Advanced 3 StaBsBcal Meteorology
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METR 5433 Spring 2019 Time: T/Th 2:30 - 3:45 PM Room: NWC 5930 Data analysis is a rou-ne part of research in the atmospheric sciences. As such, having the right set of tools and the prowess on how to use those tools is an important part to understanding the behavior of the Earth climate system. This course offers an overview of some advanced sta4s4cal methods used to interpret data in the atmospheric and oceanic sciences. The course is designed to be an applied course: i.e., the goal is to gain a working knowledge of the sta4s4cal tools most commonly used in the atmospheric sciences. Major topics include: (A) regression/correla4on and epoch analyses; (B) 4me series analysis (e.g., power spectra, filtering); (C) matrix methods for signal decomposi4on (e.g., EOFs, CCA); and (D) objec4ve mapping and covariance modeling. The course is intended for graduate students and senior undergraduates (with permission). Although previous knowledge of probability and sta4s4cs is preferable, a short review of sta4s4cal measures will be provided. You will also need knowledge of a soNware package to analyze data (e.g., Python, MATLAB, NCL, etc.). In-class examples will be done using Python / Jupyter Notebooks. Course DescripBon Instructor Dr. Jason C. Furtado Office: Na4onal Weather Center (NWC), Rm. 5240 Phone: 405.325.1391 Email: [email protected] TwiNer: @wxjay Office Hours: By appointment. Advanced StaBsBcal Meteorology
Transcript of Advanced 3 StaBsBcal Meteorology
METR5433
Spring2019Time:T/Th2:30-3:45PMRoom:NWC5930
Dataanalysisisarou-nepartofresearchintheatmosphericsciences.Assuch,havingtherightsetoftoolsandtheprowessonhowtousethosetoolsisanimportantparttounderstandingthebehavioroftheEarthclimatesystem.
Thiscourseoffersanoverviewofsomeadvancedsta4s4calmethodsusedtointerpretdataintheatmosphericandoceanicsciences.Thecourseis
designedtobeanappliedcourse:i.e.,thegoalistogainaworkingknowledgeofthesta4s4caltoolsmostcommonlyusedintheatmosphericsciences.Majortopicsinclude:(A)regression/correla4onandepochanalyses;(B)4meseriesanalysis(e.g.,powerspectra,filtering);(C)matrixmethodsforsignaldecomposi4on(e.g.,EOFs,CCA);and(D)objec4vemappingandcovariancemodeling.
Thecourseisintendedforgraduatestudentsandseniorundergraduates(withpermission).Althoughpreviousknowledgeofprobabilityandsta4s4csispreferable,ashortreviewofsta4s4calmeasureswillbeprovided.YouwillalsoneedknowledgeofasoNwarepackagetoanalyzedata(e.g.,Python,MATLAB,NCL,etc.).In-classexampleswillbedoneusingPython/JupyterNotebooks.
CourseDescripBon
InstructorDr.JasonC.FurtadoOffice:Na4onalWeatherCenter(NWC),Rm.5240Phone:405.325.1391Email:[email protected]:@wxjay
OfficeHours:Byappointment.
AdvancedStaBsBcalMeteorology
RequiredTextThere isnorequiredtext for theclass.Mostof theclasswillbetaughtwithmyownpersonalnotes.However,thereareseveralsourcesandtextsthatwillbeuseful(Textbookswillbeavailableonreserveoryoucanpurchasethem):
• Dennis Hartmann class notes on objec4ve analysis: hcp://www.atmos.washington.edu/~dennis/552_Notes_Np.html
• DiscreteInverseandStateEs0ma0onProblems-CarlWunsch,CambridgePress• Sta0s0calMethodsintheAtmosphericSciencesThirdEdi0on-DanielWilks,AcademicPress• Sta0s0calAnalysisinClimateResearch-HansvonStorchandFrancisW.Zwiers
CourseWebPageThewebpagewillbeaccessibleviahcps://canvas.ou.edu(logonusingyourOU4+4).Thereyouwillfind course materials (e.g., class notes, assignments, and examples), grades, and other news andannouncementsaboutthecourse.
