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687 results for “Nm”
Simulated thickness profiles of ALD film in a wide microchannel of 500 nm height published as Fig.4 in PCCP 24 (2022) 8645-8660
<p>A series of simulated thickness profiles of atomic layer deposition (ALD) film grown in a wide lateral high-aspect-ratio (LHAR) microchannel is archived as an Excel file. This dataset has been published as Figure 4 in the publication "Conformality of atomic layer deposition in microchannels: impact of process parameters on the simulated thickness profile" (Yim and Verkama et al., Phys. Chem. Chem. Phys. 24 (2022) 8645-8660. https://doi.org/10.1039/D1CP04758B). A diffusion-reaction model by Ylilammi et al. (Ylilammi et al., J. Appl. Phys. 123 (2018) 205301. https://doi.org/10.1063/1.5028178) was re-implemented for the simulation. For this simulation, a channel height of 500 nm, which is a typical height for microscopic PillarHallTM LHAR test chips (Yim and Ylivaara et al., Phys. Chem. Chem. Phys., 22 (2020) 23107-23120. https://doi.org/10.1039/D0CP03358H), was used.<br> The Excel file consists of 11 tabs in total: metadata, baseline thickness profile, and Fig4a to Fig4i. The baseline thickness profile and data of fig4a Fig4i are also available as a CSV file. The metadata page describes the data with its baseline conditions. The baseline conditions used in the simulation are: sticking coefficient = 0.01, temperature = 250 °C, initial partial pressure of Reactant A = 100 Pa, molar mass of Reactant A = 0.100 kg mol-1, hard-sphere diameter of Reactant A = 6 × 10-10 m, partial pressure of inert gas I = 500 Pa, molar mass of inert gas I = 0.028 kg mol-1, hard-sphere diameter of inert gas I = 3.74 × 10-10 m, mass density of deposited film = 3500 kg m-3, areal number density of metal M atoms in MyZx material = 4 nm-2, number of metal atoms in a Reactant A molecule = 1, number of metal atoms in a formula unit of growing film = 1, number of cycle = 250, desorption probability = 0.01 s-1, channel height = 500 nm, and channel width = 10 mm. The baseline thickness profile tab contains a thickness profile obtained in the baseline conditions as film thickness versus distance within a microchannel. The thickness profile stored from Fig4a to Fig4i tabs was obtained by varying individual parameters with other parameter values in baseline conditions: initial partial pressure of Reactant A (Fig4a), pulse time (Fig4b), molar mass of Reactant A (Fig4c), mass density of deposited film (Fig4d), adsorption density (Fig4e), desorption probability (Fig4f), sticking coefficient (Fig4g), temperature (Fig4h) and partial pressure of inert gas (Fig4i).</p>
Dataset to: Novel aerosol diluter – Size dependent characterization down to 1 nm particle size
<p>Dataset to: Lampimäki et al. Novel aerosol diluter – Size dependent characterization down to 1 nm particle size. Journal of Aerosol Science 172 (2023) 106180, doi: <a href="https://doi.org/10.1016/j.jaerosci.2023.106180">https://doi.org/10.1016/j.jaerosci.2023.106180</a></p>
Photoconductive receivers at 1030 nm for high average power pulsed THz detection
<p>This dataset is accompanying the paper "Photoconductive receivers at 1030 nm for high average power pulsed THz detection"</p> <p><strong>General data acquisition:</strong></p> <p>THz is generated with the tilted pulse front approach in lithium niobate at room temperature. The pump power is controlled by a motorized lambda/2-waveplate (PI DT-80) in connection with a thin-film polarizer and calibrated to a THz power meter (Ophir 3A-P-THz). The computer-controlled rotation stage allows to sweep the THz power in a reliable and reproduceable way. The probe beam is guided over an oscillating delay line, having a delay range of approximately 15 ps and a shaking frequency of 20 Hz, leading to 4800 THz traces in over 2 min measurement time. In the path of the probe beam is also a motorized rotation stage and a polarizer positioned, to control the laser probe power in the same way as the THz pump power.