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641 results for “par”
LAI & PAR Data: Light Bar - KSU (FIFE)
The purpose of the Leaf Area Index and PAR Determined from KSU Light Bar Measurements study was to collect extensive non-destructive measurements of Leaf Area Index (LAI) at the flux sites during IFC-5 (August 1989). These data were collected at thirteen locations which were coincident with the surface flux measurements within the FIFE study area from July 3, 1989 through August 18, 1989. The various fractions of the Photosynthetically Active Radiation (PAR) (i.e., diffuse, reflected, transmitted and total) were measured using a Line Quantum meter from LI-COR Inc. From these fractions the ratio of reflected to total incoming PAR was computed. LAI can be estimated from light bar measurements of PAR transmittance from measurements above and below a vegetation canopy. The use of the light bar allows rapid, multiple, and repeatable measurements of LAI at the FIFE sites. This type of measurements could not be done using destructive measurements of LAI.
MODIS-based GPP, PAR, fC4, and SANIRv estimates from SLOPE for CONUS, 2000-2019
This dataset contains estimated gross primary productivity (GPP), photosynthetically active radiation (PAR), soil adjusted near infrared reflectance of vegetation (SANIRv), the fraction of C4 crops in vegetation (fC4), and their uncertainties for the conterminous United States (CONUS) from 2000 to 2019. The daily estimates are SatelLite Only Photosynthesis Estimation (SLOPE) products at 250-m resolution. There are three distinct features of the GPP estimation algorithm: (1) SLOPE couples machine learning models with MODIS atmosphere and land products to accurately estimate PAR, (2) SLOPE couples gap-filling and filtering algorithms with surface reflectance acquired by both Terra and Aqua MODIS satellites to derive a soil-adjusted NIRv (SANIRv) dataset, and (3) SLOPE couples a temporal pattern recognition approach with a long-term Crop Data Layer (CDL) product to predict dynamic C4 crop fraction. PAR, SANIRv and C4 fraction are used to drive a parsimonious model with only two parameters to estimate GPP, along with a quantitative uncertainty, on a per-pixel and daily basis. The slope GPP product has an R2 = 0.84 and a root-mean-square error (RMSE) of 1.65 gC m-2 d-1.
EPIC Ocean Surface PAR 1 Product V02
EPIC Ocean Surface PAR The EPIC observations of the Earth’s surface lit by the Sun made 13 times during the day in spectral bands centered on 443, 551, and 680 nm are used to estimate daily mean photosynthetically available radiation (PAR) at the ice-free ocean surface. PAR is defined as the quantum energy flux from the Sun in the 400-700 nm range. Daily mean PAR is the 24-hour averaged planar flux in that spectral range reaching the surface. It is expressed in E.m-2.d-1 (Einstein per meter squared per day). The factor required to convert E.m-2 d-1 units to mW.cm-2.μm-1 units is equal to 0.838 to an inaccuracy of a few percent regardless of meteorological conditions. The EPIC daily mean PAR product is generated on Plate Carrée (equal-angle) grid with 18.4 km resolution at the equator and on 18.4 km equal-area grid, i.e., the product is compatible with Ocean Biology Processing Group ocean color products.The EPIC PAR algorithm uses a budget approach, in which the solar irradiance reaching the surface is obtained by subtracting from the irradiance arriving at the top of the atmosphere (known) the irradiance reflected to space (estimated from the EPIC Level 1b radiance data), taking into account atmospheric transmission (modeled). Clear and cloudy regions within a pixel do not need to be distinguished, which dismisses the need for often-arbitrary assumptions about cloudiness distribution and is therefore adapted to the relatively large EPIC pixels. A daily mean PAR is estimated on the source grid for each EPIC instantaneous daytime observation, assuming no cloudiness change during the day, and the individual estimates are remapped and weight-averaged using the cosine of the Sun zenith angle. In the computations, wind speed, surface pressure, and water vapor amount are extracted from NECP Reanalysis 2 data, aerosol optical thickness and angstrom coefficient fromMERRA-2 data, and ozone amount from EPIC Level 2 data. Areas contaminated by sun glint are excluded using a threshold on sun glint reflectance calculated using wind data. Ice masking is based on NSIDC near real time ice fraction data. Details about the algorithm are given in Frouinet al., (2018). Figure A1 gives an example of EPIC daily mean PAR product. Date is March 20, 2018(equinox); land