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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).

Resumen del trabajo presentado en EMS Annual Meeting 2022, celebrado en Bonn (Alemania) del 04 al 09 de septiembre de 2022., The ongoing climate change raises the question if, how and why the wind climate is changing. IPCC stated in AR6WG1 that the confidence in wind changes is “low” to “medium”; there is limited knowledge of historical wind changes and multidecadal variability. A fundamental challenge for the climate research community is to rescue old climate observations from weather archives at the National Weather Services and derive homogeneous and complete data series. At SMHI most of the meteorological data is available digitally since the 1960s, but before that only a minor part of the data is previously digitized. Historical wind speed and direction observations from 1920th to 1940th from 13 stations in Sweden have been rescued and digitized making 165 additional station years of wind data available through Swedish Meteorological and Hydrological Institute (SMHI) open data portal. Stations with instrumental measurements of wind were selected and in the early 1900-century the accordingly equipped stations were mainly found at lighthouses along the coast and at airports. The dominant type of anemometer was of cup-type and different versions are described in the article. The work followed the protocol “Guidelines on Best Practices for Climate Data Rescue” of the World Meteorological Organization. Along with digitize the wind observations meta data of the measurements done at the stations was collected and compiled as a support to the following quality control and homogenization of the wind data. The meta data showed that the most common identified possible homogeneity break was change of observer, but also change of instrument type and position were found in the records. The presentation is a part of the first work package of the WINDGUST project, which is a collaboration between the SMHI, the University of Gothenburg - Regional Climate Group (GU-RCG) and the Spanish National Research Council (CSIC). The project aim is to fill the key gap of short availability (since 1939) and temporal inhomogeneity of wind datasets in Sweden. Especially, the results could contribute to futures studies on the causes driving the current “stilling” and “reversal” debate in a global warming climate. Since previous presentations of the current work package, a data screening has been performed for the wind observations from the 13 digitized stations to visualize the data cover and monthly variability and wind speed range. Two distinct categories of stations with separate wind patterns can be established: coastal and inland stations where inland stations typically has a weak annual variation while coastal stationstypically experience the highest wind speed in November and December.

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.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.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.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.This work has partly been presented earlier in EGU2019-17792-1, EGU2020-349 and EGU21-5848.

Trabajo presentado en EGU General Assembly, celebrado en Viena (Austria) del 23 al 27 de mayo de 2022., The main reasons for the lack of data rescue and homogenization of early near-surface wind speed (WS) observations before the 1960s are insufficient manpower and lack of funding. Funding from the Swedish Research Council for Sustainable Development (FORMAS) for a joint project (ref. 2019-00509) `Assessing centennial wind speed variability from a historical weather data rescue project in Sweden (WINDGUST)¿ among the Swedish Meteorological and Hydrological Institute, the University of Gothenburg, and the Spanish National Research Council, presents a great opportunity to rescue and homogenize the early paper-based WS data in Sweden, for creating a century-long homogenized WS dataset. Here, we rescued paper-based WS records 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 WS dataset (HomogWS-se) for community use. First, background climate variation in the rescued WS series was removed, using a verified reanalysis series as a reference series to construct a difference series. A penalized maximal F test at a significance level of 0.05 was then applied to detect artificial change-points. About 38% of the detected change-points were confirmed by the known events recorded in metadata, and the average segment length split by the change-points is ~11.3 years. A mean-matching method using up to five years of data from two adjacent segments was used to adjust the earlier segments relative to the latest segment. The homogenized WS series was then obtained by adding the homogenized difference series back onto the subtracted reference series. Compared with the raw WS data, the homogenized WS data is more continuous and lacks significant non-climatic jumps. The homogenized WS series presents an initial WS stilling and subsequent recovery until the 1990s, whereas the raw WS fluctuates with no clear trend before the 1970s. The homogenized WS shows a 25% reduction in the WS stilling during 1990-2005 than the raw WS, and this reduction is significant when considering the homogenization uncertainty from reference series. The homogenized WS exhibits a significantly stronger correlation with the North Atlantic Oscillation (NAO) than that of the raw WS (0.54 vs 0.29). These results highlight the importance of the century-long homogenized WS series in increasing our ability to detect and attribute multidecadal variability and changes in WS. HomogWS-se will be released on an open-access data repository for community uses, including studying WS changes, assessing model simulations, and constraining future projections of WS and wind energy potential. The proposed homogenization procedure enables other countries or regions to rescue their early climate data and jointly build global long-term high-quality datasets.

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.