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Atmospheric methane (CH4) is a potent greenhouse gas, and its mole fraction has more than doubled since the preindustrial era. Fossil fuel extraction and use are among the largest anthropogenic sources of CH4 emissions, but the precise magnitude of these contributions is a subject of debate. Carbon-14 in CH4 (14CH4) can be used to distinguish between fossil (14C-free) CH4 emissions and contemporaneous biogenic sources; however, poorly constrained direct 14CH4 emissions from nuclear reactors have complicated this approach since the middle of the 20th century. Moreover, the partitioning of total fossil CH4 emissions (presently 172 to 195 teragrams CH4 per year) between anthropogenic and natural geological sources (such as seeps and mud volcanoes) is under debate; emission inventories suggest that the latter account for about 40 to 60 teragrams CH4 per year. Geological emissions were less than 15.4 teragrams CH4 per year at the end of the Pleistocene, about 11,600 years ago, but that period is an imperfect analogue for present-day emissions owing to the large terrestrial ice sheet cover, lower sea level and extensive permafrost. Here we use preindustrial-era ice core 14CH4 measurements to show that natural geological CH4 emissions to the atmosphere were about 1.6 teragrams CH4 per year, with a maximum of 5.4 teragrams CH4 per year (95 per cent confidence limit)—an order of magnitude lower than the currently used estimates. This result indicates that anthropogenic fossil CH4 emissions are underestimated by about 38 to 58 teragrams CH4 per year, or about 25 to 40 per cent of recent estimates. Our record highlights the human impact on the atmosphere and climate, provides a firm target for inventories of the global CH4 budget, and will help to inform strategies for targeted emission reductions.

This dataset is used for the analyis of the breeding phenology of a common toad (Bufo bufo) alpine population, and how it is associated with either climatic conditions or the genetics of the population. Toad Data Since 1982, we have captured annually all the toads that come to breed at the study pond. We then marked (first by toe-clipping, then starting in 1993 by implanting PIT tags), measured, and released them in the same place (Hemelaar, 1988; Grossenbacher, 2002). To make sure we captured both early and late arrivers, we repeated this procedure for on average 5–6 nights, with breaks in-between of about 2-4 days (i.e, the data conform to Pollock’s (1982) robust design). The length of the field work period usually covers the breeding season duration, which typically lasts about two weeks at our study pond. This design also had the advantage of not overly stressing the toads. In total, for the period 1982–2020, 3053 uniquely recognizable individuals have been caught, of which 1852 were males and 1201 females. For each individual we have a record of presence for each capture night over the study period. Given the reduced size of the pond and the repeated capture rounds within a capture night, we assumed high capture probabilities (capture probability p ≈ 0.85 per year based on a preliminary analysis of the mark-recapture data). At the population level we determined for each year a start, a peak, and an end date of breeding (i.e., first capture night, the capture night when most toads were captured, and last capture night, respectively). These calendar dates were all transformed into days of the year (where January 1st is 1), to facilitate modelling of long-term trends. Weather Data We obtained climatic data for the period 1980–2020 from the DaymetCH dataset (data obtained from Bioclimatic maps of Switzerland © WSL, based on station data from the Federal Office of Meteorology and Climatology MeteoSwiss, and elaborated by the Land Change Science group, WSL). This dataset consists of a 100-metre resolution grid of interpolated estimates of weather variables, using meteorological data from ground stations and the Daymet software (Thornton et al., 1997). We obtained data for the cell containing the breeding pond for the following variables: daily minimum, maximum, and mean temperature, daily total precipitation, and daily snow water equivalent (SWE; the equivalent amount of water stored in the snow pack). We then calculated average seasonal minimum daily temperatures (winter and spring), and cumulative seasonal precipitation (spring) and SWE (winter and spring). The csv file Season_values store these measures (one value for each of the 5 climatic variables per year, for the period 1982-2020, as the study on the toads started in 1982). We conducted all the analyses in R (R version 4.1.1; R Core Team, 2020) with RStudio (version 2022.7.1.554; R Studio Team, 2022). This project was funded by the Federal Office for the Environment (contract numbers: 20.0001.PJ/46DBED0F1 and 06.0126-PZ Artenförderung / N494-1379) and the Stiftung Temperatio.

Macrofaunal communities descriptors (abundances, biomass and traits) and environmental variables sampled in stations located in Åland Islands (Baltic Sea), between 2003 and 2022, after Marenzelleria spp. establishment.

Climate change has differentially affected the timing of seasonal events for interacting trophic levels, and this has often led to increased selection on seasonal timing. Yet, the environmental variables driving this selection have rarely been identified, limiting our ability to predict future ecological impacts of climate change. Using a dataset spanning 31 years from a natural population of pied flycatchers (Ficedula hypoleuca), we show that directional selection on timing of reproduction intensified in the first two decades (1980–2000) but weakened during the last decade (2001–2010). Against expectation, this pattern could not be explained by the temporal variation in the phenological mismatch with food abundance. We therefore explored an alternative hypothesis that selection on timing was affected by conditions individuals experience when arriving in spring at the breeding grounds: arriving early in cold conditions may reduce survival. First, we show that in female recruits, spring arrival date in the first breeding year correlates positively with hatch date; hence, early-hatched individuals experience colder conditions at arrival than late-hatched individuals. Second, we show that when temperatures at arrival in the recruitment year were high, early-hatched young had a higher recruitment probability than when temperatures were low. We interpret this as a potential cost of arriving early in colder years, and climate warming may have reduced this cost. We thus show that higher temperatures in the arrival year of recruits were associated with stronger selection for early reproduction in the years these birds were born. As arrival temperatures in the beginning of the study increased, but recently declined again, directional selection on timing of reproduction showed a nonlinear change. We demonstrate that environmental conditions with a lag of up to two years can alter selection on phenological traits in natural populations, something that has important implications for our understanding of how climate can alter patterns of selection in natural populations. Data from: Effects of spring temperatures on the strength of selection on timing of reproduction in a long-distance migratory birdData on pied flycatcher breeding, incl lay date, number of offspring produced and biotic and abiotic environmental variablesdata_breed.txt