is in black and sea ice in white. Values range from a few E.m-2.d-1at high latitudes to about 58 E.m-2.d-1 at equatorial and tropical latitudes, with atmospheric perturbances modulating the surface PAR field especially at middle latitudes. The EPIC ocean surface PAR products are available at the Atmospheric Science Data Center (ASDC) at NASA Langley Research Center: https://asdc.larc.nasa.gov. 4. Reference Robert Frouin, Jing Tan, Didier Ramon, Bryan Franz, Hiroshi Murakami, 2018: Estimating photosynthetically available radiation at the ocean surface from EPIC/DSCOVR data, Proc. SPIE 10778, Remote Sensing of the Open and Coastal Ocean and Inland Waters, 1077806 (24 October 2018); doi: 10.1117/12.2501675. Changes from version 1 1) Algorithm (consistent with PACE) Updated the calculation of atmospheric reflectance, gaseous transmittance, and atmospheric transmittance using LUTs method so that calculations are accurate at high Sun and view zenith angles; Updated the calculation of surface albedo (based on Jin et al., 2011); Updated the calculation of cloud/surface layer albedo. 2)Ancillary data Changed the sources of the ancillary data including wind speed, surface pressure, and water vapor from NCEP to MERRA2; Added cloud fraction from MERRA2, which is needed for computing direct/diffuse ratio hence surface albedo.
BOREAS TE-09 PAR & Leaf Nitrogen Data for NSA, R1
The BOREAS TE-09 team collected several data sets related to chemical and photosynthetic properties of leaves in boreal forest tree species. This data set describes the relationship between Photosynthetically Active Radiation (PAR) levels and foliage nitrogen in samples from six sites in the BOREAS NSA. This information is useful for modeling the vertical distribution of carbon fixation for these different forest types in the boreal forest. The data were collected to quantify the relationship between PAR and leaf nitrogen of black spruce, jack pine, and aspen.
DSCOVR EPIC Level 3 PAR Image
DSCOVR_EPIC_L3_PAR-image_01 is a view image showing data from DSCOVR_EPIC_L3_PAR, which is the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) Level 3 photosynthetically available radiation (PAR) version 1 data product. The EPIC observations of the Earth’s surface lit by the Sun made 13 times during the day in spectral bands centered on 443, 551, and 680 nm are used to estimate daily mean PAR at the ice-free ocean surface. PAR is defined as the quantum energy flux from the Sun in the 400-700 nm range. Daily mean PAR is the 24-hour averaged planar flux in that spectral range reaching the surface. It is expressed in E.m-2.d-1 (Einstein per meter squared per day). The factor required to convert E.m-2 d-1 units to mW.cm-2.µm-1 units are equal to 0.838 to an inaccuracy of a few percent regardless of meteorological conditions. The EPIC daily mean PAR product is generated on Plate Carrée (equal-angle) grid with an 18.4 km resolution at the equator and on an 18.4 km equal-area grid, i.e., the product is compatible with Ocean Biology Processing Group ocean color products.The EPIC PAR algorithm uses a budget approach, in which the solar irradiance reaching the surface is obtained by subtracting from the irradiance arriving at the top of the atmosphere (known), the irradiance reflected space (estimated from the EPIC Level 1b radiance data), taking into account atmospheric transmission (modeled). Clear and cloudy regions within a pixel do not need to be distinguished. This dismisses the need for often-arbitrary assumptions about cloudiness distribution and is therefore adapted to the relatively large EPIC pixels. A daily mean PAR is estimated on the source grid for each EPIC instantaneous daytime observation, assuming no cloudiness changes during the day, and the individual estimates are remapped and weight-averaged using the cosine of the Sun zenith angle. In the computations, wind speed, surface pressure, and water vapor amount are extracted from NCEP (National Centers for Environmental Prediction) Reanalysis 2 data, aerosol optical thickness, and angstrom coefficient from MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) data, and ozone amount from EPIC Level 2 data. Areas contaminated by sun glint are excluded using a threshold on sun glint reflectance calculated using wind data. Ice masking is based on NSIDC (National Snow and Ice Data Center) near real-time ice fraction data. Additional information about the EPIC ocean surface PAR products can be found at the NASA DSCOVR: EPIC website: https://epic.gsfc.nasa.gov/, under “Science -> Products -> Ocean Surface” (https://epic.gsfc.nasa.gov/science/products/ocean).
