Temperatur in Würzburg

library(tidyverse)

Warning message in system("timedatectl", intern = TRUE):
“running command 'timedatectl' had status 1”
── Attaching packages ─────────────────────────────────────── tidyverse 1.3.1 ──

✔ ggplot2 3.3.5     ✔ purrr   0.3.4
✔ tibble  3.1.4     ✔ dplyr   1.0.7
✔ tidyr   1.1.3     ✔ stringr 1.4.0
✔ readr   2.0.1     ✔ forcats 0.5.1

── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::filter() masks stats::filter()
✖ dplyr::lag()    masks stats::lag()

library(lubridate)

Attaching package: ‘lubridate’


The following objects are masked from ‘package:base’:

    date, intersect, setdiff, union

theme_set(theme_light())

data <- read_csv("data/data_OBS_DEU_PT1H_T2M.csv")

Rows: 790288 Columns: 6

── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr  (1): Produkt_Code
dbl  (3): SDO_ID, Wert, Qualitaet_Byte
dttm (1): Zeitstempel


ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

head(data)

Warning message:
“One or more parsing issues, see `problems()` for details”

A tibble: 6 × 6

Produkt_Code	SDO_ID	Zeitstempel	Wert	Qualitaet_Byte	Qualitaet_Niveau
<chr>	<dbl>	<dttm>	<dbl>	<dbl>	<dbl>
OBS_DEU_PT1H_T2M	2600	2005-03-01 00:00:00	-12.4	4	3
OBS_DEU_PT1H_T2M	2600	2005-03-01 01:00:00	-12.6	6	10
OBS_DEU_PT1H_T2M	2600	2005-03-01 02:00:00	-13.1	1	10
OBS_DEU_PT1H_T2M	2600	2005-03-01 03:00:00	-13.7	1	10
OBS_DEU_PT1H_T2M	2600	2005-03-01 04:00:00	-14.4	1	10
OBS_DEU_PT1H_T2M	2600	2005-03-01 05:00:00	-14.9	1	10

station <- read_csv("data/sdo_OBS_DEU_PT1H_T2M.csv")

Rows: 2 Columns: 6

── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (2): SDO_Name, Metadata_Link
dbl (2): SDO_ID, Hoehe_ueber_NN


ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

station

A spec_tbl_df: 2 × 6

SDO_ID	SDO_Name	Geogr_Laenge	Geogr_Breite	Hoehe_ueber_NN	Metadata_Link
<dbl>	<chr>	<dbl>	<dbl>	<dbl>	<chr>
5705	Würzburg	99576	497704	268	https://cdc.dwd.de/rest/metadata/station/html/812300016295
2600	Kitzingen	101781	497363	193	https://cdc.dwd.de/rest/metadata/station/html/812300321959

data <- data %>% mutate(SDO_ID = if_else(SDO_ID==2600, "Kitzingen", "Würzburg"))

Diesesmal schauen wir uns nur Daten aus Würzburg an

data <- data %>% filter(SDO_ID=="Würzburg")

Fragestellungen

• Was und wann war die wärmste/kälteste Temperatur die je in Würzburg gemessen wurde?
• Wann war der wärmste/kälteste Tag/Woche/Monat/Jahr in Würzburg?
• Was war die extremste Temperaturdifferenz innerhalb von 24h?
• Gibt es einen langfristigen Trend in den Temperaturdaten über die Zeit?
• Gibt es einen Hinweis darauf, dass sich die Jahreszeiten verschieben?

Wärmste/kälteste Temperatur

data %>% arrange(-Wert) %>% head

A tibble: 6 × 6

Produkt_Code	SDO_ID	Zeitstempel	Wert	Qualitaet_Byte	Qualitaet_Niveau
<chr>	<chr>	<dttm>	<dbl>	<dbl>	<dbl>
OBS_DEU_PT1H_T2M	Würzburg	2015-08-07 15:00:00	39.3	1	7
OBS_DEU_PT1H_T2M	Würzburg	2015-08-07 14:00:00	38.7	1	7
OBS_DEU_PT1H_T2M	Würzburg	2019-07-25 15:00:00	38.5	1	7
OBS_DEU_PT1H_T2M	Würzburg	2015-08-07 12:00:00	38.2	1	7
OBS_DEU_PT1H_T2M	Würzburg	2015-07-05 15:00:00	38.0	1	7
OBS_DEU_PT1H_T2M	Würzburg	2015-08-07 13:00:00	38.0	1	7

