(高清版)GBT 41214-2021 空間環(huán)境(自然和人工) 地磁活動的預報方法

空間環(huán)境(自然和人工)I Ⅲ 1 1 1 1 15.1地磁場變化 1 25.3K指數(shù)(單臺站3h范圍指數(shù)) 2 25.5aa指數(shù)(共軛振幅指數(shù)) 45.6Dst指數(shù)(暴時擾動指數(shù)) 4 4 55.9am指數(shù) 65.10PC指數(shù) 7 7 86.1概述 8 86.3中期預報 86.4長期預報 8 9 9 97.3基于物理原理的預報方法 98預報效果評估 98.1預報誤差定義 9 99遵從準則 9.1基本原理 9.2預報報告 9.3編制文檔 9.4發(fā)布 9.5存檔 Ⅱ 附錄A(資料性)地磁指數(shù)可用的網(wǎng)址 附錄B(資料性)發(fā)布空間天氣預報和/或現(xiàn)報的網(wǎng)址 附錄C(資料性)不同種類技巧評分定義 附錄D(資料性)與本文件領域相關(guān)的有用文獻(本文件未引用) 參考文獻 Ⅲ本文件按照GB/T1.1—2020《標起草。本文件等同采用ISO16698:2019《空間環(huán)境(自然Mb)中期預報(數(shù)周至數(shù)月);c)長期預報(半年至一個太陽活動周)。1本文件描述了用于預報時間尺度從短期(數(shù)小時到數(shù)月)到長期(數(shù)月至數(shù)年)的地磁指數(shù)的預報Glon地理經(jīng)度(Geographiclongitude)IMF行星際磁場(Interplanetarymagneticfield)Mlat地磁緯度(GeomagMlon地磁經(jīng)度(Geomagneticlongitude)MHD磁流體動力學(Magnetohydrodynamics)Sq太陽寧靜條件下25.3K指數(shù)(單臺站3h范圍指數(shù))值。每個觀測站采用各自固定的標準規(guī)則描述R值與K值的轉(zhuǎn)換關(guān)系。表1給出了尼梅克觀測站R0123456789注：nT即納特斯拉，為電磁場單位。表2計算地磁Kp指數(shù)的13個觀測站NE說明曲角，加拿大錫特卡，美國 勒威克，設得蘭群島，英國1969年取代阿金庫爾3表2計算地磁Kp指數(shù)的13個觀測站(續(xù))NE說明埃斯克代爾米爾，英國1988年取代魯?shù)滤箍品蚋ダ椎吕锟怂贡?，美?957年取代切爾滕納姆溫斯特，德國尼梅克，德國1998年取代維特文哈特蘭，英國1957年取代阿賓格1981年取代圖蘭吉1978年取代安伯利5.4.2Kp指數(shù)(行星性3h范圍指數(shù))8個值。取值范圍從0到9,中間共分28級：0。,0+,1-,1。,1+,…,9-,9%。其值越大，擾動越強。推導：由表2中列出的13個觀測臺站觀測得到的K指數(shù)通過轉(zhuǎn)換表進行標準化，該轉(zhuǎn)換表通過引入的復雜程序建立。先求出每個臺站的標準化的K指數(shù)Ks指數(shù)，然后用Ks指數(shù)的加權(quán)平均值確5.4.3ZKp指數(shù)(行星性日范圍指數(shù))ZKp是行星性日范圍指數(shù)，是每天8個Kp值的和。5.4.4ap指數(shù)(等效行星性3h幅度指數(shù))地磁擾動的測量單位為納特斯拉(nT),Kp指數(shù)與地磁擾動間并不是線性關(guān)系，相反，引入的ap指023456795.4.5Ap指數(shù)(等效行星性日幅度指數(shù))Ap指數(shù)通過計算每天(UT)8個ap指數(shù)的平均值獲得，每天(UT)一個值。4得。觀測站信息見表4。兩個觀測站測得的K指數(shù)通過轉(zhuǎn)換表轉(zhuǎn)換回振幅，見表5。aa指數(shù)通過南北NEλ格林威治，英國阿賓格，英國哈特蘭，英國1957~圖蘭吉，澳大利亞1979~0123456789推導：Dst指數(shù)定義為表6中列出的4個觀測站測得的H分量擾動變化D?(i=1～4)的平均值除表6計算Dst指數(shù)的4個觀測臺站E圣胡安，美國植香山，美國5對稱和對稱的高時間分辨率(1min)擾動場，引入了縱向不對稱擾動指數(shù)(ASY)和對稱擾動指數(shù)(SYM),并導出了H分量和D分量的擾動指數(shù)。推導：ASY/SYM指數(shù)由選定的中緯度的6個觀測站(見表7)D;(4)通過計算非對稱磁場的最大值和最小值之間的范圍計算得出非對稱擾動指數(shù)ASY-H和表7計算ASY/SYM指數(shù)的6個觀測臺站NEE旋轉(zhuǎn)角檀香山，美國圖森，美國弗雷德里克斯堡，美國阿拉木圖推導：極光電集流指數(shù)由位于北半球極光區(qū)的12個觀測站(見表8)觀測的H分量的地磁變化得表8計算極光電集流指數(shù)的12個觀測站和停用的3個觀測站NEE說明阿比斯庫，瑞典 巴羅，美國杰克湯森學院，美國6表8計算極光電集流指數(shù)的12個觀測站和停用的3個觀測站(續(xù))NEE說明2007年12月開始雷沃古爾，冰島1996年停止巨鯨河，俄羅斯1984年7月停止1984年9月開始推導：用于計算am指數(shù)的觀測站根據(jù)它們的經(jīng)度位置分成9組(見表9),其中5組位于北半球，馬加丹，俄羅斯1967~1969~女滿別，日本1959~1959~2002~哈特蘭，英國1959~尼梅克，德國1959~尚邦拉福雷，法國1996~1975~弗雷德里克斯堡，美國1959~7表9計算am指數(shù)的觀測站(續(xù))NE紐波特，美國1975~1959~圖森，美國1959~1986~1978~1959~馬丁·德·維維安，法國1986~圖蘭吉，澳大利亞克爾格倫群島，法國1959~?？