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Updated datasets 2024-05-08 UTC
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actions-user committed May 8, 2024
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83 changes: 83 additions & 0 deletions datasets/Daymet_V4_Daily_MonthlyLatency_1904.v1.json
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{
"type": "Collection",
"id": "Daymet_V4_Daily_MonthlyLatency_1904.v1",
"stac_version": "1.0.0",
"description": "This dataset provides Daymet Version 4 daily data on a monthly cycle as 1-km gridded estimates of daily weather variables for minimum temperature (tmin), maximum temperature (tmax), precipitation (prcp), shortwave radiation (srad), vapor pressure (vp), snow water equivalent (swe), and day length. Data are derived from the Daymet version 4 software where the primary inputs are daily observations of near-surface maximum and minimum air temperature and daily total precipitation from weather stations. The main algorithm to estimate primary Daymet variables (tmax, tmin, and prcp) at each Daymet grid is based on a combination of interpolation and extrapolation, using inputs from multiple weather stations and weights that reflect the spatial and temporal relationships between a Daymet grid and the surrounding weather stations. Secondary variables (srad, vp, and swe) are derived from the primary variables (tmax, tmin, and prcp) based on atmospheric theory and empirical relationships. The day length (dayl) estimate is based on geographic location and time of year. Data are available for the Continental North America, Puerto Rico, and Hawaii as separate spatial layers in a Lambert Conformal Conic projection and are distributed in standardized Climate and Forecast (CF)-compliant netCDF file formats.",
"links": [
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"title": "Granules in this collection"
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"title": "2022 catalog"
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"title": "Daymet Version 4 Monthly Latency: Daily Surface Weather Data",
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}
89 changes: 89 additions & 0 deletions datasets/FIFE_NOAA_SUR_58.v1.json
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"title": "Granules in this collection"
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"href": "https://cmr.earthdata.nasa.gov/stac/ORNL_DAAC/collections/FIFE_NOAA_SUR_58.v1/1985",
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"title": "1985 catalog"
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"title": "1988 catalog"
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"license": "not-provided"
}
65 changes: 65 additions & 0 deletions datasets/FIFE_WIND_LID_138.v1.json
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"title": "Wind Profile Data: LIDAR - NOAA (FIFE)",
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71 changes: 71 additions & 0 deletions datasets/Forested_Areas_Amazonas_Brazil_1515.v1.json
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{
"type": "Collection",
"id": "Forested_Areas_Amazonas_Brazil_1515.v1",
"stac_version": "1.0.0",
"description": "This data set provides LiDAR point clouds and digital terrain models (DTM) from surveys over the K34 tower site in the Cuieiras Biological Reserve, over forest inventory plots in the Adolpho Ducke Forest Reserve, and over sites of the Biological Dynamics of Forest Fragments Project (BDFFP) in Rio Preto da Eva municipality near Manaus, Amazonas, Brazil during June 2008. The surveys encompass the K34 eddy flux tower managed through the Large-scale Biosphere-Atmosphere Experiment in Amazonia, forest inventory plots managed by the Programa de Pesquisa em Biodiversidade (PPBio), and sites managed by the BDFFP. The LiDAR data was collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.",
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],
"title": "LiDAR and DTM Data from Forested Land Near Manaus, Amazonas, Brazil, 2008",
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}
71 changes: 71 additions & 0 deletions datasets/Forested_Areas_Para_Brazil_1514.v1.json
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{
"type": "Collection",
"id": "Forested_Areas_Para_Brazil_1514.v1",
"stac_version": "1.0.0",
"description": "This data set provides LiDAR point clouds and digital terrain models (DTM) from surveys over the Tapajos National Forest in Belterra municipality, Para, Brazil during late June and early July 2008. The surveys encompass the K67 and K83 eddy flux towers and a deforestation chronosequence managed through the Large-Scale Biosphere-Atmosphere Experiment in Amazonia providing long-term flux measurements of carbon dioxide. The LiDAR data was collected to measure forest canopy structure across Amazonian landscapes to monitor the effects of selective logging on forest biomass and carbon balance, and forest recovery over time.",
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"title": "Granules in this collection"
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}
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