bnlearn (version 2.0)

hailfinder: The HailFinder weather forecast system

Description

Hailfinder is a Bayesian network designed to forecast severe summer hail in northeastern Colorado.

Usage

data(hailfinder)

format

The hailfinder data set contains the following 56 variables:

• N07muVerMo(10.7mu vertical motion): a four-level factor with levelsStrongUp,WeakUp,NeutralandDown.
• SubjVertMo(subjective judgment of vertical motion): a four-level factor with levelsStrongUp,WeakUp,NeutralandDown.
• QGVertMotion(quasigeostrophic vertical motion): a four-level factor with levelsStrongUp,WeakUp,NeutralandDown.
• CombVerMo(combined vertical motion): a four-level factor with levelsStrongUp,WeakUp,NeutralandDown.
• AreaMesoALS(area of meso-alpha): a four-level factor with levelsStrongUp,WeakUp,NeutralandDown.
• SatContMoist(satellite contribution to moisture): a four-level factor with levelsVeryWet,Wet,NeutralandDry.
• RaoContMoist(reading at the forecast center for moisture): a four-level factor with levelsVeryWet,Wet,NeutralandDry.
• CombMoisture(combined moisture): a four-level factor with levelsVeryWet,Wet,NeutralandDry.
• AreaMoDryAir(area of moisture and adry air): a four-level factor with levelsVeryWet,Wet,NeutralandDry.
• VISCloudCov(visible cloud cover): a three-level factor with levelsCloudy,PCandClear.
• IRCloudCover(infrared cloud cover): a three-level factor with levelsCloudy,PCandClear.
• CombClouds(combined cloud cover): a three-level factor with levelsCloudy,PCandClear.
• CldShadeOth(cloud shading, other): a three-level factor with levelsCloudy,PCandClear.
• AMInstabMt(AM instability in the mountains): a three-level factor with levelsNone,WeakandStrong.
• InsInMt(instability in the mountains): a three-level factor with levelsNone,WeakandStrong.
• WndHodograph(wind hodograph): a four-level factor with levelsDCVZFavor,StrongWest,WesterlyandOther.
• OutflowFrMt(outflow from mountains): a three-level factor with levelsNone,WeakandStrong.
• MorningBound(morning boundaries): a three-level factor with levelsNone,WeakandStrong.
• Boundaries(boundaries): a three-level factor with levelsNone,WeakandStrong.
• CldShadeConv(cloud shading, convection): a three-level factor with levelsNone,SomeandMarked.
• CompPlFcst(composite plains forecast): a three-level factor with levelsIncCapDecIns,LittleChangeandDecCapIncIns.
• CapChange(capping change): a three-level factor with levelsDecreasing,LittleChangeandIncreasing.
• LoLevMoistAd(low-level moisture advection): a four-level factor with levelsStrongPos,WeakPos,NeutralandNegative.
• InsChange(instability change): three-level factor with levelsDecreasing,LittleChangeandIncreasing.
• MountainFcst(mountains (region 1) forecast): a three-level factor with levelsXNIL,SIGandSVR.
• Date(date): a six-level factor with levelsMay15_Jun14,Jun15_Jul1,Jul2_Jul15,Jul16_Aug10,Aug11_Aug20andAug20_Sep15.
• Scenario(scenario): an eleven-level factor with levelsA,B,C,D,E,F,G,H,I,JandK.
• ScenRelAMCIN(scenario relevant to AM convective inhibition): a two-level factor with levelsABandCThruK.
• MorningCIN(morning convective inhibition): a four-level factor with levelsNone,PartInhibit,StiflingandTotalInhibit.
• AMCINInScen(AM convective inhibition in scenario): a three-level factor with levelsLessThanAve,AverageandMoreThanAve.
• CapInScen(capping withing scenario): a three-level factor with levelsLessThanAve,AverageandMoreThanAve.
• ScenRelAMIns(scenario relevant to AM instability): a six-level factor with levelsABI,CDEJ,F,G,HandK.
• LIfr12ZDENSd(LI from 12Z DEN sounding): a four-level factor with levelsLIGt0,N1GtLIGt_4,N5GtLIGt_8andLILt_8.
• AMDewptCalPl(AM dewpoint calculations, plains): a three-level factor with levelsInstability,NeutralandStability.
• AMInsWliScen(AM instability within scenario): a three-level factor with levelsLessUnstable,AverageandMoreUnstable.
• InsSclInScen(instability scaling within scenario): a three-level factor with levelsLessUnstable,AverageandMoreUnstable.
• ScenRel34(scenario relevant to regions 2/3/4): a five-level factor with levelsACEFK,B,D,GJandHI.
• LatestCIN(latest convective inhibition): a four-level factor with levelsNone,PartInhibit,StiflingandTotalInhibit.
• LLIW(LLIW severe weather index): a four-level factor with levelsUnfavorable,Weak,ModerateandStrong.
• CurPropConv(current propensity to convection): a four-level factor with levelsNone,Slight,ModerateandStrong.
• ScnRelPlFcst(scenario relevant to plains forecast): an eleven-level factor with levelsA,B,C,D,E,F,G,H,I,JandK.
• PlainsFcst(plains forecast): a three-level factor with levelsXNIL,SIGandSVR.
• N34StarFcst(regions 2/3/4 forecast): a three-level factor with levelsXNIL,SIGandSVR.
• R5Fcst(region 5 forecast): a three-level factor with levelsXNIL,SIGandSVR.
• Dewpoints(dewpoints): a seven-level factor with levelsLowEverywhere,LowAtStation,LowSHighN,LowNHighS,LowMtsHighPl,HighEverywher,Other.
• LowLLapse(low-level lapse rate): a four-level factor with levelsCloseToDryAd,Steep,ModerateOrLeandStable.
• MeanRH(mean relative humidity): a three-level factor with levelsVeryMoist,AverageandDry.
• MidLLapse(mid-level lapse rate): a three-level factor with levelsCloseToDryAd,SteepandModerateOrLe.
• MvmtFeatures(movement of features): a four-level factor with levelsStrongFront,MarkedUpper,OtherRapidandNoMajor.
• RHRatio(realtive humidity ratio): a three-level factor with levelsMoistMDryL,DryMMoistLandother.
• SfcWndShfDis(surface wind shifts and discontinuities): a seven-level factor with levelsDenvCyclone,E_W_N,E_W_S,MovigFtorOt,DryLine,NoneandOther.
• SynForcng(synoptic forcing): a five-level factor with levelsSigNegative,NegToPos,SigPositive,PosToNegandLittleChange.
• TempDis(temperature discontinuities): a four-level factor with levelsQStationary,Moving,None,Other.
• WindAloft(wind aloft): a four-level factor with levelsLV,SWQuad,NWQuad,AllElse.
• WindFieldMt(wind fields, mountains): a two-level factor with levelsWesterlyandLVorOther.
• WindFieldPln(wind fields, plains): a six-level factor with levelsLV,DenvCyclone,LongAnticyc,E_NE,SEquadandWidespdDnsl.

