http://bolin.su.se/data/kirchner-warming-stripes-3 Nina Kirchner Bolin Centre Database 2021 Datafile Atmosphere Temperature Air temperature Data visualisation Instrumental temperature data Climate scenarios RCP Earth science services > Education/outreach Nina Kirchner 2021-02-02T15:27:58+00:00 English 3 ###### Data The dataset includes annual mean temperature data for a selection of sites from the Nordic countries. Data for each site is provided as a comma separated value (csv) file having two columns (year, temperature). ###### Figures A warming stripe for each site is available as a png file. The colour scale in each warming stripe represents the range between the coldest and warmest year in the entire period covered by the historical observations at the selected site. This holds also for warming stripes that use both historical+scenario data; i.e. also in these cases the colur scale is determined by the temperature range in the period of observations. ###### Code Two variants of an m-file with matlab (R2017a) code, that reads a data file and produces a warming stripe, is also included. The main variant assumes that only historical data is used. The second variant assumes that historical+scenario data is used. This kind of data presentation is inspired by a larger set of visualisations of climate records in the online [Climate Lab Book](https://www.climate-lab-book.ac.uk/2018/warming-stripes/) by Prof. Ed Hawkins, National Centre for Atmospheric Science at the University of Reading. The warming stripes presented here are derived from instrumental records of annual mean air temperature data for the entire Sweden, Stockholm, Uppsala, Helsinki, Oslo, and Longyearbyen on Svalbard. For the entire Sweden, warming stripes are also shown with an extension in time up to the year 2100 by merging with scenario data for the future. The scenarios used are based on the so-called Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5. These scenarios are widely used in climate science and they represent assumptions of low, medium and high future global emissions of greenhouse gases. The data used here is derived from the following sources: **Sweden, historical data (1860⁠ – ⁠2020):** Data up to 2018 was obtained from [SMHI climate indicators](http://www.smhi.se/klimatdata/meteorologi/temperatur/klimatindikator-temperatur-1.2430). This data series is a composite of 35 stations from Sweden having homogenized temperature records, managed by the Swedish Meteorological and Hydrological Institute (SMHI). Corresponding data for the years 2019 and 2020 were obtained by personal communication with Erik Kjellström and Ralf Döscher at the SMHI. **Sweden, historical (1860⁠ – ⁠2020) + RCP scenario (2021⁠ – ⁠2100):** Historical data as above for the past, extended with [SMHI climate scenario data](https://www.smhi.se/klimat/framtidens-klimat/klimatscenarier/) for the future. The scenario dataset is presented at SMHI as deviations from the average temperature in the reference period 1961–1990 for several different climate models. To merge the historical data with the scenario data here, we used scenario data generated with the climate model EC-Earth. The observed Sweden annual mean temperature (+4.65°C) in the reference period was added to the scenario data. Data from the model EC-Earth was chosen here because its warming until 2100 is very similar to the average of all models and because its variability is similar to the historical data in the reference period. **Stockholm (1756⁠ – ⁠2020):** Data from the [Stockholm Historical Weather Observations](https://bolin.su.se/data/stockholm-historical-temps-monthly-3). The variant of the Stockholm temperature series used here (variant 2 in the source) is adjusted for the urban heat island effect. See Moberg et al. (2002). **Uppsala (1722⁠ – ⁠2020):** Data up to 2018 was obtained from [SMHI](https://www.smhi.se/klimatdata/meteorologi/temperatur/uppsalas-temperaturserie-1.2855). The version of the Uppsala temperature series used here is adjusted for the urban heat island effect. See Bergström and Moberg (2002). Data for the years 2019 and 2020 were obtained by personal communication with Hans Bergström at Uppsala University, after having been adjusted in the same way. **Helsinki (1829⁠ – ⁠2020):** Data up to 2018 was obtained by personal communication with Heikki Tuomenvirta at the Finnish Meteorological Institute. The Helsinki temperature series used here has been homogenized. Data was updated to 2019 and 2020 using data for station 100971 Helsinki Kaisaniemi from the [FMI Open data](https://en.ilmatieteenlaitos.fi/open-data) resource. **Oslo (1838⁠ – ⁠2020):** Data up to 2018 was obtained by personal communication with Øyvind Nordli at the Norwegian Meteorological Institute. See Nordli et al. (2014a). The same data could be obtained from the [eKlima](http://sharki.oslo.dnmi.no/) resource. Data was updated to 2019 using data from eKlima for station 18700 Oslo Blindern. Data was then updated to 2020 using data from [Seklima](https://seklima.met.no/observations/) for station 18700 Oslo Blindern. **Longyearbyen, Svalbard (1898⁠ – ⁠2020):** Data up to 2018 was obtained by personal communication with Øyvind Nordli at the Norwegian Meteorological Institute. See Nordli et al. (2014b). The same data could be obtained from the [eKlima](http://sharki.oslo.dnmi.no/) resource. Data was updated to 2019 using data from eKlima for station 99840 Svalbard Lufthavn. Data was then updated to 2020 using data from [Seklima](https://seklima.met.no/observations/) for station 99840 Svalbard Lufthavn. Acknowledgements: Øyvind Nordli at the Norwegian Meteorological Institute and Heikki Tuomenvirta at the Finnish Meteorological Institute helped by providing data from their countries. Alasdair Skelton, Stockholm University, came up with the idea to include climate scenario data to the the warming stripes. Hans Bergström, Uppsala University, helped with updating the Uppsala series to the last few years. Anders Moberg, Stockholm University, constructed the combination of historical + scenario data for Sweden. He also contributed to development of the matlab code. Further colleagues who helped with various ideas and input at an early stage of the work leading to the creation of this dataset are mentioned in the comments to version 1. #### Version history ##### Version 3 All data files are updated with the annual mean temperatures for 2020, and renamed so that the filename reflects the update. The matlab code has been changed accordingly at lines where files are read. All warming stripe figures are updated to include observed annual mean temperatures for 2020. ##### Version 2 Data for stations Oslo and Helsinki added. All station data updated to 2019. Scenario data for the Sweden average added. Matlab code revised an provided in two variants, one for station data one for station+scenario data. ##### Version 1 Initial release. Data for stations Stockholm, Uppsala and Longyearbyen and the Sweden average. Last year with data: 2018.