More Like this

1. Hubbard Brook Experimental Forest: Flux Tower Data

   https://doi.org/10.6073/pasta/e362f097bbac92d0cec4f94e158cf762  

   Kelsey, Eric; Green, Mark; Evans, Daniel; Wright, Ellis (January 2023, Environmental Data Initiative)

   Data collected from the Hubbard Brook Flux Tower starting in August 2016 that is also uploaded to the Ameriflux website under site name US-HBK. These data are from a suite of sensors installed on the 110 ft. tower and in the soil adjacent to the tower. Flux data are collected at 10 Hz and are processed into 30-minute time steps using Licor’s Eddy Pro software. Supporting micro-meteorological data are averaged at 30 minute intervals and are included with this data set. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. 

   more » « less
2. Hubbard Brook Experimental Forest: Flux Tower Data, 2016-2024

   https://doi.org/10.6073/pasta/89665974009b139f9b1248b9ade3a5c9  

   Kelsey, Eric; Green, Mark; Evans, Daniel; Wright, Ellis (May 2025, Environmental Data Initiative)

   Data collected from the Hubbard Brook Flux Tower starting in August 2016 that is also uploaded to the Ameriflux website under site name US-HBK. These data are from a suite of sensors installed on the 110 ft. tower and in the ground below the tower. Fast data is collected at 10Hz and is processed into 30min time steps using Licor’s Eddy Pro software. Slow data are averaged at 30 minute intervals and are included with this dataset. These data were gathered as part of the Hubbard Brook Ecosystem Study (HBES). The HBES is a collaborative effort at the Hubbard Brook Experimental Forest, which is operated and maintained by the USDA Forest Service, Northern Research Station. 

   more » « less
3. SEV LTER: Tracking Vegetation Phenology Using PhenoCam Imagery at the Sevilleta National Wildlife Refuge, New Mexico, 2014-2024

   https://doi.org/10.6073/pasta/92893de6e7337372a7bbc73e606e44d6  

   Blais, Jacob J; Richardson, Andrew D (January 2024, Environmental Data Initiative)

   As of 03/03/2024, the Sevilleta Long-Term Ecological Research Program is equipped with a total of 65 digital RGB cameras, or PhenoCams, across the Sevilleta National Wildlife Refuge. These cameras are installed on eddy covariance flux towers and at a number of precipitation manipulation experiments to track vegetation phenology and productivity across dryland ecotones. PhenoCams have been paired with eddy covariance flux tower data at the site since 2014, while some Mean-Variance Experiment PhenoCams were installed as recently as June 2023. For information on PhenoCam data processing and formatting, see Richardson et al., 2018, Scientific Data (https://doi.org/10.1038/sdata.2018.28), Seyednasrollah et al., 2019, Scientific Data (https://doi.org/10.1038/s41597-019-0229-9), and the PhenoCam Network web page (https://phenocam.nau.edu/webcam/). The PhenoCam Network uses imagery from digital cameras to track vegetation phenology and seasonal changes in vegetation activity in diverse ecosystems across North America and around the world. Imagery is uploaded to the PhenoCam server hosted at Northern Arizona University, where it is made publicly available in near-real time, every 30 minutes from sunrise to sunset, 365 days a year. The data are processed using simple image analysis tools to yield a measure of canopy greenness, from which phenological metrics are extracted, characterizing the start and end of the growing season. These transition dates have been shown to align well with on-the-ground observations at various research sites. Long-term PhenoCam data can be used to track the impact of climate variability and change on the rhythm of the seasons. 

   more » « less
4. 2m processed sensible and latent heat flux, friction velocity and stability at EastGRIP site on Greenland Ice Sheet, summer 2019

   https://doi.org/10.1594/pangaea.928827  

   Steen-Larsen, Hans Christian; Wahl, Sonja (January 2021, PANGAEA)

   Processed 30 minute surface sensible and latent heat flux including quality control flags after Foken et al. (2012). The latent heat flux was calculated assuming a latent heat of sublimation of 2834 J/g snow. Friction velocity and Monin-Obukhov stability parameter estimates are provided for convenience. Processing software was EASYFLUX DL provided by Campbell Scientific.The timestamps indicate the beginning of the 30 minute averaging period . The IRGASON was installed at 2.15m facing the prevailing wind direction. 

   more » « less
5. Near-surface turbulence in the Arctic (Utqiagvik, AK, March - April 2022)

   https://doi.org/10.26208/9qa7-1e73  

   Pan, Y; Fuentes, J D; Warner, G_R T; Anderson, A J; Wang, A; Katsouros, M (January 2025, Penn State Data Commons)

   This flux-tower observational campaign occurred in Utqiagvik, AK. A 12-m tower was installed in February 2022 to collect turbulence data at a total of five heights (0.5 m, 1.5 m, 2.5 m, 3.5 m, and 7.5 m). At each height, a Campbell Scientific CSAT3B sonic anemometer was operated to measure three velocity components and virtual temperature at 50 Hz, and an R. M. Young temperature and relative sensor was operated to measure air temperature and relative humidity at 1 Hz. The effective data collection was during March--April 2022, until the tower was taken down in April 2022. This was the first dataset of Arctic turbulence collected at 50 Hz, a frequency substantially higher than previous measurements at 10 Hz and 20 Hz. Given the strongly stable conditions in the Arctic, increasing the sampling frequency to 50 Hz was critical to resolve near-surface turbulence within or at least close to the inertial subrange. 

   more » « less