GradingHomeworkAssignments: 70%FinalProject: 30%
Homework Assignments. Therewill be about 6-7 homework assignments throughout the semester.HomeworkassignmentsmustbetypedandelectronicallysubmicedthroughCanvas.Allplotsincludedwith your assignment should have proper units, labels, colorbars, and informa4ve cap4ons. Thehomeworkassignmentsareintendedforyoutoapplytheknowledgeyoulearninthecoursedirectlytodata(eithersynthe4correal).Some4mes,Iwillallowyoutosubs4tuteyourownresearchdatainlieuof theprovideddata tocompleteaproblem in theassignment.Thissubs4tu4on isdoneso thatyouhaveachancetoactuallyseehowtoapplythesetechniquestoyourownresearchwork.Youmayworkwithothersontheassignments,butyoumustturninyourownwork.
FinalProject.Thefinalprojectwillbeapaperandoralpresenta4oninwhichyoumustuseoneormoresta0s0cal techniques learned in the course to answer a real research ques4on. The project is to bechosenbasedonasetofques4onsthatyouwouldliketoanswerratherthanthetypeofdataanalysistechniqueyouwould like toapply. Youwillbe required to submitanabstractof yourwork forpriorapproval.Moredetailswillbeprovidedinclass.
1. Applysta4s4caltheorydirectlytoreal-worldmeteorologicalandclimatedatatodiscernspa4otemporalcharacteris4cs.
2. Gainfurthersta4s4cal(anddynamical)understandingoftheenvironmentalsystemofinterestandanswerrealworldresearchques4onsintheatmosphericsciences.
3. Evaluatecri4callyjournalar4clesandresearchpresenta4onswhichemploythesetechniques.
4. Developapersonaldata“toolkit”ofsta4s4calmethodsthatcanbeappliedtoyourownresearchproblemsandtasks.
GOALS
CompuBngAmaingoalofthecourseistohaveyouworkwithdatausingcomputersoNwarepackagesanddevelopyour own “sta4s4cal toolbox” for later use. All studentswho do not have a School ofMeteorology(SoM) computer account may obtain one from Shawn Riley (NWC 5640). Python and MATLAB arereadilyavailable foruseon theMetLabworksta4ons.Python isopen-sourceandcanbe installedonyour own machine. NOTE: You are free to use whatever soNware package with which you feelcomfortable.IwillprimarilyusePythoninthiscourseforin-classexamples,solu4ons,etc.Ifthereareques4onsorissueswithaccesstosoNware,pleaseseemeduringthefirstweekofclass.
CourseStyleTheoverallstructureoftheclasswillconsistoflectures,bothtradi4onalandinterac4ve,coveringthemajortopics.Thecoursewillalsofeaturein-classcodingsessions,wherebystudentswillworkinteamsand use Jupyter Notebooks (i.e., Python-based interac4ve examples) to prac4ce techniques anddevelopcode.Ques4onsandinterac4onsduringclassarewelcomeandhighlyencouraged.Ifyoudon’taskques4onswhenthingsareunclear,thenneitherofusbenefitfromclassroomlecture.
• Arrivetoclasson4meandpreparedtolearn.
• Submitassignments4mely.Nolatesubmissionsareallowedwithoutpriorapproval.
• TakeanacBveroleinthelearningprocessandaskquesBonswhenneeded.
• Seekassistancefrommeifyoudonotunderstandthematerialorneedhelpwithanassignment.
• Becourteoustootherstudents.Placeallphonesonvibrate/silence,donottext/usesocialmediaduringclass,andkeeptalkingtoaminimum.
