

Numerical weather prediction Weather prediction using mathematical models of the atmosphere and oceans

Numerical weather prediction (NWP) uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. Though first attempted in the 1920s, it was not until the advent of computer simulation in the 1950s that numerical weather predictions produced realistic results. A number of global and regional forecast models are run in different countries worldwide, using current weather observations relayed from radiosondes, weather satellites and other observing systems as inputs.

Index of meteorology articles

This is a list of meteorology topics. The terms relate to meteorology, the interdisciplinary scientific study of the atmosphere that focuses on weather processes and forecasting.

Ensemble forecasting

Ensemble forecasting is a method used in or within numerical weather prediction. Instead of making a single forecast of the most likely weather, a set of forecasts is produced. This set of forecasts aims to give an indication of the range of possible future states of the atmosphere. Ensemble forecasting is a form of Monte Carlo analysis. The multiple simulations are conducted to account for the two usual sources of uncertainty in forecast models: (1) the errors introduced by the use of imperfect initial conditions, amplified by the chaotic nature of the evolution equations of the atmosphere, which is often referred to as sensitive dependence on initial conditions; and (2) errors introduced because of imperfections in the model formulation, such as the approximate mathematical methods to solve the equations. Ideally, the verified future atmospheric state should fall within the predicted ensemble spread, and the amount of spread should be related to the uncertainty (error) of the forecast. In general, this approach can be used to make probabilistic forecasts of any dynamical system, and not just for weather prediction.

Tropical cyclone forecast model Computer program that uses meteorological data to forecast tropical cyclones

A tropical cyclone forecast model is a computer program that uses meteorological data to forecast aspects of the future state of tropical cyclones. There are three types of models: statistical, dynamical, or combined statistical-dynamic. Dynamical models utilize powerful supercomputers with sophisticated mathematical modeling software and meteorological data to calculate future weather conditions. Statistical models forecast the evolution of a tropical cyclone in a simpler manner, by extrapolating from historical datasets, and thus can be run quickly on platforms such as personal computers. Statistical-dynamical models use aspects of both types of forecasting. Four primary types of forecasts exist for tropical cyclones: track, intensity, storm surge, and rainfall. Dynamical models were not developed until the 1970s and the 1980s, with earlier efforts focused on the storm surge problem.

Atmospheric model

An atmospheric model is a mathematical model constructed around the full set of primitive dynamical equations which govern atmospheric motions. It can supplement these equations with parameterizations for turbulent diffusion, radiation, moist processes, heat exchange, soil, vegetation, surface water, the kinematic effects of terrain, and convection. Most atmospheric models are numerical, i.e. they discretize equations of motion. They can predict microscale phenomena such as tornadoes and boundary layer eddies, sub-microscale turbulent flow over buildings, as well as synoptic and global flows. The horizontal domain of a model is either global, covering the entire Earth, or regional (limited-area), covering only part of the Earth. The different types of models run are thermotropic, barotropic, hydrostatic, and nonhydrostatic. Some of the model types make assumptions about the atmosphere which lengthens the time steps used and increases computational speed.

The National Atmospheric Release Advisory Center (NARAC) is located at the University of California's Lawrence Livermore National Laboratory. It is a national support and resource center for planning, real-time assessment, emergency response, and detailed studies of incidents involving a wide variety of hazards, including nuclear, radiological, chemical, biological, and natural emissions.

The Mars Regional Atmospheric Modeling System (MRAMS) is a computer program that simulates the circulations of the Martian atmosphere at regional and local scales. MRAMS, developed by Scot Rafkin and Timothy Michaels, is derived from the Regional Atmospheric Modeling System (RAMS) developed by William R. Cotton and Roger A. Pielke to study atmospheric circulations on the Earth.

Weather Research and Forecasting Model

The Weather Research and Forecasting (WRF) Model is a numerical weather prediction (NWP) system designed to serve both atmospheric research and operational forecasting needs. NWP refers to the simulation and prediction of the atmosphere with a computer model, and WRF is a set of software for this. WRF features two dynamical (computational) cores, a data assimilation system, and a software architecture allowing for parallel computation and system extensibility. The model serves a wide range of meteorological applications across scales ranging from meters to thousands of kilometers.

In weather forecasting, model output statistics (MOS) is a multiple linear regression technique in which predictands, often near-surface quantities, are related statistically to one or more predictors. The predictors are typically forecasts from a numerical weather prediction (NWP) model, climatic data, and, if applicable, recent surface observations. Thus, output from NWP models can be transformed by the MOS technique into sensible weather parameters that are familiar to a layperson.

The Global Environmental Multiscale Model (GEM), often known as the CMC model in North America, is an integrated forecasting and data assimilation system developed in the Recherche en Prévision Numérique (RPN), Meteorological Research Branch (MRB), and the Canadian Meteorological Centre (CMC). Along with the NWS's Global Forecast System (GFS), which runs out to 16 days, the ECMWF's Integrated Forecast System (IFS), which runs out 10 days, the Naval Research Laboratory Navy Global Environmental Model (NAVGEM), which runs out eight days, and the UK Met Office's Unified Model, which runs out to six days, it is one of the five predominant synoptic scale medium-range models in general use.

