Tropical cyclone forecast model: Difference between revisions

Revision as of 01:38, 20 October 2020

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The first statistical guidance used by the [[National Hurricane Center]] was the Hurricane Analog Technique (HURRAN), which was available in 1969. It used the newly developed [[HURDAT|North Atlantic tropical cyclone database]] to find storms with similar tracks. It then shifted their tracks through the storm's current path, and used ___location, direction and speed of motion, and the date to find suitable analogs. The method did well with storms south of the [[25th parallel north|25th parallel]] which had not yet turned northward, but poorly with systems near or after recurvature.<ref name="models">{{cite book|pages=288–292|url=https://books.google.com/books?id=6gFiunmKWWAC&pg=PA297|title=Global Perspectives on Tropical Cyclones: From Science to Mitigation|author1=Chan, Johnny C. L. |author2=Jeffrey D. Kepert |name-list-style=amp |year=2010|publisher=World Scientific|isbn=978-981-4293-47-1|accessdate=2011-02-24}}</ref> Since 1972, the [[Climatology and Persistence]] (CLIPER) statistical model has been used to help generate tropical cyclone track forecasts. In the era of skillful dynamical forecasts, CLIPER is now being used as the baseline to show model and forecaster skill.<ref>{{cite journal|url=http://rammb.cira.colostate.edu/resources/docs/Statistical_Knaff.pdf|pages=80–81|title=Statistical, 5-Day Tropical Cyclone Intensity Forecasts Derived from Climatology and Persistence|volume=18|date=February 2003|accessdate=2011-02-25|journal=Weather and Forecasting|doi=10.1175/1520-0434(2003)018<0080:SDTCIF>2.0.CO;2|issn=1520-0434|last1=Knaff|first1=John A.|last2=Demaria|first2=Mark|last3=Sampson|first3=Charles R.|last4=Gross|first4=James M.|bibcode = 2003WtFor..18...80K }}</ref> The Statistical Hurricane Intensity Forecast (SHIFOR) has been used since 1979 for tropical cyclone intensity forecasting. It uses climatology and persistence to predict future intensity, including the current [[Julian day]], current cyclone intensity, the cyclone's intensity 12&nbsp;hours ago, the storm's initial latitude and longitude, as well as its zonal (east-west) and meridional (north-south) components of motion.<ref name="models"/>

A series of statistical-dynamical models, which used regression equations based upon CLIPER output and the latest output from [[primitive equations|primitive equation]] models run at the National Meteorological Center, then [[National Centers for Environmental Prediction]], were developed between the 1970s and 1990s and were named NHC73, NHC83, NHC90, NHC91, and NHC98.<ref name="NHCmodel"/><ref name="Simpson">{{cite book|url=https://books.google.com/books?id=P7DnIb2XNg0C&pg=PA111&lpg=PA111&dqq=QLM+quasi+tropical+cyclone+model+book#v=onepage&qpg=QLM%20quasi%20tropical%20cyclone%20model%20book&f=falsePA111|page=110|author=Simpson, Robert H.|title=Hurricane!: coping with disaster : progress and challenges since Galveston, 1900|publisher=[[American Geophysical Union]]|year=2003|accessdate=2011-02-25|isbn=978-0-87590-297-5|authorlink=Robert Simpson (meteorologist)}}</ref> Within the field of [[tropical cyclone track forecasting]], despite the ever-improving dynamical model guidance which occurred with increased computational power, it was not until the decade of the 1980s when [[numerical weather prediction]] showed [[Forecast skill|skill]], and until the 1990s when it consistently outperformed statistical or simple dynamical models.<ref>{{cite web|url=http://www.nhc.noaa.gov/verification/verify6.shtml|publisher=[[National Hurricane Center]]|date=2010-04-20|accessdate=2011-01-02|author=Franklin, James|title=National Hurricane Center Forecast Verification|authorlink=James Franklin (meteorologist)}}</ref> In 1994, a version of SHIFOR was created for the northwest Pacific Ocean for [[typhoon]] forecasting, known as the Statistical Typhoon Intensity Forecast (STIFOR), which used the 1971–1990 data for that region to develop intensity forecasts out to 72&nbsp;hours into the future.<ref>{{cite web|url=http://www.dtic.mil/cgi-bin/GetTRDoc?Location=U2&doc=GetTRDoc.pdf&AD=ADA290588|title=A Regression Model For the Western North Pacific Tropical Cyclone Intensity Forecast|author=Chu, Jan-Hwa|publisher=[[United States Naval Research Laboratory]]|date=November 1994|accessdate=2011-03-15}}</ref>

