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Dataset results
429 results for “December”
Temperature inversion (TI) and humidity inversion (HI) collected at Xiaomai Island, Qingdao, Shandong, China, from December 30, 2021 to March 1, 2022.
<p>This dataset presents the parameters of temperature inversion (TI) and humidity inversion (HI) calculated using a microwave radiometer. The data were collected at Xiaomai Island, Qingdao, Shandong, China, from December 30, 2021 to March 1, 2022. The parameters include the moment of occurrence, strength, base height, depth and intensity of TI and HI.</p>
Total estimated number of informal waste pickers or recyclers in Kathmandu Valley, as of December 2022
<p>Using key informants representing different parts of the informal waste management value chain, the RIPL project has produced an updated estimated total number of informal recyclers for Kathmandu Valley, in December 2022. The overview includes methods of calculation and names of key informants. </p>
Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during October-December 2017
<p>Simulation results from WRF-Chem with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China during October-December 2017 including meteorology and air quality, which are in wrfout_YYYY-MM-DD_00_00_00 file on each day during October-December 2017. The file contains these variables:</p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.
Simulation results from WRF-Chem without aerosol feedbacks in eastern China for October-December 2017
<p>Simulation results from WRF-Chem without aerosol feedbacks in eastern China for October-December 2017 including meteorology and air quality,which are in wrfout_YYYY-MM-DD_00_00_00 file on each day for October-December 2017. The file contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.</p>
Simulation results from WRF-Chem with enabling aerosol-radiation interactions in eastern China for October-December 2017
<p>Simulation results from WRF-Chem with enabling aerosol-radiation interactions in eastern China for October-December 2017 including meteorology and air quality,which are in wrfout_YYYY-MM-DD_00_00_00 file on each day for October-December 2017. The file contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB, PM2_5_DRY, o3, no2, so2, co, nh3, EXTCOF55 and ALT.</p>
Simulation results from WRF-CMAQ with enabling aerosol-radiation interactions in eastern China for September-December 2017
<p>Simulation results from WRF-CMAQ with enabling aerosol-radiation interactions in eastern China for September-December 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for September-December 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_CCTM_ACONC.zip:</p><p>Air quality file including CCTM_ACONC_v3852_YYYYMMDD.nc on each day for September-December 2017, which contains these variables:</p><p>ASO4I, ANO3I, ANH4I, ANAI, ACLI, AECI, ALVPO1I, ASVPO1I, ASVPO2I, ALVOO1I, ALVOO2I, ASVOO1I, ASVOO2I, AOTHRI, ASO4J, ANO3J, ANH4J, ANAJ, ACLJ, AECJ, AOTHRJ, AFEJ, ASIJ, ATIJ, ACAJ, AMGJ, AMNJ, AALJ, AKJ, ALVPO1J, ASVPO1J, ASVPO2J, AXYL1J, AXYL2J, AXYL3J, ATOL1J, ATOL2J, AXYL2J, AXYL3J, ATOL1J, ABNZ3J, AISO1J, AISO2J, AISO3J, ATRP1J, ATRP2J, ASQTJ, AALK1J, AALK2J, APAH1J, APAH2J, APAH3J, AORGCJ, AOLGBJ, AOLGAJ, ALVOO1J, ALVOO2J, ASVOO1J, ASVOO2J, ASVOO3J, APCSOJ, ASOIL, ACORS, ACLK, ASO4K, ANO3K, ANH4K, O3, SO2, NO2, CO, and NH3.</p><p>YYYYMM_CCTM_APMDIAG.zip:</p><p>Air quality file including CCTM_APMDIAG_v3852_YYYYMMDD.nc on each day for September-December 2017, which contains these variables:</p><p>PM25AT, PM25AC and PM25CO.</p><p>YYYYMM_CCTM_PHOTDIAG1.zip:</p><p>Air quality file including CCTM_PHOTDIAG1_v3852_YYYYMMDD.nc on each day for September-December 2017, which contains these variables:</p><p>OZONE_COLUMN, NO2_COLUMN, CO_COLUMN, SO2_COLUMN, HCHO_COLUMN, TROPO_O3_COLUMN and AOD_W550_ANGST.</p>
