Find research datasets worth reusing

Year 2010, meteorological data, 15 minute intervals, from the Marshview Farm weather station located in Newbury, MA

Year 2010 meteorological measurements at MBL Marshview Farm of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

Year 2011, meteorological data, 15 minute intervals, from the Marshview Farm weather station located in Newbury, MA

Year 2011 meteorological measurements at MBL Marshview Farm of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

Year 2013, meteorological data, 15 minute intervals, from the Marshview Farm weather station located in Newbury, MA

Year 2013 meteorological measurements at MBL Marshview Farm of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

openCC (other)Feb 2019View details →

PIE LTER year 2018, meteorological data, 15 minute intervals, from the PIE LTER Marshview Farm weather station located in Newbury, MA

Year 2018 meteorological measurements at MBL Marshview Farm of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

openCC (other)Jan 2020View details →

PIE LTER year 2019, meteorological data, 15 minute intervals, from the PIE LTER Marshview Farm weather station located in Newbury, MA.

Year 2019 meteorological measurements at MBL Marshview Farm of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

openCC (other)Mar 2021View details →

PIE LTER year 2020, meteorological data, 15 minute intervals, from the PIE LTER Marshview Farm weather station located in Newbury, MA

Year 2020 meteorological measurements at MBL Marshview Farm of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

Year 2007, meteorological data, 15 minute intervals, from weather station located at the Governor's Academy, Byfield, MA then moved to MBL Marshview Farm, Newbury, MA.

Year 2007 meteorological measurements at Governor's Academy and MBL Marshview Farm of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

Year 2000, meteorological data, 15 minute intervals, from weather station located at the Governor's Academy located in Byfield, MA.

Year 2000 meteorological measurements at Governor's Academy of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

Year 2001, meteorological data, 15 minute intervals, from weather station located at the Governor's Academy located in Byfield, MA.

Year 2001 meteorological measurements at Governor's Academy of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

Year 2002, meteorological data, 15 minute intervals, from weather station located at the Governor's Academy located in Byfield, MA.

Year 2002 meteorological measurements at Governor's Academy of air temperature, humidity, precipitation, solar radiation, photosynthetically active radiation (PAR), wind speed and direction and barometric pressure. Sensors conduct measurements every 5 secs and measurements are reported as averages or totals for 15 minute intervals. 15 minute averages are reported for air temperature, humidity, solar radiation, PAR, wind speed and direction and barometric pressure. 15 minute totals are reported for precipitation.

opencc-by-4.0Nov 2024View details →

Database of ASTI-Network Rome weather stations

The database includes hourly data of the main meteorological parameters measured in the area of Rome (Italy) by 17 of the weather stations belonging to the ASTI-Network. The dataset also includes hourly data of Urban Heat Island (UHI) intensity, calculated using the imperviousness method [1], covering the time period of two summers (June, July, August, JJA) 2019 and 2020. The data are sampled by the sensors as 5-minute averages (except for precipitation, which is cumulative) and are subjected to a filtering process before being averaged to hourly resolution. The filtering process includes the following sequential steps: interference filter, climatic filter, temporal variation filter (of which spikes are a particular case), and spatial filter. Details on the implemented algorithms are provided in [1]. The final hourly data are calculated taking the right edge, and the time zone adopted is Central European Time (UTC+1). The parameters available in the dataset include atmospheric pressure (relative and absolute), air temperature, relative humidity, wind speed, wind direction, wind gusts, rain rate, cumulative precipitation, dew point, and, where available, global radiation and UV index. More details about the variables and dataset formatting are provided in the file ‘README.txt’. The file ‘Hourly_UHI.csv’ contains the UHI intensity, calculated using a linear fit between the measured temperatures (T) and the associated imperviousness (IMP, %) [1], for each time step, resulting in hourly resolution. Assuming the linear relationship T(IMP) = mIMP + q, the UHI intensity is given by 100m, and the corresponding column in the dataset is named ‘DT=100m’. Additional columns provide statistical parameters and the average values across all stations for temperature, wind speed, rain rate, and cumulative precipitation. Further details are available in the file ‘README.txt’. The file ‘metadata.csv’ contains metadata for each weather station, such as ID, coordinates, altitude, and associated imperviousness. Figure 'asti_network_sat.png' shows their spatial distribution on 2d map. This dataset forms the basis of the paper “Measuring the urban heat island of Rome through a dense weather station network and remote sensing imperviousness data” published in December 2022 in the journal Urban Climate (<a href="https://doi.org/10.1016/j.uclim.2022.101355" target="_blank" rel="noopener">doi.org/10.1016/j.uclim.2022.101355</a>). It was also used for validating the numerical model developed within the LIFE-ASTI project. The ASTI-Network measurement network consists of rooftop weather stations and distributed throughout the city of Rome. It includes amateur stations from the Meteo Lazio network (<a href="https://meteoregionelazio.it" target="_blank" rel="noopener">meteoregionelazio.it</a>) and eight stations funded by the EU LIFE-ASTI project "Implementation of a forecasting system for urban heat island effect for the development of urban adaptation strategy" (LIFE17 CCA/GR/000108) and installed by the CNR-ISAC research team based in Rome. Bibliography 1. Cecilia, A., Casasanta, G., Petenko, I., Conidi, A., Argentini, S. Measuring the urban heat island of Rome through a dense weather station network and remote sensing imperviousness data, Urban Climate 47 (01 2022).

