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22 results for “surface albedo”
Global Daily Surface Blue-sky Albedo Climatology and Land Cover Climatology Dataset from 20-year MODIS Products (CMG)
<p>Surface albedo plays a critical role in climate, hydrological, and biogeochemical modeling and weather forecasting. Therefore, precisely mapping surface albedo climatology globally is necessary to better parameterize environmental systems. We generated a new global surface blue-sky actual and snow-free albedo climatology dataset from 20-year MODIS products from the Google Earth Engine (GEE). </p> <p>The 500m global surface blue-sky daily albedo climatology dataset is available at .... After reprojection and aggregation, the global Climate Modeling Grid (CMG) albedo climatology datasets at 0.05° and 0.5° are available here. All of the published datasets include historical and snow-free blue-sky albedo climatology data. For application convenience, the land cover climatology of MODIS product (MCD12Q1) is also generated and attached in the CMG files. The International Geosphere-Biosphere Programme (IGBP) and PFT classification results of MCD12Q1 since 2001 were reprojected and aggregated to 0.05° and 0.5° by find mode in each aggregation group. In order to check the heterogeneity of the land cover climatology, the percentage of the dominant type in each aggregation group was also calculated.</p>
What Controls the Mean East–West Sea Surface Temperature Gradient in the Equatorial Pacific: The Role of Cloud Albedo
<p>Climatologies for the climate model simulations performed by Burls and Fedorov 2014, Journal of Climate, <a href="https://doi.org/10.1175/JCLI-D-13-00255.1">https://doi.org/10.1175/JCLI-D-13-00255.1</a>. This table shows how the names of the simulation files provided in this dataset relate to the experiment names provided in Table 1 of Burls and Fedorov (2014, JOC).</p> <table> <thead> <tr> <th scope="col">Experiment # in Article (Table 1)</th> <th scope="col">Name of Files</th> </tr> </thead> <tbody> <tr> <td>1</td> <td>PreInd_T31_gx3v7*.nc</td> </tr> <tr> <td>2</td> <td>80p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>3</td> <td>60p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>4</td> <td>40p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>5</td> <td>20p_op_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>6</td> <td>20p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>7</td> <td>40p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>8</td> <td>60p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>9</td> <td>80p_LWP_1590deg_T31_gx3v7*.nc</td> </tr> <tr> <td>10</td> <td>20p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>11</td> <td>40p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>12</td> <td>60p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>13</td> <td>80p_ILWP_1590deg_tropx2_T31_gx3v7*.nc</td> </tr> <tr> <td>14</td> <td>20p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>15</td> <td>40p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>16</td> <td>60p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>17</td> <td>80p_ILWP_1590deg_tropx4_T31_gx3v7*.nc</td> </tr> <tr> <td>18</td> <td>20p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>19</td> <td>40p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>20</td> <td>60p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>21</td> <td>80p_ILWP_3060deg_tropx8_T31_gx3v7*.nc</td> </tr> <tr> <td>22</td> <td>PreInd_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>23</td> <td>40p_LWP_1590deg_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>24</td> <td>60p_LWP_1590deg_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>25</td> <td>40p_ILWP_1590deg_tropx2_0.9x1.25_gx1v6*.nc</td> </tr> <tr> <td>26</td> <td>60p_ILWP_1590deg_tropx2_0.9x1.25_gx1v6*.nc</td> </tr> </tbody> </table> <p>Article abstract:</p> <p>The mean east–west sea surface temperature gradient along the equator is a key feature of tropical climate. Tightly coupled to the atmospheric Walker circulation and the oceanic east–west thermocline tilt, it effectively defines tropical climate conditions. In the Pacific, its presence permits the El Niño–Southern Oscillation phenomenon. What determines this temperature gradient within the fully coupled ocean–atmosphere system is therefore a central question in climate dynamics, critical for understanding past and future climates. Using a comprehensive coupled model [Community Earth System Model (CESM)], the authors demonstrate how the meridional