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172 results for “temperature profile”
Sediment profiles of dissolved oxygen and nitrous oxide along with temperature and sediment water content, Rowley River, Rowley, MA
Environmental pulses, or sudden, marked changes to the conditions within an ecosystem, can be important drivers of resource availability in many systems. In this study, we investigated the effect of tidal pulsing on the fluxes of nitrous oxide (N2O), a powerful greenhouse gas, from a marine intertidal mudflat on the north shore of Massachusetts, USA. We found these tidal flat sediments to be a sink of N2O at low tide with an average uptake rate of ??6.7 6 2 lmol??m??2??h??1. Further, this N2O sink increased the longer sediments were tidally exposed. These field measurements, in conjunction with laboratory nutrient additions, revealed that this flux appears to be driven primarily by sediment denitrification. Additionally, N2O uptake was most responsive to dissolved inorganic nitrogen with phosphorus (DINþDIP) addition, suggesting that the N2O consumption process may be P limited. Furthermore, nutrient addition experiments suggest that dissimilatory nitrate reduction to ammonium (DNRA) releases N2O at the highest levels of nitrate fertilization. Our findings indicate that tidal flats are important sinks of N2O, potentially capable of offsetting the release of this potent greenhouse gas by other, nearby ecosystems.
NAUTILOS - Temperature profiles 2012-2020 - Fishing Vessels profiles by AdriFOOS platform - CNR IRBIM
<p>Dataset of depth and temperature profiles obtained from 2012 to 2020 using commercial fishing vessels of the AdriFOOS fleet in the Adriatic Sea</p> <p><span lang="EN-GB">Full metadata: </span><a title="https://data-nautilos-h2020.eu/erddap/info/AdriFOOS_profiles_2012-2020/index.html" href="https://data-nautilos-h2020.eu/erddap/info/AdriFOOS_profiles_2012-2020/index.html" target="_blank" rel="noopener"><span lang="EN-GB">https://data-nautilos-h2020.eu/erddap/info/AdriFOOS_profiles_2012-2020/index.html</span></a></p> <p><span lang="EN-GB">This dataset is part of the NAUTILOS project outcomes. NAUTILOS is funded from the European Union's Horizon 2020 research and innovation programme under grant agreement No. 101000825.</span></p>
Data archive for: Exploring the use of machine learning to improve vertical profiles of temperature and moisture
<p>Vertical profiles of temperature and dewpoint are useful in predicting deep convection that leads to severe weather that threatens property and lives. Currently, forecasters rely on observations from radiosonde launches and numerical weather prediction (NWP) models. Radiosonde observations are, however, temporally and spatially sparse, and NWP models contain inherent errors that influence short-term predictions of high-impact events. This work explores using machine learning (ML) to postprocess NWP model forecasts, combining them with satellite data to improve vertical profiles of temperature and dewpoint. We focus on different ML architectures, loss functions, and input features to optimize predictions. Because we are predicting vertical profiles at 256 levels in the atmosphere, this work provides a unique perspective at using ML for 1-D tasks. Compared to baseline profiles from the Rapid Refresh (RAP), ML predictions offer the largest improvement for dewpoint, particularly in the mid- and upper-atmosphere. emperature improvements are modest, but CAPE values are improved by up to 40%. Feature importance analyses indicate that the ML models are primarily improving incoming RAP biases. While additional model and satellite data offer some improvement to the predictions, architecture choice is more important than feature selection in fine-tuning the results. Our proposed deep residual UNet performs the best by leveraging spatial context from the input RAP profiles; however, the results are remarkably robust across model architecture. Further, uncertainty estimates for every level are well-calibrated and can provide useful information to forecasters.</p>
The temperature profile on a silicon-patterned membrane - Fig.3 Dataset
<p>This is the data set used to generate Fig.3 in the paper https://doi.org/10.1103/PRXQuantum.4.040314</p>
Aerosol, Temperature and Water Vapor profiling during the BIOSPHERE Athens Campaign - NTUA - Level 3 - June 2023
<p>June 2023 - Level 3 of the lidar data obtained by the EOLE and DEPOLE lidar systems in the National Technical University of Athens (NTUA), during the EURAMET European Partnership on Metrology (EPM) project BIOSPHERE.</p>
Aerosol, Temperature and Water Vapor profiling during the BIOSPHERE Athens Campaign - NTUA - Level 3 - July 2023