A total of 20 patients will be included to wear the Sunbit system during the time of 4 weeks. After this 4 weeks Sunbit will be recollected and data in the form of UV Indices will be extracted and analyzed. Patients will be recruited in the Department of Dermatology of the University Hospital Zürich. The target population comprises patients with a high risk of melanoma and non-melanoma skin cancer, thus especially patients with an immunosuppressive therapy due to organ transplantation. Sunbit is a new wearable UV dosimeter to measure solar radiation in real time. The purpose of this study is to track sun behavior of patients at high risk for skin cancer, to investigate the feasibility of this prototype in daily life and to investigate the technical accuracy of the Sunbit.

Tabular lift and drag coefficients of WiRE-01 blade at Reynolds number from 4000 to 10000, obtained from wall-resolved LES in OpenFOAM. For more details about the simulation setup, see Ref [1]. For more details about the blade design, see Ref. [2]. [1] Revaz, T., Lin, M., & Porté-Agel, F. (2020). Numerical framework for aerodynamic characterization of wind turbine airfoils: Application to miniature wind turbine WiRE-01. Energies, 13(21), 5612. [2] Bastankhah, M., & Porté-Agel, F. (2017). A new miniature wind turbine for wind tunnel experiments. Part i: Design and performance. Energies, 10(7), 908.

Dataset abstract This dataset contains quality-checked meteorological observations of air temperature, relative humidity, dew point, barometric pressure and observations of downwelling solar radiation and ultraviolet radiation. Further it contains the wind speed and direction relative to the ship but not corrected for air-flow distortion, and translated into the earth reference frame. For each of these variables observations are available from a portside and starboard side sensor. The dataset also contains, cloud base height and sky cover at three levels measured with a Ceilometer. As additional information the solar azimuth and altitude angle have been calculated for the ship’s position every five minutes and have been added as a one-minute time series using the nearest value. The ship’s position, heading, course and speed over ground are also provided. The wind speed measurements were made at a height of approximately 30.5 meters above sea level. The measurement height of the temperature and humidity probes is 23.7 meters above sea level. The barometric pressure was measured at 20 meters above sea level. The observations have been screened for implausible values and on some occasions despiking based on visual inspection and a rolling interquartile range filter have been applied. Solar radiation measurements are affected by shadowing of the ship, and the air temperature and humidity by the heating of air that passes over the ship. Masks are provided to flag affected observations. The wind speed readings are affected by airflow distortion and should be used with consideration until a dataset of corrected wind speeds is published. More details on airflow distortion can be requested from the contact person. Dataset contents ACE_filtered_meteorological_data_1min.csv, data file, comma-separated values diff_TA1_TA3_WDR2_5min_1.png, metadata, portable network graphics ratio_SR1_SR3_solangle_5min_1.png, metadata, portable network graphics data_file_header.txt, metadata, text README.txt, metadata, text ace_filtered_meteorological_data_change_log.txt, metadata, text Change log v1.1 - The range check for skycover (SC) and cloudlevel (CL) was added to the quality-checking routines. 53 data points violated the range check for these variables: these have now been marked as NaN. v1.0 - Initial release of verified meteorological data. Dataset license This meteorological dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full description can be found at https://creativecommons.org/licenses/by/4.0/ {"references": ["Smith, Shawn R., Mark A. Bourassa, and Ryan J. Sharp. Establishing More Truth in True Winds. JOURNAL OF ATMOSPHERIC AND OCEANIC TECHNOLOGY 16 (1999): 14.", "Stull, Roland. Wet-Bulb Temperature from Relative Humidity and Air Temperature. 2011. Journal of Applied Meteorology and Climatology 50, no. 11 (9 September 2011): 2267\u201369. https://doi.org/10.1175/JAMC-D-11-0143.1."]} The Antarctic Circumnavigation Expedition was made possible by funding from the Swiss Polar Institute and Ferring Pharmaceuticals. Antarctic Circumnavigation Expedition – Delivering Added value To Antarctica (ACE-DATA) is funded by the Swiss Data Science Center as Project number 17-02.

This dataset encompasses 12 years of hourly electricity demand observations from the Cuban electrical system, spanning the period from 2011 to 2022. This compilation of data stands as an exceptionally valuable resource for researching the patterns and forecasting the electrical demand on the Caribbean island. Analyzing this data can provide profound insights into energy consumption trends over time, facilitating more informed decision-making for energy management and policy formulation. It serves as a vital tool for stakeholders aiming to understand and adapt to the dynamic nature of electricity demand in Cuba.