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454 results for “weather data”
Lake Sunapee Instrumented Buoy: High-Frequency Weather Data, 2007-2022
The Lake Sunapee/Global Lake Ecological Observatory Network (GLEON) instrumented buoy, operated by the Lake Sunapee Protective Association (LSPA www.lakesunapee.org), is equipped with meteorologic (weather) sensors. The Lake Sunapee buoy is located near Loon Island Lighthouse (43.391°N, 72.058°W) during the summer months and in the Lake Sunapee Harbor (43.386°N, 72.081°W) (2010-current) from late fall to spring. During the first few years of data collection (2007-2010), the buoy was located near Loon Island year-round. The meteorological sensors include: a LI-COR LI-190R Quantum Photosynthetically Active Radiation (PAR) sensor (May 2018 - present), an air temperature sensor (HMP50 Vaisala, 2010-present), and a wind speed/direction sensor (WXT511 Vaisala, 2009-present) sensor. These sensors are located approximately 1.7 meters above the water's surface. The buoy is also equipped with below-water surface sensors comprised of water temperature thermistors and dissolved oxygen sensors, and as of 2021, a YSI EXO multiparameter sonde. The data from the below water sensors are available in a separate dataset (EDI data package edi.499). All data in this data package have been QAQC'd to remove obviously errant readings, highly suspicious readings, and artifacts of buoy maintenance.
Weather station data from three locations at Lake Sunapee (NH, USA), July 2019 – December 2023
Davis weather stations, owned and operated by the Lake Sunapee Protective Association (LSPA), were installed at three locations near the shoreline of Lake Sunapee (NH, USA) in July 2019. These stations collect data at 30-minute intervals for a number of weather and meteorological variables continuously throughout the year. In addition to the measured variables, a number of derived variables are also recorded at the same time intervals. Data are manually downloaded from Davis’s WeatherLink website every quarter, then collated and QAQC’d to remove any obvious outliers or recording errors in the R programming language.
Hourly weather data from the Arctic LTER Wet Sedge Inlet Experimental plots from 1994 to present, Toolik Field Station, North Slope, Alaska.
Hourly weather data from the Arctic Tundra LTER wet sedge experimental site at Toolik Lake. The following parameters are measured every minute and averaged every hour: control plot air temperature and relative humidity at 3 meters and greenhouse plot air temperature and relative humidity at 1 meters (inside the greenhouse).
AWE01 Meteorological data from the konza prairie headquarters weather station
The following weather data are included in this data set: hourly (record type 1): mean temperature, mean relative humidity, mean wind speed, mean wind direction, mean solar radiation, soil temperature, max wind speed; Daily (record type 2): maximum air temperature, minimum air temperature, mean air temperature, mean relative humidity, total solar radiation, total precipitation, maximum soil temperature, minimum soil temperature, mean soil temperature, average wind speed. These data are collectecd by a micrologger at headquarters on Konza Prairie.
Groundwater, soil moisture, light and weather data in Brownsville forest, Nassawadox, VA, 2019-2023
This dataset includes groundwater, soil moisture, weather and light data collected in eight study sites in the Brownsville forested area (VA). In particular, sites H5 and H7 characterize the high forest where healthy Pinus taeda dominate, sites L1 and L6 characterize the low forest, where barren or dead Pinus taeda are present, sites M1 and M2 characterize the medium forest, representing transition between high and low forest, transition site where dead trees and saltmarsh vegetation live together and marsh site dominated by saltmarsh vegetation. Data collection, started in January 2019, is done for VCR-LTER and CCZN (Coastal Critical Zone Network) long term projects. CTD-Diver are used to measure groundwater pressure, specific conductance and temperature. They hang from a cable in six wells, one for each study site. Water pressure is compensated using barometric pressure data collected by the weather station nearby. Water levels are georeferenced to NAVD 88. Two soil moisture sensors for each site are placed 7-10 cm and 30 cm below the ground surface to detect water content, specific conductance and temperature of the first soil layer. Two weather stations are always installed in different sites. Their position is periodically changed to cover all sites. This material is based upon work supported by the National Science Foundation under Grant No. 2012322, Collaborative Research: Network Cluster: The Coastal Critical Zone: Processes that transform landscapes and fluxes between land and sea.
The Jefferson Project 2017 weather data from seven surface weather stations on Lake George, NY, USA.