gradient in cloud albedo between the tropics and midlatitudes (Δα) sets the mean east–west sea surface temperature gradient in the equatorial Pacific. To change Δα in the numerical experiments, the authors change the optical properties of clouds by modifying the atmospheric water path, but only in the shortwave radiation scheme of the model. When Δα is varied from approximately −0.15 to 0.1, the east–west SST contrast in the equatorial Pacific reduces from 7.5°C to less than 1°C and the Walker circulation nearly collapses. These experiments reveal a near-linear dependence between Δα and the zonal temperature gradient, which generally agrees with results from the Coupled Model Intercomparison Project phase 5 (CMIP5) preindustrial control simulations. The authors explain the close relation between the two variables using an energy balance model incorporating the essential dynamics of the warm pool, cold tongue, and Walker circulation complex.</p>
Snow melt onset date estimates derived from CLARA-A2 SAL surface albedo dataset
<p>Snow melt onset date estimates for the Northern Hemisphere, 1982-2015. Derived from the CLARA-A2 SAL surface albedo dataset. Version for manuscript review.</p>
Derived data supporting the analysis of surface albedo changes from Mars 2020 observations: Probabilistic distribution of the Amplitude Spectral Densities of Supercam microphone recordings and Monte-Carlo dust devil simulations.
<p>These files contain derived data used in the analysis submitted for publication in Journal of Geophysical Research: Planets, entitled "Dust Lifting Through Surface Albedo Changes at Jezero Crater, Mars" by Vicente-Retortillo et al. The article was initially submitted on November 14, 2022, and the revised version on March 1, 2023.</p> <p>Files include the derived data and information needed to generate Figures 4 (Microphone_Data.mat and Plot_ASD_from_Microphone_Data) and 6 (remaining files) of the article.</p>
Shortwave surface albedo of glaciers in the central Chilean Andes
<p>Data used to analyse glacier surface albedo change in the central Chilean Andes for the manuscript:</p> <p>Glacier albedo reduction and drought effects in the extratropical Andes, 1986-2020</p> <p>Thomas E. Shaw1, Genesis Ulloa2, David Farías-Barahona3, Rodrigo Fernandez2, Jose Lattus2, James McPhee1,4</p> <p>1 Advanced Mining Technology Center, Universidad de Chile, Santiago, Chile<br> 2 Department of Geology, Universidad de Chile, Santiago, Chile<br> 3 Institute für Geographie, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany<br> 4 Department of Civil Engineering, Universidad de Chile, Santiago, Chile</p> <p>Corresponding author: Thomas E. Shaw (thomas.shaw@amtc.uchile.cl)<br> Keywords: Albedo, Andes, Glacier, Drought, Remote sensing, Climate</p> <p>%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</p> <p>Sub-folders:<br> <strong> [Albedo]:</strong><br> '<strong>Albedo_ChileanGlaciers_DATA.mat'</strong> = matlab file that contains a structure of all information for analyses. <br> 'DATA' structure contains: <br> NAME = Glacier name<br> ALBEDO = 3D albedo matrices for each named glacier<br> DEM = ASTER DEM of same resolution + size<br> DEMtif = as above, but within a georeferenced GRIDobj frame read by TopoToolbox<br> CLASS = classification as 0 (no data), 1 (ice) or 2 (snow)<br> OTSUindex = The histogram separation value per year (per glacier) based upon Otsu inter-class variance<br> SHADOW = Shadowed pixels based upon solar geometry<br> SOLAR_AZI = Solar Azimuth per year taken from Landsat metadata<br> SOLAR_ELE = Solar Elevation per year taken from Landsat metadata<br> NIR = The Near-Infrared band of Landsat images for the Osu classification<br> SLOPE = The calculated slope angle based upon the DEM (GRIDobj format)</p> <p><br> 'SHAPE' is an 18*1 structure of the imported shapefiles in matlab format. Can be plotted using 'mapshow'</p> <p> <strong>[Shapefiles]:</strong><br> '<strong>CentralChileGlaciers.shp</strong>' = Shapefile of glacier boundaries delineated based upon April 2020 3 m PlanetScope imagery.</p> <p><br> <strong>[Climate]:</strong><br> '<strong>Ta_Precip_HY.mat</strong>' = Mean Monthly Air temperature (°C) and monthly total precipitation (mm) at long term DGA weather stations for each Hydrological year (April-March)<br> 'TAmonth_HY' = A matrix of 35 x 12 mean month air temperatures (°C) where rows (x35) = the hydrological year starting 1985-1986 and columns (x12) = the months of the hydrological year so that the first column is April and the final column is March of the following year<br> 'PPmonth_HY' = As above but a 3D matrix of 35 x 12 x 3 for monthly sums of precipitation (mm). The rows and columns are defined above and the third dimension are the stations Riecillos (32.92°S, 70.35°W ,1290 m a.s.l.), Embalse Yeso (33.67°S, 70.08°W, 2475 m a.s.l.) and Rengo (34.19°S, 70.75°W, 515 m a.s.l.), respectively.<br> <br> </p> <p><br> <br> </p>
