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Data output complete

Here Is the Entire Analysis in  20 lines or so

source(“Global.R”)

Land<-getLandMask()

invOBJ<-loadGridInventory(getwd())

anomOBJ<-loadAnomalies(getwd())

Data<-intersect.InvAnomalies(invOBJ$Data,anomOBJ$Data)

Anom<-Data$Anomalies

Inv<-Data$GridInventory

CellMatrix<-as.GridCells(Anom,Inv)

AreaAdjusted<-CellMatrix*gridWeight(CellMatrix,Land,LAND.MASK)

AreaAdjusted<-zoo(t(AreaAdjusted),order.by=timeline,frequency=12)

AnnualArea<-annualAreaAnomaly(CellMatrix,timeline)

MonthlyTemp<-monthlyAnomaly(AreaAdjusted,timeline)

YearlyTemp<-yearlyAnomaly(MonthlyTemp,timeline)

MonthStats<-monthlyStatistics(CellMatrix,Land)

CellStats<-getCellStats(CellMatrix,Land,Inv)

StationCount<-stationCount(Anom)

That creates the data for drawing the monthly chart, the yearly chart, station count chart,a 2D area anomaly chart and 2 files of stats.

> MonthStats
Cells     Area
Jan 1900   491 34230211
Feb 1900   492 34294050
Mar 1900   497 34650684
Apr 1900   499 34843699
May 1900   500 34872124
Jun 1900   497 34664808
Jul 1900   496 34663835
Aug 1900   494 34615935
Sep 1900   496 34859375
Oct 1900   496 34761678
Nov 1900   494 34588699
Dec 1900   495 34727228
Jan 1901   489 34099445

> CellStats

Cell_Id Xres Yres   Lat    Lon      Area  Pct      Land MaxMonths Months StationCount

1        280    3    3  82.5  -61.5   3671.28 0.25    917.82      1320    528            1

2        386    3    3  79.5 -103.5   5328.92 0.26   1385.52      1320   1293            1

3        392    3    3  79.5  -85.5  13435.21 0.66   8867.24      1320   1168            1

4        425    3    3  79.5   13.5   8512.73 0.42   3575.35      1320    672            1

5        440    3    3  79.5   58.5   3861.21 0.19    733.63      1320    911            1

6        446    3    3  79.5   76.5    812.89 0.04     32.52      1320    349            1

7        501    3    3  76.5 -118.5  10413.18 0.40   4165.27      1320    350            1

8        518    3    3  76.5  -67.5  11107.39 0.43   4776.18      1320    980            1

9        534    3    3  76.5  -19.5  11020.61 0.42   4628.66      1320    373            1

10       568    3    3  76.5   82.5   1561.98 0.06     93.72      1320    463            1

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