In regards to intensity forecasting, the Statistical Hurricane Intensity Prediction Scheme (SHIPS) utilizes relationships between environmental conditions from the [[Global Forecast System]] (GFS) such as vertical [[wind shear]] and [[sea surface temperature]]s, climatology, and persistence (storm behavior) via multiple regression techniques to come up with an intensity forecast for systems in the northern Atlantic and northeastern Pacific oceans.<ref name="NHCmodel"/> A similar model was developed for the northwest Pacific Ocean and Southern Hemisphere known as the Statistical Intensity Prediction System (STIPS), which accounts for land interactions through the input environmental conditions from the [[Navy Operational Global Prediction System]] (NOGAPS) model.<ref name="STIPS">{{cite web|url=http://ams.confex.com/ams/pdfpapers/107554.pdf|title=A Statistical Intensity Model Consensus For the Joint Typhoon Warning Center|author=Sampson, Charles R., John A. Knaff, and Mark DeMaria|date=2006-03-01|accessdate=2011-03-15}}</ref> The version of SHIPS with an inland decay component is known as Decay SHIPS (DSHIPS). The Logistic Growth Equation Model (LGEM) uses the same input as SHIPS but within a simplified dynamical prediction system.<ref name="NHCmodel"/> Within [[tropical cyclone rainfall forecasting]], the Rainfall Climatology and Persistence (r-CLIPER) model was developed using microwave rainfall data from polar orbiting satellites over the ocean and first-order rainfall measurements from the land, to come up with a realistic rainfall distribution for tropical cyclones based on the National Hurricane Center's track forecast. It has been operational since 2004.<ref>{{cite book|url=https://books.google.com/books?id=8lUMg9U2y0EC&pg=PT119&dqq=r-CLIPER+book#v=onepage&qpg=r-CLIPER%20book&f=falsePT119|title=NOAA's role in space-based global precipitation estimation and application|author=National Research Council (U.S.). Committee on the Future of Rainfall Measuring Missions, National Research Council (U.S.). Board on Atmospheric Sciences and Climate|year=2007|publisher=National Academies Press|isbn=978-0-309-10298-8}}</ref> A statistical-parametric wind radii model has been developed for use at the National Hurricane Center and Joint Typhoon Warning Center which uses climatology and persistence to predict wind structure out to five days into the future.<ref name="models"/>

==Dynamical guidance==

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Tested in 1989 and 1990, The Vic Ooyama Barotropic (VICBAR) model used a [[spline (mathematics)|cubic-B spline]] representation of variables for the objective analysis of observations and solutions to the shallow-water prediction equations on nested domains, with the boundary conditions defined as the global forecast model.<ref>