Boreal Winter Hadley Cell Contraction in Response to the Incorporation of a Comprehensive Ocean Surface Albedo in CESM2
<p>Simulated output for: Boreal Winter Hadley Cell Contraction in Response to the Incorporation of a Comprehensive Ocean Surface Albedo in CESM2</p>
Data of low snow surface albedo experiment with MIROC5.2
<p>Dataset of the low snow surface albedo experiment and the control experiment using the Atmospheric GCM of MIROC5.2.</p> <p>In the low snow surface albedo experiment, the surface albedo of snow was set considerably lower than the normal values used in the control experiment. Other parameters and forcing data in both the experiments are the same. Variables are limited to those used in the research paper.</p> <ul> <li>Latent heat flux at surface (evap)</li> <li>sensible heat flux at surface (sens)</li> <li>sea level pressure (slp)</li> <li>all-sky longwave radiation flux at surface (slr)</li> <li>clear-sky longwave radiation flux at surface(slrc)</li> <li>all-sky shortwave radiation flux at surface (ssr)</li> <li>clear-sky shortwave radiation flux at surface (ssrc)</li> <li>surface air temperature (T2)</li> </ul> <p>See the research paper for the detail.</p>
Global Daily Surface Blue-sky Albedo Climatology and Land Cover Climatology Dataset from 20-year MODIS Products (500m)
<p>Only the first days of each month were uploaded to Zenodo due to the data storage limitation, and the full dataset is available at http://glass.umd.edu/albedo_clim/.</p> <p>Surface albedo plays a critical role in climate, hydrological, and biogeochemical modeling and weather forecasting. Therefore, precisely mapping surface albedo climatology globally is necessary to better parameterize environmental systems. We generated a new global surface blue-sky actual and snow-free albedo climatology dataset from 20-year MODIS products from the Google Earth Engine (GEE). </p> <p>The 500m global surface blue-sky daily albedo climatology dataset follows the basic MODIS product format and employed the sinusoidal projection. It includes historical and snow-free blue-sky albedo climatology data. For application convenience, the land cover climatology of MODIS product (MCD12Q1) is also generated and attached. The International Geosphere-Biosphere Programme (IGBP) and PFT classification climatology of MCD12Q1 since 2001 were also generated.</p>
Data for: Connecting hemispheric asymmetries of planetary albedo and surface temperature
<p>Satellite measurements show that the Northern and Southern hemispheres reflect equal amounts of short-wave radiation ("albedo symmetry"), but no theory exists on if, how, and why the symmetry is established and maintained. Ambiguously, climate models are strongly biased in albedo symmetry but agree in the sign of the response to CO<sub>2</sub>. We find that mean-state biases in albedo symmetry and surface temperature asymmetry correlate negatively. Similarly, the response of albedo asymmetry to CO<sub>2</sub> forcing correlates negatively with the magnitude of the asymmetry in surface warming. This is true across many and within single climate model simulations: a too warm or stronger warming hemisphere is darker or darkens more than its counterpart. In the 21 years of observations we find the same tendency and hypothesize a) albedo symmetry is a function of the current climate state and b) we will observe an evolution towards albedo asymmetry in coming decades.</p>
Sensitivity of Arctic Surface Temperature to Including a Comprehensive Ocean Interior Reflectance to the Ocean Surface Albedo within the Fully Coupled CESM2
<p>CESM2 simulations were performed to study the light attenuation effects at the ocean surface layer on Arctic surface temperature. This dataset provides some simulated variables analyzed in our study.</p>
Observed ocean surface albedo from a fixed offshore platform
