http://bolin.su.se/data/kirchner-warming-stripes-2 Nina Kirchner Bolin Centre Database 2020 Datafile Atmosphere Temperature Air temperature Data visualisation Instrumental temperature data Climate scenarios RCP Earth science services > Education/outreach Nina Kirchner 2020-01-30T09:53:05+00:00 English 2 None 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). A warming stripe for each site is available as a png file. 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 <a href="https://www.climate-lab-book.ac.uk/2018/warming-stripes/">Climate Lab Book</a> by Prof. Ed Hawkins, National Centre for Atmospheric Science at the University of Reading. </p> <p> 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: </p> <p> <b>Sweden, historical data (1860–2019):</b> Data from <a href="http://www.smhi.se/klimatdata/meteorologi/temperatur/klimatindikator-temperatur-1.2430">SMHI climate indicators</a>. This data series is a composite of 35 stations from Sweden having homogenized temperature records, managed by the Swedish Meteorological and Hydrological Institute (SMHI). Data for the year 2019 was obtained by personal communication with Erik Kjellström at the SMHI, as the dataset on the SMHI website was not updated at the date of publication of the current dataset. </p> <p> <b>Sweden, historical (1860–2019) + RCP scenario (2020–2100):</b> Historical data as above for the past, extended with <a href="https://www.smhi.se/klimat/framtidens-klimat/klimatscenarier/">SMHI climate scenario data</a> 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. </p> <p> <b>Stockholm (1756–2019):</b> Data from the <a href="https://bolin.su.se/data/stockholm-historical-temps-monthly-2">Stockholm Historical Weather Observations</a>. The variant of the Stockholm temperature series used here (variant ii in the source) is adjusted for the urban heat island effect. See Moberg et al. (2002). </p> <p> <b>Uppsala (1722–2019):</b> <a href="https://www.smhi.se/klimatdata/meteorologi/temperatur/uppsalas-temperaturserie-1.2855">Data from SMHI</a>. 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 year 2019 was obtained by personal communication with Hans Bergström at Uppsala University, as the dataset on the SMHI website was not updated at the date of publication of the current dataset. </p> <p> <b>Helsinki (1829–2019):</b> Data up to 2018 were obtained by personal communication with Heikki Tuomenvirta at the Finnish Meteorological Institute. The Helsinki temperature series used here has been homogenized. Data is updated to 2019 using data for station 100971 Helsinki Kaisaniemi from the <a href="https://en.ilmatieteenlaitos.fi/open-data">FMI Open data</a> resource. </p> <p> <b>Oslo (1838–2019):</b> Data up to 2018 were obtained by personal communication with Øyvind Nordli at the Norwegian Meteorological Institute. See Nordli et al. (2014a). The same data can be obtained from the <a href="http://sharki.oslo.dnmi.no">eKlima</a> resource. Data is updated to 2019 using data from eKlima for station 18700 Oslo Blindern. </p> <p> <b>Longyearbyen, Svalbard (1898–2019):</b> Data up to 2018 were obtained by personal communication with Øyvind Nordli at the Norwegian Meteorological Institute. See Nordli et al. (2014b). The same data can be obtained from the <a href="http://sharki.oslo.dnmi.no">eKlima</a> resource. Data is updated to 2019 using data from eKlima for station 99840 Svalbard Lufthavn. </p> <p> 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. 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. </p> <h4>Version history</h4> <h5>Version 2</h5> 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. <h5>Version 1</h5> Initial release. Data for stations Stockholm, Uppsala and Longyearbyen and the Sweden average. Last year with data: 2018.