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396 results for “Humidity”
Data for: Evolution of avian heat tolerance: The role of atmospheric humidity
<p>The role of atmospheric humidity in the evolution of endotherms' thermoregulatory performance remains largely unexplored, despite elevated atmospheric humidity being known to impede evaporative cooling capacity. Using a phylogenetically informed comparative framework, we tested the hypothesis that pronounced hyperthermia tolerance among birds occupying humid lowlands evolved to reduce the impact of humidity-impeded scope for evaporative heat dissipation by comparing heat tolerance limits (HTL; maximum tolerable air temperature), maximum body temperatures (<em>T</em><sub>b</sub><em>max</em>) and associated thermoregulatory variables in humid (19.2 g H<sub>2</sub>O m<sup>− 3</sup>) <em>versus</em> dry (1.1 g H<sub>2</sub>O m<sup>− 3</sup>) air among 30 species from three climatically distinct sites (arid, mesic montane and humid lowland). Humidity-associated decreases in evaporative water loss and resting metabolic rate were 27 - 38% and 21 - 27%, respectively, and did not differ significantly between climatic sites. Decreases in heat tolerance limits were significantly larger among arid-zone (mean ± SD = 3.13 ± 1.12 °C) and montane species (2.44 ± 1.0 °C) compared to lowland species (1.23 ± 1.34 °C), with more pronounced hyperthermia among lowland (<em>T</em><sub>b</sub><em>max</em> = 46.26 ± 0.48°C) and montane birds (<em>T</em><sub>b</sub><em>max</em> = 46.19 ± 0.92°C) compared to arid-zone species (45.23 ± 0.24°C). Our findings reveal a functional link between facultative hyperthermia and humidity-related constraints on evaporative cooling, providing novel insights into how hygric and thermal environments interact to constrain avian performance during hot weather. Moreover, the macrophysiological patterns we report provide further support for the concept of a continuum from thermal specialization to thermal generalization among endotherms, with adaptive variation in body temperature correlated with prevailing climatic conditions.</p>
Empirical data and model simulations of the effect of repeated hurricanes on soil carbon dynamics in a humid tropical forest
<p>Increasing hurricane frequency and intensity with climate change is likely to affect soil organic carbon (C) stocks in tropical forests. We examined the cycling of C between soil pools and with depth at the Luquillo Experimental Forest in Puerto Rico in soils over a 30-year period that spanned repeated hurricanes. We used a non-linear matrix model of soil C pools and fluxes ("soilR") and constrained the parameters with soil and litter survey data. Soil chemistry and stable and radiocarbon isotopes were measured from three soil depths across a topographic gradient in 1988 and 2018. Our results suggest that pulses and subsequent reduction of inputs caused by severe hurricanes in 1989, 1998, and two in 2017 led to faster mean transit times and younger mean ages of soil C in the particulate, occluded, and mineral-associated soil organic matter pools at 0–10 cm and 35–60 cm depths relative to a modeled control soil with constant inputs over the thirty years. Between 1988 and 2018, the occluded C stock increased, and d<sup>13</sup>C in all pools decreased, while changes in particulate and mineral-associated C were undetectable. The differences between 1988 and 2018 suggest that hurricane disturbance results in a dilution of the occluded light C pool with an influx of young, debris-deposited C, and possible microbial scavenging of old and young C in the particulate and mineral-associated pools. These effects led to a younger total soil C pool with faster mean transit times. Our results suggest that increasing frequency of intense hurricanes will speed up rates of C cycling in tropical forests, and eventually lead to net losses of C from tropical forest soils.</p>
Supporting Data for "Climate Sensitivity and Relative Humidity Changes in Global Storm-Resolving Model Simulations of Climate Change"
<p>Code and netcdf files of processed X-SHiELD and CMIP6 simulations to reproduce the figures of Timothy M. Merlis, Kai-Yuan Cheng, Ilai Guendelman, Lucas Harris, Christopher S. Bretherton, Maximilien Bolot, Linjiong Zhou, Alex Kaltenbaugh, Spencer K. Clark, Gabriel A. Vecchi, and Stephan Fueglistaler (2024): "Climate Sensitivity and Relative Humidity Changes in Global Storm-Resolving Model Simulations of Climate Change".</p>
Snow pit dataset from "Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest"