Simulation results from WRF-CMAQ without aerosol feedbacks in eastern China for September-December 2017
<p>Simulation results from WRF-CMAQ without aerosol feedbacks in eastern China for September-December 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for September-December 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_CCTM_ACONC.zip:</p><p>Air quality file including CCTM_ACONC_v3852_YYYYMMDD.nc on each day for September-December 2017, which contains these variables:</p><p>ASO4I, ANO3I, ANH4I, ANAI, ACLI, AECI, ALVPO1I, ASVPO1I, ASVPO2I, ALVOO1I, ALVOO2I, ASVOO1I, ASVOO2I, AOTHRI, ASO4J, ANO3J, ANH4J, ANAJ, ACLJ, AECJ, AOTHRJ, AFEJ, ASIJ, ATIJ, ACAJ, AMGJ, AMNJ, AALJ, AKJ, ALVPO1J, ASVPO1J, ASVPO2J, AXYL1J, AXYL2J, AXYL3J, ATOL1J, ATOL2J, AXYL2J, AXYL3J, ATOL1J, ABNZ3J, AISO1J, AISO2J, AISO3J, ATRP1J, ATRP2J, ASQTJ, AALK1J, AALK2J, APAH1J, APAH2J, APAH3J, AORGCJ, AOLGBJ, AOLGAJ, ALVOO1J, ALVOO2J, ASVOO1J, ASVOO2J, ASVOO3J, APCSOJ, ASOIL, ACORS, ACLK, ASO4K, ANO3K, ANH4K, O3, SO2, NO2, CO, and NH3.</p><p>YYYYMM_CCTM_APMDIAG.zip:</p><p>Air quality file including CCTM_APMDIAG_v3852_YYYYMMDD.nc on each day for September-December 2017, which contains these variables:</p><p>PM25AT, PM25AC and PM25CO.</p><p>YYYYMM_CCTM_PHOTDIAG1.zip:</p><p>Air quality file including CCTM_PHOTDIAG1_v3852_YYYYMMDD.nc on each day for September-December 2017, which contains these variables:</p><p>OZONE_COLUMN, NO2_COLUMN, CO_COLUMN, SO2_COLUMN, HCHO_COLUMN, TROPO_O3_COLUMN and AOD_W550_ANGST.</p>
Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for October-December 2017
<p>Simulation results from WRF-CHIMERE without aerosol feedbacks in eastern China for October-December 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for October-December 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for October-December 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for October-December 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions in eastern China for October-December 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for October-December 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for October-December 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for October-December 2017
<p>Simulation results from WRF-CHIMERE with enabling aerosol-radiation interactions and aerosol-cloud interactions in eastern China for October-December 2017 including meteorology and air quality:</p><p>YYYYMM_wrfout.zip:</p><p>Meteorological file including wrfout_YYYY-MM-DD_00_00_00 on each day for October-December 2017, which contains these variables:</p><p>T2, Q2, PSFC, U10, V10, RAINC, RAINSH, RAINNC, PBLH, SWDOWN, GLW, SWUPT, LWUPT, CLDFRA, QCLOUD, P, PB, T, VAPOR, PH, PHB</p><p>YYYYMM_out.zip</p><p>Air quality file including out.YYYYMMDD00_24_PHD.nc on each day for October-December 2017, which contains these variables:</p><p>PM25, O3, SO2, NO2, CO and optdaero.</p>
Guided a Research Project titled "Bottle Biospheres: An Innovative Idea to understanding life" which was submitted by Ms. Dakhni Fatima in Pure Sciences. December 12, 2022.
