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40 results for “Diurnal cycle”
Diurnal cycle of the semi-direct effect from a persistent absorbing aerosol layer over marine stratocumulus in large-eddy simulations: supporting dataset
<p>Relevant data for reproducing figures and tables from Herbert et al., 2020, Atmospheric Chemistry and Physics: "Diurnal cycle of the semi-direct effect from a persistent absorbing aerosol layer over marine stratocumulus in large-eddy simulations".</p> <p>The tar file contains the relevant netcdf files that contain simulation output from the MET Office large eddy model (LEM). Each netcdf file corresponds to a single model setup and experiment - details of which can be found within the published manuscript. Information concerning the LEM, and details on how to obtain access to the code, can be found at http://appconv.metoffice.com/LEM/index.html.</p> <p>The file 'relevant_information.pdf' contains two tables. The first provides the names of each netcdf file that was used to produce each figure in the manuscript. The second provides the metadata for the netcdf variables that were used to produce the figures and tables.</p> <p>The netcdf filename provides information on the experiment setup as follows:</p> <p>run-identifier-number _ length-of-run _ AOD-of-layer _ GAP-between-cloud-and-layer _ THICKNESS-of-layer _ 'bigarray' _ special-setups-for-sensitivity-experiments</p> <p>For example, r1360_8day_transient_aod02_0dz_250th_bigarray_nodrizz is run number r1360, simulating 8 days, with the aerosol layer properties AOD=0.2, cloud-to-aerosol gap of 0m, layer thickness of 250m, in the sensitivity setup where precipitation has been switched off.</p>
CFS model monthly mean diurnal cycles of ocean and atmosphere variables at TAO mooring locations
<p>v0.1.3</p> <p>cfsm501_ocn_2002_2006_TAOpoints_hourly.tgz -- contains netCDF files of hourly ocean variables: one ocean file per month over 4 years (2002-2006).</p> <p>Each file contains water temperature with dimensions (time, depth, lat, lon) at TAO locations. If joining multiple files together, concatenate along the time axis.</p> <p>-------------------------</p> <p>v0.1.2</p> <p>cfsm501_atmo_2002_2006_TAOpoints_3D_monthlyMeanDiurnalCycle.tgz -- contains netCDF files of monthly mean diurnal cycle of atmosphere variables: one atmosphere file per month over 4 years (2002-2006).</p> <p>Each file contains multiple variables with dimensions (time, hour, plev, lat, lon) at TAO locations. The dimension "time" is of length 1 in all files. If joining multiple files together, concatenate along the time axis. The "hour" dimension represents the 24 hours of the diurnal cycle.</p> <p>Note that this version of the data has NOT had the 3-day high pass filter applied before the diurnal cycle calculation.</p> <p>-------------------------</p> <p>v0.1.1</p> <p>cfsm501_atmo_2002_2006_TAOpoints_hourly.tgz -- contains netCDF files of hourly atmosphere variables: one atmosphere file per month over 4 years (2002-2006).</p> <p>Each file contains multiple variables with dimensions (time, lat, lon) at TAO locations. If joining multiple files together, concatenate along the time axis.</p> <p>-------------------------</p> <p>v 0.1.0</p> <p>cfsm501_atmo_ocn_2002_2006_TAOpoints_monthlyMeanDiurnalCycle.tgz -- contains netCDF files of monthly mean diurnal cycle of ocean and atmosphere variables: one atmosphere and one ocean file per month over 4 years (2002-2006).</p> <p>Each file contains multiple variables with dimensions (time, hour, [depth,] lat, lon) at TAO locations. The dimension "time" is of length 1 in all files. If joining multiple files together, concatenate along the time axis. The "hour" dimension represents the 24 hours of the diurnal cycle.</p> <p>Note that this version of the data has NOT had the 3-day high pass filter applied before the diurnal cycle calculation.</p>
Dataset for "Diurnal, seasonal, and interannual variations in δ(18O) of atmospheric O2 and its application to evaluate natural/anthropogenic changes in oxygen, carbon, and water cycles" by Ishidoya et al.