source

Abramson B, Brown J, Edwards W, Murphy A, Winkler RL (1996). "Hailfinder: A Bayesian system for forecasting severe weather". International Journal of Forecasting, 12(1), 57-71.

Elidan G (2001). "Bayesian Network Repository". http://www.cs.huji.ac.il/labs/compbio/Repository/.

Examples

# load the data and build the correct network from the model string.
data(hailfinder)
res = empty.graph(names(hailfinder))
modelstring(res) = paste("[N07muVerMo][SubjVertMo][QGVertMotion][SatContMoist]",
  "[RaoContMoist][VISCloudCov][IRCloudCover][AMInstabMt][WndHodograph]",
  "[MorningBound][LoLevMoistAd][Date][MorningCIN][LIfr12ZDENSd][AMDewptCalPl]",
  "[LatestCIN][LLIW][CombVerMo|N07muVerMo:SubjVertMo:QGVertMotion]",
  "[CombMoisture|SatContMoist:RaoContMoist][CombClouds|VISCloudCov:IRCloudCover]",
  "[Scenario|Date][CurPropConv|LatestCIN:LLIW][AreaMesoALS|CombVerMo]",
  "[ScenRelAMCIN|Scenario][ScenRelAMIns|Scenario][ScenRel34|Scenario]",
  "[ScnRelPlFcst|Scenario][Dewpoints|Scenario][LowLLapse|Scenario]",
  "[MeanRH|Scenario][MidLLapse|Scenario][MvmtFeatures|Scenario][RHRatio|Scenario]",
  "[SfcWndShfDis|Scenario][SynForcng|Scenario][TempDis|Scenario]",
  "[WindAloft|Scenario][WindFieldMt|Scenario][WindFieldPln|Scenario]",
  "[AreaMoDryAir|AreaMesoALS:CombMoisture][AMCINInScen|ScenRelAMCIN:MorningCIN]",
  "[AMInsWliScen|ScenRelAMIns:LIfr12ZDENSd:AMDewptCalPl]",
  "[CldShadeOth|AreaMesoALS:AreaMoDryAir:CombClouds][InsInMt|CldShadeOth:AMInstabMt]",
  "[OutflowFrMt|InsInMt:WndHodograph][CldShadeConv|InsInMt:WndHodograph]",
  "[MountainFcst|InsInMt][Boundaries|WndHodograph:OutflowFrMt:MorningBound]",
  "[CompPlFcst|AreaMesoALS:CldShadeOth:Boundaries:CldShadeConv]",
  "[CapChange|CompPlFcst][InsChange|CompPlFcst:LoLevMoistAd]",
  "[CapInScen|CapChange:AMCINInScen][InsSclInScen|InsChange:AMInsWliScen]",
  "[PlainsFcst|CapInScen:InsSclInScen:CurPropConv:ScnRelPlFcst]",
  "[N34StarFcst|ScenRel34:PlainsFcst][R5Fcst|MountainFcst:N34StarFcst]",
  sep = "")
# there are too many nodes for plot(), use graphviz.plot().
graphviz.plot(res)