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116 TaylorDiagramdaylight/nighttime, day of the week, by levels of a numeric variable e.g. wind speed or by land-usetype etc.To consider several pollutants on one plot, a column identifying the pollutant name can be used e.g.pollutant. Then the Taylor Diagram can be plotted as (assuming a data frame thedata):TaylorDiagram(thedata, obs = "obs", mod = "mod",which will give the model performance by pollutant in each panel.group = "model", type = "pollutant")Note that it is important that each panel represents data with the same mean observed data acrossdifferent groups. Therefore TaylorDiagram(mydata, group = "model", type = "season")is OK, whereas TaylorDiagram(mydata, group = "season", type = "model") is not becauseeach panel (representing a model) will have four different mean values — one for each season.Generally, the option group is either missing (one model being evaluated) or represents a columngiving the model name. However, the data can be normalised using the normalise option. Normalisationis carried out on a per group/type basis making it possible to compare data on different scalese.g. TaylorDiagram(mydata, group = "season", type = "model", normalise = TRUE).In this way it is possible to compare different pollutants, sites etc. in the same panel.Also note that if multiple sites are present it makes sense to use type = "site" to ensure that eachpanel represents an individual site with its own specific standard deviation etc. If this is not the casethen select a single site from the data first e.g. subset(mydata, site == "Harwell").ValueAs well as generating the plot itself, TaylorDiagram also returns an object of class “openair”. Theobject includes three main components: call, the command used to generate the plot; data, the dataframe of summarised information used to make the plot; and plot, the plot itself. If retained, e.g.using output
TaylorDiagram 117See Alsotaylor.diagram from the plotrix package from which some of the annotation code was used.Examples## in the examples below, most effort goes into making some artificial data## the function itself can be run very simply## dummy model data for 2003dat
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Package ‘openair’September 19,
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4 aqStatsused. All functions check
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6 calcFno2Examples## Statistics for
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8 calcPercentilecalcPercentileCalcu
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10 calendarPlotannotatestatisticcol
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14 conditionalEvalon to cutData to
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16 conditionalQuantileArgumentsmyda
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18 corPlot## make some dummy predic
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20 cutDataSee Alsotaylor.diagram fr
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22 drawOpenKeyof this option is to
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24 drawOpenKeyvpView port to be use
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26 GoogleMapsPlotcex.range = c(2, 1
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28 GoogleMapsPlotDetailsValueNoteke
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30 importtimetime.formattz.intz.out
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32 importADMSdrop.input.datesOption
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34 importAURNimportAURNAURN data im
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36 importAURN• BIR2 Birmingham Ea
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38 importAURN• ISL London Islingt
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40 importAURNValue• WBRO Sandwell
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42 importAURNCsvis.siteHeader name
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44 importKCL## diurnal.error(so2.15
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46 importKCLAll PM10 statistics on
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48 importKCL• BY1 | Bromley - Ren
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50 importKCL• GL1 | Glasgow Centr
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52 importKCL• LB4 | Lambeth - Bri
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54 importKCL• RG4 | Reigate and B
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56 importKCL• TE0 | Tendring St O
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58 importKCLValue• ZT4 | Tunbridg
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60 importSAQNExamples## import AQ d
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62 importSAQN• | ABD8 | Aberdeen
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64 importSAQN• | PAI3 | Paisley G
Page 66 and 67: 66 importTrajlocalfor example.Used
Page 68 and 69: 68 kernelExceedpollutant Mandatory.
Page 70 and 71: 70 linearRelationlinearRelationLine
Page 72 and 73: 72 modStatsSee AlsocalcFno2Examples
Page 74 and 75: 74 mydataReferencesWillmott, C.J.,
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Page 78 and 79: 78 openColoursnNote that because of
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Page 82 and 83: 82 polarAnnulusnormalise = FALSE, k
Page 84 and 85: 84 polarAnnuluskey.footerkey.positi
Page 86 and 87: 86 polarClustercolsDetailsangle.sca
Page 88 and 89: 88 polarFreq## how many points are
Page 90 and 91: 90 polarFreqborder.colThe colour of
Page 92 and 93: 92 polarPlotDescriptionFunction for
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Page 96 and 97: 96 polarPlotValueAs well as generat
Page 98 and 99: 98 rollingMeanExamples#example 1##s
Page 100 and 101: 100 scatterPlotavg.timedata.threshs
Page 102 and 103: 102 scatterPlot... Other graphical
Page 104 and 105: 104 selectByDate## multiple types a
Page 106 and 107: 106 selectRunningselectRunningFunct
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Page 110 and 111: 110 splitByDate# several pollutants
Page 112 and 113: 112 summaryPlotpollutantperiodbreak
Page 114 and 115: 114 TaylorDiagramUsageTaylorDiagram
Page 118 and 119: 118 TheilSen## Not run:## all model
Page 120 and 121: 120 TheilSenDetailsdate.breaks- 1)
Page 122 and 123: 122 timeAverageTheilSen(mydata, pol
Page 124 and 125: 124 timePlotAuthor(s)David CarslawS
Page 126 and 127: 126 timePlottypecolsplot.typekeylog
Page 128 and 129: 128 timePlotAuthor(s)David CarslawS
Page 130 and 131: 130 timeVariationtypegroupdifferenc
Page 132 and 133: 132 timeVariationAuthor(s)David Car
Page 134 and 135: 134 trajClustertypecolssplit.aftert
Page 136 and 137: 136 trajLevelsmoothstatisticpercent
Page 138 and 139: 138 trendLevelkc1 -20 & lon 40 & l
Page 140 and 141: 140 trendLeveldrop.unused.typesHide
Page 142 and 143: 142 windRosews.intThe Wind speed in
Page 144 and 145: 144 windRoseValueNoteset of wind sp
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