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This study investigates the centennial-scale (i.e., since 1926) variability of observed near-surface wind speed across Sweden. Results show that wind speed underwent various phases of change during 1926–2019: (a) a clear slowdown during 1926–1960; (b) a stabilization from 1960 to 1990; (c) another clear slowdown during 1990–2003; (d) a slight recovery/stabilization period for 2003–2014, which may continue with a possible new slowdown. Furthermore, the performance of three reanalysis products in representing past wind variations is evaluated. The observed low-frequency variability is properly simulated by the selected reanalyses and is linked to the variations of different large-scale atmospheric circulation patterns (e.g., the North Atlantic Oscillation). However, the evident periods of decreasing trend during 1926–1960 and 1990–2003, which drive most of the stilling in the last century, are missing in the reanalyses and cannot be realistically modeled through multiple linear regression by only using indexes of atmospheric circulation. Therefore, this study reveals that changes in large-scale atmospheric circulation mainly drives the low-frequency variability of observed near-surface wind speed, while other factors (e.g., changes in surface roughness) are crucial for explaining the periods of strong terrestrial stilling across Sweden.

Creating a century-long homogenized near-surface wind speed observation dataset is essential to improve our current knowledge about the uncertainty and causes of wind speed stilling and recovery. Here, we rescued paper-based records of wind speed measurements dating back to the 1920s at 13 stations in Sweden and established a four-step homogenization procedure to generate the first 10-member centennial homogenized wind speed dataset (HomogWS-se) for community use. Results show that about 38¿% of the detected change points were confirmed by the known metadata events, and the average segment length split by the change points is ~11.3 years. Compared with the raw wind speed series, the homogenized series is more continuous and lacks significant non-climatic jumps. The homogenized series presents an initial wind speed stilling and subsequent recovery until the 1990s, whereas the raw series fluctuates with no clear trend before the 1970s. The homogenized series shows a 25¿% reduction in the wind speed stilling during 1990¿2005 than the raw series, and this reduction is significant when considering the homogenization uncertainty. The homogenized wind speed series exhibits a significantly stronger correlation with the North Atlantic oscillation index than that of the raw series (0.54 vs. 0.29). These results highlight the importance of the century-long homogenized series in increasing our ability to detect and attribute multidecadal variability and changes in wind speed. The proposed homogenization procedure enables other countries or regions to rescue their early climate data and jointly build global long-term high-quality datasets. HomogWS-se is publicly available from the Zenodo repository at https://doi.org/10.5281/zenodo.5850264 (Zhou et al., 2022)., This study was funded by Swedish FORMAS (2019-00509) and VR (2017-03780, 2019-03954), as well as the Swedish National Strategical Research Programs BECC and MERGE. Cesar Azorin-Molina was supported by the IBER-STILLING project RTI2018-095749-A-100 (MCIU/AEI/FEDER,UE), the VENTS project AICO/2021/023 (GVA) and the CSIC Interdisciplinary Thematic Platform PTI-CLIMA. Lorenzo Minola was funded by the International Postdoc grant from the Swedish Research Council (2021-00444).

Instrumental measurements of wind speed and direction from the 1920s to the 1940s from 13 stations in Sweden have been rescued and digitized, making 165 additional station years of wind data available through the Swedish Meteorological and Hydrological Institute's open data portal. These stations measured wind through different versions of cup-type anemometers and were mainly situated at lighthouses along the coasts and at airports. The work followed the protocol “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization consisting of (i) designing a template for digitization, (ii) digitizing records in paper journals by a scanner, (iii) typing numbers of wind speed and direction data into the template, and (iv) performing quality control of the raw observation data. Along with the digitization of the wind observations, meta data from the stations were collected and compiled as support to the following quality control and homogenization of the wind data. The meta data mainly consist of changes in observer and a small number of changes in instrument types and positions. The rescue of these early wind observations can help improve our understanding of long-term wind changes and multidecadal variability (e.g. the “stilling” vs. “reversal” phenomena) but also to evaluate and assess climate simulations of the past. Digitized data can be accessed through the Swedish Meteorological and Hydrological Institute and the following Zenodo repository: https://doi.org/10.5281/zenodo.5850264 (Zhou et al., 2022).

Trabajo presentado en EGU General Assembly, celebrada en modalidad virtual del 19 al 30 de abril de 2021., Here we present the progress of the first work package (WP1) 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); previously introduced in EGU2019-17792-1 and EGU2020-3491. In a global climate change, one of the major uncertainties on the causes driving the climate variability of winds (i.e., the “stilling” phenomenon and the recent “recovery” since the 2010s) is mainly due to short availability (i.e., since the 1960s) and low quality of observed wind records as stated by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). The WINDGUST is a joint initiative between the Swedish Meteorological and Hydrological Institute (SMHI) and the University of Gothenburg 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. During 2020, we worked in WP1 to rescue historical wind speed series available in the old weather archives at SMHI for the 1920s-1930s. In the process we followed the “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization. Our protocol consisted on: (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. We will report the advances and current status, challenges and experiences learned during the development of WP1. Until new year 2020/2021 eight out of thirteen selected stations spanning over the years 1925 to 1948 have been scanned and digitized by three staff members of SMHI during 1,660 manhours.

Trabajo presentado en EGU General Assembly, celebrada en modalidad virtual del 4 al 8 de mayo de 2020., This contribution presents the first work package (WP1) of the project ¿Assessing centennial wind speed variability from a historical weather data rescue project in Sweden¿, funded by FORMAS ¿ A Swedish Research Council for Sustainable Development (ref. 2019-00509); previously reported in EGU2019-17792-1. Under a warming climate, one of the major uncertainties on the causes driving the climate variability of winds over land (i.e., the ¿stilling¿ phenomenon and the recent ¿recovery¿ since the 2010s) is mainly due to short availability (i.e. since the 1960s) and low quality of observed wind records as stated by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). In this study we present the first steps of a joint initiative between the Swedish Meteorological and Hydrological Institute (SMHI) and the University of Gothenburg 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. The aim of the WP1 is to rescue historical wind speed series available in the old weather archives at SMHI for the 1920s-1930s. 13 stations with daily wind speed data (in meters per second) during the period 1925-1938 have been selected for digitization; i.e., spanning back our records 2 decades more. To get wind observations from paper to screen we will follow the ¿Guidelines on Best Practices for Climate Data Rescue¿ of the World Meteorological Organization. Our protocol will consist on (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. WP2 will ensure the quality and homogeneity of wind speed series rescued.