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1,574 results for “atmospheres”
Sonora Bobcat: cloud-free, substellar atmosphere models, spectra, photometry, evolution, and chemistry
<p><strong>OVERVIEW</strong></p> <p>Presented here are models for non-irradiated, substellar mass objects belonging to the Sonora model series, described in Marley et al. (2021). The files presented here are model temperature-pressure structures ("structure"), emergent spectra from the top of the atmosphere ("spectra"), thermal evolution and photometry ("evolution_and_photometry"), and rainout chemical equilibrium tables used to compute the models ("chemistry"). </p> <p>Atmospheric structure and spectra .tar file names specify metallicity [M/H] and carbon-to-oxygen ratio (C/O) relative to solar. For example, "structures+0.0_co1.5<a href="../api/files/2e9ce76a-67fc-4fd6-ae5c-f88f16c610ea/structures%2B0.0_co1.5.tar.gz">.</a>tar.gz" contains the set of radiative-convective equilibrium atmospheric structures for solar metallicity ("+0.0") with C/O=1.5 times the solar abundance. The _co*.* is omitted for solar C/O, or co_1.0. The individual file naming convention is described below. All stated abundances and ratios are relative to Lodders (2010) abundances, see Marley et al. (2021) for details and use caution when referring to other abundance tabulations.</p> <p>This particular set of model atmosphere structures and associated spectra, photometry, and evolution, which we name <strong>Sonora Bobcat</strong>, are for cloudless objects with 3.25 ≤ log g (cgs) ≤ 5.5 and 200 ≤ Teff ≤ 2400K. Steps in T<sub>eff</sub> vary from 25K to 1000K and steps in log g are 0.25 or 0.5. Some combinations of model grid parameters include additional values of the gravity. Models are provided for [M/H] = -0.5, 0.0, and +0.5 and "rainout" chemical equilibrium. A limited set of models with carbon-to-oxygen ratio of 0.5 and 1.5 times solar abundance are also included. For the convenience of having a rectangular table in (T<sub>eff</sub>, gravity) space, models are calculated in regimes that are not reached by the evolution, such as very high gravity and very low T<sub>eff</sub>. Refer to the companion evolution tables to identify combinations of T<sub>eff</sub> and log g outside the bounds covered by the evolution.</p> <p><strong>ATMOSPHERIC STRUCTURE</strong></p> <p>Atmospheric structure and spectra filenames specify Teff and gravity (in mks units) along with [M/H] and (C/O) relative to solar. "co1.5" in version and spectra header nomenclature refers to 1.5 times the solar C/O ratio. _co*.* is generally omitted for 1.0, the solar value. For example, the file t1000g316nc_m-0.5.dat contains the structure of a model with T<sub>eff</sub>=1000K, g=316m/s<sup>2</sup> (the exact value of the gravity is given<sup> </sup>in the first line of the file, see below) , [Fe/H]=-0.5, and C/O=1.0 times the solar value. </p> <p>Temperature structure and spectra files have a one line header giving "Teff, grav(MKS), Y, f_sed, kz_min, [Fe/H], C/O, f_hole". Teff and grav are the effective temperature (K) and gravity (MKS), Y is the He mass fraction. f_sed is a cloud parameterization which is not relevant for these cloudless models and is arbitrarily given as 0.0. Likewise kz_min relates to the atmospheric eddy diffusion coefficient, which is also not relevant for these chemical equilibrium models and is arbitrarily set equal to a placeholder value that is not used in these models. [Fe/H] and C/O are the metallicity and C/O ratios as described above. [Fe/H] is identical to [M/H]. f_hole is another cloud parameter for cloudy models, not relevant to these cloudless models.</p> <p>Columns in the atmosphere structure files describe the atmosphere at discrete levels. Columns give: level index, P(bar), T(K), internally used check parameter, adiabatic temperature gradient (d ln T / d ln P), local temperature gradient (d ln T / d ln P), atmospheric density (g / cm<sup>3</sup>).</p> <p><strong>EVOLUTION AND PHOTOMETRY</strong></p> <p>Evolution and Photometry tables are described in detail in a README file included in that tar file. Evolution files connect mass, effective temperature, radius, age, gravity, and moment of inertia for these model sets. Each set of model spectra is complemented with tables of fluxes and of absolute magnitudes in a number of photometric systems commonly used in brown dwarf and exoplanet research (MKO, Keck, 2MASS, SDSS, WISE, Spitzer IRAC, etc). Fluxes and magnitudes for the full set of JWST filters is also included in separate tables. Magnitudes are computed on the Vega system (using the Vega spectrum of Bohlin & Gilliland 2004) or on the AB system (e.g. for SDSS).