README.md

In BirgerNi/degreedays: Returns monthly degree days from DWD for locations in Germany

degreedays

The goal of degreedays is to download heating degree days from weather stations throughout Germany from DWD Climate Data Center (CDC) and provide some convenience functions.

Data set description:

Recent monthly degree days according to VDI 3807 for Germany, quality control not completed yet, version v19.3, last accessed: 2021-12-02.

More information may be found on the opendata-server.

Installation

You can install the development version of degreedays from GitHub.

# install.packages("devtools")
devtools::install_github("BirgerNi/degreedays")

Usage

You can download the whole data set with download_dwd_data.

library(degreedays)
df <- download_dwd_data()
df

#> # A tibble: 70,635 × 7
#>       id   lon   lat station                year_month monthly_degree_days n_hdd
#>    <int> <dbl> <dbl> <chr>                       <mth>               <dbl> <dbl>
#>  1     3  6.09  50.8 AACHEN (WEWA)            2010 Jan                643.    31
#>  2    44  8.24  52.9 GROSSENKNETEN            2010 Jan                703.    31
#>  3    71  8.98  48.2 ALBSTADT-BADKAP          2010 Jan                742.    31
#>  4    73 13.0   48.6 ALDERSBACH-KRIESTORF     2010 Jan                722.    31
#>  5    78  7.91  52.5 ALFHAUSEN                2010 Jan                703.    31
#>  6    91  9.34  50.7 ALSFELD-EIFA             2010 Jan                731.    31
#>  7   102  8.13  53.9 ALTE WESER (AWST)        2010 Jan                677.    31
#>  8   131 12.9   51.1 ALTGERINGSWALDE          2010 Jan                776.    31
#>  9   142 11.3   48.4 ALTOMUENSTER-MAISBRUNN   2010 Jan                725.    31
#> 10   150  8.12  49.7 ALZEY                    2010 Jan                690.    31
#> # … with 70,625 more rows

You may want to convert data to tsibble and keep only complete or almost complete data sets.

tidy_hdd(df, threshold = 0.95)
#> # A tsibble: 62,187 x 7 [1M]
#> # Key:       id [440]
#>       id   lon   lat station       year_month monthly_degree_days n_hdd
#>    <int> <dbl> <dbl> <chr>              <mth>               <dbl> <dbl>
#>  1    44  8.24  52.9 GROSSENKNETEN   2010 Jan               703.     31
#>  2    44  8.24  52.9 GROSSENKNETEN   2010 Feb               569.     28
#>  3    44  8.24  52.9 GROSSENKNETEN   2010 Mär               458      31
#>  4    44  8.24  52.9 GROSSENKNETEN   2010 Apr               320.     28
#>  5    44  8.24  52.9 GROSSENKNETEN   2010 Mai               298.     29
#>  6    44  8.24  52.9 GROSSENKNETEN   2010 Jun                93.7    14
#>  7    44  8.24  52.9 GROSSENKNETEN   2010 Jul                 0       0
#>  8    44  8.24  52.9 GROSSENKNETEN   2010 Aug                42.9     6
#>  9    44  8.24  52.9 GROSSENKNETEN   2010 Sep               192.     25
#> 10    44  8.24  52.9 GROSSENKNETEN   2010 Okt               309.     27
#> # … with 62,177 more rows

Calculate the monthly mean for a given period with calc_monthly_mean().

df %>%
  tidy_hdd(threshold = 0.95) %>%
  calc_monthly_mean(from = 2006, to = 2020)
#> # A tibble: 5,306 × 4
#>       id station       month monthly_mean
#>    <int> <chr>         <dbl>        <dbl>
#>  1    44 GROSSENKNETEN     1        556. 
#>  2    44 GROSSENKNETEN     2        492. 
#>  3    44 GROSSENKNETEN     3        453. 
#>  4    44 GROSSENKNETEN     4        307. 
#>  5    44 GROSSENKNETEN     5        193. 
#>  6    44 GROSSENKNETEN     6         71.9
#>  7    44 GROSSENKNETEN     7         34.5
#>  8    44 GROSSENKNETEN     8         31.9
#>  9    44 GROSSENKNETEN     9        142. 
#> 10    44 GROSSENKNETEN    10        278. 
#> # … with 5,296 more rows

BirgerNi/degreedays documentation built on Jan. 1, 2022, 2:06 p.m.