The Jefferson Project at Lake George – a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association – combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake’s food web and overall water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2017, The Jefferson Project had five weather monitoring stations around the lake collecting data on precipitation, temperature, wind, and air quality. These stations are 'WX-CedarLane', 'WX-DFWI', 'WX-GullRock', 'WX-MossyPoint' and 'WX-WhaleRock'. Weather data from two vertical profiler sites, 'VP-AnthonysNose' and 'VP-TeaIsland', are also included in this dataset. The stations have a sensor payload that include some combination of the following sensors: HC2-S3 sensor, Campbell Scientific CS616 soil moisture sensor, LiCor LI-200R pyranometers, RM Young 85006 anemometer, Vaisala Weather Transmitter WXT series (520 & 530 models), HyQuest TB3 tipping bucket rain gauge, N-Con wet deposition sampler. The sensors collect data at high-frequency (~1 sample per minute) and the data is transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. Data provided is level 4 data which has undergone data correction and down sampling to an hourly frequency.
The Jefferson Project 2018 weather data from eight surface weather stations on Lake George, NY, USA.
The Jefferson Project at Lake George -- a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association -- combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at <https://jeffersonproject.rpi.edu/> In 2018, The Jefferson Project had six weather monitoring stations around the lake collecting data on precipitation, temperature, wind, and air quality. These stations are WX_CedarLane, WX_DFWI, WX_PilotKnob, WX_GullRock, WX_MossyPoint, and WX_WhaleRock. Weather data from two vertical profiler sites, VP_AnthonysNose and VP_TeaIsland, are also included in this dataset. The stations have a sensor payload that include some combination of the following sensors: Rotronic HC2-S3 sensor, Campbell Scientific CS616 soil moisture sensor, Li-Cor LI-200R pyranometers, RM Young 85006 anemometer, Vaisala Weather Transmitter WXT series (520 & 530 models), HyQuest TB3 tipping bucket rain gauge, N-Con wet deposition sampler. The sensors collect data at high-frequency (~1 sample per minute) and the data is transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. Data provided is level 4 data which has undergone data correction and downsampling to an hourly frequency.
The Jefferson Project 2019 weather data from ten surface weather stations on Lake George, NY, USA.
The Jefferson Project at Lake George – a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association – combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2019, The Jefferson Project had seven weather monitoring stations around the lake collecting data on precipitation, temperature, wind speed, wind direction, barometric pressure, and relative humidiity. These stations are WX_CedarLane, WX_DFWI, WX_GullRock, WX_MossyPoint, WX_WhaleRock, WX_PilotKnob, and WX_Glenburnie. Weather data from three vertical profiler sites (VP_AnthonysNose, VP_CalvesPen, and VP_TeaIsland) are also included in this dataset. The stations have a sensor payload that include some combination of the following sensors: Rotronic HC2-S3 sensor, Campbell Scientific CS616 soil moisture sensor, Li-Cor LI-200R pyranometers, RM Young 85006 anemometer, Vaisala Weather Transmitter WXT series (520 & 530 models), HyQuest TB3 tipping bucket rain gauge, N-Con wet deposition sampler. The sensors collect data at high-frequency (~1 sample per minute) and the data is transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. Data provided is level 4 data which has undergone data correction and downsampling to an hourly frequency.
The Jefferson Project 2020 weather data from seven surface weather stations on Lake George, NY, USA.
The Jefferson Project at Lake George – a partnership between Rensselaer Polytechnic Institute, IBM Research, and Lake George Association – combines Internet of Things technology and powerful analytics with science to create a new model for environmental monitoring and prediction. The project is building a computing platform that captures and analyzes data from a network of sensors tracking water quality and movement. These sensor data are combined with other monitoring and experimental data to create a thorough understanding of the factors that drive the lake's food web, hydrology, and water quality. More information about The Jefferson Project is available at https://jeffersonproject.rpi.edu/ In 2020, The Jefferson Project had seven weather monitoring stations around the lake collecting data on precipitation, temperature, wind speed, wind direction, barometric pressure, and relative humidiity. These stations are WX_CedarLane, WX_DFWI, WX_GullRock, WX_MossyPoint, WX_WhaleRock, WX_PilotKnob, and WX_Glenburnie. The stations have a sensor payload that include some combination of the following sensors: Rotronic HC2-S3 sensor, Campbell Scientific CS616 soil moisture sensor, Li-Cor LI-200R pyranometers, RM Young 85006 anemometer, Vaisala Weather Transmitter WXT series (520 & 530 models), HyQuest TB3 tipping bucket rain gauge, and N-Con wet deposition sampler. The sensors collect data at high-frequency (~1 sample per minute) and the data are transferred in near real-time to off-site databases for monitoring and review by Jefferson Project researchers. The data provided here are level 4 data which has undergone data correction and downsampling to an hourly frequency.