</p> <p><strong>SPECTRA</strong></p> <p>The model spectra each contain close to 362000 wavelength points. The resolving power varies with wavelength and ranges from R=6000 to 200000 but is otherwise the same for all spectra. The first line gives the model parameters in the same format as the structure files described above. This is followed by the spectrum</p> <p>Column 1: wavelength in µm</p> <p>Column 2: <strong>Radiation flux <em>F<sub>ν</sub></em></strong><sub> </sub>= \(4\pi\) x Eddington flux <em>H</em><sub>ν</sub>, in erg/cm<sup>2</sup>/s/Hz (always exercise caution with factors of \(4\pi\) when comparing to the radiation and Eddington flux, e.g., see Section 3.3 of Hubeny & Mihalas, "Theory of Stellar Atmospheres")</p> <p>The spectral fluxes are given at the top of the atmosphere and are strictly monochromatic. The model spectrum provides no information in the wavelength range between two tabulated points. Unless a spectral line or feature is well resolved,<em> interpolation in wavelength is not advised</em>. For comparison with data, the model spectra need to be convolved and binned to the instrumental resolution and sampling. In our experience, a minimum of 10 wavelength points is necessary to obtain a reasonable average flux over a wavelength interval. This is a rule of thumb and caution is advised, especially when comparing with high resolution data. The flux received at Earth is that given in the table scaled by (R/D)<sup>2</sup> where R is the radius of the object (given in the companion evolution tables) and D its distance. </p> <p>The solar spectra and photometry are the same as those archived at https://zenodo.org/record/1309035#.YOyz4S1h2X0, which did not provide the T(P) profiles available here.</p> <p><strong>CHEMISTRY</strong></p> <p>We also separately include rainout chemical equilibrium tables for these same atmospheric bulk abundances. These chemistry files are described in detail by their own README file. Additional chemistry tables, beyond those used for the models presented here, are also included for completeness. Users interested in the chemical abundances of the structure models must interpolate within the matching chemistry file for the atmospheric species of interest.</p> <p><strong>CREDITS</strong></p> <p>If you use these tables in your research, please cite Marley et al. (2021, Astrophysical Journal, Volume 920, Issue 2, id.85.)</p> <p>16 Feb 2024: Error corrected in Column 2 heading. Column 2 is the Radiation flux, not the Eddington flux as previously stated. Citation updated.</p> <p> </p>
Phosphorus Chemistry in the Earth's Upper Atmosphere
<p><strong>Phosphorus Chemistry in the Earth’s Upper Atmosphere</strong></p> <p>by</p> <p>John M.C. Plane<sup>1*</sup>, Wuhu Feng<sup>1,2</sup> and Kevin M. Douglas<sup>1</sup></p> <p><sup>1</sup> School of Chemistry, University of Leeds, UK</p> <p><sup>2</sup> National Centre for Atmospheric Science and School of Earth and Environment, University of Leeds, UK</p> <p> </p> <p>The repository contains the data used in the above paper.</p>
Raw and analyzed data for manuscript "Reduction of copper surface oxide using a sub-atmospheric dielectric barrier discharge plasma"
<p><strong>Abstract:</strong> Oxide layers on metal surfaces adversely affect processability and material properties in many industrial applications. Although several plasma-based approaches for deoxidation were investigated in the past, oftentimes they either work under conditions expensive to create or require long processing times. In this study, the deoxidation effect of a non-thermal dielectric barrier discharge plasma in an Ar/H<sub>2</sub> gas mixture at 100 hPa and 20 °C was investigated on copper surfaces with a native oxide layer. The chemical structure of surfaces before and after deoxidation was analyzed by X-ray photoelectron spectroscopy (XPS). The results revealed that ~98 % of the surface lattice oxide Cu<sub>2</sub>O was reduced to Cu after around 20 s of plasma treatment, whereas all oxygen contaminants were almost completely removed from Cu surface after around 50 s. Additionally, the kinetics of the reduction of surface oxide was studied and a Johnson-Mehl-Avrami-Erofeev-Kholmogorov kinetic model was proposed. The analysis of the morphology of surfaces was performed with atomic force microscopy (AFM), showing minor changes in the roughness after deoxidation. Moreover, optical emission spectroscopy (OES) showed atomic hydrogen radicals in the plasma phase, which likely causes deoxidation effect.</p>