肆_澤群島，法國1973~1959~阿根廷島，烏克蘭1959~1973~南喬洽亞島，英國表10計算PC指數(shù)的觀測站觀測站，國家/地區(qū)E圖勒(卡納克),格陵蘭島8地磁指數(shù)預報的準確性和預報方法取決于預報的時間尺度。6.2～6.4介紹了幾種現(xiàn)有的預報方模型(MHD模擬等。大多數(shù)預報方法需要實時的太陽風參數(shù)和準實時的地磁觀測作為輸入。根據(jù)太●類型(4)見參考文獻[25]。●類型(3)見參考文獻[32];9前一個時間間隔的數(shù)據(jù)作為輸入(見參考文獻[67]);另一種使用太陽風參數(shù)作為輸入(見參考文獻有一些神經(jīng)網(wǎng)絡模型和深度學習模型適用于數(shù)天至一個太陽黑子活動周的時間尺度的預報。其地磁指數(shù)預報結(jié)果應公開可供第三方(如：對預報結(jié)果感興趣的個人或機構(gòu))進行評估和應用。1)數(shù)據(jù)類型；2)數(shù)據(jù)源；3)數(shù)據(jù)的時間分辨率；4)數(shù)據(jù)點數(shù)；5)數(shù)據(jù)采集時間。1)預報數(shù)據(jù)類型；2)預報數(shù)據(jù)的時間；3)預報制作時間。1)預報方法類型(從第6章所列的四類預報方法中選擇，否則應進行簡要描述);2)聯(lián)系點。9.5存檔https://www.gfz-potsdam.de/kp-indehttp://isgi.unistra.fr/about_indices.php(aa,am,Kp,AEhttp://wdc.kugi.kyoto-u.ac.jp/wdc/Sec3.html(AE,Dst,ASY/SYM,RT-A/ftp://ftp.space.dtu.dk/WDC/ind/natural-hazards/geomagnetism(RT-Uhttps://www.swpc.noaa./ISTP/diahttp://www.ises-spaceweatherhttp://hirweb.nict.go.au/Space_We/models/modelinfo.php?modehttp://www.lund.irf.se//cism/和http://lasp.colorado,edu/cism//SolarC(資料性)不同種類技巧評分定義C.1二分量預報表C.1列出了公式(C.1)～公式(C.5)中使用的列聯(lián)表。表C.1預報結(jié)果和觀測結(jié)果比較的列聯(lián)表是否是x(命中)y(漏報)否z(虛報)w(正確否定)真技巧評分(T)定義為：Gilbert技巧評分(G)定義為：Heidke技巧評分(H)定義為：C.2持續(xù)變量預報均方誤差技巧評分(S)定義為：E——均方誤差；f.——第i次預報值；x;——第i次觀測值；第1～n次觀測值的平均值。Planet.SpaceSci.1986,34(1)pp.77-92[2]AyalaSolares,J.R.,H.-L.Wei,R.J.Boynton,S.N.WalkerandS.A.Billings(2016),Modelingandpredictionofglobalmagneticdisturbanceinnear-EarthspusingNARXmodels,SpaceWeather,14,8[3]BakerD.N.,BargatzeL.F.,ZJ.Geomag.Geoelectr.1986,38(11)pp.1[4]BakerD.N.,WeigelR.S.,RiglerF.,McPherronRSun-to-magnetospheremodelinJ.Atmos.Sol.-Terr.Phys.2004,66pp.15-16,pp.1491-1497[5]BargatzeL.F.,BakerD.N.,McpherronR.L.,HonesE.W.MagnetosphsponseforManyLevelsofGeomagnetic-Activity.J.Geophys.Res.1985,90(NA7)pp.6387-6394[6]BlanchardG.T.,McPherronR.L.AnalysisoftheLinear-ResponseFunctionRelatingAltoVbsforIndividualSubstorms.J.Geophys.Res.1995,100(A10)pp.19155-19165[7]ClauerC.R.Thetechniqueoflinenetospherecoupling.In:SolarWind-MagnetosphereCoupling,(KamideY.,SlavinJ.ScientificPublishi[8]ClauerC.R.,McPherronR.L.,SearlsC.,KivelsonM.G.Solar-WinZoneGeomagnetic-Activity.Geophys.Res.Lett.1981,8(8)pp.915-918[9]DoggettK.A.(1993),Anoperationalforecastverratory,inSolar-Terrestrialpredictions,IV,ProceedingsofaWorkshop,editedbyJ.Hr[10]DoggettK.A.