Content deleted Content added
No edit summary |
m (GR) File:Two women operating ENIAC.gif → File:Two women operating ENIAC (full resolution).jpg Higher res |
||
| (3 intermediate revisions by 2 users not shown) | |||
Line 14:
== History ==
{{Main|History of numerical weather prediction}}
[[File:Two women operating ENIAC (full resolution).
The [[history of numerical weather prediction]] began in the 1920s through the efforts of [[Lewis Fry Richardson]], who used procedures originally developed by [[Vilhelm Bjerknes]]<ref name="Lynch JCP"/> to produce by hand a six-hour forecast for the state of the atmosphere over two points in central Europe, taking at least six weeks to do so.<ref>{{cite journal |last1=Simmons |first1=A. J. |last2=Hollingsworth |first2=A. |date=2002 |title=Some aspects of the improvement in skill of numerical weather prediction |url=https://doi.org/10.1256/003590002321042135 |journal=Quarterly Journal of the Royal Meteorological Society |volume=128 |issue=580 |pages=647–677 | doi=10.1256/003590002321042135|bibcode=2002QJRMS.128..647S |s2cid=121625425 |url-access=subscription }}</ref><ref name="Lynch JCP">{{cite journal|last=[[Peter Lynch (meteorologist)|Lynch]]|first=Peter|title=The origins of computer weather prediction and climate modeling|journal=[[Journal of Computational Physics]]|date=March 2008|volume=227|issue=7|pages=3431–44|doi=10.1016/j.jcp.2007.02.034|bibcode=2008JCoPh.227.3431L|url=http://www.rsmas.miami.edu/personal/miskandarani/Courses/MPO662/Lynch,Peter/OriginsCompWF.JCP227.pdf|access-date=2010-12-23|url-status=dead|archive-url=https://web.archive.org/web/20100708191309/http://www.rsmas.miami.edu/personal/miskandarani/Courses/MPO662/Lynch,Peter/OriginsCompWF.JCP227.pdf|archive-date=2010-07-08}}</ref><ref name="Lynch Ch1">{{cite book|last=Lynch|first=Peter|title=The Emergence of Numerical Weather Prediction|url=https://archive.org/details/emergencenumeric00lync|url-access=limited|year=2006|publisher=[[Cambridge University Press]]|isbn=978-0-521-85729-1|pages=[https://archive.org/details/emergencenumeric00lync/page/n11 1]–27|chapter=Weather Prediction by Numerical Process}}</ref> It was not until the advent of the computer and [[computer simulation]]s that computation time was reduced to less than the forecast period itself. The [[ENIAC]] was used to create the first weather forecasts via computer in 1950, based on a highly simplified approximation to the atmospheric governing equations.<ref name="Charney 1950"/><ref>{{cite book|title=Storm Watchers|page=[https://archive.org/details/stormwatcherstur00cox_df1/page/208 208]|year=2002|author=Cox, John D.|publisher=John Wiley & Sons, Inc.|isbn=978-0-471-38108-2|url=https://archive.org/details/stormwatcherstur00cox_df1/page/208}}</ref> In 1954, [[Carl-Gustav Rossby]]'s group at the [[Swedish Meteorological and Hydrological Institute]] used the same model to produce the first operational forecast (i.e., a routine prediction for practical use).<ref name="Harper BAMS">{{cite journal|last=Harper|first=Kristine|author2=Uccellini, Louis W. |author3=Kalnay, Eugenia |author4=Carey, Kenneth |author5= Morone, Lauren |title=2007: 50th Anniversary of Operational Numerical Weather Prediction|journal=[[Bulletin of the American Meteorological Society]]|date=May 2007|volume=88|issue=5|pages=639–650|doi=10.1175/BAMS-88-5-639|bibcode=2007BAMS...88..639H|doi-access=free}}</ref> Operational numerical weather prediction in the United States began in 1955 under the Joint Numerical Weather Prediction Unit (JNWPU), a joint project by the [[U.S. Air Force]], [[U.S. Navy|Navy]] and [[U.S. Weather Bureau|Weather Bureau]].<ref>{{cite web|author=American Institute of Physics|date=2008-03-25|url=http://www.aip.org/history/sloan/gcm/ |title=Atmospheric General Circulation Modeling|access-date=2008-01-13 |archive-url = https://web.archive.org/web/20080325084036/http://www.aip.org/history/sloan/gcm/ |archive-date = 2008-03-25}}</ref> In 1956, [[Norm Phillips|Norman Phillips]] developed a mathematical model which could realistically depict monthly and seasonal patterns in the troposphere; this became the first successful [[climate model]].<ref name="Phillips">{{cite journal|last=Phillips|first=Norman A.|title=The general circulation of the atmosphere: a numerical experiment|journal=Quarterly Journal of the Royal Meteorological Society|date=April 1956|volume=82|issue=352|pages=123–154|doi=10.1002/qj.49708235202|bibcode=1956QJRMS..82..123P}}</ref><ref name="Cox210">{{cite book|title=Storm Watchers|page=[https://archive.org/details/stormwatcherstur00cox_df1/page/210 210]|year=2002|author=Cox, John D.