opencc-by-4.0Feb 2024View details →

ClimateForecasts: Globally Observed Environmental Data for 15,504 Weather Station Locations

ClimateForecasts is a database that provides environmental data for 15,504 weather station locations and 49 environmental variables, including 38 bioclimatic variables, 8 soil variables and 3 topographic variables. Data were extracted from the same 30 arc-seconds global grid layers that were prepared when making the TreeGOER (Tree Globally Observed Environmental Ranges) database that is available from <a href="https://doi.org/10.5281/zenodo.7922927">https://doi.org/10.5281/zenodo.7922927</a><a name="_Hlk141002106"></a>. Details on the preparations of these layers are provided by Kindt, R. (2023). TreeGOER: A database with globally observed environmental ranges for 48,129 tree species. Global Change Biology 29: 6303–6318. <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914</a>. A similar extraction process was used for the CitiesGOER database that is also available from Zenodo via <a href="../doi/10.5281/zenodo.8175429">https://zenodo.org/doi/10.5281/zenodo.8175429</a>. ClimateForecasts (as the CitiesGOER) was designed to be used together with TreeGOER and possibly also with the <a href="https://worldagroforestry.org/output/globalusefulnativetrees">GlobalUsefulNativeTrees</a> database (Kindt et al. <a href="https://www.nature.com/articles/s41598-023-39552-1">2023</a>) to allow users to filter suitable tree species based on environmental conditions of the planting site. One example of combining data from these different sets in the R statistical environment is available from this Rpub: <a href="https://rpubs.com/Roeland-KINDT/1114902">https://rpubs.com/Roeland-KINDT/1114902</a>. The identities including the geographical coordinates of weather stations were sourced from <a href="https://meteostat.net/en/">Meteostat</a>, specifically by downloading (17-FEB-2024) the <a href="https://dev.meteostat.net/bulk/stations.html">‘lite dump’ data set</a> with information for active weather stations only. Two weather stations where the country could not be determined from the ISO 3166-1 code of ‘XA’ were removed. If weather stations had the same name, but occurred in different ISO 3166-2 regions, this region code was added to the name of the weather station between square brackets. Afterwards duplicates (weather stations of the same name and region) were manually removed. Bioclimatic variables for future climates correspond to the median values from 24 Global Climate Models (GCMs) for Shared Socio-Economic Pathway (SSP) 1-2.6 for the 2050s (2041-2060), from 21 GCMs for SSP 3-7.0 for the 2050s and from 13 GCMs for SSP 5-8.5 for the 2090s. Similar methods were used to calculate these median values as in the case studies for the <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">TreeGOER manuscript</a> (calculations were partially done via the <a href="https://rdrr.io/cran/BiodiversityR/man/ensemble.envirem.html">BiodiversityR::ensemble.envirem.run</a> function and with downscaled bioclimatic and monthly climate 2.5 arc-minutes <a href="https://www.worldclim.org/data/cmip6/cmip6_clim2.5m.html">future grid layers available from WorldClim 2.1</a>). Maps were added in version 2024.03 where locations of weather stations were shown on a map of the Climatic Moisture Index (CMI). These maps were created by a similar process as in the <a href="../doi/10.5281/zenodo.8252756">TreeGOER Global Zones Atlas</a> from the environmental raster layers used to create the TreeGOER via the <a href="https://cran.r-project.org/web/packages/terra/">terra package</a> (Hijmans et al. 2022, version 1.7-46) in the <a href="https://cran.r-project.org/">R 4.2.1 environment</a>. Added country boundaries were obtained from <a href="https://www.naturalearthdata.com/downloads/10m-cultural-vectors/">Natural Earth</a> as <a href="https://www.naturalearthdata.com/http/www.naturalearthdata.com/download/10m/cultural/ne_10m_admin_0_countries.zip">Admin 0 – countries vector layers</a> (version 5.1.1). Also added after obtaining them from Natural Earth were <a href="https://www.naturalearthdata.com/http/www.naturalearthdata.com/download/10m/cultural/ne_10m_admin_0_boundary_lines_disputed_areas.zip">Admin 0 – Breakaway, Disputed areas</a> (version 5.1.0, coloured yellow