https://researchdata.se/en/catalogue Search results en The Chalmers Hydrometeor Inversion Product from the Arctic Weather Satellite (CHIP-AWS) provides estimates of ice hydrometeor masses in the atmosphere across the globe within the +/-60° latitude region. This dataset represents a level 2 processing of AWS level 1B instrument data. This archival dataset contains retrievals for the entire AWS 2025 record. For more recent retrievals see: https://clouds-and-precip.group/datasets/chip-aws/ Mon, 02 Nov 2026 13:12:04 GMT https://researchdata.se/en/catalogue/dataset/2026-135 https://researchdata.se/en/catalogue/dataset/2026-135 Chalmers University of Technology Peter McEvoy Eleanor May Patrick Eriksson Accurate long-term GNSS-derived atmospheric water vapour time series are essential when used in climate research. However, these records are frequently affected by interventions, e.g., change of hardware at the station. We investigate the homogenization of integrated water vapour (IWV) time series co-located GNSS stations at 19 sites in Sweden and one site in Denmark. Fri, 04 Sep 2026 15:31:59 GMT https://researchdata.se/en/catalogue/dataset/2026-270 https://researchdata.se/en/catalogue/dataset/2026-270 Chalmers University of Technology Gunnar Elgered Tong Ning The International Cooperative Programme on Integrated Monitoring of Air Pollution Effects on Ecosystems (ICP IM) presents a comprehensive long-term dataset of ongoing integrated ecosystem monitoring from European forested catchments. The dataset encompasses measurements from monitoring stations across 14 European countries, with temporal coverage extending for most sites from the 1990s to 2020. The dataset will be updated with new data once per year. The integrated monitoring approach applies over multiple monitoring subprogrammes to simultaneously measure physical, chemical, and biological properties across ecosystem compartments including atmosphere, precipitation, throughfall, soil, soil water, groundwater, runoff water, vegetation, and biota. All measurements follow standardised protocols detailed in the ICP IM Manual, ensuring data quality and comparability across sites and time periods. The dataset supports research on ecosystem responses to air pollution, climate change impacts, and biogeochemical cycling. Data is provided by sub-programme (all sites and all years with data in one file), geographic co-ordinates for sites are available in a separate file. Historical data from inactive sites in Belarus, Denmark, Iceland and the United Kingdom are currently available by request, as is data from Finland in sub-programmes TF,SF,SC,SW,FC,LF,FD,VG,EP and BV, and data from Poland. The monitoring is done under the framework of the UN Convention on Long-Range Transboundary Air Pollution (CLRTAP) and also has an important role in reporting under the EU national emissions ceiling directive (NECD). Users are strongly encouraged to refer to the ICP IM Monitoring Manual which describes in detail the methods used to make measurements in the field and the laboratory, the data formats used, explanations of column headers and flags used in all subprogrammes and example files. This is provided alongside the data. Fri, 04 Sep 2026 12:11:42 GMT https://researchdata.se/en/catalogue/dataset/2024-180 https://researchdata.se/en/catalogue/dataset/2024-180 Swedish University of Agricultural Sciences James Weldon Wenche Aas Barbara Albiniak Algirdas Augustaitis Ieva Baužienė Camilla Capelli Nicholas Clarke Thomas Cummins Heleen de Wit Thomas Dirnböck Ika Djukic Karin Eklöf Martin Forsius Martyn Futter Ulf Grandin Sergey Gromov Adéla Holubová Šmejkalová Ricardo Ibañez Iveta Indriksone Sara Jutterström Johannes Kobler Heidi Koger Angelika Kölbl Andrzej Kostrzewski Anna Koukhta Pavel Krám Robert Kruszyk Esther Lasheras Kairi Lõhmus Mikołaj Majewski Hampus Markensten Rafael Miranda Michael Mirtl Filip Moldan Giancarlo Papitto Johannes Peterseil Ainis Pivoras Gisela Pröll Pernilla Rönnback Carolina Santamaría Jesus Miguel Santamaría Thomas Plha Krzysztof Skotak David Elustondo Mercedes Valerio Sarah Venier Lieke Vlaar Jussi Vuorenmaa Nicole Wellbrock Liisa Ukonmaanaho Ulla Makkonen The data set contains indicators related to future spring frost occurrence in Fennoscandia. The indicators were calculated from the daily average and daily minimum air temperature data from the regional climate model simulations from the CORDEX-CMIP5 project. These climate model simulations have previously been bias-adjusted