Regional Atmospheric Modeling System

Last updated

The Regional Atmospheric Modeling System (RAMS) is a set of computer programs that simulate the atmosphere for weather and climate research and for numerical weather prediction (NWP). Other components include a data analysis and a visualization package. [1]

Contents

RAMS was developed in the 1980s at Colorado State University (CSU), spearheaded by William R. Cotton and Roger A. Pielke, for mesoscale meteorological modeling. Subsequent development is primarily done by Robert L. Walko and Craig J. Tremback under the supervision of Cotton and Pielke. It is a comprehensive non-hydrostatic model. It is written primarily in Fortran with some C code and it runs best under the Unix operating system. [2] Version 6 was released in 2009. [3]

RAMS is the basis for a system simulating the Martian atmosphere that is named MRAMS. [4]

See also

Related Research Articles

Meteorology 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.

Climate model Quantitative methods used to simulate climate

Numerical climate models use quantitative methods to simulate the interactions of the important drivers of climate, including atmosphere, oceans, land surface and ice. They are used for a variety of purposes from study of the dynamics of the climate system to projections of future climate. Climate models may also be qualitative models and also narratives, largely descriptive, of possible futures.

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.

Richard Siegmund Lindzen is an American atmospheric physicist known for his work in the dynamics of the middle atmosphere, atmospheric tides, and ozone photochemistry. He has published more than 200 scientific papers and books. From 1983 until his retirement in 2013, he was Alfred P. Sloan Professor of Meteorology at the Massachusetts Institute of Technology. He was a lead author of Chapter 7, "Physical Climate Processes and Feedbacks," of the Intergovernmental Panel on Climate Change's Third Assessment Report on climate change. He has disputed the scientific consensus on climate change.

Roger A. Pielke

Roger A. Pielke Sr. is an American meteorologist with interests in climate variability and climate change, environmental vulnerability, numerical modeling, atmospheric dynamics, land/ocean – atmosphere interactions, and large eddy/turbulent boundary layer modeling. He particularly focuses on mesoscale weather and climate processes but also investigates on the global, regional, and microscale. Pielke is an ISI Highly Cited Researcher.

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.

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 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.

Syukuro Manabe

Syukuro "Suki" Manabe is a Japanese-American meteorologist and climatologist who pioneered the use of computers to simulate global climate change and natural climate variations. He was awarded the 2021 Nobel Prize in Physics jointly with Klaus Hasselmann and Giorgio Parisi for groundbreaking contributions to the "physical modeling of earth's climate, quantifying variability and reliably predicting global warming."

William R. Cotton is an American cloud physicist and mesoscale meteorology educator. He is a professor in the Department of Atmospheric Science at the Colorado State University (CSU).

Weather and Society Integrated Studies

Weather and Society Integrated Studies (WAS*IS) is an international movement that is changing the weather enterprise by integrating social science into meteorological research and practice. WAS*IS was formed to build an interdisciplinary community of practitioners, researchers and decision makers collaborating to effectively understand how to improve weather warnings, incorporate societal impacts into weather forecasts, and use social science tools and methods. WAS*IS is changing the culture from what WAS to what IS the future of integrated studies

Carmen Nicole Moelders is an American atmospheric scientist. Her work is mainly focused on hydrometeorology, mesoscale meteorology, cloud physics, land-atmosphere interaction, air pollution, wildfire modeling, and wind power modeling.

SAFE AIR is an advanced atmospheric pollution dispersion model for calculating concentrations of atmospheric pollutants emitted both continuously or intermittently from point, line, volume and area sources. It adopts an integrated Gaussian puff modeling system. SAFE AIR consists of three main parts: the meteorological pre-processor WINDS to calculate wind fields, the meteorological pre-processor ABLE to calculate atmospheric parameters and a lagrangian multisource model named P6 to calculate pollutant dispersion. SAFE AIR is included in the online Model Documentation System (MDS) of the European Environment Agency (EEA) and of the Italian Agency for the Protection of the Environment (APAT).

Wind wave model Way to depict the sea state and predict the evolution of the energy of wind waves using numerical techniques

In fluid dynamics, wind wave modeling describes the effort to depict the sea state and predict the evolution of the energy of wind waves using numerical techniques. These simulations consider atmospheric wind forcing, nonlinear wave interactions, and frictional dissipation, and they output statistics describing wave heights, periods, and propagation directions for regional seas or global oceans. Such wave hindcasts and wave forecasts are extremely important for commercial interests on the high seas. For example, the shipping industry requires guidance for operational planning and tactical seakeeping purposes.

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.

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, 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.

Richard A. Anthes was a long time president of the University Corporation for Atmospheric Research. The Anthes Building in Boulder, Colorado, is the first UCAR-owned building to be named for an eminent scientist – and a living one at that.” His area of study at the University of Wisconsin, Madison, focused on hurricanes and tropical cyclones. Dr. Anthes taught as a professor for ten years at Pennsylvania State University before accepting a position at the National Center for Atmospheric Research as director of the Atmospheric and Prediction Division in 1981, a position he kept until 1986 when he became director of NCAR. In 1988, he started working as president of UCAR, and retired from that position in 2012. During his presidency at UCAR, he participated or chaired over forty different national committees for agencies such as NASA, NSF, and NOAA. He also established a program aimed at increasing participation in the atmospheric sciences called SOARS .

Janice Coen is a Project Scientist at the National Center for Atmospheric Research in Boulder, Colorado. Her work focuses on understanding and predicting wildland fire behavior through the use of wildfire modeling software. She has made major contributions to the field through her coupled weather—wildland fire computer simulation models.

Roland Aloysius Madden, an American meteorologist, was a staff scientist at the National Center for Atmospheric Research (NCAR) from 1967 to 2002. His research centers on diagnostic studies of the atmosphere. Madden is a fellow of the American Meteorological Society (AMS) and a recipient of the 2002 Jule G. Charney Award of the AMS.

Roger Lhermitte

Roger M. Lhermitte was a French meteorologist who "pioneered the development of meteorological Doppler radar." His career extended from the 1950s until his death where he made numerous contributions to the field of Radar Meteorology resulting in over 100 publications and numerous patents.

References

  1. "A Description of RAMS". rams.atmos.colostate.edu. Retrieved 2018-03-20.
  2. Pielke, Roger A.; W. R. Cotton; R. L. Walko; C. J. Tremback; W. A. Lyons; L. D. Grasso; M. E. Nicholls; M. D. Moran; D. A. Wesley; T. J. Lee; J. H. Copeland (1992). "A comprehensive meteorological modeling system—RAMS". Meteorol. Atmos. Phys. 49 (1–4): 69–91. Bibcode:1992MAP....49...69P. doi:10.1007/BF01025401.
  3. ATMET Software and Data Archived 2014-07-12 at the Wayback Machine
  4. Rafkin, Scott C. R.; R. M. Haberle; T. I. Michaels (2001). "The Mars Regional Atmospheric Modeling System (MRAMS): Model description and selected simulations". Icarus. 151 (2): 228–56. Bibcode:2001Icar..151..228R. doi:10.1006/icar.2001.6605.