hailfinder: The HailFinder weather forecast system (synthetic) data set

In vspinu/bnlearn: Bayesian network structure learning, parameter learning and inference

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 levels StrongUp, WeakUp, Neutral and Down.

• SubjVertMo (subjective judgment of vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down.

• QGVertMotion (quasigeostrophic vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down.

• CombVerMo (combined vertical motion): a four-level factor with levels StrongUp, WeakUp, Neutral and Down.

• AreaMesoALS (area of meso-alpha): a four-level factor with levels StrongUp, WeakUp, Neutral and Down.

• SatContMoist (satellite contribution to moisture): a four-level factor with levels VeryWet, Wet, Neutral and Dry.

• RaoContMoist (reading at the forecast center for moisture): a four-level factor with levels VeryWet, Wet, Neutral and Dry.

• CombMoisture (combined moisture): a four-level factor with levels VeryWet, Wet, Neutral and Dry.

• AreaMoDryAir (area of moisture and adry air): a four-level factor with levels VeryWet, Wet, Neutral and Dry.

• VISCloudCov (visible cloud cover): a three-level factor with levels Cloudy, PC and Clear.

• IRCloudCover (infrared cloud cover): a three-level factor with levels Cloudy, PC and Clear.

• CombClouds (combined cloud cover): a three-level factor with levels Cloudy, PC and Clear.

• CldShadeOth (cloud shading, other): a three-level factor with levels Cloudy, PC and Clear.

• AMInstabMt (AM instability in the mountains): a three-level factor with levels None, Weak and Strong.

• InsInMt (instability in the mountains): a three-level factor with levels None, Weak and Strong.

• WndHodograph (wind hodograph): a four-level factor with levels DCVZFavor, StrongWest, Westerly and Other.

• OutflowFrMt (outflow from mountains): a three-level factor with levels None, Weak and Strong.

• MorningBound (morning boundaries): a three-level factor with levels None, Weak and Strong.

• Boundaries (boundaries): a three-level factor with levels None, Weak and Strong.

• CldShadeConv (cloud shading, convection): a three-level factor with levels None, Some and Marked.

• CompPlFcst (composite plains forecast): a three-level factor with levels IncCapDecIns, LittleChange and DecCapIncIns.

• CapChange (capping change): a three-level factor with levels Decreasing, LittleChange and Increasing.

• LoLevMoistAd (low-level moisture advection): a four-level factor with levels StrongPos, WeakPos, Neutral and Negative.

• InsChange (instability change): three-level factor with levels Decreasing, LittleChange and Increasing.

• MountainFcst (mountains (region 1) forecast): a three-level factor with levels XNIL, SIG and SVR.

• Date (date): a six-level factor with levels May15_Jun14, Jun15_Jul1, Jul2_Jul15, Jul16_Aug10, Aug11_Aug20 and Aug20_Sep15.

• Scenario (scenario): an eleven-level factor with levels A, B, C, D, E, F, G, H, I, J and K.

• ScenRelAMCIN (scenario relevant to AM convective inhibition): a two-level factor with levels AB and CThruK.

• MorningCIN (morning convective inhibition): a four-level factor with levels None, PartInhibit, Stifling and TotalInhibit.

• AMCINInScen (AM convective inhibition in scenario): a three-level factor with levels LessThanAve, Average and MoreThanAve.

• CapInScen (capping withing scenario): a three-level factor with levels LessThanAve, Average and MoreThanAve.

• ScenRelAMIns (scenario relevant to AM instability): a six-level factor with levels ABI, CDEJ, F, G, H and K.

• LIfr12ZDENSd (LI from 12Z DEN sounding): a four-level factor with levels LIGt0, N1GtLIGt_4, N5GtLIGt_8 and LILt_8.

• AMDewptCalPl (AM dewpoint calculations, plains): a three-level factor with levels Instability, Neutral and Stability.

• AMInsWliScen (AM instability within scenario): a three-level factor with levels LessUnstable, Average and MoreUnstable.

• InsSclInScen (instability scaling within scenario): a three-level factor with levels LessUnstable, Average and MoreUnstable.

• ScenRel34 (scenario relevant to regions 2/3/4): a five-level factor with levels ACEFK, B, D, GJ and HI.

• LatestCIN (latest convective inhibition): a four-level factor with levels None, PartInhibit, Stifling and TotalInhibit.

• LLIW (LLIW severe weather index): a four-level factor with levels Unfavorable, Weak, Moderate and Strong.

• CurPropConv (current propensity to convection): a four-level factor with levels None, Slight, Moderate and Strong.

• ScnRelPlFcst (scenario relevant to plains forecast): an eleven-level factor with levels A, B, C, D, E, F, G, H, I, J and K.

• PlainsFcst (plains forecast): a three-level factor with levels XNIL, SIG and SVR.

• N34StarFcst (regions 2/3/4 forecast): a three-level factor with levels XNIL, SIG and SVR.

• R5Fcst (region 5 forecast): a three-level factor with levels XNIL, SIG and SVR.

• Dewpoints (dewpoints): a seven-level factor with levels LowEverywhere, LowAtStation, LowSHighN, LowNHighS, LowMtsHighPl, HighEverywher, Other.

• LowLLapse (low-level lapse rate): a four-level factor with levels CloseToDryAd, Steep, ModerateOrLe and Stable.

• MeanRH (mean relative humidity): a three-level factor with levels VeryMoist, Average and Dry.

• MidLLapse (mid-level lapse rate): a three-level factor with levels CloseToDryAd, Steep and ModerateOrLe.

• MvmtFeatures (movement of features): a four-level factor with levels StrongFront, MarkedUpper, OtherRapid and NoMajor.

• RHRatio (realtive humidity ratio): a three-level factor with levels MoistMDryL, DryMMoistL and other.

• SfcWndShfDis (surface wind shifts and discontinuities): a seven-level factor with levels DenvCyclone, E_W_N, E_W_S, MovigFtorOt, DryLine, None and Other.

• SynForcng (synoptic forcing): a five-level factor with levels SigNegative, NegToPos, SigPositive, PosToNeg and LittleChange.

• TempDis (temperature discontinuities): a four-level factor with levels QStationary, Moving, None, Other.

• WindAloft (wind aloft): a four-level factor with levels LV, SWQuad, NWQuad, AllElse.

• WindFieldMt (wind fields, mountains): a two-level factor with levels Westerly and LVorOther.

• WindFieldPln (wind fields, plains): a six-level factor with levels LV, DenvCyclone, LongAnticyc, E_NE, SEquad and WidespdDnsl.

Note

The complete BN can be downloaded from http://www.bnlearn.com/bnrepository.

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/site/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][N34StarFcst|ScenRel34:PlainsFcst]",
  "[CompPlFcst|AreaMesoALS:CldShadeOth:Boundaries:CldShadeConv][CapChange|CompPlFcst]",
  "[InsChange|CompPlFcst:LoLevMoistAd][CapInScen|CapChange:AMCINInScen]",
  "[InsSclInScen|InsChange:AMInsWliScen][R5Fcst|MountainFcst:N34StarFcst]",
  "[PlainsFcst|CapInScen:InsSclInScen:CurPropConv:ScnRelPlFcst]",
  sep = "")
## Not run: 
# there are too many nodes for plot(), use graphviz.plot().
graphviz.plot(res)
## End(Not run)

vspinu/bnlearn documentation built on May 3, 2019, 7:08 p.m.