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The Global Forecast System (GFS) is a global numerical weather prediction system containing a global computer model and variational analysis run by the United States' National Weather Service (NWS).
The mathematical model is run four times a day, and produces forecasts for up to 16 days in advance, but with decreased spatial resolution after 10 days. The forecast skill generally decreases with time (as with any numerical weather prediction model) and for longer term forecasts, only the larger scales retain significant accuracy. It is one of the predominant synoptic scale medium-range models in general use.
The GFS model is a FV3 model with an approximate horizontal resolution of 13 km for the days 0-16 days. In the vertical, the model is divided into 127 layers and extends to the mesopause (roughly ~80 km), and temporally, it produces forecast output every hour for the first 120 hours, [1] three hourly through day 10 and 12 hourly through day 16. The output from the GFS is also used to produce model output statistics.
In addition to the main model, the GFS is also the basis of a lower-resolution 30-member (31, counting the control and operational members) ensemble that runs concurrently with the operational GFS and is available on the same time scales. This ensemble is referred to as the "Global Ensemble Forecast System" (GEFS). The GFS ensemble is combined with Canada's Global Environmental Multiscale Model ensemble to form the North American Ensemble Forecast System (NAEFS).
As with most works of the U.S. government, GFS data is not copyrighted and is available for free in the public domain under provisions of U.S. law. Because of this, the model serves as the basis for the forecasts of numerous private, commercial, and foreign weather companies.
By 2015, the GFS model had fallen behind the accuracy of other global weather models. [2] [3] This was most notable in the GFS model incorrectly predicting Hurricane Sandy turning out to sea until four days before landfall, while the European Centre for Medium-Range Weather Forecasts' model predicted landfall correctly at 7 days. Much of this was suggested to be due to limits in computational resources within the National Weather Service. In response, the NWS purchased new supercomputers, increasing processing power from 776 teraflops to 5.78 petaflops. [4] [5] [6] As of the 12z run on 19 July 2017, the GFS model has been upgraded. Unlike the recently-upgraded ECMWF, the new GFS behaves a bit differently in the tropics and in other regions compared to the previous version. [7] This version accounts more accurately for variables such as the Madden–Julian oscillation and the Saharan Air Layer. In 2018, the processing power was increased again to 8.4 petaflops, [8] The agency also tested a potential replacement model with different mechanics, the flow-following, finite-volume icosahedral model (FIM), in the early 2010s; it abandoned that model around 2016, after it did not show substantial improvement over the GFS.
In 2019, a major upgrade was held for the GFS, converting it from the GSM (Global Spectral Model) to the new FV3 dycore. Horizontal and vertical resolution remained the same but this set the foundation for what is now known as the UFS (Unified Forecast System). On March 22, 2021, the NOAA upgraded the GFS model, coupling it with the WaveWatch III global wave model, which will increase the GFS's resolution from 64 to 127 vertical levels, while extending the WaveWatch III forecasting window from 10 to 16 days. This left some meteorologists hopeful that the GFSv16 upgrade would be enough to close the accuracy gap with the ECMWF's model, which was considered to be the most accurate global weather model at the time. [9] [10]
On June 12, 2019, after several years of testing, NOAA upgraded the GFS with a new dynamical core, the GFDL Finite-Volume Cubed-Sphere Dynamical Core (FV3), which uses the finite volume method instead of the spectral method used by earlier versions of the GFS. The resulting model, initially developed under the name FV3GFS, inherited the GFS moniker, with the legacy GFS continuing to be run until September 2019. [11] [12] Initial testing of the FV3-based GFS showed promise, improving upon the large-scale prediction skill and hurricane track accuracy of the legacy GFS. [13]
With the initial operational implementation of FV3GFS now accomplished, NOAA's Environmental Modeling Center (EMC) global modeling focus has turned towards development of the next GFS (v16) upgrade, which will include doubled vertical resolution (64 to 127 layers), more advanced physics, data assimilation system upgrades, and coupling to a NCEP's Global Wave Model using the Unified Forecast System (UFS) community model. GFSv16 was implemented on March 22, 2021. [14]
On 23 September 2020, the first global UFS application at NCEP was implemented in the Global Ensemble Forecast System (GEFS v12). The components of this upgrade include:
This implementation is the first global-scale coupled system at NCEP, and replaces the previous standalone Global Wave Ensemble and the NEMS GFS Aerosol Component (NGAC) systems. More details can be found at the EMC Model Evaluation Group’s GEFS v12 web site, the EMC GEFS web page, and the EMC GEFS-Aerosol web page.
The European Centre for Medium-Range Weather Forecasts (ECMWF) is an independent intergovernmental organisation supported by most of the nations of Europe. It is based at three sites: Shinfield Park, Reading, United Kingdom; Bologna, Italy; and Bonn, Germany. It operates one of the largest supercomputer complexes in Europe and the world's largest archive of numerical weather prediction data.
