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18 results for “Spectral emissivity”
Thermal infrared emissivity spectral library of silicates measured under the Mercury simulated environment
<p>This is the thermal emissivity spectral library of silicates measured as a function of temperature under Mercury simulated environment. Data is measured at the Planetary Spectroscopy Laboratory (PSL), Institute of Planetary Research, German Aerospace Center (DLR), Berlin. The spectral library will be used for mineral identification of Mercury surface using MERTIS datasets. The manuscript related to this work is submitted to Icarus on the title "<strong>Thermal Infrared Spectroscopy (7-14 µm) of Silicates under Simulated Mercury Daytime Surface Conditions and their Detection: Supporting MERTIS onboard the BepiColombo Mission".</strong></p>
On effective spectral wideband models for clear sky atmospheric emissivity and transmissivity
<p><strong>Overview</strong></p> <p>The HDF5 file contains primary measurement data and secondary processing data that was used to assess clear sky effective emissivity and transmissivity estimates and generate the results in the associated manuscript (accepted and forthcoming).</p> <p>Data is indexed by solar time and provided per site for years 2010 through 2015. Sample Python code is provided to reconstruct training and validation sets by concatenating all 'tra' or 'val' samples across sites. Results can be explored by modifying choice of filters and constructing new training and validation sets.</p> <p><strong>Data usage</strong></p> <p>The usage of the data presented here is intended for research and development purposes only and implies explicit reference to the paper:<br><em>Matsunobu, L. M., & Coimbra, C. F. M. (2024). On effective spectral wideband models for clear sky atmospheric emissivity and transmissivity. Journal of Geophysical Research: Atmospheres, 129, e2023JD039798. https://doi.org/10.1029/2023JD039798</em></p> <p><strong>Data description</strong></p> <p>Column names and descriptions are as follows:<br>- dlw_m: measured downwelling longwave [W/m^2]<br>- ghi_m: measured global horizontal irradiance [W/m^2]<br>- dni_m: measured direct normal irradiance [W/m^2]<br>- dhi_m: measured diffuse horizontal irradiance [W/m^2]<br>- rh_m: measured relative humidity [%]<br>- pa_m: measured atmospheric pressure [hPa]<br>- t_m: measured temperature [K]<br>- sza: solar zenith angle [deg]<br>- ghi_c: clear sky global horizontal irradiance [W/m^2]<br>- dni_c: clear sky direct normal irradiance [W/m^2]<br>- dhi_c: clear sky diffuse horizontal irradiance [W/m^2]<br>- cs1: clear sky filter 1<br>- cs2: clear sky filter 2<br>- site_elev: station elevation [m]<br>- clr_pct: fraction of samples identified as clear for the given site and day<br>- clr_num: number of samples identified as clear for the given site and day<br>- pw_hpa: water vapor partial pressure [hPa]<br>- alt_correction: altitude correction<br>- tra: indicate if sample is included in training set<br>- val: indicate if sample is included in validation set<br>- sqrt_pw: square root of non-dimensional water vapor partial pressure<br>- e_sky: effective clear sky emissivity</p> <p>The last two columns, 'sqrt_pw' and 'e_sky' represent the input and target for linear regression, i.e. e_sky = c_1 + (c_2 * sqrt_pw).<br>Altitude corrected sky emissivity, or expected emissivity for a station at sea-level, is found by e_sky - alt_correction.</p> <p><strong>Sample code (Python v3.8)</strong></p> <pre>import pandas as pd site = "GWC" # or other station code df = pd.read_hdf("data.h5", key=site) # import single site</pre> <p>Training and validation sets can be reconstructed as below. Linear regression on 'sqrt_pw' to predict 'e_sky' - 'alt_correction' in the resultant training set will reproduce results in the associated manuscript.</p> <pre>training = [] validation = [] surfrad_sites = ['BON', 'DRA', 'FPK', 'GWC', 'PSU', 'SXF', 'TBL'] for site in surfrad_sites: # loop through sites df = pd.read_hdf("data.h5", key=site) df["site"] = site # add site name training.append(df.loc[df.tra]) # append samples marked as training validation.append(df.loc[df.val]) # append samples marked as validation # join respective set samples across sites training = pd.concat(training, ignore_index=False) validation = pd.concat(validation, ignore_index=False)</pre> <p>Reproduce regression results</p> <pre>from sklearn.linear_model import LinearRegression c1 = 0.6 # set intercept (c1 constant) x = training.sqrt_pw.to_numpy().reshape(-1, 1) y = training.e_sky - training.alt_correction - c1 # adjust for altitude and c1 y = y.to_numpy().reshape(-1, 1) model = LinearRegression(fit_intercept=False) model.fit(x, y) c2 = model.coef_[0][0] print(f"c1={c1:.3f}, c2={c2:.3f}") # output: c1=0.600, c2=1.652</pre>
Nocturnal Light Emitting Diode Induced Fluorescence (LEDIF): A new technique to measure the chlorophyll a fluorescence emission spectral distribution of plant canopies in situ