in the atlas) and <a href="https://www.naturalearthdata.com/http/www.naturalearthdata.com/download/10m/cultural/ne_10m_roads.zip">Roads</a> (version 5.0.0, coloured red in the atlas). For countries where the GlobalUsefulNativeTrees database included subnational levels, boundaries were added and depicted as dot-dash lines. These subnational levels correspond to level 3 boundaries in the World Geographical Scheme for Recording Plant Distributions. These were obtained from <a href="https://github.com/tdwg/wgsrpd">https://github.com/tdwg/wgsrpd</a>. Check <a href="https://github.com/tdwg/wgsrpd/blob/master/109-488-1-ED/2nd%20Edition/TDWG_geo2.pdf">Brummit 2001</a> for details such as the maps shown at the end of this document. Maps for version 2024.07 modified the dimensions of the sheets to those used in version 2024.06 of the <a href="../doi/10.5281/zenodo.8252756">TreeGOER Global Zones Atlas</a>. Another modification was the inclusion of Natural Earth boundaries for <a href="https://www.naturalearthdata.com/http/www.naturalearthdata.com/download/10m/physical/ne_10m_lakes.zip">Lakes</a> (version 5.0.0, coloured darkblue in the atlas). Version 2024.10 includes a new data set that documents the location of the city locations in Holdridge Life Zones. Information is given for historical (1901-1920), contemporary (1979-2013) and future (2061-2080; separately for RCP 4.5 and RCP 8.5) that are <a href="https://datadryad.org/stash/dataset/doi:10.5061/dryad.41ns1rnff">available for download from DRYAD</a> and were created for the following article: Elsen et al. 2022. Accelerated shifts in terrestrial life zones under rapid climate change. Global Change Biology, 28, 918–935. <a href="https://doi.org/10.1111/gcb.15962">https://doi.org/10.1111/gcb.15962</a>. Version 2024.10 further includes Holdridge Life Zones for the climates available from the previously included climates, calculating biotemperatures and life zones with similar methods as used by Holdridge (<a href="https://www.jstor.org/stable/1675393?seq=1">1947</a>; <a href="https://app.ingemmet.gob.pe/biblioteca/pdf/Amb-56.pdf">1967</a>) and Elsen et al. (<a href="https://doi.org/10.1111/gcb.15962">2022</a>) (for future climates, median values were determined first for monthly maximum and minimum temperatures across GCMs ). The distributions of the 48,129 species documented in TreeGOER across the Holdridge Life Zones are given in this Zenodo archive: <a href="https://zenodo.org/records/14020914">https://zenodo.org/records/14020914</a>. Version 2024.11 includes a new data set that documents the location of the weather stations in Köppen-Geiger climate zones. Information is given for historical (1901-1930, 1931-1960, 1961-1990) and future (2041-2070 and 2071-2099) climates, with for the future climates seven scenarios each (SSP 1-1.9, SSP 1-2.6, SSP 2-4.5, SSP 3-7.0, SSP 4-3.4, SSP 4-6.0 and SSP 5-8.5). This data set was created from raster layers available via: Beck, H.E., McVicar, T.R., Vergopolan, N. et al. High-resolution (1 km) Köppen-Geiger maps for 1901–2099 based on constrained CMIP6 projections. Sci Data 10, 724 (2023). <a href="https://doi.org/10.1038/s41597-023-02549-6">https://doi.org/10.1038/s41597-023-02549-6</a>. Version 2025.03 includes extra columns for the baseline, 2050s and 2090s datasets that partially correspond to climate zones used in the <a href="https://worldagroforestry.org/output/globalusefulnativetrees">GlobalUsefulNativeTrees</a> database. One of these zones are the <a href="https://rawgit.com/valentinitnelav/plotbiomes/master/html/Whittaker_biomes_dataset.html">Whittaker biome types</a>, available as a polygon from the <a href="https://rawgit.com/valentinitnelav/plotbiomes/master/html/Whittaker_biomes_dataset.html">plotbiomes</a> package (see also <a href="https://www.davidzeleny.net/wiki/lib/exe/fetch.php/vegecol:materials:ricklefs_bioms_chapter_5.pdf">here</a>). Whittaker biome types were extracted with similar R scripts as described by <a href="https://rpubs.com/Roeland-KINDT/1275232">Kindt 2025</a> (these were also used to calculate environmental ranges of TreeGOER species, as archived <a href="https://zenodo.org/records/14908944">here</a>). Version 2025.03 further includes information for the baseline climate on the steady state water table depth, obtained from a 30 arc-seconds raster layer calculated by the GLOBGM v1.0 model (Verkaik et al. <a href="https://gmd.copernicus.org/articles/17/275/2024/">2024</a>).   