The National Weather Service (NWS) is an agency of the United States federal government that is tasked with providing weather forecasts, warnings of hazardous weather, and other weather-related products to organizations and the public for the purposes of protection, safety, and general information. It is a part of the National Oceanic and Atmospheric Administration (NOAA) branch of the Department of Commerce, and is headquartered in Silver Spring, Maryland, within the Washington metropolitan area. The agency was known as the United States Weather Bureau from 1890 until it adopted its current name in 1970.
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 (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.
The Environmental Modeling Center (EMC) is a United States Government agency, which improves numerical weather, marine and climate predictions at the National Centers for Environmental Prediction (NCEP), through a broad program of research in data assimilation and modeling. In support of the NCEP operational forecasting mission, the EMC develops, improves and monitors data assimilation systems and models of the atmosphere, ocean and coupled system, using advanced methods developed internally as well as cooperatively with scientists from universities, NOAA laboratories and other government agencies, and the international scientific community.
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.
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.
In atmospheric science, 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 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, the UK Met Office's Unified Model, which runs out to seven days, and Deutscher Wetterdienst's ICON, which runs out to 7.5 days, it is one of the global medium-range models in general use.
The Hurricane Weather Research and Forecasting (HWRF) model is a specialized version of the weather research and forecasting model and is used to forecast the track and intensity of tropical cyclones. The model was developed by the National Oceanic and Atmospheric Administration (NOAA), the U.S. Naval Research Laboratory, the University of Rhode Island, and Florida State University. It became operational in 2007.
Computational geophysics is the field of study that uses any type of numerical computations to generate and analyze models of complex geophysical systems. It can be considered an extension, or sub-field, of both computational physics and geophysics. In recent years, computational power, data availability, and modelling capabilities have all improved exponentially, making computational geophysics a more populated discipline. Due to the large computational size of many geophysical problems, high-performance computing can be required to handle analysis. Modeling applications of computational geophysics include atmospheric modelling, oceanic modelling, general circulation models, and geological modelling. In addition to modelling, some problems in remote sensing fall within the scope of computational geophysics such as tomography, inverse problems, and 3D reconstruction.
The Unified Model is a numerical weather prediction and climate modeling software suite originally developed by the United Kingdom Met Office, and now both used and further developed by many weather-forecasting agencies around the world. The Unified Model gets its name because a single model is used across a range of both timescales and spatial scales. The models are grid-point based, rather than wave based, and are run on a variety of supercomputers around the world. The Unified Model atmosphere can be coupled to a number of ocean models. At the Met Office it is used for the main suite of Global Model, North Atlantic and Europe model (NAE) and a high-resolution UK model (UKV), in addition to a variety of Crisis Area Models and other models that can be run on demand. Similar Unified Model suites with global and regional domains are used by many other national or military weather agencies around the world for operational forecasting.
The Integrated Forecasting System (IFS) is a global numerical weather prediction system jointly developed and maintained by the European Centre for Medium-Range Weather Forecasts (ECMWF) based in Reading, England, and Météo-France based in Toulouse. The version of the IFS run at ECMWF is often referred to as the "ECMWF" or the "European model" in North America, to distinguish it from the American Global Forecast System.
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 and use 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.
The Rapid Refresh is a numerical weather prediction (NWP) model. The model is designed to provide short-range hourly weather forecasts for North America. The Rapid Refresh was officially made operational on 1 May 2012, replacing the Rapid Update Cycle (RUC). The model also serves as the boundary conditions for the higher-resolution High Resolution Rapid Refresh (HRRR) model, that uses a 3 km (1.9 mi) grid spacing on a domain covering the continental United States.
The Flow-following, finite-volume Icosahedral Model (FIM) is an experimental numerical weather prediction model that was developed at the Earth System Research Laboratory in the United States from 2008 to 2016.
The THORPEX Interactive Grand Global Ensemble (TIGGE) is an implementation of ensemble forecasting for global weather forecasting and is part of THORPEX, an international research programme established in 2003 by the World Meteorological Organization to accelerate improvements in the utility and accuracy of weather forecasts up to two weeks ahead.
The North American Ensemble Forecast System (NAEFS) is a joint project involving the Meteorological Service of Canada (MSC) in Canada, the National Weather Service (NWS) in the United States, and the National Meteorological Service of Mexico (NMSM) in Mexico providing numerical weather prediction ensemble guidance for the 1- to 16-day forecast period. The NAEFS combines the Canadian MSC and the US NWS global ensemble prediction systems, improving probabilistic operational guidance over what can be built from any individual country's ensemble. Model guidance from the NAEFS is incorporated into the forecasts of the respective national agencies.