<p>This repository contains data reported in the below study:</p> <p>Atherton, J., Liu, W. and Porcar-Castell, A., 2019. Nocturnal Light Emitting Diode Induced Fluorescence (LEDIF): A new technique to measure the chlorophyll a fluorescence emission spectral distribution of plant canopies in situ. <em>Remote Sensing of Environment</em>.</p> <p>Each text file contains the data-set used to produce the relevant figure (see file name). You can find the data to produce A.4. online at https://avaa.tdata.fi/web/smart/smear/ </p> <p>Please pay attention to the following before using this data.</p> <ol> <li><strong>Figure2_lampRadPanel_Wm2srnm.txt</strong>: Note that the shapes are of interest here. The magnitude is not the same as the incident light at top of canopy, as these spectra were measured in a laboratory. See paper section A.1. for more details. </li> <li><strong>Figure3_LEDIFspectra_Wm2srnm.txt</strong>: This data contains the whole observed spectrum including the non-fluorescence regions, which were saturated (warped) in the visible. The fluorescence region is approximately > 650 nm. </li> <li><strong>Figure4_AQYspectra_nm.txt</strong>: As with Figure3 the whole spectrum is included here.</li> <li><strong>FigureA3_repLEDIFspectra_[pmay/psep/usep]._nm.txt</strong>: Data from which the mean spectra (Figure3) were calculated, including the uncorrected red spectra. I have split these by canopy type to avoid name conflicts.</li> </ol> <p> </p>
Spectral Contamination of the 6300Å Emission in Single-Etalon Fabry-Perot Interferometers - Data
<p>Raw ".fit" image data files from Santarem Brazil and from Cachoeira Paulista Brazil are included. These raw data are used to create Figures 8, 9b, 10 and 13 of the titled publication. Filenames with prefix "bb" are CCD image exposures from the Santarem Fabry-Perot interferometer (FPI). Filenames with prefix "br" are CCD image exposures from the Cachoeira Paulista FPI. All raw images including calibration images are included. Filename suffixes carry the temporal sequence number of the exposure and a text identifier of the image type. The types are "bi" (CCD bias images); "dk" (dark images); "ff" (flat field); "la" (laser); "sk" (sky).</p> <p> </p>
Absorption and Emission Spectral Data of Room-temperature Rhodamine 6G Dye Solution and some typical Dye Microcavity parameters
<p>The repository contains spectral absorption and emission data [absorption cross section and Einstein coefficients] of rhodamine 6G dye solved in ethylene glycol at room temperature over the visible spectral range from 400.25nm to 619.85nm. In addition, typical values for the cavity loss rate are given for the same wavelength range. The data can be used e.g. for studies of two-dimensional thermalized photon gases and Bose-Einstein condensates of photons inside dye-filled optical microcavities.</p> <p><strong>Methodology</strong></p> <p>The absorption data has been obtained by white-light absorption spectroscopy of dye solutions with increasing concentration {0.01,0.1,1} mMol/Litre. The combined spectra have been calibrated with the rhodamine absorption cross section at 532nm wavelength, which we have independently determined in transmission measurements with a 532nm laser. The absorption cross section in this data repository constitutes a universal material property that is generally valid for rhodamine 6G solved in ethylene glycol at room temperature.</p> <p>The Einstein coefficient for absorption B_12 has been obtained specifically for the volume of the transverse ground mode in an optical microcavity formed by two curved mirrors with radius of curvature R = 1 and cavity length D = 1.5µm; see e.g. Klaers et al., <em>Nature</em> <strong>468</strong>, 545–548 (2010), Schmitt, <em>Phys. B: At. Mol. Opt. Phys.</em> <strong>51</strong>, 173001 (2018) and related work by the authors. For typical dye concentrations near 1mMol/Litre, approximately 10^8 molecules are contained in the ground mode volume. The Einstein coefficient for emission B_21 is deduced from B_12 assuming the Kennard Stepanov relation: B_21/B_12 = Exp[-h*c*(1/lambda - 1/lambda_zpl)/(k_B T)], where lambda_zpl = 545nm denotes the zero-phonon line of rhodamine 6G dye (h: Planck's constant, c: speed of light, lambda: wavelength, k_B: Boltzmann's constant, T: temperature). We have verified that the resulting B_21 spectrum agrees well with reference fluorescence spectra of rhodamine 6G. </p> <p>The spectral cavity loss rate c/(n0*D)*(1-R-A) with refractive index n0 = 1.43 and mirror absorption loss A = 1ppm is deduced from the wavelength-dependent mirror reflectivity R, which we have measured in cavity ring-down measurements at more than 10 wavelengths in the interval between 530nm to 605nm. For this, a tuneable dye laser was resonantly coupled into a 3.3cm-long cavity formed by the corresponding highly-reflecting dielectric mirrors. Note that the reciprocal values of the loss rates give the 1/e lifetime of the photons in the cavity.</p> <p><strong>Data format</strong></p> <p>The file 'data.dat' contains all data sorted by columns: wavelength (in units of nm), absorption cross section (in units of m^2), Einstein coefficients for absorption and emission (both in units of Hz), cavity loss rate (in units of Hz).</p>
