This page shows some historical weather data for Sweden, and provides a guide for downloading data from the Swedish Met Office (SMHI) website (see the end of the page).

Stockholm Observatory has a long history of meteorological measurements, with daily maximum and minimum temperature data available back to 1859 (see below for data sources). The main focus of this page is on daily minimum temperatures recorded at Stockholm Observatory, and on the question of how representative they are of Southern Sweden, given the near-coastal position of Stockholm, urban heating, and the very local environment near the thermometers.


The figure above shows that winter coldwaves since around 1990 have been less frequent and less severe than before that date. Note also the relatively large frequency and severity of coldwaves before 1900. The very cold weather in the early 1940s is probably of historical significance, as this was the time when the German army was in Russia in WW2.

See below for analysis plots of “abnormal” warmth of very cold nights at Stockholm Observatory.


The figure above shows that since around 1990 the frequency and severity of very cold winter days have been lower than before that date. Note also the coldwaves before around 1900.


The daily temperature data plotted above is a simple concatenation of data for Stockholm Observatory from the following sources:


The following photo shows the positions of the thermometers at Stockholm Observatory, both good places to park a car to reduce overnight frost:

Source of the photo above, and details of the site history:

Moberg A, Bergström H, Ruiz Krigsman J, Svanered O. 2002: Daily air temperature
and pressure series for Stockholm (1756-1998). Climatic Change 53: 171-212

The following map, from the SMHI website, shows the position of Stockholm Observatory, and of some of the stations used for analysis of the Observatory data:

The following figure shows daily winter (1st December to 28th February) Tmin differences (Observatory – station) between the Observatory and nearby stations:

The figure above reflects the fact that “warm” winter nights give a similar minimum temperature at all local stations, whereas cold winter nights are usually substantially warmer in the Observatory data, relative to that of the other local stations. Some snapshot comparisons are shown below to illustrate that statement.

Similar anomalous warmth on very cold winter nights is seen in comparisons with most other near neighbours, throughout the full period of Observatory data, from 1859 to 2021. It is only coastal stations that have similar winter Tmin values for coldwaves.

The following figure shows a scatter plot of daily winter Tmin at Stockholm Observatory, versus the recorded differences in Tmin between the Observatory and Bromma Airport:

Note the similarity in winter Tmins recorded at the Observatory and Bromma Airport for both very warm and very cold nights, the coldest nights of -23 to -26C gave similar recorded temperatures at both sites.

The conclusion is that Stockholm Observatory winter Tmin data is NOT representative of Southern Sweden, which in general has substantially colder winter nights during coldwaves.

The reasons why coldwaves are recorded with anomalous warmth at Stockholm Observatory may be as follows:

  • Background Urban Heating
  • Very local heating due to the buildings and vegetation near the thermometers

Maritime influence is unlikely to be significant in the Tmin differences, as the comparison stations, and Stockholm Observatory, are all at similar distances from the sea.


Air temperature (and other) data can be accessed from the Swedish Meteorological and Hydrological Institute (SMHI) via the following link (in Swedish only):


Select the desired data via the tab “VALJ PARAMETER” shown on the following screenshot:

In the example shown above the data selected is daily (dygn) minimum and maximum (min och max) air temperature (Lufttemperatur). The other first row columns are for (selected) hours, and monthly (manad) data.

Rainfall amount in Swedish is nederbördsmängd.

The data are provided as csv files, which can be opened with a spreadsheet, or a text editor.

Missing data is simply absent, but when all the data for a particular time is missing the entire line is absent, an example is as follows, in which the second line of data has been inserted manually, with NaN for the missing values:

EXTRACT FROM: smhi-opendata_19_20_98210_20211228_150757.csv

1887-08-29 20:00:01;1887-08-30 20:00:00;1887-08-30;14.5;G;22.5;G
1887-08-30 20:00:01;1887-08-30 20:00:00;1887-08-31;NaN;G;NaN;G (this line inserted manually)
1887-08-31 20:00:01;1887-09-01 20:00:00;1887-09-01;12.0;G;20.0;G

It is quite common for days, weeks, months and years to have contiguous segments of missing data.


The core of the MATLAB software used (available on request) to read text files (an extract is shown above) derived from the SMHI csv files is as follows:

[times1, times2, times3, Tmins, flags1, Tmaxs, flags2] = …
textread(filename,’%s %s %s %f %s %f %s’, ‘delimiter’, ‘;’, ’emptyvalue’, NaN);

The software assumes that a line of data is present for every day, achieved by manual infilling of short periods of missing lines, and splitting the data into several files when there are long periods of missing lines.


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