{{cite journal | doi = 10.1175/1520-0493(1992)120<1628:ANSMFH>2.0.CO;2 | year = 1992 | volume = 120 | pages = 1628–1643 | title = A Nested Spectral Model for Hurricane Track Forecasting | author = Demaria, Mark | journal = Monthly Weather Review | last2 = Aberson | first2 = Sim D. | last3 = Ooyama | first3 = Katsuyuki V. | last4 = Lord | first4 = Stephen J. | issn = 1520-0493 | issue = 8|bibcode = 1992MWRv..120.1628D | doi-access = free }}</ref> It was implemented operationally as the Limited Area Sine Transform Barotropic (LBAR) model in 1992, using the GFS for boundary conditions.<ref name="models"/> By 1990, Australia had developed its own storm surge model which was able to be run in a few minutes on a personal computer.<ref>{{cite journal|title=Computer Techniques: A Real-Time System For Forecasting Tropical Cyclone Storm Surges|author=Hubbert, Graeme D., Greg J. Holland, Lance M. Leslie, Michael J. Manton|date=March 1991|pages=86–87|journal=Weather and Forecasting|issn=1520-0434|volume=6|issue=1|doi=10.1175/1520-0434(1991)006<0086:ARTSFF>2.0.CO;2|bibcode=1991WtFor...6...86H|doi-access=free}}</ref> The [[Japan Meteorological Agency]] (JMA) developed its own Typhoon Model (TYM) in 1994,<ref>{{cite book|url=https://books.google.com/books?id=De3JAP1N_wEC&pg=PA172&lpg=PA172&dqq=japan+meteorological+agency+typhoon+model+book#v=onepage&qpg=japan%20meteorological%20agency%20typhoon%20model%20book&f=falsePA172|title=Early warning systems for natural disaster reduction|page=172|author1=Zschau, Jochen |author2=Andreas N. Küppers |name-list-style=amp |year=2003|publisher=Springer|isbn=978-3-540-67962-2|accessdate=2011-03-16}}</ref> and in 1998, the agency began using its own dynamic [[storm surge]] model.<ref>{{cite web|url=http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/techrev/text11-3.pdf|title=Outline of the Storm Surge Prediction Model at the Japan Meteorological Agency|page=25|author=Higaki, Masakazu, Hironori Hayashibara, and Futoshi Nozaki|date=2009-04-20|accessdate=2011-03-15|publisher=[[Japan Meteorological Agency]]}}</ref>

[[File:Irene13.gif|right|thumb|A NOAA prediction for [[Hurricane Irene (2011)|Hurricane Irene]] ]]

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The JMA has produced an 11-member ensemble forecast system for typhoons known as the Typhoon Ensemble Prediction System (TEPS) since February 2008, which is run out to 132&nbsp;hours into the future. It uses a lower resolution version (with larger grid spacing) of its GSM, with ten perturbed members and one non-perturbed member. The system reduces errors by an average of {{convert|40|km|mi}} five days into the future when compared to its higher resolution GSM.<ref>{{cite web|url=http://www.jma.go.jp/jma/jma-eng/jma-center/rsmc-hp-pub-eg/techrev/text11-2.pdf|title=Outline of the Typhoon Ensemble Prediction System at the Japan Meteorological Agency|author1=Yamaguchi, Munehiko |author2=Takuya Komori |name-list-style=amp |pages=14–15|date=2009-04-20|accessdate=2011-03-15|publisher=[[Japan Meteorological Agency]]}}</ref>

The Florida State Super Ensemble (FSSE) is produced from a suite of models which then uses statistical regression equations developed over a training phase to reduce their biases, which produces forecasts better than the member models or their mean solution. It uses 11&nbsp;global models, including five developed at [[Florida State University]], the Unified Model, the GFS, the NOGAPS, the United States Navy NOGAPS, the Australian Bureau of Meteorology Research Centre (BMRC) model, and Canadian [[Recherche en Prévision Numérique]] (RPN) model. It shows significant skill in track, intensity, and rainfall predictions of tropical cyclones.<ref>{{cite book|pages=532–545|url=https://books.google.com/books?id=c-rY28QQCj8C&pg=PA532&dqq=Florida+State+Superensemble+hurricane+book#v=onepage&qpg=Florida%20State%20Superensemble%20hurricane%20book&f=falsePA532|title=Predictability of weather and climate|author1=Palmer, Tim |author2=Renate Hagedorn |name-list-style=amp |year=2006|publisher=Cambridge University Press|isbn=978-0-521-84882-4|accessdate=2011-02-26}}</ref>

The Systematic Approach Forecast Aid (SAFA) was developed by the Joint Typhoon Warning Center to create a selective consensus forecast which removed more erroneous forecasts at a 72‑hour time frame from consideration using the United States Navy NOGAPS model, the GFDL, the Japan Meteorological Agency's global and typhoon models, as well as the UKMET. All the models improved during SAFA's five-year history and removing erroneous forecasts proved difficult to do in operations.<ref>{{cite journal|title=Notes and Correspondence: Operational Evaluation of a Selective Consensus in the Western North Pacific Basin|author=Sampson, Charles R., John A. Knaff, and Edward M. Fukada|pages=671–675|date=June 2007|journal=Weather and Forecasting|volume=22|doi=10.1175/WAF991.1|issue=3|bibcode = 2007WtFor..22..671S }}</ref>