When using ClimateForecasts in your work, cite this depository and the following: <ul> <li>Fick, S. E., & Hijmans, R. J. (2017). WorldClim 2: New 1‐km spatial resolution climate surfaces for global land areas. International Journal of Climatology, 37(12), 4302–4315. <a href="https://doi.org/10.1002/joc.5086">https://doi.org/10.1002/joc.5086</a></li> <li>Title, P. O., & Bemmels, J. B. (2018). ENVIREM: An expanded set of bioclimatic and topographic variables increases flexibility and improves performance of ecological niche modeling. Ecography, 41(2), 291–307. <a href="https://doi.org/10.1111/ecog.02880">https://doi.org/10.1111/ecog.02880</a></li> <li>Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., & Rossiter, D. (2021). SoilGrids 2.0: Producing soil information for the globe with quantified spatial uncertainty. SOIL, 7(1), 217–240. <a href="https://doi.org/10.5194/soil-7-217-2021">https://doi.org/10.5194/soil-7-217-2021</a></li> <li>Kindt, R. (2023). TreeGOER: A database with globally observed environmental ranges for 48,129 tree species. Global Change Biology, 00, 1–16. <a href="https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914">https://onlinelibrary.wiley.com/doi/10.1111/gcb.16914</a>.</li> <li>Meteostat (2024) Weather stations: Lite dump with active weather stations. <a href="https://github.com/meteostat/weather-stations">https://github.com/meteostat/weather-stations</a> (accessed 17-FEB-2024)</li> </ul> When using information from the Holdridge Life Zones, also cite: <ul> <li>Elsen, P. R., Saxon, E. C., Simmons, B. A., Ward, M., Williams, B. A., Grantham, H. S., Kark, S., Levin, N., Perez-Hammerle, K.-V., Reside, A. E., & Watson, J. E. M. (2022). Accelerated shifts in terrestrial life zones under rapid climate change. Global Change Biology, 28, 918–935. <a href="https://doi.org/10.1111/gcb.15962">https://doi.org/10.1111/gcb.15962</a></li> </ul> When using information from Köppen-Geiger climate zones, also cite: <ul> <li>Beck, H.E., McVicar, T.R., Vergopolan, N., Berg, A., Lutsko, N.J., Dufour, A., Zeng, Z., Jiang, X., van Dijk, A.I. and Miralles, D.G. 2023. High-resolution (1 km) Köppen-Geiger maps for 1901–2099 based on constrained CMIP6 projections. Sci Data 10, 724. <a href="https://doi.org/10.1038/s41597-023-02549-6">https://doi.org/10.1038/s41597-023-02549-6</a></li> </ul> When using information on the Whittaker biome types, also cite: <ul> <li>Ricklefs, R. E., Relyea, R. (2018). Ecology: The Economy of Nature. United States: W.H. Freeman.</li> <li>Whittaker, R. H. (1970). Communities and ecosystems.</li> <li>Valentin Ștefan, & Sam Levin. (2018). plotbiomes: R package for plotting Whittaker biomes with ggplot2 (v1.0.0). Zenodo. <a href="https://doi.org/10.5281/zenodo.7145245">https://doi.org/10.5281/zenodo.7145245</a></li> </ul> When using information on the steady state water table depth, also cite: <ul> <li>Verkaik, J., Sutanudjaja, E. H., Oude Essink, G. H., Lin, H. X., & Bierkens, M. F. (2024). GLOBGM v1. 0: a parallel implementation of a 30 arcsec PCR-GLOBWB-MODFLOW global-scale groundwater model. Geoscientific Model Development, 17(1), 275-300. <a href="https://gmd.copernicus.org/articles/17/275/2024/">https://gmd.copernicus.org/articles/17/275/2024/</a></li> </ul>   The development of ClimateForecasts and its partial integration in version 2024.03 of the GlobalUsefulNativeTrees database was supported by the Darwin Initiative to project DAREX001 of Developing a Global Biodiversity Standard certification for tree-planting and restoration, by Norway’s International Climate and Forest Initiative through the Royal Norwegian Embassy in Ethiopia to the Provision of Adequate Tree Seed Portfolio project in Ethiopia, by the Green Climate Fund through the IUCN-led Transforming the Eastern Province of Rwanda through Adaptation project and through the Readiness proposal on Climate Appropriate Portfolios of Tree Diversity for Burkina Faso, by the Bezos Earth Fund to the Quality Tree Seed for Africa in Kenya and Rwanda project and by the German International Climate Initiative (IKI) to the regional tree seed programme on The Right Tree for the Right Place for the Right Purpose in Africa.