<p>This original dataset contains snow pit measurements collected at Montmorency Forest (47.29°N, 71.17°W) from 22 November, 2018 to 6 June, 2019. The study site is a balsam fir – whit birch stand on a 12° slope of north-east aspect. The dataset is described in the publication “<strong><em>Comparison of snowpack structure in gaps and under the canopy in a humid boreal forest</em></strong>” from Bouchard et al., 2022. In this dataset you can find:</p> <p> </p> <ul> <li>inside forest gaps: <ul> <li>26 snow height measurements (26 data points)</li> <li>26 snowpack stratigraphy (380 data points)</li> <li>26 snow temperature profiles (427 data points)</li> <li>26 snow density profiles (803 data points)</li> <li>2 snow specific surface area (SSA) profiles (97 data points)</li> </ul> </li> </ul> <p> </p> <ul> <li>under the canopy: <ul> <li>26 snow height measurements (26 data points)</li> <li>26 snowpack stratigraphy (227 data points)</li> <li>26 snow temperature profiles (325 data points)</li> <li>26 snow density profiles (623 data points)</li> <li>2 snow SSA profiles (89 data points)</li> </ul> </li> </ul> <p> </p> <p>For density measurements, the height value corresponds to the center of the 3-cm thick box cutter. For the SSA, the value is measured optically at the top of the sample. This value is representative of the top 1 cm of the snow sample, as this is the typical e-folding depth of 1310 nm radiation in snow. Grain type codes for the snowpack stratigraphy corresponds to the <em>International Classification for Seasonal Snow </em>(Fierz et al., 2009):</p> <p> </p> <ul> <li>PP: Precipitation particle</li> <li>DF: Decomposed and Fragmented precipitation particles</li> <li>RG: Rounded Grains</li> <li>FC: Faceted Crystals</li> <li>DH: Depth Hoar</li> <li>MFpc: Melt Forms – rounded polycrystals</li> <li>MFcl: Melt Forms – clustered rounded grains</li> <li>MFcr: Melt Forms – melt-freeze crusts</li> <li>IF: Ice Formations</li> </ul>
HadISDH land: gridded global monthly land surface humidity data version 4.4.0.2021f
<p>HadISDH.land.4.4.0.2021f (Met Office Hadley Centre Integrated Surface Dataset of Humidity) is a near-global gridded monthly mean land surface humidity climate monitoring product created from in situ observations of air temperature and dew point temperature from weather stations. The dataset begins in January 1973. The observations have been quality controlled and homogenised. Uncertainty estimates for observation issues and gridbox sampling are provided.</p> <p>The data are monthly gridded (5 degree by 5 degree) fields. Products are available for temperature and six humidity variables: specific humidity (q), relative humidity (RH), dew point temperature (Td), wet bulb temperature (Tw), vapour pressure (e), dew point depression (DPD).</p> <p>This version extends the 4.3.1.2020f version to the end of 2021 and constitutes a minor update to HadISDH due to changing the climatology period from 1981-2010 to 1991-2020. All other processing steps for HadISDH remain identical. Users are advised to read the update document in the Docs section for full details.</p> <p>As in previous years, the annual scrape of NOAA's Integrated Surface Dataset for HadISD.3.2.0.2021f, which is the basis of HadISDH.land, has pulled through some historical changes to stations. This, and the additional year of data, results in small changes to station selection. The homogeneity adjustments differ slightly due to sensitivity to the addition and loss of stations, historical changes to stations previously included and the additional 12 months of data.</p> <p>To keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.</p> <p>For more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISDH blog: <a href="http://hadisdh.blogspot.co.uk/">http://hadisdh.blogspot.co.uk/</a></p> <p>References:</p> <p>When using the dataset in a paper please cite the following papers (see Docs for link to the publications) and this dataset (using the "citable as" reference):</p> <p>Willett, K. M., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Parker, D. E., Jones, P. D., and Williams Jr., C. N.: HadISDH land surface multi-variable humidity and temperature record for climate monitoring, Clim. Past, 10, 1983-2006, doi:10.5194/cp-10-1983-2014, 2014.</p> <p>Dunn, R. J. H., et al. 2016: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geoscientific Instrumentation, Methods and Data Systems, 5, 473-491.</p> <p>Smith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704-708, doi:10.1175/2011BAMS3015.1</p> <p>We strongly recommend that you read these papers before making use of the data, more detail on the dataset can be found in an earlier publication:</p> <p>Willett, K. M., Williams Jr., C. N., Dunn, R. J. H., Thorne, P. W., Bell, S., de Podesta, M., Jones, P. D., and Parker D. E., 2013: HadISDH: An updated land surface specific humidity product for climate monitoring. Climate of the Past, 9, 657-677, doi:10.5194/cp-9-657-2013.</p>