<p>July 2023 - Level 3 of the lidar data obtained by the EOLE and DEPOLE lidar systems in the National Technical University of Athens (NTUA), during the EURAMET European Partnership on Metrology (EPM) project BIOSPHERE.</p>
Aerosol, Temperature and Water Vapor profiling during the BIOSPHERE Athens Campaign - NTUA - Level 3 - August 2023
<p>August 2023 - Level 3 of the lidar data obtained by the EOLE and DEPOLE lidar systems in the National Technical University of Athens (NTUA), during the EURAMET European Partnership on Metrology (EPM) project BIOSPHERE.</p>
Coded data and R scripts for the article-Toward a dynamic behavioral profile of the Mandarin Chinese temperature term re
<p>These are the coded dataset and R scripts for the article "Towards a dynamic behavioral profile of Mandarin Chinese temperature term re: A diachronic semasiological approach".</p>
Measurements of water levels and water temperature profiles in Lake Kinneret, in summer, during the period (2000 – 2020)
<p><em>The datasets include measurements of water levels and water temperature profiles in Lake Kinneret, in summer, during the period (2000 – 2020). </em><em>Lake Kinneret is located in Israel. </em>Shipboard measurements of water temperature profiles were taken at the deepest point of ~40 m near the lake center (32.82 N; 35.60 E). The <em>AML MINOS X probe was used (specifications are available online at <a href="https://geo-matching.com/ctd-systems/minos-x-ctd/svp">https://geo-matching.com/ctd-systems/minos-x-ctd/svp</a>). </em><em>Data of water temperature profiles are associated with the Kinneret Limnological Laboratory, Israel Oceanographic and Limnological Research (</em><a href="http://kinneret.ocean.org.il/ar_3d_vb.aspx"><em>http://kinneret.ocean.org.il/ar_3d_vb.aspx</em></a><em> ). Data of Lake Kinneret water levels are associated with the Israel Water and Sewage Authority (</em><a href="https://www.gov.il/en/departments/water_authority/govil-landing-page">https://www.gov.il/en/departments/water_authority/govil-landing-page</a><em> ). Data format: xlsx file. </em>There are two sheets in the Excel file: the first sheet includes water temperature profiles, while the second sheet includes lake water levels, in summer, during the period (2000 – 2020). </p>
Respirometry protocols for avian thermoregulation at high air temperatures: stepped and steady-state profiles yield similar results
<p>Relationships between air temperature (Tair) and avian body temperature (Tb), resting metabolic rate (RMR) and evaporative water loss (EWL) during acute heat exposure can be quantified through respirometry using several approaches. One involves birds exposed to a stepped series of progressively increasing Tair setpoints for short periods (< 20-30 min), whereas a second seeks to achieve steady-state conditions by exposing birds to a single Tair for longer periods (> 1-2 h). To compare these two approaches, we measured Tb, RMR and EWL over Tair = 28 C to 44 C in the dark-capped bulbul (Pycnonotus tricolor). The two protocols yielded indistinguishable values of Tb, RMR and EWL and related variables at most Tair values, revealing that both are appropriate for quantifying avian thermal physiology during heat exposure over the range of Tair in the present study. The stepped protocol, however, has several ethical and practical advantages. </p>
IAA/CSIC Temperature and CO2 density profiles in Mars Year 34 retrieved from the 1st year of NOMAD/TGO solar occultation observations [dataset]
<p>Dataset associated to manuscript 2022JE007278, "Martian atmospheric temperature and density profiles during the 1st year of NOMAD/TGO solar occultation measurements", submitted on Feb 28th, 2022, to Journal of Geophysical Research - Planets (AGU) for the Special Issue "ExoMars Trace Gas Orbiter: One Martian Year of Science".</p> <p>Format and Number of datafiles: 1 README.txt and 1 tar file containing 325 ASCII files, one for each retrieved NOMAD scan. Each of these files contains one vertical profile of 7 parameters: altitude (km), Temperature in the last iteration (K), atmospheric pressure (mb), Temperature of First Guess (K), pressure of First Guess (mb), Temperature retrieval error (K) and diagonal element fo the Averaging Kernel matrix at that tangent altitude (normalized to 0-1). Also, the header of each file contains extra info, like the NOMAD "internal" data filename, and the ranges in latitude, longitude, Local time, Solar Longitude, tangent heights observed, and Line-of-Sight shift needed to obtain a good fit, together with the number of altitudes in the retrieval vector (usually around 100 km). See README file for more details.<br> </p>
Hovmöller diagram of ARGO subsurface temperature anomalies with histograms of daily profile data count