opencc-zeroMar 2024View details →

Tarmachan Automatic Weather Station (National Trust for Scotland/University of Dundee)

Mountain weather station on the south-facing slopes of Meall nan Tarmachan on the National Trust for Scotland's National Nature Reserve (NNR).  The site is at 710 m above sea level, overlooking Loch Tay.  Snowcover has historically been an important part of the climate of the site, but in recent years has become increasingly transient. The NNR is the most important in Scotland for its arctic alpine flora, we are noticing changes in species distribution and to habitats indicative of the effects of climate change.  Hence the establishment of this weather station to allow changes in climate at altitude to be monitored.  This site installed May 2018 ~20 m beyond the headwall of a disused quarry.  Winds may cause undercatch of rainfall (though the gauge is of an aerodynamic design) and more particularly snow.  Recorded wind speeds may underestimate winds generally around the mountain owing to effects of the quarry wall. An earlier site was operated nearby in the early 2000s but sadly data have been lost. Data are recorded on a Campbell Scientific CR1000 data logger, running with 10 s scan rate and 15 min logging interval. Snow depths may be inferred by examining TCDT (temperature-corrected depth to target) data - obtained from a SR50A sensor on an arm c. 2.3 m above ground.  These are available only for limited periods in 2019 and again winter 2021/22, and are now discontinued.  However, snow cover can be inferred by examining the differential between air temperature and ground temperature: the ground sensor is insulated when snow covers the ground. Sensor details: see metdata Real-time data are displayed graphically at <a href="https://hydro-data.dundee.ac.uk/tarmachan" target="_blank" rel="noopener">https://hydro-data.dundee.ac.uk/tarmachan</a> (no downloads)

opencc-by-4.0Sep 2021View details →

DTR from 189 weather stations in the contiguous USA from 2015 to 2020

Temperature data was collected from the National Climatic Data Center (NCDC, 2021). It is considered as the world’s largest archive of data regarding weather. For this study, data was collected from the year of 2010 to 2020. Data was taken from the 48 States of the contiguous USA and the DC. For 42 of these States, 4 stations were analyzed per State. For 6 of these States and the DC, 3 stations were analyzed from each. In total, data of 189 stations across the USA were collected.