<p>The ocean surface albedo (OSA) is an important parameter in numerical ocean models and air‒sea heat flux calculations. Radiation observations were conducted to study the OSA in the northern South China Sea using a fixed offshore tower-based platform. The platform was located at 21.44° N, 111.39° E, with an average water depth of approximately 16 m. It consisted of a main tower and two auxiliary towers. The auxiliary towers were approximately 6 m from the main tower and their lower edges were approximately 6 m from the mean sea surface.</p> <p>A four-component net radiometer (CNR4) was installed on the lower edge of the southeast auxiliary tower through a 2-m long boom to simultaneously measure the upward and downward broadband solar radiation having spectral bands between 305 and 2800 nm. A bottom-mounted Nortek acoustic Doppler current profiler was used to measure surface waves. Other ancillary meteorological instruments were used to measure meteorological parameters, including wind speed and water vapor pressure.</p> <p>The observation period lasted from September 2017 to December 2018. The measured broadband radiation was collected in 30-min segments. To obtain an accurate and reliable radiation dataset, three specific types of data were removed from the dataset: (1) local afternoon data; (2) data with solar altitude angles < 10°; (3) data with downward solar radiation of < 30 W m<sup>−2</sup>. After this quality control, 2433 segments of data can be used to study the OSA.</p>
Data for: Connecting hemispheric asymmetries of planetary albedo and surface temperature
Open the record for dataset details and reuse information.
A monthly shortwave radiative forcing kernel for surface albedo change using CERES satellite data
We present a radiative kernel for surface albedo change founded on a novel, simplified parameterization of shortwave radiative transfer driven with inputs from the Clouds and the Earth’s Radiant Energy System (CERES) Energy Balance and Filled (EBAF) Edition 4.0 products based on a 16-year climatology (2001-2016). Both monthly temporally-explicit and monthly climatological mean CERES albedo change kernels (CACK) are provided with their respective uncertainty layers. Octave script files for generating monthly CACK from CERES EBAF data and demonstrating the application of CACK with user-specified temporal and spatial extents are also included.
Effects of flowers on land surface albedo and soil microclimate
<p>The phenology of vegetation, namely leaf-out and senescence, can influence the Earth's climate over regional spatial scales and long time periods (e.g., over 30 years or more), in addition to microclimates over local spatial scales and shorter time periods (weeks to months). However, the effects of flowers on climate and microclimate are unknown. We investigate whether flowers can influence light reflected by the land surface and soil microclimate in a subalpine meadow. We conducted a flower removal experiment with a common sunflower species, Helianthella quinquenervis, for 3 years (2015, 2017, and 2019). The flower removal treatment simulates the appearance of the meadow when Helianthella flowers earlier under climate change and loses its flowers to frost (other plant structures are not damaged by frost). We test the hypotheses that a reduction in cover of yellow flowers leads to a greener land surface, lower reflectance, warmer and drier soils, and increased plant water stress. Flower removal plots are greener, reflect less light, exhibit up to 1.2 °C warmer soil temperatures during the warmest daylight hours, and contain ca. 1% less soil moisture compared to controls. However, soils were warmer in only 2 of the 3 years, when flower abundance was high. Helianthella water use efficiency did not differ between removal and control plots. Our study provides evidence for a previously undocumented effect of flowers on soil microclimate, an effect that is likely mediated by climate change and flowering phenology. Many anthropogenic environmental changes alter landscape albedo, all of which could be mediated by flowers: climate change, plant invasions, and agriculture. This study highlights how further consideration of the effects of flowers on land surface albedo could improve our understanding of the effects of vegetation on microclimate.</p>
Model dataset for the journal publication titled "Improved snow albedo evolution in Noah-MP land surface model coupled with a physical snowpack radiative transfer scheme"
<div> <p>This is the Noah-MP model simulation dataset for the journal publication titled "Improved snow albedo evolution in Noah-MP land surface model coupled with a physical snowpack radiative transfer scheme"</p> <p> </p> </div>
Effects of flowers on land surface albedo and soil microclimate
Open the record for dataset details and reuse information.
