Version 45 (modified by juaco, 8 years ago) (diff)

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Total precipitation at the Gulf of Guinea for January 2010 forecasted in October 2009 (lead month 3) by the System4 model (seasonal range, 15 members) is next represented for each member, using the spplot method for the SpatialGridDataFrame class of library sp:

Data are loaded by introducing the required values for dataset, spatio-temporal window and lead month definition. Note that the argument members is omitted, which means that by default all available members (15 in this case, will be returned).

> gg.pr <- loadSeasonalForecast("System4_seasonal_15", var="tp", lonLim=c(-30,20),


names(gg.pr)
str(gg.pr$MemberData)  pr.list <- lapply(1:length(gg.pr$MemberData), function(x) colSums(gg.pr$MemberData[[x]])) df <- do.call("data.frame", pr.list) names(df) <- names(gg.pr$MemberData)

class(gg.pr$LonLatCoords) sgdf <- SpatialGridDataFrame(gg.pr$LonLatCoords, df)

spplot(sgdf, scales=list(draw = TRUE), col.regions = rev(terrain.colors(50)), at = seq(0, ceiling(max(sgdf@data)),10))


It is often useful to have a world map underneath as a visual reference

> data(world_map)
> wl <- as(world_map, "SpatialLines")
> l1 <- list("sp.lines", wl)


Suppose we are interested in the visualization of four particular members, forecasting a particularly high precipitation over the southern region. We can choose which ones to display using the zcol argument:

> spplot(sgdf, zcol = c(4,9,13,14), scales=list(draw = TRUE), col.regions = rev(terrain.colors(50)),
+ at = seq(0, ceiling(max(sgdf@data)),10), sp.layout = list(l1))