Bottom-of-atmosphere reflectance data from aerial imaging for Lake Mulargia (Sardinia, Italy) (2020/09/24)
<p>This dataset contains the surface reflectance Hyspex images derived with ATCOR code by CNR of Lake Mulargia (Sardinia, Italy). The acquisition was done by CGR Spa (Italy).</p>
Comparison of radiative transfer schemes for the calculation of aerosol radiative forcing in Mars' atmosphere
<p>Output datasets for Figures (fig. 1 to 10) for the intercomparison of radiative transfer algorithms for the calculation of aerosol radiative forcing in the Martian atmosphere.</p>
Astroclimate measurements on several points over Eastern hemisphere in 2-mm and 3-millimeter atmospheric transparency windows using tipping radiometer
<p>We are presenting results of the atmospheric propagation observations which our research group has been conducting since 2012. Over this time, we have gathered statistical data of atmospheric propagation over a number of sites which possibly can be used for radio astronomical observations in the millimetre and sub-millimetre bandwidths. The Zenith opacity was studied by the atmospheric dip method in the 3 mm and 2 mm atmospheric windows. The dataset is recommended to use for estimation of atmospheric propagation for the purpose of radio astronomy and telecommunications.</p> <p>The “tau-meter” (named MIAP-2) allows us to estimate an integral absorption by using the atmospheric dip method. The hardware includes a radiometric system comprising two self-contained radiometers operating in two different bands of 84-99 GHz (λ ~ 3 mm) and 132-148 GHz (λ ~ 2 mm), a rotary support, a control, and a firmware system. The radiometers work in modulation mode within 36 Hz modulation frequency. Floating mirror allows radiometer to scan the sky in the interval of 0 – 88.5 elevation angles (6 total). The output record contains the voltages of synchronous detector for each angle in 2 wavebands. The voltage is proportional to brightness temperature of the sky in corresponding waveband. (It has negative value for technical reasons.)</p> <p>The dataset contains raw data observed by radiometer: Local date and time, a several detector voltages on different elevation angles for 2 wavebands, as well as service information header. The first 6 columns contain optical depth calculated by old method and it’s no more used in data processing since the new algorithm has been invented in 2018.</p>
Effects Of Atmospheric Attenuation On The Lightning Spectrum
<p>Spectrum carries important information reflecting atomic and molecular processes inside a light source. Accurate spectral diagnosis is vital in revealing the microscopic physical mechanism of the lightning discharge process. Spectral correction was applied considering the influence of atmospheric attenuation, grating efficiency, and camera response on the observed spectrum, thereby solving the problems of atmospheric attenuation in long distance lightning spectrum observations. Based on the restored spectrum, the temperature of the lightning return stroke channel was calculated by the ionic and atomic lines respectively. The result showed that corrected temperature at the initial stage of the return stroke, calculated by the ionic line, could reach up to 40,000 K, which was about 10,000 K higher than the values directly obtained from the observed spectrum. Atmospheric attenuation of the atomic spectral line in the nearinfrared band is relatively weak; therefore, atmospheric attenuation was inferred to have a relatively less effect on the channel temperature that was calculated by the atomic spectral lines. This work provided the attenuation ratio of the characteristic lines in lightning spectra with distance, and can used for more precisely quantitative investigation on the physical characteristics of the lightning process. It also has application value for improving the spectral diagnostic techniques on celestial body and other natural luminous process.<br> </p>
ATASF: Tri-hourly anomaly of tropical atmospheric surface fluxes.