SAFARI 2000 Surface Albedo and Radiation Fluxes at Mongu and Skukuza, 2000-2002
Top-of-the-canopy broadband albedo and radiation fluxes are calculated from measurements at the Mongu and Skukuza flux tower sites in southern Africa from March 2000 through December 2002. Data were collected by instrumentation deployed at the top of the 30 m tower in the Kataba Local Forest near Mongu, Zambia, and atop the 20 m tower at the Skukuza tower site in Kruger National Park, South Africa. At the Mongu site, Kipp and Zonen albedometers housing both upward- and downward-looking pyranometers were outfitted with clear and red domes to collect broadband albedo and radiation fluxes in the shortwave (SW) and near-infrared (NIR) wavebands, respectively. The data are mean values provided at 15-minute intervals for 2000-2002. At the Skukuza tower, Kipp and Zonen albedometers (also outfitted with clear and red domes) collected broadband albedo and radiation fluxes in the SW and NIR wavebands. In addition, a pyrgeometer was used to collect longwave radiation flux in thermal infrared (TIR) wavebands. The data at Skukuza are mean values provided at 30-minute intervals for 2000-2002, except for the TIR data, which are provided for 2001 and 2002 only. For both sites, photosynthetically active radiation can be calculated from measurements.The data are provided in comma-delimited ASCII files, with column headers. The SW and NIR data for both sites are provided in one file per year per site for 2000-2002. The Skukuza longwave data are provided separately, and for years 2001 and 2002 only.
PROVE Surface albedo of Jornada Experimental Range, New Mexico, 1997
The objective of this study was to determine the spatial variations in field measurements of broadband albedo as related to the ground cover and under a range of solar conditions during the Prototype Validation Exercise (PROVE) at the Jornada Experimental Range in New Mexico on May 20-30, 1997. The surface albedo was sampled as described in Barnsley et al. (2000) at intervals along transects radiating north, south, east, and west from the main instrumentation tower at the transitional vegetation site. Several of these transects were sampled on more than one occasion, under a range of solar illumination conditions. At the grassland site, albedo measurements were taken along a single transect, sampled at 10-m intervals, at three different times of day (i.e., at different solar zenith angles). In addition to the albedo data, hemispherical photographs were taken at each of the sample sites to provide a visual record, and the images were classified to estimate the proportion of bare soil, live vegetation, and woody ground cover.