Dataset for surface spectral emissivity retrieval
<p>We provide two databases, one for clear sky conditions and another for cloudy sky conditions, for both January and July 2021. Each database consists of input files for the CLAIM (CLouds and Atmospheric Inversion Module) code, as described in Sgheri et al. 2022, as well as output files. The input files contain data regarding the surface, atmospheric composition, and potential clouds. Additionally, the output files encompass computed variables essential for our analysis, including errors, precipitable water vapor, surface temperature, and thermal contrast.</p>
Data of normal spectral emissivity measurements for Ta, Mo, W and Nb
<p>Data aquired during my master thesis about the normal spectral emissivty of Ta, Mo, W and Nb measured with an ohmic pulse heating apparatus and a us-DOAP</p>
Figure data for the paper: "Spectral Observations of Optical Emissions Associated with Terrestrial Gamma-Ray Flashes"
<p>This repository contains 13 files with data which were used to produce the figures in the paper "Spectral Observations of Optical Emissions Associated with Terrestrial Gamma-Ray Flashes" by Heumesser et al. The description of the different files is included in the supporting information of the paper and additionally uploaded here, see "2020GL090700_OpticalEmissionsAssociatedwithTGFs_SupportingInformation".</p>
Spectral emissivity of isotropic graphite from 1290 K to 2300 K
<p>This dataset contains spectral emissivity values determined from 1290 K to 2300 K by two laboratories on a batch of specimens machined in the same block of isotropic graphite.</p>
Spectral emissivity of sandblasted molybdenum from 1250 K to 3190 K
<p>This dataset contains spectral emissivity values determined from 1250 K to 3190 K by three laboratories on a batch of sandblasted specimens machined in the same block of molybdenum.</p>
Spectral data used in "Stratospheric-trace-gas-profile retrievals from balloon-borne limb imaging of mid-infrared emission spectra"
<p>The calibrated spectral data used in the trace gas retrievals by the Limb Imaging Fourier Transform Spectrometer Experiment (LIFE).</p>
Spectral hardness of X- and gamma-ray emissions from lightning stepped and dart leaders
<p>This repository has four folders dedicated to the 11 triggers outlined in the manuscript. Within each folder, the data is organized according to the four sensors:</p><ol><li><strong>Slow Antenna Folder:</strong> For every trigger, there is a corresponding .asc file paired with a complementary .readme file. Additionally, this folder includes a <i>.txt </i>file that lists the file names and UTC times.</li><li><strong>LEFA:</strong> The <i>*.txt</i> files within this section consist of four columns representing seconds after midnight (UTC), instrument power voltage, sensitive channel, medium channel, and unsensitive channel. The file names adhere to the format <i>lefa2-yymmdd-hhmm00.txt</i>, each containing one minute of LEFA data.</li><li><strong>DAS:</strong> Files in this category follow the format <i>XRAY_yyyy.mm.dd_hh-mm-ss_milliseconds.channel[B,C, or D].csv</i>, with UTC time. The file name corresponds to time zero in the data. The first column denotes seconds from/after zero, while the second column represents the measured data in Volts. The channels (B, C, D) correspond to Fast Antenna, LaBr detector, and NaI detector, respectively. The instrument has a sampling rate of 180 MHz.</li><li><strong>Fieldmill:</strong>The file names in this section adhere to the format<i> kv2022mmdd-hhmm.flt </i>and are accompanied by a calibration file.</li></ol>
EAMv2 anthropogenic aerosol emissions data in model-native spectral-element grid
<p>Anthropogenic aerosol emissions data from surface and elevated sources in E3SM Model-native grid. Data available for standard uniform resolution in EAMv2 (ne30pg2) and North America Regionally Refined Model (NA RRM). Data were prepared as a part of the improved emission treatment in E3SMv2 (available at: https://doi.org/10.5281/zenodo.7823633).</p>
Spectral emissivity of sandblasted tungsten from 1370 K to 4100 K
<p>This dataset contains spectral emissivity values determined from 1370 K to 4100 K by three laboratories on a batch of sandblasted specimens machined in the same block of tungsten.</p>
Global Surface Emissivity Spectral Atlas (GSESA) V01