Die heißeste gemessene Temparatur in Würzburg gab es mit 39,3°C am 7. August 2015

data %>% arrange(Wert) %>% head

A tibble: 6 × 6

Produkt_Code	SDO_ID	Zeitstempel	Wert	Qualitaet_Byte	Qualitaet_Niveau
<chr>	<chr>	<dttm>	<dbl>	<dbl>	<dbl>
OBS_DEU_PT1H_T2M	Würzburg	1956-02-10 08:00:00	-23.4	0	5
OBS_DEU_PT1H_T2M	Würzburg	1956-02-10 07:00:00	-23.2	0	5
OBS_DEU_PT1H_T2M	Würzburg	1956-02-10 06:00:00	-23.1	0	5
OBS_DEU_PT1H_T2M	Würzburg	1956-02-10 05:00:00	-22.7	0	5
OBS_DEU_PT1H_T2M	Würzburg	1956-02-10 09:00:00	-22.6	0	5
OBS_DEU_PT1H_T2M	Würzburg	1956-02-10 04:00:00	-22.0	0	5

Die kälteste gemessene Temparatur in Würzburg gab es mit -23,4°C am 10. Februar 1956

Wärmster/kältester Tag/Woche/Monat/Jahr

Tag

data %>%
    mutate(tag = floor_date(Zeitstempel, unit="day")) %>%
    group_by(tag) %>%
    summarize(Wert=mean(Wert)) %>%
    arrange(-Wert) %>%
    head

A tibble: 6 × 2

tag	Wert
<dttm>	<dbl>
2015-08-07	30.33750
2019-07-25	30.22917
2015-07-04	30.08333
2019-07-26	29.79583
2003-08-13	29.18750
2015-07-05	29.02083

Der heißeste Tag war mit einer Tagesdurchschnittstemperatur von 30,3°C der 7. August 2015.

data %>%
    mutate(tag = floor_date(Zeitstempel, unit="day")) %>%
    group_by(tag) %>%
    summarize(Wert=mean(Wert)) %>%
    arrange(Wert) %>%
    head

A tibble: 6 × 2

tag	Wert
<dttm>	<dbl>
1956-02-01	-18.15833
1956-02-10	-16.99167
1985-01-08	-16.81667
1969-12-21	-16.77083
1968-01-13	-16.00833
1956-02-09	-15.61667

Der kälteste Tag war mit einer Tagesdurchschnittstemperatur von -18,2°C der 1. Februar 1956.

Größte Temperaturdifferenz in 24h

Erstmal innerhalb eines Tages (also von 0 bis 24Uhr)

data %>%
    mutate(tag = floor_date(Zeitstempel, unit="day")) %>%
    group_by(tag) %>%
    summarize(span=diff(range(Wert))) %>%
    arrange(-span) %>%
    head

A tibble: 6 × 2

tag	span
<dttm>	<dbl>
1968-01-14	24.9
1955-02-27	23.5
1962-09-03	23.4
1949-08-06	22.4
2003-05-05	22.4
1949-04-24	22.0

Am 14. Januar 1968 gab es innerhalb eines Tages einen Temperatur Unterschied von 24,9°C, wow!

data %>% filter(year(Zeitstempel)==1968, month(Zeitstempel)==1, day(Zeitstempel)==14) %>% ggplot(aes(Zeitstempel, Wert)) + geom_line()

Jetzt ordentlich in einem Sliding Window von 24h

library(slider)

data %>%
    mutate(span_last_24h = slide_index_dbl(Wert, Zeitstempel, ~diff(range(.x)), .before = lubridate::hours(23), .complete=TRUE)) %>%
    arrange(-span_last_24h)

