28 Mar 2024
 | 28 Mar 2024

Spatially aggregated climate indicators over Sweden (1860–2020), Part 1: Temperature

Christophe Sturm

Abstract. Climate indicators are useful tools to synthesise climate information from multiple station time-series into a single national indicator. The method applied should be spatially representative and robust over time. We introduce a new method, based on Empirical Orthogonal Functions (EOF) during the calibration period 1961–2018, in order to reconstruct the climate indicator for temperature in Sweden for the full 1860–2020 period of available observations.

The new method delivers results in good overall agreement with the reference method (i.e. arithmetic mean from selected stations in the reference network). Discrepancies are found prior to 1900, primarily related to the reduced number of active stations: the robustness of the indicator estimation is assessed by an ensemble computation with added random noise, which confirms that the ensemble spread increases significantly prior to 1880.

The present study establishes that the 10-year running averaged temperature indicator rose from −1.03 °C in 1903 to +1.19 °C in 2010 (with respect to a mean value of 4.64 °C over the 1961–2018 calibration period), i.e. an increase by +2.22 °C in a century. The temperature difference between 1860 and 2020 was largest for winter (DJF) averages (+3 °C) and minimal for summer (+2 °C).

The leading EOF patterns illustrate the spatial modes of variability for climate variability, with a predominantly homogeneous, mono-modal distribution for temperature. For precipitation, the first EOF pattern displays more pronounced regional features (maximum over the West coast), which is completed by a north-south seesaw pattern for the second EOF. We illustrate that EOF patterns calculated from observation data reproduce the major features of EOF calculated from GridClim, a gridded data-set over Sweden, for annual and seasonal averages. The leading EOF patterns vary significantly for seasonal averages (DJF, MAM, JJA, SON) for temperature.

Finally, future developments of the EOF-method are discussed for calculating regional aggregated climate indicators, their relationship to synoptic circulation patterns and the benefits of homogenisation of observation series.

The EOF-based method to compute a spatially aggregated indicator for precipitation is presented in a companion article (Sturm, 2024a). The code and data for this study is available on Zenodo (Sturm, 2024b).

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Christophe Sturm

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-582', Anonymous Referee #1, 13 Apr 2024
  • RC2: 'Comment on egusphere-2024-582', Anonymous Referee #2, 30 Apr 2024
Christophe Sturm
Christophe Sturm


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Short summary
In light of anthropogenic climate change, climate indicators are useful to illustrate how temperature varies over time. It is however no trivial task: missing data, changing networks make it difficult to calculate the indicator. This study introduces a new method for temperature over Sweden since 1860. Unlike the previous method, the new method incorporates hundreds of stations and applies weighing coefficients that reflect the leading modes of variability, established during 1961–2018.