<p><strong>ATASF dataset</strong> is a product that contains the tri-hourly surface anomalies of the entire tropical region (180°W - 178.125°E/33.3328°S – 31.4281°N) of the heat fluxes and of the incident and reflected radiation. These are calculated from 20th Century Reanalysis V2c data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at <a href="http://www.esrl.noaa.gov/psd/">http://www.esrl.noaa.gov/psd/</a>. This product contains the variables:</p> <ol> <li>Tri-hourly convective precipitation rate (kg m^{-2} s)</li> <li>Tri-hourly downward longwave radiation flux at surface (w m^{-2})</li> <li>Tri-hourly downward solar radiation flux at surface (w m^{-2})</li> <li>Tri-hourly upward longwave radiation flux at surface (w m^{-2})</li> <li>Tri-hourly upward solar radiation flux at surface (w m^{-2})</li> <li>Tri-hourly latent heat net flux at surface (w m^{-2})</li> <li>Tri-hourly sensible heat net flux at surface (w m^{-2})</li> </ol> <p>All these 3D grids have a period of time from 1851-01-01 00:00:00 to 2014-12-31 21:00:00, with a spatial resolution of 1.875 x 1.904732 degrees. The objective of this dataset is to facilitate researchers to study the anomalies of these 7 parameters on the ocean surface during the occurrence of short and medium duration physical processes such as low pressures, cold fronts, hurricanes and others.</p>
Research Compendium for Harrington et al. (2021): "An Open-Source Bayesian Atmospheric Radiative Transfer (BART) Code: I. Design, Tests, and Application to Exoplanet HD 189733 b"
<p>This archive is the Reproducible Research Compendium for<br> <br> An Open-Source Bayesian Atmospheric Radiative Transfer (BART) Code: I. Design, Tests, and Application to Exoplanet HD 189733 b<br> <br> by Harrington et al. (2021), published in The Planetary Science Journal.<br> <br> BART is an atmospheric parameter retrieval code. It infers the properties of planetary atmospheres from spectroscopic observations. The compendium includes all the software, documentation, configuration files, plots, and data published in the paper. The compendium is under the Reproducible Research Software License; see LICENSE file. The README provides additional information and describes the contents of each compressed .tar.gz file.</p>
Animated E3SM V1 High Resolution Labrador Sea Ice Thickness and Concentration with mid-20th Century Atmospheric Constituents
<p>This animated GIF file visualizes daily grid-cell mean sea ice thickness and concentration for the Labrador Sea region from version 1 of the Energy Exascale Earth System Model (E3SM) using 25km Atmosphere/Land and 8-16km Sea Ice-Ocean resolutions as described in the manuscript "The DOE E3SM coupled model version 1: Description 1 and results at high resolution". River routing is resolved at 0.125˚. This fully coupled simulation was spun-up for 6 years, and then proceeded for 50 subsequent years using HighResMIP protocols for continuuous 1950s atmospheric constituents. This animation shows sea thickness evolution in each frame for five model years 46 to 50, inclusive, with rendered transparency determined from sea ice concentration to demonstrate the influence of ocean eddies around the southern tip of Greenland. The coastline is the true model boundary. The animation is best viewed using a web browser.</p>
Animated E3SM V1 High Resolution Full Coupled Sea Ice Thickness and Extent with mid-20th Century Atmospheric Constituents
<p>This animated GIF file visualizes daily grid-cell mean sea ice thickness from version 1 of the Energy Exascale Earth System Model (E3SM) using 25km Atmosphere/Land and 8-16km Sea Ice-Ocean resolutions as described in the manuscript "The DOE E3SM coupled mo del version 1: Description 1 and results at high resolution". River routing is resolved at 0.125˚. This fully coupled simulation was spun-up for 6 years, and then proceeded for 50 subsequent years using HighResMIP protocols for continuuous 1950s atmospheric constituents. The animation shows both pan-Arctic and Southern Ocean daily sea thickness evolution in each frame for model years 46 to 55, truncated at 15% sea ice concentration, and is best viewed from within a web browser.</p>