<p>The dataset used in the paper "Diurnal, seasonal, and interannual variations in δ(18O) of atmospheric O2 and its application to evaluate natural/anthropogenic changes in oxygen, carbon, and water cycles" by Ishidoya et al. The doi of the preprint of the paper is https://doi.org/10.5194/egusphere-2024-654. The dataset contains the diurnal cycles of delta_atm(18O), delta(O2/N2), y(CO2), and delta(Ar/N2) at Tsukuba, Japan averaged for the period 2013-2022 ("data_for_Fig4.csv"), the rolling average values of delta_atm(18O) and delta(O2/N2) anomalies for 300 data at TKB during August and February, 2017 ("data_for_Fig6.csv"), and the monthly mean values of delta_atm(18O) and the delta(O2/N2) at TKB for the period 2013-2022("data_for_Fig7.csv"). The raw data before averaging are also presented ("raw_data_2013.csv" to "raw_data_2022.csv"). See text of Ishidoya et al. in more details. </p> <p> </p>
Assessment of the sea surface temperature diurnal cycle in CNRM-CM6-1 based on its 1D coupled configuration - model outputs
<p>These tar file are associated with an article submitted to Geoscientific Model Development under identification number gmd-2021-413 (https://www.geoscientific-model-development.net): Assessment of the sea surface temperature diurnal cycle in CNRM-CM6-1 based on its 1D coupled configuration<br> By A. Voldoire, R. Roehrig, H. Giordani, R. Waldman, Y. Zhang, S. Xie, MN Bouin</p> <p>3 files correspond to code components that can be distributed freely</p> <p>- surfex.tgz for the surfex v8.0 distributed under a Cecill-C License</p> <p>- oasis-mct-3.0.tgz for oasis-mct3.0 distributed under a GNU General Public License</p> <p>- nemo_v3.6.tgz for the nemo, distibuted under a Cecill-C License</p> <p>These three components are mainly fortran codes.</p> <p>The last file "<a href="https://zenodo.org/api/files/e94922e7-22eb-445b-acc3-03e11ca1af6b/CNRM-CM6-1D_published_experiments.tgz?versionId=2460ec63-89f5-415f-9613-1954f048b238">CNRM-CM6-1D_published_experiments.tgz </a>" contains all model outputs that have been used in this article. These model outputs are in netcdf format and organized by experiment.</p>
Key habitat for male Strix nebulosa (Great Gray Owls) varies across the diurnal cycle and reflects sex-specific role, data archive
<p>We used GPS tracking and remotely-sensed environmental data to evaluate whether breeding-season habitat selection by adult male <em>Strix nebulosa </em>(Great Gray Owls) (n = 19) varied across diurnal periods (dawn, day, dusk, and night). To address knowledge gaps related to nocturnal habitat, we also evaluated finer-scale, microhabitat selection by male owls at night. Here, we include both the remotely-sensed habitat data and on-the-ground microhabitat data associated with owl locations. Generally, <em>S. nebulosa </em>are associated with mature forests for nesting and meadows for foraging. Yet, in our study, owls avoided herbaceous wetlands during the day but strongly selected them at dawn, dusk, and at night, indicating context-dependent habitat selection. Moreover, owls avoided dry meadows at all times of the day, suggesting that wet rather than xeric meadows are important for foraging. Owls also preferred nighttime microhabitats that facilitated foraging, such as those with presence of primary prey and open understories dominated by graminoids and forbs. During the daytime, owls preferred higher canopy cover and areas with increased soil moisture, which likely provided suitable roosting habitat. Understanding of habitat preferences across sexes, activity periods, and other contexts can improve the identification and conservation of critical habitat for wildlife.</p>
The Diurnal Cycle of Integrated Kinetic Energy and Wind Radii in a Simulated Tropical Cyclone
<p>Model source code and output of a 340-day-long Cloud Model 1 simulation of a tropical cyclone and associated post-processing scripts.</p>
Codes and datasets associated with the paper "Dynamic LES modeling of a diurnal cycle"
<p>Here, you will find some of the codes, images, and datasets utilized in the article: </p> <p>Basu et al. (2008). "Dynamic LES modeling of a diurnal cycle", Journal of Applied Meteorology and Climatology, 47, 1156-1174. (<a href="https://journals.ametsoc.org/doi/pdf/10.1175/2007JAMC1677.1">https://journals.ametsoc.org/doi/pdf/10.1175/2007JAMC1677.1</a>)</p> <p>Matlab codes: MatlabCodes.tar.gz (Contains all the analyses and visualization codes used in the paper)</p> <p>Observational data: Wangara_Observations.tar.gz (These data were manually typed directly from the original Wangara document)</p> <p>LES data (binary): LES_160x160x160.tar.gz and LES_80x80x80.tar.gz</p>
Roles of Forests in Moderating the Diurnal Cycle of Land-Atmosphere Interactions
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Metabolic responses of two pioneer wood decay fungi to diurnally cycling temperature
<p>This dataset contains pre-processed untargeted GC-MS metabolomics and direct shotgun proteomics from a microcosm woodblock experiment described in the paper "Rawlings et al (2021) Metabolic responses of two pioneer wood decay fungi to diurnally cycling temperature. Ecology."</p> <p>The experiment investigates the effect of diurnal cycling of temperature on the metabolism of two wood decay species, <em>Mucidula mucida</em> and <em>Exidia glandulosa</em>. We colonised beech woodblocks with the two species (separate microcosms) and exposed them to either a diurnally cycling (mean 15 ± 10°C) or constant (15°C) temperature, in a fully factorial design. After 8 weeks we extracted the full complement of metabolites and proteins in the wood to examine the extent to which the abundances of metabolic products were altered.</p> <p>The main results of the experiment were that products linked to lignin breakdown, the citric acid cycle, pentose phosphate pathway, carbohydrate metabolism, fatty acid metabolism and protein biosynthesis and turnover were under-enriched in fluctuating, compared to stable temperatures, in the generalist <i>M. mucida</i>. Conversely <i>E. glandulosa</i> showed little differential response to the experimental treatments which may be linked with its preference for habitats exhibiting abiotic stress. </p>
Supporting data for Optimal closed-loop wake steering, Part 2: Diurnal cycle atmospheric boundary layer conditions
<p>Supporting data for "Optimal closed-loop wake steering, Part 2: Diurnal cycle atmospheric boundary layer conditions" by Michael F. Howland, Aditya S. Ghate, Jesús Bas Quesada, Juan José Pena Martínez, Wei Zhong, Felipe Palou Larrañaga, Sanjiva K. Lele, and John O. Dabiri</p> <p>See README for data description.</p> <p>The code is available at: https://github.com/FPAL-Stanford-University/PadeOps</p>
Understanding the diurnal cycle of midlatitude sporadic E. The role of metal atoms.