A spec_tbl_df: 645879 × 7

Produkt_Code	SDO_ID	Zeitstempel	Wert	Qualitaet_Byte	Qualitaet_Niveau	span_last_24h
<chr>	<chr>	<dttm>	<dbl>	<dbl>	<dbl>	<dbl>
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 06:00:00	-16.8	0	5	26.1
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 07:00:00	-16.4	0	5	26.1
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 08:00:00	-16.2	0	5	26.1
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 09:00:00	-16.2	0	5	25.9
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 10:00:00	-16.3	0	5	25.9
OBS_DEU_PT1H_T2M	Würzburg	1968-01-14 22:00:00	7.1	0	5	25.6
OBS_DEU_PT1H_T2M	Würzburg	1968-01-14 21:00:00	7.0	0	5	25.5
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 05:00:00	-16.2	0	5	25.5
OBS_DEU_PT1H_T2M	Würzburg	1968-01-14 20:00:00	6.9	0	5	25.4
OBS_DEU_PT1H_T2M	Würzburg	1968-01-14 19:00:00	6.8	0	5	25.3
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 04:00:00	-15.8	0	5	25.1
OBS_DEU_PT1H_T2M	Würzburg	1968-01-14 23:00:00	5.8	0	5	24.9
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 11:00:00	-16.3	0	5	24.8
OBS_DEU_PT1H_T2M	Würzburg	1968-01-14 18:00:00	6.0	0	5	24.5
OBS_DEU_PT1H_T2M	Würzburg	1968-01-15 00:00:00	6.9	0	5	24.1
OBS_DEU_PT1H_T2M	Würzburg	1968-01-14 17:00:00	5.4	0	5	23.9
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 12:00:00	-15.3	0	5	23.7
OBS_DEU_PT1H_T2M	Würzburg	1968-01-15 03:00:00	7.8	0	5	23.7
OBS_DEU_PT1H_T2M	Würzburg	1968-01-15 01:00:00	7.1	0	5	23.6
OBS_DEU_PT1H_T2M	Würzburg	1968-01-15 04:00:00	8.0	0	5	23.6
OBS_DEU_PT1H_T2M	Würzburg	1979-01-01 03:00:00	-14.3	0	5	23.6
OBS_DEU_PT1H_T2M	Würzburg	1955-02-27 08:00:00	-11.7	0	5	23.5
OBS_DEU_PT1H_T2M	Würzburg	1955-02-27 09:00:00	-8.7	0	5	23.5
OBS_DEU_PT1H_T2M	Würzburg	1955-02-27 10:00:00	-5.3	0	5	23.5
OBS_DEU_PT1H_T2M	Würzburg	1955-02-27 11:00:00	-3.8	0	5	23.5
OBS_DEU_PT1H_T2M	Würzburg	1955-02-27 12:00:00	-2.6	0	5	23.5
OBS_DEU_PT1H_T2M	Würzburg	1955-02-27 13:00:00	-1.3	0	5	23.5
OBS_DEU_PT1H_T2M	Würzburg	1955-02-27 14:00:00	-1.2	0	5	23.5
OBS_DEU_PT1H_T2M	Würzburg	1955-02-27 15:00:00	-0.3	0	5	23.5
OBS_DEU_PT1H_T2M	Würzburg	1955-02-27 16:00:00	-0.8	0	5	23.5
⋮	⋮	⋮	⋮	⋮	⋮	⋮
OBS_DEU_PT1H_T2M	Würzburg	1978-12-04 15:00:00	0.1	0	5	0.3
OBS_DEU_PT1H_T2M	Würzburg	1953-12-12 13:00:00	5.2	0	5	0.3
OBS_DEU_PT1H_T2M	Würzburg	1953-12-12 14:00:00	5.3	0	5	0.2
OBS_DEU_PT1H_T2M	Würzburg	1987-11-28 10:00:00	2.0	0	7	0.2
OBS_DEU_PT1H_T2M	Würzburg	1987-11-28 11:00:00	2.0	0	7	0.2
OBS_DEU_PT1H_T2M	Würzburg	1987-11-28 12:00:00	2.0	0	7	0.2
OBS_DEU_PT1H_T2M	Würzburg	2019-09-10 10:00:00	14.7	6	7	0.0
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 01:00:00	-2.6	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 02:00:00	-1.9	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 03:00:00	-1.7	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 04:00:00	-1.0	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 05:00:00	-0.6	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 06:00:00	-0.5	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 07:00:00	-0.6	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 08:00:00	-0.5	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 09:00:00	-0.5	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 10:00:00	-0.4	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 11:00:00	0.0	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 12:00:00	0.6	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 13:00:00	0.7	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 14:00:00	0.8	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 15:00:00	0.7	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 16:00:00	0.7	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 17:00:00	0.8	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 18:00:00	1.0	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 19:00:00	1.6	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 20:00:00	1.8	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 21:00:00	2.0	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 22:00:00	2.8	0	5	NA
OBS_DEU_PT1H_T2M	Würzburg	1948-01-01 23:00:00	2.9	0	5	NA

data %>% filter(Zeitstempel<ymd("1979-01-02"), Zeitstempel>=ymd("1978-12-31")) %>% ggplot(aes(Zeitstempel, Wert)) + geom_line()

Die größte Differenz gab es an Neujahr 1979 als die Temperatur über Nacht von fast 10°C um 26,1°C auf -16,8°C fiel. Dagegen ist die angeblich geringste Differenz innerhalb eines Tages am 10. September 2019 (0,0°C Schwankung) ein Artefakt auf Grund fehlender Daten.

data %>% filter(Zeitstempel<ymd("2019-09-11"), Zeitstempel>=ymd("2019-09-08")) %>% ggplot(aes(Zeitstempel, Wert)) + geom_line()