Animated E3SM V1 High Resolution Mertz Polynya Sea Ice Thickness and Concentration with mid-20th Century Atmospheric Constituents
<p>This animated GIF file visualizes daily grid-cell mean sea ice thickness and concentration for the Mertz Glacier Polynya region of the East Antarctic coast from version 1 of the Energy Exascale Earth System Model (E3SM) using 25km Atmosphere/Land and 8-16km Sea Ice-Ocean resolutions as described in the manuscript "The DOE E3SM coupled model version 1: Description 1 and results at high resolution". River routing is resolved at 0.125˚. This fully coupled simulation was spun-up for 6 years, and then proceeded for 50 subsequent years using HighResMIP protocols for continuuous 1950s atmospheric constituents. This animation shows sea thickness evolution in each frame for ten model years 46 to 55, inclusive, with shading transparency determined by sea ice concentration, and grid cell outlines dissappearing where there is less than 0.1% sea ice concentration. The coastline is the true model boundary. This animation is best viewed using a web browser.</p>
Model data used for the paper: "Heat extremes driven by amplification of phase-locked circumglobal waves forced by topography in an idealized atmospheric model"
<p>Atmospheric model output to reproduce the results of the study: "<strong>Heat Extremes Driven by Amplification of Phase-Locked Circumglobal Waves Forced by Topography in an Idealized Atmospheric Model" </strong>published in Geophysical Research letters.<br> <br> Authors: B. Jiménez-Esteve. K. Kornhuber and D. I.V. Domeisen <br> <br> DOI: <a href="https://doi.org/10.1029/2021GL096337">https://doi.org/10.1029/2021GL096337</a><br> <br> For more information about the model setup and the design of the experiments please refer to the above publication.</p>
Thermosphere Hough Mode Extensions (HMEs) for Solar Tides in Earth's Atmosphere
<p>The scientific basis for the atmospheric solar tide HME files contained here is described in Forbes et al. (2022). The directory "HME2022-Hough-UV functions-Tides" contains solutions to Laplace's Tidal Equation for the eastward(westward) propagating diurnal tides with zonal wavenumbers s = -1, -2, -3(+1, +2); the eastward(westward) propagating semidiurnal tides with zonal wavenumbers s = -1, -2, -3(+1, +2, +3, +4, +6); the zonally-symmetric (s = 0) diurnal and semidiurnal tides; and the westward-propagating terdiurnal tide with s = +3. In a widely-used abbreviated notation, these are, respectively: DE1, DE2, DE3, DW1, DW2; SE1, SE2, SE3, SW1, SW2, SW3, SW4, SW6; D0, S0; and TW3. These tides correspond to those measured in Earth's mesosphere and thermosphere. The directory "HME2022-output files-Tides" provides the amplitudes and phases (UT hour of maximum at 0 longitude) of eastward, southward, and vertical winds (m/s), temperatures (K), density perturbations relative to mean, and geopotential height (m) as a function of height (z, every ~4 km) and latitude (deg, every 3 deg), corresponding to several (2 to 7) HMEs for each of the aforementioned tides. Generally the number of HMEs corresponding to each tide is determined by the vertical wavelength Lz of each HME; HMEs with Lz < 30 km are excluded due to their inability to effectively penetrate into the thermosphere above 100 km altitude. The directory "HME_Legacy output files-Tides" includes a prior version of these HMEs that were used in several papers in the literature, but not publicly distributed. The data for each HME extend from pole to pole and from 0 to 400 km altitude. Each directory contains a README file containing further information on the data files.</p>
Data for "Energetic Particle Fluxes onto Callisto's Atmosphere" by Liuzzo et al., 2022
