METR5433

Spring2018Time:T/Th2:30-3:45PMRoom:NWC5930

Dataanalysisisarou-nepartofmanytypesofresearchintheatmosphericsciences.Assuch,havingtherightsetoftoolsandtheprowessonhowtousethosetoolsisanimportantparttounderstandingthebehavioroftheclimatesystem.

Thiscourseoffersanoverviewofsomeadvancedsta4s4calmethodsusedtointerpretdataintheatmosphericandoceanicsciences.Itisdesignedtobe

anappliedcourse:i.e.,thegoalistogainaworkingknowledgeofthesta4s4caltoolsmostcommonlyusedintheatmosphericsciences.Majortopicstobecoveredinclude:(A)regression/correla4onandepochanalyses;(B)4meseriesanalysis(e.g.,powerspectra,filtering,waveletanalysis);(C)matrixmethodsforsignaldecomposi4on(e.g.,EOFs,CCA);and(D)objec4vemappingandcovariancemodeling.

Thecourseisintendedforgraduatestudentsandseniorundergraduates(withpermission).Althoughpreviousknowledgeofprobabilityandsta4s4csispreferable,ashortreviewofsta4s4calmeasureswillbeprovided.YouwillalsoneedaworkingknowledgeofasoOwarepackagetoanalyzedata(e.g.,Python,MATLAB,IDL,NCL,etc.).Thiswillbeimportantbecauseofthehighlyappliednatureofthecourse.

CourseDescripCon

Instructor

Dr.JasonC.FurtadoOffice:Na4onalWeatherCenter(NWC),Rm.5240Phone:405.325.1391Email:jfurtado@ou.edu

OfficeHours:Byappointment.

AdvancedStaCsCcalMeteorology

RequiredTextThere isnorequiredtext for theclass.Mostof theclasswillbetaughtwithmyownpersonalnotes.However,thereareseveralsourcesandtextsthatwillbeuseful(Textbookswillbeavailableonreserveoryoucanpurchasethem):

• Dennis Hartmann class notes on objec4ve analysis: hap://www.atmos.washington.edu/~dennis/552_Notes_Op.html

• DiscreteInverseandStateEs0ma0onProblems-CarlWunsch,CambridgePress• Sta0s0calMethodsintheAtmosphericSciencesSecondEdi0on-DanielWilks,AcademicPress• Sta0s0calAnalysisinClimateResearch-HansvonStorchandFrancisW.Zwiers

CourseWebPageThewebpagewillbeaccessibleviahaps://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.HomeworkassignmentsmustbetypedandelectronicallysubmiaedthroughCanvas.Allplotsincludedwith your assignment should have proper units, labels, colorbars, and informa4ve cap4ons. Thesehomeworkassignmentsareintendedforyoutoapplytheknowledgeyoulearninthecoursedirectlytodata (either synthe4c or real). Some4mes, I will allow you to subs4tute your own research data (ifapplicable) in lieuoftheprovideddatatocompleteaproblemintheassignment.Thissubs4tu4onisdonesothatyouhaveachancetoactuallyseehowtoapplythesetechniquestoyourownresearchwork.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. Cri4callyevaluatejournalar4clesandresearchpresenta4onswhichemploythesetechniques.

4. Developapersonaldata“toolkit”ofsta4s4calmethodsthatcanbeappliedtoyourownresearchproblemsandtasks.

GOALS

CompuCngAmaingoalofthecourseistohaveyouworkwithdatausingcomputersoOwarepackagesanddevelopyour 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 soOware package with which you feelcomfortable.IwillprimarilyusePythoninthiscourseforin-classexamples,solu4ons,etc.Ifthereareques4onsorissueswithaccesstosoOware,pleaseseemeduringthefirstweekofclass.

CourseStyleTheoverallstructureoftheclasswillconsistoflectures,bothtradi4onalandinterac4ve,coveringthemajor topics. I will also present examples in class of using the actual techniques to analyzemeteorological and climate data. Many examples will be in Jupyter Notebooks (i.e., Python-basedinterac4veexamples).Ques4onsandinterac4onsduringclassarewelcomeandhighlyencouraged. Ifyoudon’taskques4onswhenthingsareunclear,thenneitherofusbenefitfromclassroomlecture.

• Arrivetoclasson4meandpreparedtolearn.

• Submitassignments4mely.Nolatesubmissionsareallowedwithoutpriorapproval.

• TakeanacCveroleinthelearningprocessandaskquesConswhenneeded.

• Seekassistancefrommeifyoudonotunderstandthematerialorneedhelpwithanassignment.

• Becourteoustootherstudents.Placeallphonesonvibrate/silence,donottext/usesocialmediaduringclass,andkeeptalkingtoaminimum.

EXPECTATIONSOFTHESTUDENT

ReasonableAccommodaConPolicy TheUniversityofOklahomaiscommiaedtoprovidingreasonableaccommoda4onforallstudentswithdisabili4es.Studentswithdisabili4eswhorequireaccommoda4oninthiscoursearerequestedtospeakwithmeassoonaspossible.Studentswithdisabili4esmustberegisteredwiththeDisabilityResourceCenterprior to receivingaccommoda4ons in thiscourse.TheDisabilityResourceCenter is located inUniversityCommunityCenter(730CollegeAve).Phone:405.325.3852.E-mail:drc@ou.edu

AcademicMisconductChea4ngisstrictlyprohibitedattheUniversityofOklahoma.Simplyput, itdevaluesyourdegreeandendsupmarringyourcharacterandreputa4on.Forspecificdefini4onsonwhatcons4tuteschea4ng,review the Student’sGuide toAcademic Integrity at hap://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.

TitleIXResourcesandReporCngRequirementFor 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 at405.325.3546orbjm@ou.edu.Formoreinforma4on,pleasevisithap://www.ou.edu/eoo.html.

AdjustmentsforPregnancy/ChildbirthRelatedIssuesShouldyouneedmodifica4onsoradjustments toyour course requirementsbecauseofdocumentedpregnancy-relatedorchildbirth-related issues,pleasecontactmeortheDisabilityResourceCenterat405.325.3852assoonaspossible.Also,pleaseseehap://www.ou.edu/eoo/faqs/pregnancy-faqs.htmlforanswerstocommonlyaskedques4ons.

FinalProjectPresentaConswillbedoneduringthefinalweekofclassesandduringtheFinalExamPeriod.

FINALEXAMPERIOD:FRIDAY,MAY11,20181:30-3:30PM

***NOCLASS:Thursday,Feb15(AGUOceanSciencesMee4ng)

CourseOutline

I. FundamentalStaCsCcs+LeastSquaresMethods(a) Reviewoffundamentalsta4s4calmeasures/Sta4s4caltests(b) Composite/Epochanalysis(c) SignificanceTes4ng(d) Correla4ontheory/Regressionandcorrela4onanalysis/Mul4-variateregression(e) Applica4onsofregression/correla4ontheory(e.g.,covariancemodeling)

II. MatrixMethods(a) Linearalgebrareview(b) Empiricalorthogonalfunc4ons(EOFs)/principalcomponentanalysis(PCA)(c) Extendedandmul4variateEOFs(d) Maximumcovarianceanalysis(MCA)&canonicalcorrela4onanalysis(CCA)

III. TimeSeriesAnalysis(a) Autocorrela4on(b) Harmonicanalysis,powerspectralanalysis,andsignificancetes4ngforspectralpeaks(c) Cross-spectralanalysis(d) Filteringandfilterdesigns-Bestprac4cestouse

IV. AddiConalTopics(asCmeallows)(a) Objec4veMapping/Kriging(b) Waveletanalysis