Outline of meteorology Overview of and topical guide to meteorology

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History of numerical weather prediction Aspect of meteorological history

The history of numerical weather prediction considers how current weather conditions as input into mathematical models of the atmosphere and oceans to predict the weather and future sea state has changed over the years. Though first attempted manually in the 1920s, it was not until the advent of the computer and computer simulation that computation time was reduced to less than the forecast period itself. ENIAC was used to create the first forecasts via computer in 1950, and over the years more powerful computers have been used to increase the size of initial datasets as well as include more complicated versions of the equations of motion. The development of global forecasting models led to the first climate models. The development of limited area (regional) models facilitated advances in forecasting the tracks of tropical cyclone as well as air quality in the 1970s and 1980s.

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<span class="mw-page-title-main">Marine weather forecasting</span> Forecasts of weather conditions at sea

Marine weather forecasting is the process by which mariners and meteorological organizations attempt to forecast future weather conditions over the Earth's oceans. Mariners have had rules of thumb regarding the navigation around tropical cyclones for many years, dividing a storm into halves and sailing through the normally weaker and more navigable half of their circulation. Marine weather forecasts by various weather organizations can be traced back to the sinking of the Royal Charter in 1859 and the RMS Titanic in 1912.

References

  1. ↑ Ahrens, C. Donald (2008). Essentials of meteorology: an invitation to the atmosphere. Cengage Learning. p. 244. ISBN   978-0-495-11558-8.
  2. ↑ Kotsch, William J. (1983). Weather For th Mariner. Naval Institute Press. pp. 236–239. ISBN   978-0-87021-756-2.
  3. ↑ United States Naval Air Training Command (April 2003). Aviation Weather Student Guide (PDF). Corpus Christi, Texas Naval Air Station. pp. 2–5, 2–6. Retrieved 2011-02-26.
  4. ↑ United States Department of Agriculture (1941). Climate and Man: Part Two. The Minerva Group, Inc. pp. 647–651. ISBN   978-1-4102-1539-0.
  5. 1 2 Storm Prediction Center (2011). "Forecast Products". National Centers for Environmental Prediction . Retrieved 2011-02-27.
  6. ↑ Federal Aviation Administration (2007). Gliding Flyer Handbook. Skyhorse Publishing, Inc. pp. 9–30, 9–31. ISBN   978-1-60239-061-4.
  7. ↑ Hydrometeorological Prediction Center (2011). "Short Range Forecasts". National Centers for Environmental Prediction . Retrieved 2011-02-26.
  8. ↑ Ocean Prediction Center (2011), Atlantic Offshore, National Centers for Environmental Prediction
  9. ↑ Aviation Weather Center (2011). "Analysis and forecast surface conditions (prog charts)". National Centers for Environmental Prediction . Retrieved 2011-02-26.
  10. ↑ Ahrens, C. Donald (2008). Essentials of meteorology: an invitation to the atmosphere. Cengage Learning. p. 244. ISBN   978-0-495-11558-8.
  11. ↑ Pielke, Roger A. (2002). Mesoscale Meteorological Modeling . Academic Press. pp.  48–49. ISBN   0-12-554766-8.
  12. ↑ Pielke, Roger A. (2002). Mesoscale Meteorological Modeling . Academic Press. pp.  18–19. ISBN   0-12-554766-8.
  13. ↑ Pielke, Roger A. (2002). Mesoscale Meteorological Modeling . Academic Press. pp.  285–287. ISBN   0-12-554766-8.
  14. ↑ Sunderam, V. S.; van Albada, G. Dick; Peter, M. A.; Sloot, J. J. Dongarra (2005). Computational Science – ICCS 2005: 5th International Conference, Atlanta, GA, USA, May 22–25, 2005, Proceedings, Part 1. Springer. p. 132. ISBN   978-3-540-26032-5.
  15. ↑ Zwieflhofer, Walter; Kreitz, Norbert; European Centre for Medium Range Weather Forecasts (2001). Developments in teracomputing: proceedings of the ninth ECMWF Workshop on the Use of High Performance Computing in Meteorology. World Scientific. p. 276. ISBN   978-981-02-4761-4.
  16. ↑ Chan, Johnny C. L. & Jeffrey D. Kepert (2010). Global Perspectives on Tropical Cyclones: From Science to Mitigation. World Scientific. pp. 295–296. ISBN   978-981-4293-47-1.
  17. ↑ Holton, James R. (2004). An introduction to dynamic meteorology, Volume 1. Academic Press. p. 480. ISBN   978-0-12-354015-7.
  18. ↑ Brown, Molly E. (2008). Famine early warning systems and remote sensing data. Springer. p. 121. ISBN   978-3-540-75367-4.
  19. ↑ Eugenia Kalnay (2003). Atmospheric Modeling, Data Assimilation and Predictability (PDF). Cambridge University Press. p. 7. ISBN   0-521-79179-0 . Retrieved 2011-02-27.
  20. ↑ Sverre Petterssen (1957). "A Note on Verification of Prognostic Charts". Tellus A. 9 (3): 314. doi:10.1111/j.2153-3490.1957.tb01887.x.
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