Near Real-Time MODIS/Terra L3 Global Daily 500m SIN Grid Snow Cover, Snow Albedo, and Snow Surface Properties, Version 1
This data set contains the following parameters: snow fraction (on the ground), viewable snow fraction, snow cover duration, snow grain size, dust concentration, snow albedo (on horizontal surface), snow albedo (on sloped surface), and radiative forcing. All variables are spatially and temporally complete after interpolation. Days without observation is also included so that users can determine how many days since a satellite observation occurred.The data set is derived from a version of the spectral mixture analysis (SMA) approach called the Snow Property Inversion from Remote Sensing (SPIReS, <a href="https://www.sciencedirect.com/science/article/pii/S0034425725001464?via%3Dihub#bb0040">Bair et al, 2021</a>). This dataset uses surface reflectance inputs from <a href="https://lpdaac.usgs.gov/products/mod09gav061/">MOD09GA v6.1</a> and includes additional outputs not included in the original version of SPIReS: snow albedo and snow radiative forcing.The SPIReS SMA model considers three spectral endmembers: snow, shade, and a snow-free background reflectance, which is identified for each MODIS pixel as the average MOD09GA reflectance measured typically between 1 August and 30 September for a given year in the northern hemisphere. dust concentration is solved for simultaneously with fractional snow cover and snow grain size during the spectral unmixing process. SPIReS snow albedo are derived using a lookup table that incorporates snow grain size, dust concentration, and surface illumination (<a href="https://www.sciencedirect.com/science/article/pii/S0034425725001464?via%3Dihub#bb0025">Bair et al., 2019</a>). After the fSCA, grain size, and dust concentration are determined, these properties are filled, smoothed, and adjusted for canopy gap size, shade, and permanent ice. SPIReS radiative forcing are derived using a lookup table that incorporates LAP concentration and clear sky incoming solar irradiance. Data are available from 01 October 2024 to present. These data are provided in the netCDF-4 format with a Sinusoidal projection and are currently available for the western United States (MODIS tiles h08v04, h08v05, h09v04, h09v05, h10v04). Additional tiles will be added over time. For data prior to 01 October 2024, please see the historical dataset (<a href="https://doi.org/10.7265/a3vr-c014">Rittger et al., 2025</a>) created by Snow Today at NSIDC.Data can be accessed via ftp://dtn.rc.colorado.edu/shares/snow-today/spires/SPIRES_NRT_V01Note: Authors Rittger, K. and Lenard, S. contributed equally to this work
Historical MODIS/Terra L3 Global Daily 500m SIN Grid Snow Cover, Snow Albedo, and Snow Surface Properties, Version 1
This data set contains the following parameters: snow fraction (on the ground), viewable snow fraction, snow cover duration, snow grain size, dust concentration, snow albedo (on horizontal surface), snow albedo (on sloped surface), and radiative forcing. All variables are spatially and temporally complete after interpolation. Days without observation is also included so that users can determine how many days since a satellite observation occurred. The data set is derived from a version of the spectral mixture analysis (SMA) approach called the Snow Property Inversion from Remote Sensing (SPIReS, <a href="https://www.sciencedirect.com/science/article/pii/S0034425725001464?via%3Dihub#bb0040">Bair et al, 2021</a>). This dataset uses surface reflectance inputs from <a href="https://lpdaac.usgs.gov/products/mod09gav061/">MOD09GA v6.1</a> and includes additional outputs not included in the original version of SPIReS: snow albedo and snow radiative forcing. The SPIReS SMA model considers three spectral endmembers: snow, shade, and a snow-free background reflectance, which is identified for each MODIS pixel as the average MOD09GA reflectance measured typically between 1 August and 30 September for a given year in the northern hemisphere. dust concentration is solved for simultaneously with fractional snow cover and snow grain size during the spectral unmixing process. SPIReS snow albedo are derived using a lookup table that incorporates snow grain size, dust concentration, and surface illumination (<a href="https://www.sciencedirect.com/science/article/pii/S0034425725001464?via%3Dihub#bb0025">Bair et al., 2019</a>). After the fSCA, grain size, and dust concentration are determined, these properties are filled, smoothed, and adjusted for canopy gap size, shade, and permanent ice. SPIReS radiative forcing are derived using a lookup table that incorporates LAP concentration and clear sky incoming solar irradiance. Data are available from 01 March 2000 to 30 September 2024. These data are provided in the netCDF-4 format with a Sinusoidal projection and are currently available for the western United States (MODIS tiles h08v04, h08v05, h09v04, h09v05, h10v04). Additional tiles will be added over time. For data after 30 September 2024, please see the near real-time dataset (<a href="https://doi.org/10.7265/hs6b-zg21">Rittger et al., 2025</a>) created by Snow Today at NSIDC.Data can be accessed via ftp://dtn.rc.colorado.edu/shares/snow-today/spires/SPIRES_HIST_V01
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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.