Weather station data acquired across multiple locations on the San Joaquin Experimental Range, California, 2011-2017
These weather station records were collected as part of a larger study relating microclimates to tree seedling survival in southern California mountains. These weather station records are for studies at the San Joaquin Experimental Range (Lat 37.083, Long -119.716, elevation 210-520 m, www.fs.fed.us/psw/ef/san_joaquin/). Weather stations were located at six sites across the landscape. Sites were selected to sample topographic variation in surface and air temperatures within a narrow range of elevations on northeast to southwest-facing slopes, ridges, and valleys. Three full weather stations (north slope, south slope, and valley floor) monitored precipitation, wind, insolation, temperature, relative humidity, and soil moisture. Three micro stations (west slope, east slope, and ridge) measured soil moisture at -20 cm. Data was recorded on a 10-minute interval using HOBO (Onset, www.onsetcomp.com) devices.
Hourly weather data from the Arctic LTER Moist Acidic Tussock Experimental plots from 2011 to present, Toolik Filed Station, North Slope, Alaska.
Hourly weather data from the LTER Moist Acidic Tussock Experimental plots. The station was installed in 1990 in block 2 of the Toolik LTER experimental moist acidic tussock plots. The plots are located on a hillside near Toolik Lake (68 38' N, 149 36'W). Global solar radiation, photosynthetic active radiation, unfrozen precipitation, air temperature, relative humidity, wind speed, and wind direction are measured at 3 meters. Additional sensors in greenhouses and shade houses plots measure air temperature, relative humidity and photosynthetic active radiation during the growing season. The sensors are read every minute and averaged or totaled every hour.
Climate data from the SINERR/GCE/UGAMI weather station at Marsh Landing on Sapelo Island, Georgia, from 01-Jan-2015 to 31-Dec-2015
Air temperature, relative humidity, barometric pressure, precipitation, photosynthetically-available and total solar radiation, and wind speed and direction were measured using an automated Campbell Scientific Instruments climate station installed at Marsh Landing on Sapelo Island, Georgia. Observations were logged at 15 minute intervals throughout the study period. The sensors were mounted on a 10m aluminum tower, with wind sensors mounted at the top, light sensors at approximately 5m, and other sensors at 2-3m to minimize interference from the surrounding landscape. This climate station was jointly operated by the Sapelo Island National Estuarine Research Reserve, the Georgia Coastal Ecosystems LTER Project, and University of Georgia Marine Institute.
Climate data from the SINERR/GCE/UGAMI weather station at Marsh Landing on Sapelo Island, Georgia, from 01-Jan-2016 to 31-Dec-2016
Air temperature, relative humidity, barometric pressure, precipitation, photosynthetically-available and total solar radiation, and wind speed and direction were measured using an automated Campbell Scientific Instruments climate station installed at Marsh Landing on Sapelo Island, Georgia. Observations were logged at 15 minute intervals throughout the study period. The sensors were mounted on a 10m aluminum tower, with wind sensors mounted at the top, light sensors at approximately 5m, and other sensors at 2-3m to minimize interference from the surrounding landscape. This climate station was jointly operated by the Sapelo Island National Estuarine Research Reserve, the Georgia Coastal Ecosystems LTER Project, and University of Georgia Marine Institute.
Long-term Climate data from the SINERR/GCE/UGAMI weather station at Marsh Landing on Sapelo Island, Georgia, from 03-Jan-2003 to 31-Dec-2019
Air temperature, relative humidity, barometric pressure, precipitation, photosynthetically-available and total solar radiation, and wind speed and direction were measured using an automated Campbell Scientific Instruments climate station installed at Marsh Landing on Sapelo Island, Georgia. Observations were logged at 15 minute intervals throughout the study period. The sensors were mounted on a 10m aluminum tower, with wind sensors mounted at the top, light sensors at approximately 5m, and other sensors at 2-3m to minimize interference from the surrounding landscape. Annual data sets from 2003 to 2019 were then synthesized and standardized to create a long-term, monotonic time series data set that will be updated annually. This climate station was jointly operated by the Sapelo Island National Estuarine Research Reserve, the Georgia Coastal Ecosystems LTER Project, and University of Georgia Marine Institute.