</p> <p>The THz is received by a ErAs:InAlGaAs photoconductive antenna (PCA) developed at TU Darmstadt, which is optimized for 1030 nm. The THz receiving side has a silicon lens, concentrating the THz radiation on an H-dipole antenna with a center dipole length of 25 µm and a photoconductive gap of 5 µm. On the backside, the probe beam is coupled with a microscope objective for the near infrared range (Mitutoyo M Plan Apo NIR 20X). The small current of the PCA receiver is converted to a useable voltage range with a transimpedance amplifier (Femto DLPCA-200) with a gain of 10^7 V/A.</p> <p>For each combination of THz pump power and laser probe power (sampling beam), a measurement file with 2 min recording length and a sampling rate of 200 kSa/s is recorded with the DAQ (Dewesoft Sirius Mini). The exported file-format HDF-5.</p> <p>HDF-5 is an efficient (binary), cross-platform data format and can be read easily by i.e. Python or Matlab. The graphical user interface “HDFView” can be downloaded for free (after registration) from <a href="https://www.hdfgroup.org/downloads/hdfview/">https://www.hdfgroup.org/downloads/hdfview/</a>. It allows to explore the folder structure of an HDF-5 file but is not necessary when using Python or Matlab.</p> <p>The structure of a single HDF-5 from the uploaded raw data is</p> <ul> <li>A folder called "AI", standing for analog input <ul> <li>The dataset "AI 1" stands for the first analog channel, containing the position of the scanning delay line. The voltage can be converted to “THz time” with a conversion factor, where 20 V correspond to 15 ps delay.</li> <li>The dataset “AI 2”, which is voltage signal from the transimpedance amplifier and proportional to the THz electric field.</li> </ul> </li> </ul> <p>There are additional attributes in the root-folder of the HDF-5 file.</p> <p>The processed data (used in the figures) can be found in the files labeled Fig.X.h5, except for Fig.7, which only contains a single curve and is a .txt file.</p>
MCU data in a Cypress 65 nm SRAM from heavy ions and protons collected at ground facilities
<p>The dataset contains the raw MCU data collected at ground facilities under heavy ion and proton irradiation in the scope or RADSAGA and RADNEXT project. The device under consideration is the CY62167GE30-45ZXI, a 65 nm commercial SRAM available from Infineon (formerly Cypress). Note that the internal ECC has been disabled for this data collection. More information on data collection are available through this paper (<a href="https://doi.org/10.1109/REDW51883.2020.9325822">10.1109/REDW51883.2020.9325822</a>). The MCU were determined through the procedure explained in these two papers (<a href="https://doi.org/10.1109/TNS.2014.2313742">10.1109/TNS.2014.2313742</a> and <a href="https://doi.org/10.1109/TNS.2015.2496874">10.1109/TNS.2015.2496874</a>).</p>
Extreme Drought in Grasslands Experiment (EDGE): High frequency measurements from the northern Chihuahuan Desert site, Sevilleta National Wildlife Refuge, NM, USA (2013-2023)
The Extreme Drought in Grasslands Experiment (EDGE) is distributed across six representative grassland ecosystems of the central United States. EDGE serves as an important research platform for understanding the resistance and resilience of these grassland ecosystems to extreme prolonged drought as well as to changes in precipitation seasonality. This data package contains high-frequency environmental sensor measurements from the northern Chihuahuan Desert site, dominated by black grama (Bouteloua eriopoda), located in the Sevilleta National Wildlife Refuge in central New Mexico.
