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This study analyses for the first time observed surface mean wind speed (SWS) and gusts over the Iberian Peninsula (IP) in the frequency domain for 1961–2019, with the goal of exploring sources of predictability in the interannual and decadal scales. The main result is the high significant correlation between surface winds and the stratospheric polar vortex for periods close to 1 year with a time lag of about 2–3 months with respect to the antiphase, that is, a negative correlation in which the polar vortex modulates winds in the region. Furthermore, we found that the SWS and gusts are decoupled for periods between 9 and 11 years with a marked seasonal dependence in its intensity. Finally, we detected discrepancies between the spectra shown by surface winds from observations and ERA5‐Land reanalysis, suggesting that simulated data do not accurately reproduce the variability of surface wind speeds. Plain Language Summary In the climate system, there are oscillations that are repeated with specific time periods over time; the best known example is the El Niño‐Southern Oscillation, which affects much of the world's climate. In this study, we apply a spectral analysis to: (a) characterize the spectrum of near‐surface mean wind speed and gusts in the Iberian Peninsula; (b) relate the oscillations of both wind variables with those of other parameters of the climate system; and, (c) identify sources of predictability. The most outstanding result is the high significant correlation between the mean wind speed and gusts with the stratospheric polar vortex with a time lag of about 2–3 months. This means that with an anomalously weak (strong) polar vortex we might expect strong (weak) surface winds 2–3 months later. This study has direct socioeconomic and environmental implications for for example, wind energy production, agriculture and hydrology, pollutant dispersion, among others, as it could predict interannual‐ to decadal‐scales wind speed behavior in the region. Key Points Surface winds correlate with the stratospheric polar vortex in periods close to 1 year, with a 2–3 months lag with respect to the anti‐phase Surface mean wind speed and gusts are decoupled for periods between 9 and 11 years, being greater in summer and disappearing in winter Spectral analysis showed differences between observed and ERA5‐Land reanalysis surface winds

A World Meteorological Organization weather and climate extremes committee has judged that the world’s longest reported distance for a single lightning flash occurred with a horizontal distance of 321 km (199.5 mi) over Oklahoma in 2007, while the world’s longest reported duration for a single lightning flash is an event that lasted continuously for 7.74 s over southern France in 2012. In addition, the committee has unanimously recommended amendment of the AMS Glossary of Meteorology definition of lightning discharge as a “series of electrical processes taking place within 1 s” by removing the phrase “within 1 s” and replacing it with “continuously.” Validation of these new world extremes 1) demonstrates the recent and ongoing dramatic augmentations and improvements to regional lightning detection and measurement networks, 2) provides reinforcement regarding the dangers of lightning, and 3) provides new information for lightning engineering concerns.

There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate dataset for the preindustrial period so far. Measurement(s) temperature of air Technology Type(s) weather stations Sample Characteristic - Environment Air - temperature, precipitation and pressre Sample Characteristic - Location Global Dataset

Quantitative approaches to climate risk management such as mapping or impact modelling rely on past meteorological data with daily or sub‐daily resolution, a large fraction of which have not yet been digitized. Over the last decade or so, a number of projects have contributed to the rescue of some of these data. Here we provide a summary of a survey we have undertaken of several meteorological and climate data rescue projects, in order to identify the needs of climate data rescue services. To make these efforts more sustainable, additional integrated activities are needed. We argue that meteorological and climate data rescue must be seen as a continuous, coordinated long‐term effort. Technical developments (e.g. data assimilation), new scientific questions (e.g. process understanding of extreme events) and new social (e.g. risk assessment, health) or economic (e.g. new renewable energy sources, agriculture and forestry, tourism, infrastructure, etc.) services are highlighting the immense value of data previously neglected or never considered. This continuous effort is currently undertaken by projects of various sizes, structure, funding and staffing, as well as by dedicated programmes, ranging from those within many national weather services down to “grassroots” initiatives. These activities are often not sufficiently coordinated, staffed, or funded at an international level and will benefit considerably from climate data rescue services being established within the Copernicus Climate Change Service (C3S) (https://climate.copernicus.eu/). Open Practices This article has earned an Open Data badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki.

On 13 September 1922, a temperature of 58°C (136.4°F) was purportedly recorded at El Azizia (approximately 40 km south-southwest of Tripoli) in what is now modern-day Libya. That temperature record of 58°C has been cited by numerous world-record sources as the highest recorded temperature for the planet. During 2010–11, a World Meteorological Organization (WMO) Commission of Climatology (CCl) special international panel of meteorological experts conducted an in-depth investigation of this record temperature for the WMO World Archive of Weather and Climate Extremes (http://wmo.asu.edu/). This committee identified five major concerns with the 1922 El Azizia temperature extreme record, specifically 1) potentially problematical instrumentation, 2) a probable new and inexperienced observer at the time of observation, 3) unrepresentative microclimate of the observation site, 4) poor correspondence of the extreme to other locations, and 5) poor comparison to subsequent temperature values recorded at the site. Based on these concerns, the WMO World Archive of Weather and Climate Extremes rejected this temperature extreme of 58°C as the highest temperature officially recorded on the planet. The WMO assessment is that the highest recorded surface temperature of 56.7°C (134°F) was measured on 10 July 1913 at Greenland Ranch (Death Valley), California.