Sustainable power generation for at least one month from ambient humidity using unique nanofluidic diode
<p>The continuous energy-harvesting in moisture environment is attractive for the development of clean energy source. Controlling the transport of ionized mobile charge in intelligent nanoporous membrane systems is a promising strategy to develop the moisture-enabled electric generator. However, existing designs still suffer from low output power density. Moreover, these devices can only produce short-term (mostly a few seconds or a few hours, rarely for a few days) voltage and current output in the ambient environment. Here, we show an ionic diode–type hybrid membrane capable of continuously generating energy in the ambient environment. The built-in electric field of the nanofluidic diode-type PN junction helps the selective ions separation and the steady-state one-way ion charge transfer. This directional ion migration is further converted to electron transportation at the surface of electrodes via oxidation-reduction reaction and charge adsorption, thus resulting in a continuous voltage and current with high energy conversion efficiency.</p>
Farmers' preference of Indigenous legume fodder trees and shrubs in semi humid condition of southern Ethiopia
<p>the study was conducted to asses the farmers feed value preferance of the indigenous legume fodder tree and shrub species. 21 ILFTS species were identified the farmers preferance score was assesed for all the species. focus group discussion was held to determine the parameters for the preferance score. accordingly five parameters namely feed value, growth rate, biomass yield, compatability and multifuctionality were identified the parameters for prefrance scoring. </p>
Annual indices of heat and humidity, U.S. Army installations, 1990-2018
<p>R data files for annual indices of heat of 25 Continental U.S. (CONUS) U.S. Army installations from 1990-2018 in list and long formats.</p> <p>Annual indices were derived from hourly meteorological estimates from the North American Land Data Assimilation System 2 (NLDAS-2) forcing dataset served as the primary source of weather and atmospheric data. We selected NLDAS grid cells containing the centroid of each installation based on shapefiles from the Department of Defense (DoD) Military Installations, Ranges, and Training Areas (MIRTA) Dataset. We calculated relative humidity from specific humidity, temperature, and atmospheric pressure; heat index (HI) from temperature and relative humidity based on a US National Weather Service algorithm; and outdoor WBGT from air temperature, relative humidity, solar irradiance, barometric pressure, and wind speed using the method of Liljegren <em>et al.</em></p>
Cutaneous Evaporative Water Loss in Lizards is Variable across Body Regions and Plastic in Response to Humidity
<p>Data and code associated with the 2022 publication in Herpetologica (doi:10.1655/Herpetologica-D-21-00030.1).</p>
Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus - data set of indoor temperature and relative humidity
<p>This data supplements the journal article: </p> <p>Buechler E, Pallin S, Boudreaux P, Stockdale M. Probabilistic modeling of the indoor climates of residential buildings using EnergyPlus. <em>Journal of Building Physics</em>. 2017;41(3):225-246. doi:<a href="https://doi.org/10.1177/1744259117701893">10.1177/1744259117701893</a></p> <p>Abstract:</p> <p>The indoor air temperature and relative humidity in residential buildings significantly affect material moisture durability, heating, ventilation, and air-conditioning system performance, and occupant comfort. Therefore, indoor climate data are generally required to define boundary conditions in numerical models that evaluate envelope durability and equipment performance. However, indoor climate data obtained from field studies are influenced by weather, occupant behavior, and internal loads and are generally unrepresentative of the residential building stock. Likewise, whole-building simulation models typically neglect stochastic variables and yield deterministic results that are applicable to only a single home in a specific climate. The purpose of this study was to probabilistically model homes with the simulation engine EnergyPlus to generate indoor climate data that are widely applicable to residential buildings. Monte Carlo methods