Extreme Drought in Grasslands Experiment (EDGE): High frequency measurements from the southern Great Plains site, Sevilleta National Wildlife Refuge, NM, USA (2013-2023)
The Extreme Drought in Grasslands Experiment (EDGE) is distributed across six representative grassland ecosystems of the central United States. EDGE serves as an important research platform for understanding the resistance and resilience of these grassland ecosystems to extreme prolonged drought as well as to changes in precipitation seasonality. This data package contains high-frequency environmental sensor measurements from the southern Great Plains site, dominated by blue grama (Bouteloua gracilis), located in the Sevilleta National Wildlife Refuge in central New Mexico.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Black Butte Meteorological Station (BLBT), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Black Butte Meteorological Station (BLBT). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetblbt/. These data complement and extend meteorological data recorded by an adjacent station (Met54), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Bronco Well Meteorological Station (BRWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Bronco Well Meteorological Station (BRWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetbrwl/. These data complement and extend meteorological data recorded by an adjacent station (Met45), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Burris Well Meteorological Station (BUWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Burris Well Meteorological Station (BUWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetbuwl/. These data complement and extend meteorological data recorded by an adjacent station (Met50), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Contreras Meteorological Station (CONT), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Burris Well Meteorological Station (BUWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetcont/.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Cerro Montoso Meteorological Station (CRMT), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Cerro Montoso Meteorological Station (CRMT). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetcrmt/. These data complement and extend meteorological data recorded by an adjacent station (Met42), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Deep Well Meteorological Station (DPWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Deep Well Meteorological Station (DPWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetdpwl/. These data complement and extend meteorological data recorded by an adjacent station (Met40), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Sevilleta Field Station Meteorological Station (FSTN), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Sevilleta Field Station Meteorological Station (FSTN). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetfstn/. These data complement and extend meteorological data recorded by an adjacent station (Met01), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Five Points Meteorological Station (FVPT), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Five Points Meteorological Station (FVPT). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetfvpt/. These data complement and extend meteorological data recorded by an adjacent station (Met49), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Goat Draw Meteorological Station (GTDR), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Goat Draw Meteorological Station (GTDR). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetgtdr/. These data complement and extend meteorological data recorded by an adjacent station (Met48), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Rio Salado Meteorological Station (RIOS), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Rio Salado Meteorological Station (RIOS). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetrios/. These data complement and extend meteorological data recorded by an adjacent station (Met44), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Sepultura Meteorological Station (SEPU), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Sepultura Meteorological Station (SEPU). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetsepu/.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the South Gate Meteorological Station (SOGT), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the South Gate Meteorological Station (SOGT). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmetsogt/. These data complement and extend meteorological data recorded by an adjacent station (Met41), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Test Well Meteorological Station (TSWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Test Well Meteorological Station (TSWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmettswl/. These data complement and extend meteorological data recorded by an adjacent station (Met52b), accessible at: https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-sev&identifier=1.
Sevilleta Field Station Meteorological Network (SevMET): High frequency measurements from the Tule 222 Well Meteorological Station (TUWL), Sevilleta National Wildlife Refuge, NM, USA, 2024-ongoing.
The Sevilleta Field Station Meteorological Network (SevMET) is a spatially distributed, long-term climate monitoring network established to enhance and expand climate monitoring across a variety of dryland ecosystems (e.g., grasslands, shrublands, woodlands) within the Sevilleta National Wildlife Refuge in central New Mexico. Ecosystem processes in drylands are strongly regulated by climatic drivers that are highly variable in space and time, both within and among years. Therefore, accurate measurement of environmental variables at high spatial and temporal resolution is fundamental to understanding biophysical processes in these ecosystems. SevMET consists of fifteen standardized research-grade weather stations located across multiple dryland ecosystem types (e.g., grasslands, shrublands, woodlands) representative of the southwestern US. Stations continuously measure a standard suite of meteorological variables at five-minute intervals, including air temperature, relative humidity, precipitation, photosynthetically active radiation, incoming shortwave radiation, wind speed and direction, dew point, vapor pressure, and, at a subset of stations, barometric pressure. Stations also measure a suite of soil parameters (bulk electrical conductivity, dielectric permittivity, temperature, and volumetric water content) at six depths (5, 10, 20, 30, 40, and 50 cm) below the ground surface using 1-2 integrated soil profilers. Additionally, phenocams at each station capture images at thirty-minute intervals during daylight hours. This data package contains high-frequency meteorological measurements from the Tule 222 Well Meteorological Station (TUWL). Phenocam images can be accessed through the PhenoCam Network at: https://phenocam.nau.edu/webcam/sites/sevmettuwl/.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
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.