Integrative AUF1 PAR-CLIP analysis uncovers AUF1 roles in translation and genome integrity (Ribosome)
GEO Series GSE52976. Homo sapiens. 3 samples. Type: Non-coding RNA profiling by high throughput sequencing; Other.
Characterizing expression and processing of precursor and mature human tRNAs by hydro-tRNAseq and PAR-CLIP
GEO Series GSE95683. Homo sapiens. 6 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Advancing Functional Utility of PAR-CLIP by Quantifying Background Binding to mRNAs and lncRNAs
GEO Series GSE50989. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing; Other; Non-coding RNA profiling by high throughput sequencing.
Photoactivatable-Ribonucleotide-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP) of RNA-binding proteins (RBPs), IGF2BP1 and IGF2BP3 in the K562 CML-derived cell line
GEO Series GSE138063. Homo sapiens. 4 samples. Type: Other.
Epitranscriptomic cytidine methylation of the Hepatitis B viral RNA encapsidation signal ensure the reverse transcription of viral RNA [PAR-CLIP]
GEO Series GSE250108. Homo sapiens. 2 samples. Type: Other.
AGO-PAR-CLIP of DG75 and BCBL-1
GEO Series GSE43909. Homo sapiens. 4 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Global Target mRNA Specification and Regulation by RNA-Binding Protein ZFP36/Tristetraprolin/TTP [PAR-CLIP]
GEO Series GSE53184. Homo sapiens. 1 samples. Type: Expression profiling by high throughput sequencing.
RNA binding protein PRRC2B mediates translation of specific proteins and regulates cell cycle progression [PAR_Clip-seq]
GEO Series GSE220057. Homo sapiens. 4 samples. Type: Other.
microRNA Targetome Analysis of Latently KSHV-infected Primary Effusion Lymphoma Cell lines Using PAR-CLIP [Illumina]
GEO Series GSE32109. Homo sapiens. 6 samples. Type: Non-coding RNA profiling by high throughput sequencing.
PAR-CLIP for JARID2 in mouse embryonic stem cells
GEO Series GSE48517. Mus musculus. 4 samples. Type: Other.
eIF3 PAR-CLIP in 293T cells
GEO Series GSE65004. Homo sapiens. 12 samples. Type: Other.
DHX36 resolves G-rich structures in mRNA untranslated region to allow their translation [PAR-CLIP-seq]
GEO Series GSE105171. Homo sapiens. 4 samples. Type: Expression profiling by high throughput sequencing.
A fast PAR-CLIP variant using phenolic extractions
GEO Series GSE113628. Homo sapiens. 6 samples. Type: Expression profiling by high throughput sequencing; Other.
The mRNA-bound proteome and its global occupancy profile on protein-coding transcripts [PAR-CLIP]
GEO Series GSE38201. Homo sapiens. 5 samples. Type: Expression profiling by high throughput sequencing.
PAR-CLIP-seq reveals RNAs directly interacting with CTCF in human transformed cell line U2OS
GEO Series GSE53554. Homo sapiens. 3 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
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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.
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