You’ll have already felt this, but here’s a bit of encouragement about the number of diving days as we progress through Cape Town’s brief autumn (OK, I think we’ve already done that) and into winter proper. The average wind speed has dropped, and more and more of the day – on average – is relatively windless. Is there a historical precedent that we can appeal to, and conclude that the weather in late autumn and early winter will be good for diving?
I don’t have a precedent going back more than one year, which may cause you to question conclusions based on it, but I offer it to you anyway. The slice of pie shown below was calculated from our home weather station wind measurements, taken in April, May and June 2014. It shows the average wind speed during each of those months, at each hour of the day. (I’ve previously shown you some other information derived from these same measurements, here.)
We can learn several things from this segment of a circular chart. First, the daily average wind speed during any hourly period in April-June 2014 didn’t get much above 8 knots, which is about 15 km/h. Of course the wind did blow stronger (and less strongly) than this, but this is a chart of the average. Looking at where those bright green slices are on the chart, we can see that during these months, it’s windiest between the hours of 7am and 2pm (just when you want to go diving). Finally, you can see that April was windier than May, and May was windier than June (less green, less yellow, more beige). So conditions for being out on and in the ocean improved as we moved further into winter 2014.
Is it fair to infer something – an expectation – about winter 2015 from this chart? I think it wouldn’t be unreasonable to do so, as long as you’re not too dogmatic about it.
A note on the graph
This is a slice (manually edited out of the original) of a circular plot that I did using code cannibalised and modified from Jason and Doug’s Penang climate blog. I had to reverse the labels for the times of day because I’m only showing you the bottom of the circle. The meat of the plotting function looks like this (thanks to Pretty R):
ggplot(df_summarised, aes(x=month, y=hour, fill=speed)) + geom_tile(colour="grey70") + scale_fill_gradientn(colours = rev(topo.colors(7)),name="Wind Speed\n(knots)\n")+ scale_y_continuous(breaks = seq(0,23), labels=c("12.00am","1:00am","2:00am","3:00am","4:00am","5:00am","6:00am","7:00am","8:00am","9:00am","10:00am","11:00am","12:00pm", "1:00pm","2:00pm","3:00pm","4:00pm","5:00pm","6:00pm","7:00pm","8:00pm","9:00pm","10:00pm","11:00pm")) + coord_polar(theta="x") + ylab("HOUR OF DAY")+ xlab("")+ ggtitle("Wind Speed by month and time of day")+ theme(panel.background=element_blank(), axis.title.y=element_text(size=10,hjust=0.75,colour="grey20"), axis.title.x=element_text(size=7,colour="grey20"), panel.grid=element_blank(), axis.ticks=element_blank(), axis.text.y=element_text(size=5,colour="grey20"), axis.text.x=element_text(size=10,colour="grey20",face="bold"), plot.title = element_text(lineheight=1.2, face="bold",size = 14, colour = "grey20"), plot.margin = unit(c(-0.25,0.25,-1,0.25), "in"), legend.key.width=unit(c(0.2,0.2),"in"))
I didn’t want to put the entire year’s data up here in a full circular plot because I think it’s a little too useful to share, if you know what I mean! You can see what a complete plot looks like on Jason and Doug’s blog – examples here and here.