<p>Hovmöller diagram of ARGO subsurface temperature anomalies with histograms of daily profile data count over two different zones in the pacific ocean. The anomalies were computed from GODAS reanalysis over a 1981-2010 climatology .</p>
Vertical temperature profiles obtained from Venus Express and Akatsuki radio occultation data using FSI
<p>Vertical temperature profiles of Venusian atmosphere obtained from selected radio occultation data taken in ESA's Venus Express and JAXA's Akatsuki missions. The temperatures were retrieved using a radio holographic method, Full Spectrum Inversion (FSI). The data list and format are given in two Excel files and the data are given in text files with an extension ".dat".</p>
Monthly average profiles of Distributed Temperature Sensing at Thwaites Eastern Ice Shelf
<p>Monthly average profiles of Distributed Temperature Sensing (DTS) for Thwaites Eastern Ice Shelf used in Dotto et al. (under review). The profiles are from April 2020, September 2020 and February 2021 and cover the ice-shelf-ocean interface depths. DTS utilizes a fibre-optic cable installed within the ice and through the ocean, and it uses Raman backscattered photons to estimate the in situ temperature of the fiber (Hausner et al 2011). The DTS interrogators (Silixa XT-DTS, Silixa LLC. Elstree, UK) used a spatial sampling of 25 cm. Each DTS profile uses a 1-minute integration time to reduce signal to noise. Independent temperature measurements from the MicroCATs are employed to calibrate the backscatter signal (Tyler et al., 2013; Hausner et al 2011).</p> <p> </p> <p>Hausner, M. B., Suárez, F., Glander, K. E., van de Giesen, N., Selker, J. S. & Tyler, S. W. Calibrating single-ended fiber-optic Raman spectra distributed temperature sensing data. Sensors (Basel), 11(11), 10,859–10,879 (2011).</p> <p>Tyler, S. W., Holland, D. M., Zagorodnov, V., Stern, A. A., Sladek, C., Kobs, S., White, S., Suárez, F. & Bryenton, J. Using distributed temperature sensors to monitor an Antarctic ice shelf and sub-ice-shelf cavity. Journal of Glaciology, 59(215), 583–591 (2013).</p> <p>Dotto, T. S., Heywood, K., Hall, R. et al. Ocean variability beneath Thwaites Eastern Ice Shelf driven by the Pine Island Bay Gyre strength, 11 October 2022, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-1466534/v1]</p>
Asphalt profile temperatures and weather data of CyPaTs test track
<p>This dataset includes asphalt temperature measurements and weather data of CyPaTs test track located at Campus Groenenborger, University of Antwerp, Antwerp, Belgium. The recorded asphalt temperature measurements and weather data is between March 17<sup>th</sup>, 2021, and March 14<sup>th</sup>, 2022. There are five sheets in each excel file, containing asphalt temperatures at various depths (near-surface, 4cm, 7cm and 10 below asphalt surface), and corresponding weather data. The total number of data points is 371707, with each of these data points including information on weather parameters and 45 sensors embedded in different layers of the asphalt pavement.</p> <ol> <li>Date (time): time of the recorded data</li> <li>TC_x-x: label of the temperature sensor embedded in asphalt pavement, in °C</li> <li>Ta: ambient air temperature, in °C</li> <li>RH: relative humidity, in %</li> <li>FF: wind speed, in m/s</li> <li>SR: solar radiation, in W/m<sup>2</sup></li> </ol>
Aerosol, Temperature and Water Vapor profiling during the BIOSPHERE Athens Campaign (June-August 2023) - NTUA
<p>Level 2 of the lidar data obtained by the EOLE and DEPOLE lidar systems in the National Technical University of Athens (NTUA), during the EURAMET European Partnership on Metrology (EPM) project BIOSPHERE (June - August 2023). </p>
Temperature Profiles During Laser Activation in Ureteroscopic Lithotripsy
ClinicalTrials.gov study NCT05677425. IPD Sharing: NO. Countries: 1. Publications: 1.
Respirometry protocols for avian thermoregulation at high air temperatures: stepped and steady-state profiles yield similar results
Open the record for dataset details and reuse information.
Data archive for: Exploring the use of machine learning to improve vertical profiles of temperature and moisture
Open the record for dataset details and reuse information.
Data from: Mild temperatures differentiate while extreme temperatures unify gene expression profiles among populations of Dicosmoecus gilvipes in California
Open the record for dataset details and reuse information.
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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)
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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.