Abstract

<p>Global wind climate is one of the aspects of the ongoing climate change that until recent days has lacked robust knowledge of past and future trends. IPCC stated in AR6WG1 that the confidence in wind changes is “low” to “medium” which stress that there is still much to learn about wind changes and multidecadal variability in a warming climate (IPCC AR6WG1). One of the reasons have been a shortage of digitally available historical wind observations as input data to studies of historical variations in wind climate.</p><p>Here we present the results of work package 1 of the project “Assessing centennial wind speed variability from a historical weather data rescue project in Sweden” (WINDGUST, funded by FORMAS – A Swedish Research Council for Sustainable Development (ref. 2019-00509)). The WINDGUST project is a joint initiative between the Swedish Meteorological and Hydrological Institute (SMHI), the University of Gothenburg (UGOT) and the Spanish National Research Council (CSIC) aimed at filling the key gap of short availability and low quality of wind datasets, and improve the limited knowledge on the causes driving wind speed variability in a changing climate across Sweden.</p><p>In work package 1 historical wind observations from Sweden have been rescued and digitized during 2020 and 2021. Observations from 13 stations around Sweden, mostly along the coast, for the decades 1920 to 1940 were digitized, adding up to 165 stationyears of data. The digitized data from around 1920 to 2021 is freely available from the SMHI data portal: www.smhi.se/data. Meta data for the digitized stations were also collected and compiled as a support for the following quality control and homogenization in work package 2 in the WINDGUST project also presented at EGU 2022.</p><p>The work followed the “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization and consisted of three steps. These three steps were: (i) designing a template for digitization; (ii) digitizing papers by an imaging process based on scanning and photographs; and (iii) typing numbers of wind speed data into the template and storing the values in the observational data base at the SMHI.</p><p>This work has partly been presented earlier in EGU2019-17792-1, EGU2020-349 and EGU21-5848.</p>

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