to minimise systematic errors, as described in the included documentation, and use Representative Concentration Pathways RCP2.6, RCP4.5, and RCP8.5. The indices follow the conventions of the Climix tool and comprise: - start of growing season [gsstart], - last spring frost [lsf], - number of spring frost days [fdgsstart], and - late frost lag since vegetation onset [lflsvo] The indices are given as NetCDF files with yearly time-resolution and a spatial grid spacing of approximately 12.5x12.5km, one file for each index/GCM/RCM/RCP combination. Ensemble averages are also included, one file for each index/RCP combination. The underlying bias-adjusted gridded daily average near-surface air temperature and daily minimum near-surface air temperature data are also included, one file for each GCM/RCM/RCP combination. Tue, 07 Jul 2026 10:43:04 GMT https://researchdata.se/en/catalogue/dataset/2026-178 https://researchdata.se/en/catalogue/dataset/2026-178 SMHI - Swedish Meteorological and Hydrological Institute Gustav Strandberg From August 9 - September 19, 2025, the icebreaker Oden carried out an expedition with the Canadian icebreaker CCGS Louis S. St-Laurent to map the seabed in the Arctic Ocean, which took place within the framework of the UNCLOS program (United Nations Convention on the Law of the Sea). In symbiosis with this, an extensive Early Career Scientist program also took place on board, consisting of the course The Arctic Ocean Climate System. Mon, 16 Feb 2026 15:16:51 GMT https://researchdata.se/en/catalogue/dataset/2025-249 https://researchdata.se/en/catalogue/dataset/2025-249 Swedish Polar Research Secretariat Enh. för fartygsbaserat forskningsstöd Polarforskningssekretariatet This dataset was used to assess pre-treatment conditions of 6 sites that were selected to undergo riparian thinning experiment. All sites were in riparian forests along small streams in central Sweden, and the riparian forests were middle-age production forests, dominated by spruce. All forests were in the age for thinning. Before thinning was applied, riparian conditions, including forest structure (species composition, size of trees), ground vegetation (vascular plants and bryophytes), large wood (species composition, size, decomposition stage) and microlimate conditions (soil moisture and temperature, air humidity and temperature, incoming radiation) were assessed. The pre-thinning raw data from the summer-autumn of 2022 (June-October) are included in this data set. Tue, 26 Aug 2025 11:07:22 GMT https://researchdata.se/en/catalogue/dataset/2024-25 https://researchdata.se/en/catalogue/dataset/2024-25 Swedish University of Agricultural Sciences Lenka Kuglerová Eva Ring Eliza Maher Hasselquist Emelie Fredriksson From May until September 2020, micro- and macroclimatic temperature were measured along a 1200 km latitudinal gradient in Sweden. Microclimatic temperature was measured hourly under the bark of spruce logs, while macroclimatic temperature refers to measured air temperature 1.3 m above the ground at the same study sites. From April until September 2021, saproxylic beetles were collected at these study sites. The data set "boreal_forest_climate_data" contains 12 columns and 88 rows. Block: six different study sites are distributed from southern (1) to northern Sweden (6). Plot: five study plots that contains one study site. Block 1: Plot 11-15 Block 2: Plot 6-10 Block 3: 16-20 Block 4: 21-25 Block 5: 1-5 Block 6: 26-30 Shade: three different shade level at one plot. 1: sun-exposed, 2: intermediately shaded and 3: fully-shaded. Mikro- and makrotemp: mean temperatures per Block, plot and shade. CTI: community temperature index per Block, plot, and shade. Bark: Remaining bark at every spruce log. Diameter: Diameter of the spruce logs. Regional climate: Average temperature measured by nearby weather stations for every block over the period from May-September 1990-2020 in °C. Aspect: Aspect in degrees of every plot. Species richness: Species richness per Block, plot, and shade. Totalab: Abundance per Block, plot, and shade. Dataset "specieslist_xylo" contains 6 columns and 3460 rows. Log: 15 Spruce logs distributed over different shade levels on every plot. Spruce logs 1,4,7,10 and 13 on shade level 1; spruce logs 2,5,8,11 and 14 on shade level 2 and spruce logs 3,6,9,12, and 15 on shade level 3. Sampling_date: Date, when beetle species were collected. Species: Name of saproxylic beetle species found in each spruce log. Number: Number of each