(1994),VerificationofNOAASpaceEnviJanuary-31December1994,[11]DoxasI,HortonW.Magnetosphericdynamicsfromadynamicsmodel.Phys.Plasmas.1999,6(5)p[12]DoxasI.,HortonW.,SmithJ.P.Aphysicsbasednonlineardynamicalwinddrivenmagnetosphere-ionospheresystem.Phys.Chem.Earth(C).1[13]DoxasI.,HortonW.,SmithJ.P.Aphysicsbasednonlineardynawinddrivenmagnetosphere-ionospheresystem.Phys.Chem.Earth(C).1[14]DryerM.,AkasofuS.I,KroehlH.Wsolar/interplanetary/magnetosphere/ionosphereconnection:astrategyforpredictionofgeomagneticstorms.AdvancesAstro.Sci,1986,pp.58.[15]EcherE.,AlvesM.V.,GonzalezW.D.Geoeffectivenessofinterplanetaryshocksduringsolarminimum(1995—1996)andsolarmaximum(2000).Sol.Phys.2004,221(2)pp.361-380dexandpolarcappotential.In:SolarWind-MagnetosphereCoupling,(KamideY.,SlavinJ.A.,eds.).TerraScientificPublishingCo,1986,pp.[17]FotiM.A.,ArizmendiC.M.RandnessAnInterdisciplinaryJournalontheComplexGeometryofNature.1997,5(1)pp.169-173[18]FrancqC.,MenvielleM.Amodelfortheapplicationtoprediction.Geophys.J.Int.1996,125(3)[19]FreemanJ.,NagaiA.,ReiffP.,DenigW.,Gu(1993),Theuseofneuralnetworkstopredictmagnetosphricforecastmodel,inProceedingsofArtificialIntelligenWorkshop,editedbyJ.A.Joselyn,H.LundstedtandJ.Trolinger,pp.167[20]FreemanJ.W.,WolfR.A.,SpiroR.W.,HausmanB.A.,BalesB.timemagnetosphericspecificationfinalreport.RiceUniv,Houston,Texas,1994[21]GannonJ.L.,LoveJ.J.,FribergP.A.,StewartD.C.,Lisowskiport,2011-1030,10p.Gavrishchaka,V.V.andGanguli,S.B.(2001),Supportvectormachineasanefficienttoolforhigh-dimensionaldataprocessing:Res.2011,106(A12)pp.29911-29914.Availablea[22]GavrishchakaV.V.,GanguliS.B.Optimizationoftheneural-networkgeomagneticforforecastinglarge-amplitudesubstorme[23]GehredP.A.(1996),tionstatistics,inNOAATechnicalM[24]GholipourA.,LucasC.,AraabiB.N.Blackboxmodelingofmagnetosphericdynamicstoforecastgeomagneticactivity.SpaceWeather—theInternationalJournalofRescarchandApplications.[25]GleisnerH.,LundstedtH.Responseoftheauroralelectrojetstothesolarwwithneuralnetworks.J.Geophys.Res.1997,102(A7)pp.14269-14278AnnalesGeophysicae-AtmospheresHydrospheresand[27]GlcisnerH.,LundstedtH.AuroralelectrojetpredictionswithGeophys.Res.2001,106(A11)pp.2[28]GleisnerH.,Lundsdatausingtime-delayneuralnetwor[29]GleisnerH.,LundstedtH.,WintoftP.Theresponseoftheauroralelectrojwindmodelledwithneuralnetworks.J.Geophys.Res.1996[30]GoertzC.K.,ShanL.H.,SmithR.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