<p>Data files corresponding to the publication "Energetic Particle Fluxes onto Callisto’s Atmosphere" by Liuzzo et al., 2022.</p>
Data for: The Martian atmospheric waves perturbation Datasets (MAWPD) version 2.0
<p class="MsoNormal"><span>The Martian atmospheric waves perturbation Datasets (MAWPD) version 2.0 is the first observation-based climatology dataset of Martian atmospheric waves.</span></p> <p class="MsoNormal"><span>It contains climatology-gridded temperature, gravity waves, and tides spanning the whole Martian year. MAWPD uses the Data INterpolating Empirical Orthogonal Functions method (DINEOF) reconstruction method for data assimilation with the observational data from the Mars Global Surveyor (MGS), Mars Reconnaissance Orbiter (MRO), Mars Atmosphere and Volatile EvolutioN (MAVEN), Mars Pathfinder (MP), Mars Phoenix Lander (MPL), Mars Exploration Rover (MER) and Mars Express (MEX) temperature retrievals. The dataset includes gridded fields of temperature (Level 1 data) as well as the physical quantities of GWs (Level 2 data, amplitude, and potential energies), SPWs and tides (Level 2 data, amplitude, and phase).</span></p> <p class="MsoNormal"><span>We found the MAWPD can well reflect the climatological variations of gravity and tidal waves in the Martian atmosphere. The dataset is useful for observation-based scientific studies concerning Martian atmospheric waves, e.g., circulation, dust storms, and the wave excitation mechanism on Mars, and their comparison with the reanalysis dataset.</span></p>
Detection of Atmospheric Rivers in the Northern Hemisphere based on ERA5 reanalysis data and the IPART algorithm, 1979-2020
<p># 1. Overview</p> <p>This is a catalogue of atmospheric river (AR) detections over the Northern Hemisphere, based on 6-hourly ERA5 reanalysis dataset and the Image-Processing based Atmospheric River Tracking (IPART) algorithm.</p> <p>Time domain of the data:</p> <ul> <li>From 1979-Jan-01 to 2020-Dec-31</li> <li>Temporal resolution is 6-hourly</li> </ul> <p>Spatial domain of the data:</p> <ul> <li>Northern Hemisphere, land and ocean</li> <li>Spatial resolution is 0.25 * 0.25 degrees latitude/longitude</li> </ul> <p>Input data from ERA5 include:</p> <ul> <li>Vertical integral of northward water vapour flux, in kg/(m s).</li> <li>Vertical integral of eastward water vapour flux, in kg/(m s).</li> </ul> <p>Data in the Northern Hemisphere domain (0 - 90 N), at 0.25 * 0.25 degrees latitude/longitude resolution are obtained from https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5.</p> <p>Version v3.0.8 of the IPART Python module used for detection and tracking of atmospheric rivers is preserved at <strong>10.5281/zenodo.4164826</strong>, available via Creative Commons Attribution 4.0 International license and developed openly at the Github repository https://github.com/ihesp/IPART.</p> <p># 2. File naming convention</p> <p>The data files are named using the following convention:</p> <p>ar_YYYYMM.nc</p> <p>where:</p> <ul> <li>YYYY: 4-digit year number</li> <li>MM: 2-digit month number</li> </ul> <p>E.g. `ar_199902.nc` means detections in Feb of 1999.</p> <p>Months are calendar months, including Feb-29th in leap-years.</p> <p># 3. Data format</p> <p>Data are saved in netCDF format.</p> <p>Each data file contains one 3-dimensional array, of a shape `(t, 360, 1440)`, where:</p> <ul> <li>`t`: length of the time dimension. Since data are 6-hourly, t equals 4 * num_of_days_in_month.</li> <li>`360`: latitude dimension, from 0 - 90N, with a 0.25-degree step.</li> <li>`1440`: longitude dimension, from 80 - 440 E (shifted eastward by 80 degrees to put both the Pacific and Atlantic oceans within the domain), with a 0.25-degree step.</li> </ul> <p>Each time slice of the data contains maps of the Northern Hemisphere, with integer values in grid cells. Possible values are:</p> <ul> <li>0: meaning no AR is detected in the grid cell.