species found in each spruce log. STI: Species temperature index for every beetle species. Tue, 20 May 2025 13:06:08 GMT https://researchdata.se/en/catalogue/dataset/2023-8-1 https://researchdata.se/en/catalogue/dataset/2023-8-1 Swedish University of Agricultural Sciences Anika Gossmann Thomas Ranius Martin Schroeder Erik Öckinger Ly Lindman Data contains daily Rossby wave spectra that were obtained from a double Fourier transform, in space and time, and displayed in harmonics with wavenumber n and phase speed c. The underlying dataset for the space-time Fourier analysis is meridional wind of ERA5. For further details about data, see section 2.3 in Schutte et al., 2024 (https://doi.org/10.5194/wcd-5-733-2024). Data is split into two files: 1. allyears_NDJFMA_35_75_spectra_v_61d_strato.nc - spectra averaged between 35◦N-75◦N for the stratosphere (10, 50, 100 and 200 hPa) and, 2. allyears_NDJFMA_35_75_spectra_v_61d_tropo.nc - spectra averaged between 35◦N-75◦N in the troposphere (250, 400, 500, 600, 700 and 850 hPa). The files contain data for November to April (NDJFMA) for years 1979 to 2021. Tue, 11 Feb 2025 16:04:53 GMT https://researchdata.se/en/catalogue/dataset/2024-441 https://researchdata.se/en/catalogue/dataset/2024-441 Uppsala University Jacopo Riboldi Michael Schutte In August – September 2024, the North of Greenland expedition with IB Oden went to Northern Greenland and the adjacent Arctic Ocean, including the Lincoln Sea. The expedition is based on the research theme GEOEO, which is carried out within the Polar Research Process. The North of Greenland 2024 expedition addresses scientific questions focused on providing new knowledge on the marine cryosphere’s dynamic history and response to future climate change, including implications for marine and terrestrial ecosystems in North Greenland and the adjacent Arctic Ocean and the North Greenland Ice Sheet’s contribution to global sea-level rise. This dataset contains meteorological, oceanographic, and ship data collected during the international expedition GEOEO 2024. The data includes: Meteorological variables: Air temperature, humidity, wind direction/speed, atmospheric pressure, cloud height/cloudiness, and photosynthetically active radiation (PAR). Oceanographic variables: Sea water temperature, conductivity, salinity, and sound velocity. Ship data: Position, speed, course, heading, and water depth. A file titled "Parameterlist ShipData GEOEO 2024" describes the variables. Quality Information: No additional processing or quality checks have been performed on the data. Users should take this into account when handling and analyzing the data. Tue, 11 Feb 2025 09:17:55 GMT https://researchdata.se/en/catalogue/dataset/2024-645 https://researchdata.se/en/catalogue/dataset/2024-645 Swedish Polar Research Secretariat We have used eight co-located GNSS stations, with different antenna mounts, to estimate atmospheric signal propagation delays in the zenith direction and linear horizontal gradients. The gradients are compared with the results from a water vapour radiometer (WVR). Water drops in the atmosphere has a negative influence on the retrieval accuracy of the WVR. Hence we see a better agreement using WVR data with a liquid water content (LWC) less than 0.05mm compared to when LWC values of up to 0.7mm are included. We have used two different constraints when estimating the linear gradients from the GNSS data. Using a weak constraint enhances the GNSS estimates to track large gradients of short duration at the cost of increased formal errors. To mitigate random noise in the GNSS data, we adopted a fusion approach averaging estimates from the GNSS stations. This resulted in significant improvements for the agreement with WVR data, a maximum of 17% increase in the correlation and a 14% reduction in the root-mean-square (rms) difference for the east gradients. The corresponding values for the north gradients are both 25%. Overall, no large differences in terms of quality were observed for the eight GNSS stations. However, one station shows slightly poorer agreement for the north gradients compared to the others. This is attributed to the station's proximity to a radio telescope, which causes data loss of observations at low elevation angles in the south-south-west direction. Thu, 16 Jan 2025 09:11:15 GMT https://researchdata.se/en/catalogue/dataset/2024-515 https://researchdata.se/en/catalogue/dataset/2024-515 Chalmers University of Technology Gunnar Elgered Tong Ning