18 - use case: longest time series in Berlin

18.1 select station

Choose station in Berlin with longest monthly average recordings (according to metadata, which is not always correct).

ids <- findID("Berlin", exactmatch=FALSE)
head(ids)

##    Berlin (Rosenthal)    Berlin Brandenburg      Berlin-Adlershof 
##                   394                   427                   395 
## Berlin-Alexanderplatz           Berlin-Buch Berlin-Charlottenburg 
##                   399                   400                   401

data("metaIndex")
berlin <- metaIndex[with(metaIndex, 
              Stations_id %in% ids & res=="monthly" & var=="kl" & per=="historical"),]
berlin$ndays <- as.numeric(berlin$bis_datum - berlin$von_datum)
berlin <- berryFunctions::sortDF(berlin, ndays)
berlin$von_datum <- as.character(berlin$von_datum) # avoid huxtable error
berlin$bis_datum <- as.character(berlin$bis_datum)
berlin # Dahlem (FU) has data since 1719 !

Stations_id	von_datum	bis_datum	Stationshoehe	geoBreite	geoLaenge	Stationsname	Bundesland	res	var	per	hasfile	ndays
403	1719-01-01	2023-08-31	51	52.5	13.3	Berlin-Dahlem (FU)	Berlin	monthly	kl	historical	TRUE	1.11e+05
400	1889-01-01	2023-08-31	60	52.6	13.5	Berlin-Buch	Berlin	monthly	kl	historical	TRUE	4.92e+04
402	1830-01-01	1962-12-31	55	52.5	13.3	Berlin-Dahlem (LFAG)	Berlin	monthly	kl	historical	TRUE	4.86e+04
429	1890-07-01	1987-01-31	32	52.6	13.2	Berlin-Spandau	Berlin	monthly	kl	historical	TRUE	3.53e+04
433	1938-01-01	2023-08-31	48	52.5	13.4	Berlin-Tempelhof	Berlin	monthly	kl	historical	TRUE	3.13e+04
424	1901-01-01	1980-12-31	36	52.5	13.5	Berlin-Ostkreuz	Berlin	monthly	kl	historical	TRUE	2.92e+04
422	1892-01-01	1964-12-31	35	52.5	13.4	Berlin-Mitte	Berlin	monthly	kl	historical	TRUE	2.67e+04
3147	1951-03-01	2023-08-31	390	48.8	12.2	Mallersdorf-Pfaffenberg-Oberlindhart	Bayern	monthly	kl	historical	TRUE	2.65e+04
408	1883-01-01	1951-11-30	35	52.5	13.4	Berlin-Invalidenstrasse	Berlin	monthly	kl	historical	TRUE	2.52e+04
427	1957-01-01	2023-08-31	46	52.4	13.5	Berlin Brandenburg	Brandenburg	monthly	kl	historical	TRUE	2.43e+04
430	1961-01-01	2021-04-30	36	52.6	13.3	Berlin-Tegel	Berlin	monthly	kl	historical	TRUE	2.2e+04
5138	1945-01-01	2003-12-31	446	47.8	9.16	Ueberlingen/Bodensee	Baden-Wuerttemberg	monthly	kl	historical	TRUE	2.15e+04
435	1964-01-01	2006-12-31	45	52.4	13.2	Berlin-Zehlendorf	Berlin	monthly	kl	historical	TRUE	1.57e+04
399	1975-01-01	2015-05-31	36	52.5	13.4	Berlin-Alexanderplatz	Berlin	monthly	kl	historical	TRUE	1.48e+04
425	1946-01-01	1982-06-30	38	52.4	13.5	Berlin-Rudow	Berlin	monthly	kl	historical	TRUE	1.33e+04
420	1993-05-01	2023-07-31	61	52.5	13.6	Berlin-Marzahn	Berlin	monthly	kl	historical	TRUE	1.1e+04
417	1930-09-01	1956-10-31	43	52.4	13.3	Berlin-Lichterfelde (Sued)	Berlin	monthly	kl	historical	TRUE	9.56e+03
410	1996-06-01	2020-05-31	33	52.4	13.7	Berlin-Kaniswall	Berlin	monthly	kl	historical	TRUE	8.76e+03
407	1958-01-01	1978-03-31	48	52.6	13.3	Berlin-Frohnau	Berlin	monthly	kl	historical	TRUE	7.39e+03
432	1978-04-01	1994-12-31	36	52.6	13.3	Berlin-Tegeler Fliesstal	Berlin	monthly	kl	historical	TRUE	6.12e+03
416	1982-07-01	1996-09-30	47	52.4	13.4	Berlin-Lichtenrade	Berlin	monthly	kl	historical	TRUE	5.20e+03
434	1947-01-01	1960-12-31	35	52.5	13.5	Berlin-Treptow	Berlin	monthly	kl	historical	TRUE	5.11e+03
395	1948-07-01	1953-12-31	38	52.4	13.5	Berlin-Adlershof	Berlin	monthly	kl	historical	TRUE	2.01e+03
405	1951-04-01	1954-12-31	37	52.5	13.7	Berlin-Friedrichshagen	Berlin	monthly	kl	historical	TRUE	1.37e+03

18.2 download and inspect data

url <- selectDWD("Berlin-Dahlem (FU)", res="monthly", var="kl", per="h")
kl <- dataDWD(url, varnames=TRUE)
plot(kl$MESS_DATUM, kl$MO_TT.Lufttemperatur, type="l", las=1) # pretty complete

18.3 aggregates by month

monthly <- tapply(kl$MO_TT.Lufttemperatur, format(kl$MESS_DATUM,"%m"), quantile, probs=0:10/10)
monthly <- sapply(monthly, I)

plot(1, type="n", xlim=c(1,12), ylim=range(monthly), xaxt="n", las=1, 
     xlab="Vis by Berry B, github.com/brry/rdwd", ylab="monthly temperature average",
     main="Temperature variation in Berlin is highest in winter")
axis(1, 2:12-0.5, labels=FALSE)
axis(1, 1:12, substr(month.abb,1,1), tick=FALSE, line=-0.5)
for(m in 1:12) for(q in 1:5) lines(c(m,m), monthly[c(q,12-q),m], lend=1, 
                                   col=berryFunctions::addAlpha("red",0.2), lwd=5)
for(m in 1:12) points(m, mean(monthly[,m]), pch=3)