EXPECTATIONSOFTHESTUDENT
ReasonableAccommodaBonPolicy TheUniversityofOklahomaiscommicedtoprovidingreasonableaccommoda4onforallstudentswithdisabili4es.Studentswithdisabili4eswhorequireaccommoda4oninthiscoursearerequestedtospeakwithmeassoonaspossible.Studentswithdisabili4esmustberegisteredwiththeDisabilityResourceCenterprior to receivingaccommoda4ons in thiscourse.TheDisabilityResourceCenter is located inUniversityCommunityCenter(730CollegeAve).Phone:405.325.3852.E-mail:[email protected]
AcademicMisconductChea4ngisstrictlyprohibitedattheUniversityofOklahoma.Simplyput, itdevaluesyourdegreeandendsupmarringyourcharacterandreputa4on.Forspecificdefini4onsonwhatcons4tuteschea4ng,review the Student’sGuide toAcademic Integrity at hcp://integrity.ou.edu/students.html. If you arecaughtchea4ng,Iamobligatedtoreportit.Sanc4onsforacademicmisconductincludeexpulsionfromtheUniversityandanFinthiscourse.BOTTOMLINE:Don’tcheat—it’snotworthit.
To be successful in this class, all workmust be yours and yours alone. Youmay work together onhomeworkassignments,butyoumustsubmityourownoriginalworkforgrading.
ReligiousHolidaysOU policy is to excuse absences of students that result from religious observances and to providewithoutpenalty for thereschedulingofexamina4onsandaddi4onal requiredclassworkthatmayfallonreligiousholidays.Anystudentwhohasareligiousholidayfallonadayanassignmentisdue,pleaseseemenolaterthanoneweekbeforethedeadlinesoastomakeotherarrangements.
TitleIXResourcesandReporBngRequirementFor any concerns regarding gender-based discrimina4on, sexual harassment, sexual assault, da4ng/domes4cviolence,orstalking,theUniversityoffersavarietyofresources.Tolearnmoreortoreportanincident,pleasecontacttheSexualMisconductOfficeat405.325.2215orsmo@ou.edu.Incidentscanalsobereportedconfiden4allytoOUAdvocates(405.615.0013)24hoursaday,7daysaweek. Pleasebeadvisedthataprofessor/GA/TAisrequiredtoreportinstancesofsexualharassment,sexualassault,ordiscrimina4ontotheSexualMisconductOffice. Inquiriesregardingnon-discrimina4onpoliciesmaybe directed to: Bobby J. Mason, University Equal Opportunity Officer and Title IX Coordinator [email protected],pleasevisithcp://www.ou.edu/eoo.html.
AdjustmentsforPregnancy-andParenBng-RelatedIssuesShouldyouneedmodifica4onsoradjustments toyour course requirementsbecauseofdocumentedpregnancy-relatedorchildbirth-related issues,pleasecontactmeortheDisabilityResourceCenterat405.325.3852assoonaspossible.Also,pleaseseehcp://www.ou.edu/eoo/faqs/pregnancy-faqs.htmlforanswerstocommonlyaskedques4ons.
FinalProjectPresentaBonswillbedoneduringthefinalweekofclassesandduringtheFinalExamPeriod.
FINALEXAMPERIOD:TUESDAY,MAY7,20191:30-3:30PM
CourseOutline
I. IntroducBon,FundamentalStaBsBcs,andLeastSquaresMethods(a) Reviewoffundamentalsta4s4calmeasures/Sta4s4caltests(b) Linearalgebrareview(c) Composite/Epochanalysis(d) SignificanceTes4ng(e) Regression/correla4ontheoryanditsapplica4ons(e.g.,covariancemodeling)
II. MatrixMethods(a) Empiricalorthogonalfunc4ons(EOFs)/principalcomponentanalysis(PCA)(b) Extendedandmul4variateEOFs(c) Maximumcovarianceanalysis(MCA)&canonicalcorrela4onanalysis(CCA)
III. TimeSeriesAnalysis(a) Autocorrela4on(b) Harmonicanalysis,powerspectralanalysis,andsignificancetes4ngforspectralpeaks(c) Cross-spectralanalysis(d) Filteringandfilterdesigns
IV. AddiBonalTopics(asBmeallows)(a) Waveletanalysis(b) Objec4veMapping/Kriging