opencc-by-4.0Feb 2022View details →

Lancer Park Weather Station Data from 2022-01-06 to 2022-02-14

General Metadata for Lancer Park Environmental Education Center Atmospheric Sampling Station Files Specific metadata for each deployment can be found as text files with the file format of: <pre><code>LP_weather_YYYY-MM-DD_metadata.txt</code></pre> Where YYYY-MM-DD is the date that the sampling period ended. Metadata File Created <ul> <li>2019-10-27 by KF</li> </ul> File Modified Description These data are from a weather station installed at the Longwood University Environmental Education Center at Lancer Park (37.308189, -78.402768) as part of the Longwood Environmental Observatory. All data are CC-BY and should be cited using the DOI available at <a href="https://zenodo.org/communities/leo/">https://zenodo.org/communities/leo/</a> Station Specifics The specific at each site are: <pre><code>* Barometric Pressure (mmHg) - Campbell Scientific CS100 Barometric Pressure Sensor * Light Flux Density (kW/m^2) - Campbell Scientific Pyranometer CS300 * Light Total Flux (kJ/m^2) - Campbell Scientific Pyranometer CS300 * Rainfall (mm) - Texas Electronics TE525 Tipping Bucket * Temperature (dC) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Relative Humidity (%) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Wind Speed (m/s) - RM Young 05103 Wind Speed and Direction Sensor * Wind Direction (degrees from true N) - RM Young 05103 Wind Speed and Direction Sensor * Data Collection - Campbell Scientific CR200 Data Logger * The sensors are sampled every 15 minutes</code></pre> Measurement Parameters, units, and Variable Names <pre><code>* DATE - the date that the record was collected (YYYY-MM-DD) * TIMESTAMP - the date and time that the record was collected (YYYY-MM-DD HH:MM:SS) * RECORD.x - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Avg - The average battery voltage (Volts) * BattV - The battery voltage at the time of the sampling (Volts) * BP_mmHg_Avg - The average barometric pressure over the sampling interval (mmHg) * BP_mmHg_Std - The standard deviation of the average barometric pressure (mmHg) * BP_mmHg - The barometric pressure at the time of the sampling (mmHg) * Rain_mm_Tot - The total rainfall during the sampling interval (mm) * AirTC_Avg - The average air temperature during the sampling interval (dC) * AirTC_Std - The standard deviation of the average air temperature (dC) * AirTC - the air temperature at the time of the sampling (dC) * RH - the relative humidity at the time of the sampling (%) * RH_Min - the minimum relative humidity recorded (%) * RH_TMn - the time that the minimum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RH_Max - the maximum relative humidity recorded (%) * RH_TMx - the time that the maximum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RECORD.y - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Min - the minimum battery voltage (Volts) * SlrkW_Avg - the average light flux density during the sampling interval (kW/m^2) * SlrkW_Std - the standard deviation of the average light flux density (kW/m^2) * SlrkW - the light flux density at the time of the sampling (kW/m^2) * SlrMJ_Tot - the total light flux (MJ/m^2) * WS_ms_Avg - the average wind speed during the sampling interval (m/s) * WS_ms_Std - the standard deviation of the average wind speed (m/s) * WS_ms - the wind speed at the time of the sampling event (m/s) * WindDir - the wind direction at the time of the sampling event (degrees from true N) * WS_ms_S_WVT - the average wind speed over the previous 15 minutes (m/s) * WindDir_D1_WVT - the average wind direction over the previous 15 minutes (degrees from true N) * WindDir_SD1_WVT - the standard deviation of the average wind direction over the previous 15 minutes (degrees from true N)</code></pre>

opencc-by-4.0Mar 2022View details →

Assessment of future wind speed and wind power changes over South Greenland using the MAR regional climate model : MAR ouptuts and KATABATA weather stations timeseries