Climate data from the SINERR/GCE/UGAMI weather station at Marsh Landing on Sapelo Island, Georgia, from 01-Jan-2017 to 31-Dec-2017
Air temperature, relative humidity, barometric pressure, precipitation, photosynthetically-available and total solar radiation, and wind speed and direction were measured using an automated Campbell Scientific Instruments climate station installed at Marsh Landing on Sapelo Island, Georgia. Observations were logged at 15 minute intervals throughout the study period. The sensors were mounted on a 10m aluminum tower, with wind sensors mounted at the top, light sensors at approximately 5m, and other sensors at 2-3m to minimize interference from the surrounding landscape. This climate station was jointly operated by the Sapelo Island National Estuarine Research Reserve, the Georgia Coastal Ecosystems LTER Project, and University of Georgia Marine Institute.
Precipitation data from a standard can rain gauge at the LTER weather station, Jornada Basin, southern New Mexico, USA, 1992-ongoing
This data package contains precipitation measurements collected from a "dipstick" rain gauge (NOAA standard can type) at the LTER Weather Station in the Jornada Basin, southern New Mexico, USA. The primary purpose of this data set is to validate the LTER Weather Station tipping bucket rain gauge data. The dipstick rain gauge (DSRG) data is measured at least weekly during scheduled maintenance trips to the LTER Weather Station to maintain the evaporation pan water levels. During the summer months this may be twice a week. Additionally, DSRG data is collected after any rain event that requires the collection of the Wetfall/Dryfall precipitation buckets which are located about 10 meters from the DSRG. This is usually any amount greater than 0.02 inches. DSRG data is also collected after very small events when personnel are in the vicinity. Rain gauge records at this gauge began in 1992 and the study is ongoing.
Locally verified daily temperature and precipitation data from a NOAA weather station at USDA Jornada Experimental Range headquarters, southern New Mexico USA, 1914-2006
This data package contains locally verified daily meteorological observations from a NOAA National Weather Service station located at the USDA Jornada Experimental Range headquarters in southern New Mexico, USA. Daily data has been collected there by USDA staff since 1914 for minimum and maximum air temperature and daily accumulated precipitation using standard U.S. climatological service instrumentation and procedures. The included data were verified and transcribed directly from the original paper data sheets and have undergone quality control and assurance procedures different than those in place at NOAA. These data therefore differ from those directly downloadable from NOAA servers. Local verification and transcription of observations from the data sheets ceased in 2006 and data are now directly entered to the NOAA system. Therefore, this dataset is complete and will no longer be added to. All observations from this weather station have also undergone NOAA QA/QC procedures and those data are available by accessing the Jornada Experimental Range, NM US GHCN station through the National Climatic Data Center portal (https://www.ncdc.noaa.gov/cdo-web/datasets/GHCND/stations/GHCND:USC00294426/detail - daily and monthly data are available).
Locally verified monthly summary temperature and precipitation data from a NOAA weather station at USDA Jornada Experimental Range headquarters, southern New Mexico USA, 1914-1998
This data package contains locally verified monthly meteorological observations from a NOAA National Weather Service station located at the USDA Jornada Experimental Range headquarters in southern New Mexico, USA. Monthly summary data (based on daily observations) has been collected there by USDA staff since 1914 for minimum and maximum air temperature and daily accumulated precipitation using standard U.S. climatological service instrumentation and procedures. The included data were verified and transcribed directly from the original paper data sheets and have undergone quality control and assurance procedures different than those in place at NOAA. These data therefore differ from those directly downloadable from NOAA servers. Local verification and transcription of observations from the data sheets ceased in 1998 and data are now directly entered to the NOAA system. Therefore, this dataset is complete and will no longer be added to. All observations from this weather station have also undergone NOAA QA/QC procedures and those data are available by accessing the Jornada Experimental Range, NM US GHCN station through the National Climatic Data Center portal https://www.ncdc.noaa.gov/cdo-web/datasets/GSOM/stations/GHCND:USC00294426/detail - daily and monthly data are available).
PIE LTER, meteorological data, 15 minute intervals, from the Marshview Farm weather station located in Newbury, MA, year 2021
Meteorological measurements for 2021 at MBL Marshview Farm, Newbury, MA. Sensors conduct measurements every 5 seconds 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.
PIE LTER 15-minute meteorological data from the Marshview Farm weather station located in Newbury, MA, year 2022
Meteorological measurements for 2022 at MBL Marshview Farm, Newbury, MA. Sensors conduct measurements every 5 seconds 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.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.