|publisher=John Wiley & Sons, Inc.|isbn=978-0-471-38108-2|url=https://archive.org/details/stormwatcherstur00cox_df1/page/210}}</ref> Following Phillips' work, several groups began working to create [[general circulation model]]s.<ref name="Lynch Ch10">{{cite book|last=Lynch|first=Peter|title=The Emergence of Numerical Weather Prediction|url=https://archive.org/details/emergencenumeric00lync|url-access=limited|year=2006|publisher=[[Cambridge University Press]]|isbn=978-0-521-85729-1|pages=[https://archive.org/details/emergencenumeric00lync/page/n216 206]–208|chapter=The ENIAC Integrations}}</ref> The first general circulation climate model that combined both oceanic and atmospheric processes was developed in the late 1960s at the [[NOAA]] [[Geophysical Fluid Dynamics Laboratory]].<ref>{{cite web|url=http://celebrating200years.noaa.gov/breakthroughs/climate_model/welcome.html|title=The First Climate Model|author=[[National Oceanic and Atmospheric Administration]]|date=2008-05-22|access-date=2011-01-08}}</ref>
As computers have become more powerful, the size of the initial data sets has increased and [[Atmospheric model#Types|newer atmospheric models]] have been developed to take advantage of the added available computing power. These newer models include more physical processes in the simplifications of the [[Navier–Stokes equations|equations of motion]] in numerical simulations of the atmosphere.<ref name="Harper BAMS"/> In 1966, [[West Germany]] and the United States began producing operational forecasts based on [[primitive equations|primitive-equation models]], followed by the United Kingdom in 1972 and Australia in 1977.<ref name="Lynch JCP"/><ref name="Leslie BOM">{{cite journal|last=Leslie|first=L.M.|author2=Dietachmeyer, G.S. |title=Real-time limited area numerical weather prediction in Australia: a historical perspective|journal=Australian Meteorological Magazine|date=December 1992|volume=41|issue=SP|pages=61–77|url=http://www.bom.gov.au/amoj/docs/1992/leslie2.pdf|access-date=2011-01-03}}</ref> The development of limited area (regional) models facilitated advances in forecasting the tracks of [[tropical cyclone]]s as well as [[air quality]] in the 1970s and 1980s.<ref name="Shuman W&F">{{cite journal|last=Shuman|first=Frederick G.|author-link=Frederick Gale Shuman|title=History of Numerical Weather Prediction at the National Meteorological Center|journal=[[Weather and Forecasting]]|date=September 1989|volume=4|issue=3|pages=286–296|doi=10.1175/1520-0434(1989)004<0286:HONWPA>2.0.CO;2|bibcode=1989WtFor...4..286S|doi-access=free}}</ref><ref>{{cite book|title=Air pollution modeling and its application VIII, Volume 8|author=Steyn, D. G.|publisher=Birkhäuser|year=1991|pages=241–242|isbn=978-0-306-43828-8}}</ref> By the early 1980s models began to include the interactions of soil and vegetation with the atmosphere, which led to more realistic forecasts.<ref>{{cite journal|url=http://www.geog.ucla.edu/~yxue/pdf/1996jgr.pdf |title=Impact of vegetation properties on U. S. summer weather prediction |page=7419 |author1=Xue, Yongkang |author2=Fennessey, Michael J. |journal=[[Journal of Geophysical Research]] |volume=101 |issue=D3 |date=1996-03-20 |access-date=2011-01-06 |doi=10.1029/95JD02169 |bibcode=1996JGR...101.7419X |url-status=dead |archive-url=https://web.archive.org/web/20100710080304/http://www.geog.ucla.edu/~yxue/pdf/1996jgr.pdf |archive-date=2010-07-10 |citeseerx=10.1.1.453.551 }}</ref>
Line 43:
==Domains==
[[File:Sigma-z-coordinates.svg|thumb|280px|A cross-section of the atmosphere over terrain with a [[Sigma coordinate system|sigma
The horizontal [[Domain of a function|___domain of a model]] is either ''global'', covering the entire Earth, or ''regional'', covering only part of the Earth. Regional models (also known as ''limited-area'' models, or LAMs) allow for the use of finer grid spacing than global models because the available computational resources are focused on a specific area instead of being spread over the globe. This allows regional models to resolve explicitly smaller-scale meteorological phenomena that cannot be represented on the coarser grid of a global model. Regional models use a global model to specify conditions at the edge of their ___domain ([[boundary condition]]s) in order to allow systems from outside the regional model ___domain to move into its area. Uncertainty and errors within regional models are introduced by the global model used for the boundary conditions of the edge of the regional model, as well as errors attributable to the regional model itself.<ref>{{cite book|url=https://books.google.com/books?id=6RQ3dnjE8lgC&pg=PA261|title=Numerical Weather and Climate Prediction|author=Warner, Thomas Tomkins |publisher=[[Cambridge University Press]]|year=2010|isbn=978-0-521-51389-0|page=259}}</ref>