Daliy MARv3.12 outputs and KATABATA weather stations timeseries used in : Lambin, C., Fettweis, X., Kittel, C., Fonder, M., & Ernst, D. (2022).Assessment of future wind speed and wind power changes over South Greenland using the Modèle Atmosphérique Régional regional climate model. International Journal of Climatology, 43(1),558–574. https://doi.org/10.1002/joc.7795574

opencc-by-4.0Mar 2022View details →

Hull Springs Weather Station 2022-02-05 to 2022-03-08

<pre># General Metadata for Hull Springs Farm Atmospheric Sampling Station ## Files Specific metadata for each deployment can be found as text files with the file format of: HSF_weather_YYYY-MM-DD_metadata.txt Where YYYY-MM-DD is the date that the sampling period ended. ## File Created * 2019-10-27 by KF ## File Modified ## Description These data are from a weather station installed at Hull Springs Farm near the "Yellow House" (38.121683, -76.666781) as part of the Longwood Environmental Observatory. All data are CC-BY and should be cited using the DOI available at https://zenodo.org/communities/leo/ ## Station Specifics The specific at each site are: * Barometric Pressure (mmHg) - Campbell Scientific CS100 Barometric Pressure Sensor * Light Flux Density (kW/m^2) - Campbell Scientific Pyranometer CS300 * Light Total Flux (kJ/m^2) - Campbell Scientific Pyranometer CS300 * Rainfall (mm) - Texas Electronics TE525 Tipping Bucket * Temperature (dC) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Relative Humidity (%) - Campbell Scientific CS215 Temperature and Relative Humidity Sensor * Wind Speed (m/s) - RM Young 05103 Wind Speed and Direction Sensor * Wind Direction (degrees from true N) - RM Young 05103 Wind Speed and Direction Sensor * Data Collection - Campbell Scientific CR200 Data Logger * The sensors are sampled every 15 minutes ## Measurement Parameters, units, and Variable Names * DATE - the date that the record was collected (YYYY-MM-DD) * TIMESTAMP - the date and time that the record was collected (YYYY-MM-DD HH:MM:SS) * RECORD.x - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Avg - The average battery voltage (Volts) * BattV - The battery voltage at the time of the sampling (Volts) * BP_mmHg_Avg - The average barometric pressure over the sampling interval (mmHg) * BP_mmHg_Std - The standard deviation of the average barometric pressure (mmHg) * BP_mmHg - The barometric pressure at the time of the sampling (mmHg) * Rain_mm_Tot - The total rainfall during the sampling interval (mm) NOTE: These data were not collected due to hardware failure. * AirTC_Avg - The average air temperature during the sampling interval (dC) * AirTC_Std - The standard deviation of the average air temperature (dC) * AirTC - the air temperature at the time of the sampling (dC) * RH - the relative humidity at the time of the sampling (%) * RH_Min - the minimum relative humidity recorded (%) * RH_TMn - the time that the minimum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RH_Max - the maximum relative humidity recorded (%) * RH_TMx - the time that the maximum relative humidity measurement occurred (YYYY-MM-DD HH:MM:SS) * RECORD.y - a unique identifying number provided from the data logger for table 1 from the original downloaded data. * BattV_Min - the minimum battery voltage (Volts) * SlrkW_Avg - the average light flux density during the sampling interval (kW/m^2) * SlrkW_Std - the standard deviation of the average light flux density (kW/m^2) * SlrkW - the light flux density at the time of the sampling (kW/m^2) * SlrMJ_Tot - the total light flux (MJ/m^2) * WS_ms_Avg - the average wind speed during the sampling interval (m/s) * WS_ms_Std - the standard deviation of the average wind speed (m/s) * WS_ms - the wind speed at the time of the sampling event (m/s) * WindDir - the wind direction at the time of the sampling event (degrees from true N) * WS_ms_S_WVT - the average wind speed over the previous 15 minutes (m/s) * WindDir_D1_WVT - the average wind direction over the previous 15 minutes (degrees from true N) * WindDir_SD1_WVT - the standard deviation of the average wind direction over the previous 15 minutes (degrees from true N)</pre>

opencc-by-4.0Nov 2019View details →

Figure 3 in Validation of Wind Speed Calculated on Satellite Altimetry Data by Measurements on Weather Stations Located Along the White Sea Coast

Figure 3. The dependence of the speed wind at a height Figure 4. In-situ MS data breakdown scheme for a

opencc-by-4.0Nov 2019View details →

Figure 5 in Validation of Wind Speed Calculated on Satellite Altimetry Data by Measurements on Weather Stations Located Along the White Sea Coast

Figure 5. The dependence of the correlation coefficient between in-situ wind speed at the WS and remote sensing data on the orientation angle of the main quadrants (a) and their position relative to the White Sea coastline (b).