<p>Guided a Research Project titled <strong>“Bottle Biospheres: An Innovative Idea to understanding life” </strong>which was submitted by <strong>Ms. Dakhni Fatima </strong>in <strong>Pure Sciences in Aavishkar. December 12, 2022</strong></p>
SSUSI Images acquired by Ultraviolet Spectrographic Imager aboard DMSP satellite from October to December during 2004-2006
<p>SSUSI is a far ultraviolet scanning imaging spectrometer, which can detect 5 spectral bands of ultraviolet aurora (HI-Lyman α@121.6 nm、 OI@130.4nm、 OI@135.6 nm、 N2-LBHS@140-160 nm and N2-LBHL@160-180 nm) for synchronous scanning imaging observation, its mirror rotates perpendicular to the satellite orbit, and each scan produces an image of 16 ×156pixels. Due to the DMSP satellites need 20-30 minutes to fly over the polar regions, SSUSI can obtain an image covering 1/3 to 1/2 of the auroral oval with a spatial resolution of about 10 × 10 km for each polar flight.In order to reduce the influence of dayglow on SSUSI image data, we only use data from October to December 2004 to 2006 for the study of substorm detection (the aurora oval region in the northern hemisphere during this period is in the polar night region, and the aurora image is weakly affected by dayglow and solar light).<br> The zip file SSUSIdata_mat contains two folders, the plain folder contains the data without the westbound surge structure and the wts folder contains the files with the westbound surge structure.</p>
Permits issued in respect of South Africa's National Environmental Management: Biodiversity Act's Alien and Invasive Species Regulations over the period October 2014–December 2022
<p>Data based on records of permits issued by the South African Department of Forestry, Fisheries, and the Environment (DFFE) to conduct activities on listed invasive species restricted under the NEM:BA A&IS Regulations of 2014<br> This is based on the file <Copy of Official AIS Permit Register (31 Aug 2019).xlsx> with updates to 2020 based on the updates in the file <AIS Permit Register Updated to 21 January 2021.xlsx> and updates to Dec 2022 based on the file <AIS Permit register updated up to 31 Decenber 2022.xlsx><br> Compiled for the purposes of the reporting process "The Status of Biological Invasions and their Management in South Africa", see http://iasreport.sanbi.org.za/ for more details. Can access the latest report on Zenodo http://dx.doi.org/10.5281/zenodo.3947613 and the latest species list associated with the report via http://dx.doi.org/10.5281/zenodo.3947659<br> For details of how this was constructed see the relevant workflow in the status report process.<br> Where appropriate the rationale for issuing a permit is as per the wording of the regulations and lists of 2020 (see below for the full citation)<br> Each row represents a permit for a particular species for a particular activity. Permit numbers can cover multiple taxa<br> The original data-set has details of the applicant and their contact numbers, who the permit was handled by, and the method by and date on which the permit was sent to the permit holder, these have been redacted<br> Note there can be multiple permits issued to the same permit holder for the same species for the same purposes with the same start and end date<br> In cases where two permits were issued to the same applicant and one of which was for research, both were deemed for research even if it was not specified as such</p> <p>For enquiries contact: invasives@sanbi.org.za or IAS.report.SANBI@gmail.com</p> <p>Suggested citation (noting that in most cases it will be more appropriate to reference the Department responsible itself): SANBI (2023) Permits issued in respect of South Africa's National Environmental Management: Biodiversity Act's Alien and Invasive Species Regulations over the period October 2014 – December 2022. version 20230809. Zenodo. https://dx.doi.org/10.5281/zenodo.8229321</p>
Computer Simulation of Viking Voyages: Roar_Ege_December_2015
<p>Contains computer simulated routes of Viking voyages for the Roar Ege, with wind data from December 2015. Divided by Route_Month_Year_RouteNumber_Date_Time.</p>
Computer Simulation of Viking Voyages: Oseberg_December_2021
<p>Contains computer simulated routes of Viking voyages for the Oseberg, with wind data from December 2021. Divided by Route_Month_Year_RouteNumber_Date_Time.</p>
Computer Simulation of Viking Voyages: Oseberg_December_2005
<p>Contains computer simulated routes of Viking voyages for the Oseberg, with wind data from December 2005. Divided by Route_Month_Year_RouteNumber_Date_Time.</p>
Computer Simulation of Viking Voyages: Oseberg_December_1985
<p>Contains computer simulated routes of Viking voyages for the Oseberg, with wind data from December 1985. Divided by Route_Month_Year_RouteNumber_Date_Time.</p>
Computer Simulation of Viking Voyages: Oseberg_December_2015
<p>Contains computer simulated routes of Viking voyages for the Oseberg, with wind data from December 2015. Divided by Route_Month_Year_RouteNumber_Date_Time.</p>
Computer Simulation of Viking Voyages: Oseberg_December_1974
<p>Contains computer simulated routes of Viking voyages for the Oseberg, with wind data from December 1974. Divided by Route_Month_Year_RouteNumber_Date_Time.</p>
Computer Simulation of Viking Voyages: Roar_Ege_December_2005
<p>Contains computer simulated routes of Viking voyages for the Roar Ege, with wind data from December 2005. Divided by Route_Month_Year_RouteNumber_Date_Time.</p>
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
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.