Historical climatic data from station observations taken in North African and Middle East Mediterranean countries since the second half of the 19th century have been digitized and quality‐controlled in the framework of the EU‐funded European Reanalysis and Observations for Monitoring (EURO4M) project. Daily maximum and minimum temperatures and precipitation totals, along with sub‐daily data for surface air pressure have been recovered by using historical data sources involving book/logbook collections archived in national and international data centres. The new dataset produced comprises climatic time series for 79 stations that have operated in southern and eastern Mediterranean countries. While the developed time series have data gaps, every effort has been made to infill these gaps, to improve assessments of the long‐term changes in climate variability in the region.

The aim of time series homogenization is to remove nonclimatic effects, such as changes in station location, instrumentation, observation practices, and so on, from observed data. Statistical homogenization usually reduces the nonclimatic effects but does not remove them completely. In the Spanish “MULTITEST” project, the efficiencies of automatic homogenization methods were tested on large benchmark datasets of a wide range of statistical properties. In this study, test results for nine versions, based on five homogenization methods—the adapted Caussinus-Mestre algorithm for the homogenization of networks of climatic time series (ACMANT), “Climatol,” multiple analysis of series for homogenization (MASH), the pairwise homogenization algorithm (PHA), and “RHtests”—are presented and evaluated. The tests were executed with 12 synthetic/surrogate monthly temperature test datasets containing 100–500 networks with 5–40 time series in each. Residual centered root-mean-square errors and residual trend biases were calculated both for individual station series and for network mean series. The results show that a larger fraction of the nonclimatic biases can be removed from station series than from network-mean series. The largest error reduction is found for the long-term linear trends of individual time series in datasets with a high signal-to-noise ratio (SNR), where the mean residual error is only 14%–36% of the raw data error. When the SNR is low, most of the results still indicate error reductions, although with smaller ratios than for large SNR. In general, ACMANT gave the most accurate homogenization results. In the accuracy of individual time series ACMANT is closely followed by Climatol, and for the accurate calculation of mean climatic trends over large geographical regions both PHA and ACMANT are recommended.

The currently limited availability of long and high-quality surface instrumental climate records continues to hamper our ability to carry out more robust assessments of the climate. Such assessments are needed to better understand, detect, predict and respond to global climate variability and change. Despite the wealthy heritage of past climate data and recent efforts to improve data availability and accessibility, much more surface data could be digitised. Additionally, some long records are not of the quality needed for more confidently supporting any climate assessment, service, or application. The present paper discusses the usefulness of undertaking integrated data rescue (DARE) activities by showing several climate assessments as examples. It describes emerging DARE activities worldwide, with a focus on the World Meteorological Organization Mediterranean Data Rescue (MEDARE) and the Atmospheric Circulation Reconstructions over the Earth (ACRE) initiatives to assess the benefits historical instrumental climate data can bring to studies of climate variability and change that consider the 21st century.

Most studies on wind variability have deepened into the stilling vs. reversal phenomena at global to regional scales, while the long-term changes in local-scale winds such as sea-breezes (SB) represent a gap of knowledge in climate research. The state-of-the-art of the wind variability studies suggests a hypothetical reinforcement of SB at coastal stations. We first developed a robust automated method for the identification of SB days. Then, by using homogenized wind observations from 16 stations across Eastern Spain, we identified 9,349 episodes for analyzing the multidecadal variability and trends in SB speeds, gusts and occurrence for 1961–2019. The major finding is the opposite trends and decoupled variability of SB speeds and gusts: the SB speeds declined significantly in all seasons (except for winter), and the SB gusts strengthened at the annual scale and in autumn–winter, being most significant in autumn. Our results also show that the SB occurrence has increased across most of Eastern Spain, although presenting contrasting seasonal trends: positive in winter and negative in summer. We found that more frequent anticyclonic conditions, NAOI + and MOI + are positively linked to the increased winter occurrence; however, the causes behind the opposite trends in SB speeds and gusts remain unclear. The SB changes are complex to explain, involving both large-scale circulation and physical-local factors that challenge the understanding of the opposite trends. Further investigation is needed to assess whether these trends are a widespread phenomenon, while climate models could simulate the drivers behind these decoupled SB changes in a warmer climate.

Two reports of Antarctic region potential new record high temperature observations (18.3°C, 6 February 2020 at Esperanza station and 20.8°C, 9 February 2020 at a Brazilian automated permafrost monitoring station on Seymour Island) were evaluated by a World Meteorological Organization (WMO) panel of atmospheric scientists. The latter figure was reported as 20.75°C in the media. The panel considered the synoptic situation and instrumental setups. It determined that a large high pressure system over the area created föhn conditions and resulted in local warming for both situations. Examination of the data and metadata of the Esperanza station observation revealed no major concerns. However, analysis of data and metadata of the Seymour Island permafrost monitoring station indicated that an improvised radiation shield led to a demonstrable thermal bias error for the temperature sensor. Consequently, the WMO has accepted the 18.3°C value for 1200 LST 6 February 2020 (1500 UTC 6 February 2020) at the Argentine Esperanza station as the new “Antarctic region (continental, including mainland and surrounding islands) highest temperature recorded observation” but rejected the 20.8°C observation at the Brazilian automated Seymour Island permafrost monitoring station as biased. The committee strongly emphasizes the permafrost monitoring station was not badly designed for its purpose, but the project investigators were forced to improvise a nonoptimal radiation shield after losing the original covering. Second, with regard to media dissemination of this type of information, the committee urges increased caution in early announcements as many media outlets often tend to sensationalize and mischaracterize potential records.