Line 127:
On a molecular scale, there are two main competing reaction processes involved in the degradation of [[cellulose]], or wood fuels, in [[wildfire]]s. When there is a low amount of moisture in a cellulose fiber, [[volatilization]] of the fuel occurs; this process will generate intermediate gaseous products that will ultimately be the source of [[combustion]]. When moisture is present—or when enough heat is being carried away from the fiber, [[charring]] occurs. The [[chemical kinetics]] of both reactions indicate that there is a point at which the level of moisture is low enough—and/or heating rates high enough—for combustion processes to become self-sufficient. Consequently, changes in wind speed, direction, moisture, temperature, or [[lapse rate]] at different levels of the atmosphere can have a significant impact on the behavior and growth of a wildfire. Since the wildfire acts as a heat source to the atmospheric flow, the wildfire can modify local [[advection]] patterns, introducing a [[Feedback|feedback loop]] between the fire and the atmosphere.<ref name="Sullivan wildfire">{{cite journal|last=Sullivan|first=Andrew L.|title=Wildland surface fire spread modelling, 1990–2007. 1: Physical and quasi-physical models|journal=International Journal of Wildland Fire|date=June 2009|volume=18|issue=4|page=349|doi=10.1071/WF06143|arxiv=0706.3074|s2cid=16173400}}</ref>
A simplified two-dimensional model for the spread of wildfires that used [[convection]] to represent the effects of wind and terrain, as well as [[Thermal radiation|radiative heat transfer]] as the dominant method of heat transport led to [[reaction–diffusion system]]s of [[partial differential equation]]s.<ref name="Asensio-2002-WFM">{{cite journal|author1=Asensio, M. I. |author2=L. Ferragut |name-list-style=amp |title=On a wildland fire model with radiation|journal=International Journal for Numerical Methods in Engineering|volume=54|issue=1 |pages=137–157|year=2002|doi=10.1002/nme.420|bibcode = 2002IJNME..54..137A |s2cid=122302719 }}</ref><ref name="Mandel-2008-WMD">{{cite journal|author=Mandel, Jan, [[Lynn Schreyer|Lynn S. Bennethum]], Jonathan D. Beezley, [[Janice Coen|Janice L. Coen]], Craig C. Douglas, Minjeong Kim, and Anthony Vodacek|title=A wildfire model with data assimilation|journal=Mathematics and Computers in Simulation|volume=79|pages=584–606|year=2008|doi=10.1016/j.matcom.2008.03.015|arxiv=0709.0086|bibcode=2007arXiv0709.0086M|issue=3|s2cid=839881}}</ref> More complex models join numerical weather models or [[computational fluid dynamics]] models with a wildfire component which allow the feedback effects between the fire and the atmosphere to be estimated.<ref name="Sullivan wildfire"/> The additional complexity in the latter class of models translates to a corresponding increase in their computer power requirements. In fact, a full three-dimensional treatment of [[combustion]] via [[direct numerical simulation]] at scales relevant for atmospheric modeling is not currently practical because of the excessive computational cost such a simulation would require. Numerical weather models have limited forecast skill at spatial resolutions under {{convert|1|km|mi|1|sp=us}}, forcing complex wildfire models to parameterize the fire in order to calculate how the winds will be modified locally by the wildfire, and to use those modified winds to determine the rate at which the fire will spread locally.<ref name="Clark-1996-CAFb">{{cite journal|author=Clark, T. L., M. A. Jenkins, J. Coen, and David Packham|title=A coupled atmospheric-fire model: Convective Froude number and dynamic fingering|journal=International Journal of Wildland Fire|volume=6|pages=177–190|year=1996|doi=10.1071/WF9960177|issue=4|url=https://zenodo.org/record/1236052}}</ref><ref name="Clark-1996-CAF">{{cite journal|author=Clark, Terry L., Marry Ann Jenkins, Janice Coen, and David Packham|title=A coupled atmospheric-fire model: Convective feedback on fire line dynamics|journal=Journal of Applied Meteorology|volume=35|pages=875–901|year=1996|doi=10.1175/1520-0450(1996)035<0875:ACAMCF>2.0.CO;2|bibcode=1996JApMe..35..875C|issue=6|doi-access=free}}</ref><ref name="Rothermel-1972-MMP">{{cite web |author=Rothermel, Richard C. |date=January 1972 |title=A mathematical model for predicting fire spread in wildland fires
== See also ==
| |||
.jpg){kind=link}