<p>We provide the Arecibo dataset and the FORTRAN program used to produce Figure 4, of the paper (MS# 2023JA031336) enitled "Understanding the diurnal variation of midlatitude sporadic E. The role of metal atoms- ", which was submitted for publication in the Journal of Geophysical Research - Space Physics, January 2023.Write to Christos Haldoupis</p> <p> </p>
Understanding the diurnal cycle of midlatitude sporadic E. The role of metal atoms
<p>We provide the Arecibo dataset and the FORTRAN program used to produce Figure 4, of the paper (MS# 2023JA031336) entitled "Understanding the diurnal variation of midlatitude sporadic E. The role of metal atoms- ", which was submitted for publication in the Journal of Geophysical Research - Space Physics.</p>
Understanding the diurnal cycle of midlatitude sporadic E. The role of metal atoms
<p>We provide the Arecibo dataset and the FORTRAN program used to produce Figure 4, of the paper (MS# 2023JA031336) entitled "Understanding the diurnal variation of midlatitude sporadic E. The role of metal atoms- ", which was submitted for publication in the Journal of Geophysical Research - Space Physics.</p>
Understanding the diurnal cycle of midlatitude sporadic E. The role of metal atoms.
<p>Dataset and FORTRAN program used to produce Figure 4, of the paper (MS# 2023JA031336) entitled "Understanding the diurnal variation of midlatitude sporadic E. The role of metal atoms- ", which was submitted for publication in the Journal of Geophysical Research - Space Physics. The data file was provided by Qihou Zhou of Miami University in Ohio and the program by co-author Chris Meek, University of Saskatchewan.</p>
Data from: Seasonal temperature, the lunar cycle and diurnal rhythms interact in a combinatorial manner to modulate genomic responses to the environment in a reef-building coral
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Metabolic responses of two pioneer wood decay fungi to diurnally cycling temperature
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The diurnal cycle of the horizontal wind field over complex terrain detected with coplanar Doppler lidar scans
<p>This data set contains a 24-h movie (21:00 UTC 23 July to 21:00 UTC 24 July) of the horizontal wind field in a horizontal plane of about 5 km x 5 km in size about 62 m above the city of Stuttgart in south-western Germany. The horizontal wind fields are retrieved from coplanar horizontal scans from three Doppler lidars positioned on opposing slopes and are available with 1-min temporal resolution and 100 m horizontal resolution. The data shows the diurnal cycle of the horizontal wind. During nighttime, downvalley wind establishes in the Neckar Valley and during daytime convective cells moving downstream are visible.<br> The measurements were conducted within the the framework of the Urban Climate under Change [UC]^2 program.</p>
Multisensor Advanced Climatology Mean Liquid Water Path Diurnal Cycle L3 Monthly 1 degree x 1 degree V1 (MACLWP_diurnal) at GES DISC
The Multi-Sensor Advanced Climatology of Liquid Water Path (MAC-LWP) data set contains monthly 1.0-degree ocean-only estimates of cloud liquid water path (MACLWP_mean), total water path (MACTWP_mean) which includes both cloud and rain water, and monthly climatologies of cloud liquid water path diurnal cycle amplitudes and phases (MACLWP_diurnal). The MACTWP_mean field can also be used as a quality-control screen for the MACLWP_mean field as discussed in Elsaesser et al. (2017), where uncertainty increases as the ratio of cloud to total water path increases. The MAC-LWP algorithm uses as input the Remote Sensing Systems (RSS) Version 7 0.25 degree-resolution retrieval products (produced using the SSM/I, AMSR-E, TMI, AMSR-2, GMI, SSMIS, and WindSat satellite sensors), and performs a bias correction on all input RSS cloud water path products based on AMSR-E matchups to clear-sky MODIS scenes. The MAC-LWP algorithm ensures that spurious trends and variability in the cloud fields arising from drifting satellite overpass times are mitigated by simultaneously solving for the monthly average cloud and total water paths and monthly-mean diurnal cycles, as discussed in O’Dell et al. (2008). Additional details on the algorithm and data fields can be found in Elsaesser et al. (2017).
Transcriptomics analysis of the Chlamydomonas reinhardtii diurnal cycle.
GEO Series GSE112394. Chlamydomonas reinhardtii. 16 samples. Type: Expression profiling by high throughput sequencing.
Regulatory logic of the coupled diurnal and feeding cycles in the mouse liver
GEO Series GSE60578. Mus musculus. 59 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by array.
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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.