</li> <li>1, 2, ... ,n: integer labels, each corresponding to the region of an AR entity.</li> </ul> <p># 4. Important parameters in the IPART algorithm</p> <p>Here are the most important parameters used when detecting ARs from ERA5 data using the IPART python module:</p> <ul> <li> THR filtering kernel: `[16, 13, 13]`. `16` means 16 time slices, or equivalently 4 days given 6-hourly input data. `13` means 13 grid cells, or equivalently ~325 km, given 0.25 degrees latitude/longitude input data. Note that both of these temporal and spacial lengths are half of the sizes of the filtering kernel.</li> <li> minimum area: `50 * 1e4`, in km^2, minimum size of AR region candidates.</li> <li> maximum area: `1800 * 1e4`, in km^2, maximum size of AR region candidates.</li> <li> minimum L/W: `2.0`, minimum length/width ratio of AR region candiates.</li> <li> minimum length: `2000`, in km, minimum length of AR region candidates.</li> <li> minimum latitude: `20`, minimum latitude of the geometrical centroid of an AR region candidate.</li> <li> maximum latitude: `80`, maximum latitude of the geometrical centroid of an AR region candidate.</li> </ul> <p>For more details regarding these parameters, as well as the IPART algorithm, please refer to our published works:</p> <ul> <li>Xu, G., Ma, X., Chang, P., and Wang, L.: Image-processing-based atmospheric river tracking method version 1 (IPART-1), Geosci. Model Dev., 13, 4639–4662, https://doi.org/10.5194/gmd-13-4639-2020, 2020.</li> </ul> <p>Or the Github repository that houses the IPART module:</p> <ul> <li>https://github.com/ihesp/IPART</li> </ul>
Resources for publication "Meteorologically normalised long-term trends of atmospheric ammonia (NH3) in Switzerland/Liechtenstein and the explanatory role of gas-aerosol partitioning"
<p>Resources for publication "Meteorologically normalised long-term trends of atmospheric ammonia (NH3) in Switzerland/Liechtenstein and the explanatory role of gas-aerosol partitioning".</p>
Figures of Influence of Time-Varying Atmospheric Channel on Time Reversal Spatial Power Combination of Sparse Array on Ground
<p>A mathematical model of TR (Time Reversal) power combination in the slowly time-varying atmospheric channel and the concept of channel time-varying factor are proposed to study the feasibility of TR technique for spatial power combination in incompletely reciprocal channels. Combining the theoretical analysis and Monte Carlo simulations, we analyze the relationship between the power combination efficiency and the permittivity of the time-varying atmospheric channel, which follows a normal distribution.</p> <p>In this data file, simulation results obtained by commercial software MATLAB are listed. The results indicate that the power combination efficiency of the TR technique will be lower than that of the completely reciprocal channel if the atmospheric channel is slowly varied, and the faster the channel changes, the lower the efficiency becomes. In order to keep the power combination efficiency above 50%, the channel time-varying factor needs to be less than about 54.3% of the signal period. And when it takes more than 90%, the signals radiated by each antenna have been completely incoherent at target point.</p>
Long-term atmospheric precipitation monitoring in Hornsund region (Fuglebekken) - raw data
<p>Since 2004, snow and rain samples have been collected in the Fuglebekken catchment in close vicinity of the Polish Polar Station Hornsund. The rain and snow samples are collected after every event. The pH, conductivity and chemical composition (major ions) are analysed at the Polish Polar Station’s chemical laboratory. The rain gauge is checked approximately once a day.</p> <p>Presented data from 2016 to 2022</p> <p>The data has not been checked, which means that it is raw data.</p>
ScienceDex guides
Understand access before you commit
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.