The Global Surface Emissivity Spectral Atlas (GSESA) database contains global, monthly climatology infrared emissivity functional Empirical Orthogonal Function (EOF) scores in 0.25 x 0.25 latitude-longitude resolution. An eigenvector file and a reader file allow customers to produce emissivity spectra. The emissivity functional EOF scores were developed using the Infrared Atmospheric Sounding Interferometer (IASI) instrument on the METOP-A, METOP-B, and METOP-C satellites for the period 2007-07-01 to 2025-01-31. An inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral infrared (IR) sounders, was developed to simultaneously retrieve atmospheric thermodynamic and surface or cloud microphysical parameters. This inversion scheme was applied to the IASI instrument. Rapidly produced surface spectral emissivity (SSE) is initially evaluated through quality control checks on the retrievals of other impacted surface and atmospheric parameters. The GSESA data are provided in binary format, with sample reader files that can be used in a Fortan IDE to read a functional emissivity EOF compressed file (e.g., MFEMI_MONTH01_A_V5P.bin) and its EOF eigenvector file (IASI_B_EV_FUNC_GLOBAL_V4.bin) to produce spectral emissivity at a certain location (latitude and longitude). A sample reader file can be used in a Matlab IDE is also provided. These data were created with funding from the NASA Internal Scientist Funding Model for the National Airborne Sounder Testbed-Interferometer (NAST-I).
Spectral Emission Dependence of Tin-Vacancy Centers in Diamond from Thermal Processing and Chemical Functionalization
<p>A systematic photoluminescence (PL) investigation of the spectral emission properties of individual optical defects fabricated in diamond upon ion implantation and annealing is reported. Three spectral lines at 620, 631, and 647 nm are identified and attributed to the SnV center due to their occurrence in the PL spectra of the very same single-photon emitting defects. It is shown that the relative occurrence of the three spectral features can be modified by oxidizing the sample surface following thermal annealing. The relevant emission properties of each class of individual emitters, including the excited state emission lifetime and the emission intensity saturation parameters are reported.</p>
First ISCCP Regional Experiment (FIRE) Cirrus Phase II Spectral Radiance Experiment (SPECTRE) SIRIS High Resolution Emission Data
The First ISCCP Regional Experiments have been designed to improve data products and cloud/radiation parameterizations used in general circulation models (GCMs). Specifically, the goals of FIRE are (1) to seek the basic understanding of the interaction of physical processes in determining life cycles of cirrus and marine stratocumulus systems and the radiative properties of these clouds during their life cycles and (2) to investigate the interrelationships between ISCCP data, GCM parameterizations, and higher space and time resolution cloud data. To-date, four intensive field-observation periods were planned and executed: a cirrus IFO (October 13 - November 2, 1986); a marine stratocumulus IFO off the southwestern coast of California (June 29 - July 20, 1987); a second cirrus IFO in southeastern Kansas (November 13 - December 7, 1991); and a second marine stratocumulus IFO in the eastern North Atlantic Ocean (June 1 - June 28, 1992). Each mission combined coordinated satellite, airborne, and surface observations with modeling studies to investigate the cloud properties and physical processes of the cloud systems.SPECTRE/SIRIS high spectral resolution observations were obtained at Coffeyville, Kansas in November - December 1991. The SIRIS instrument has been previously flown for balloon-borne studies of stratospheric chemistry relevant to the ozone cycles. It is a modified version of a Bomem continuously scanning Fourier transform spectrometer, operating in emission mode. The following instrument parameters were applicable for the Coffeyville SPECTRE campaign. The field-of-view, 0.5 degrees full width at half-maximum, was directed towards the zenith, except for a day when limb were recorded. The highest emission-mode spectral resolution recorded during SPECTRE was taken by SIRIS 0.06 cm-1, apodized. Scan times varied from one to a few minutes, depending onthe resolution. The instrument was run at ambient temperature, withthe Si:Ga detectors at liquid helium (LHe) temperature. Data are limited by photon noise from the emission from the instrument and from the atmosphere itself. Therefore data were recorded with two different width bandpasses: 1) narrow bandpass cooled filters in channels 1-4, which reduces the background noise, yielding higher signal-to-noise; and 2) wide band in channel 5 for more complete spectral coverage.It was the goal of SPECTRE to acquire clear-sky radiance spectra under a variety of temperature and water vapor conditions.
Origins, Spectral Interpretation, Resource Identification, Security, Regolith Explorer (OSIRIS-REx): Thermal Emission Spectrometer (OTES) Bundle
This bundle collects all the operational data products produced by the OSIRIS-REx Thermal Emission (OTES). OTES is used for the spectral characterization of the surface of (101955) Bennu.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.