were used to perform 840,000 simulations on the Oak Ridge National Laboratory supercomputer (Titan) that accounted for stochastic variation in internal loads, air tightness, home size, and thermostat set points. The Effective Moisture Penetration Depth model was used to consider the effects of moisture buffering. The effects of location and building type on indoor climate were analyzed by evaluating six building types and 14 locations across the United States. The average monthly net indoor moisture supply values were calculated for each climate zone, and the distributions of indoor air temperature and relative humidity conditions were compared with ASHRAE 160 and EN 15026 design conditions. The indoor climate data will be incorporated into an online database tool to aid the building community in designing effective heating, ventilation, and air-conditioning systems and moisture durable building envelopes.</p> <p>This supplemental data set includes the hourly temperature and relative humidity for the 10th, 50th, and 90th percentile simulations for each building type in each climate zone. The column headings are of the following format buildingtype_climatezone_output_percentile.</p> <p>There are six building types, B1 (unfinished basement 1-story), B2 (unfinished basement 2-story), C1 (unvented crawlspace 1-story), C2 (unvented crawlspace 2-story), S1 (slab 1-story), and S2 (slab 2-story).</p>
In-vitro gas production kinetics and methane emission potential of selected indigenous legume fodder tree and shrubs in the semi-humid condition of the southern Ethiopia
<p>The data is about the gas production production characteristics and methane emission potential of the selected eleven species of indigenous legume fodder tree and shrubs in the semi-humid condition of the southern Ethiopia. </p>
Data files for analysis of scaling relations between relative and absolute humidity and rainfall extremes
<p>data belonging to: https://github.com/mister-superCC/CCscaling-Evaluation</p> <p>Contains:</p> <p>Dutch observarions in netcdf: KNMI_20201124_hourly.nc</p> <p>Model data as an R object file: DATA_SCALING_PRINCIPLES.tar.gz</p> <p>Processed model and observational data (including SFR) in: data_hourly_bootstrap.tar.gz and data_hourly_bootstrap_abs.tar.gz</p>
Data from DHT22 a sensor humidity and temperature
<p>data from DHT22 a sensor humidity and temperature</p>
Data for manuscript "Mid-Pliocene glaciation preceded by a 0.5-million-year North African humid period"
<p>This repository contains model data accompanying the manuscript:</p> <p>Udara Amarathunga, Eelco J. Rohling, Katharine M. Grant, Alexander Francke, James Latimer, Robert M. Klaebe, David Heslop, Andrew P. Roberts and David K. Hutchinson, 2024: <strong>Mid-Pliocene glaciation preceded by a 0.5-million-year North African humid period</strong>, <em>Nature Geoscience</em>, <a href="https://doi.org/10.1038/s41561-024-01472-8">10.1038/s41561-024-01472-8</a> </p> <p>There are three main folders:</p> <ul> <li><strong>inputs.tgz</strong>: containing input files for each simulation</li> <li><strong>outputs.tgz</strong>: containing model outputs (as shown in the manuscript)</li> <li><strong>restarts.tgz</strong>: containing restart file bundles for the end of each simulation.</li> </ul> <p>There are three experiments, as described in the manuscript. These are labelled:</p> <ul> <li><strong>early_plio:</strong> Early Pliocene (3.312 - 5.3 Myr)</li> <li><strong>plio_glac: </strong>M2 glacial (3.264 - 3.312 Myr)</li> <li><strong>plio_m2: </strong>Mid-Pliocene glacials (3.0 - 3.264 Myr)</li> </ul> <p>The output data are either monthly or annual frequency, as indicated by the filename. 3D ocean outputs are in annual frequency only, while some surface 2D ocean fields are provided at monthly resolution. 3D atmosphere outputs are in monthly frequency.</p> <p><strong>All data are provided in self-describing netcdf format.</strong></p> <p>The model uses GFDL CM2.1, reconfigured with MOM5.1, which is available to download from https://github.com/mom-ocean/MOM5.</p>
Homogenisation of daily temperature and humidity series in the United Kingdom
<p>Data to accompany the publication "Homogenisation of daily temperature and humidity series in the United Kingdom". Building on previous experience with continental and global data sets, we use a quantile-matching approach to homogenise temperature and humidity series measured by a network of 220 stations in the United Kingdom (UK). The data set spans 160 years at daily resolution, although data coverage varies greatly in time, space, and across variables.</p>
El Niño Enhances Exposure to Humid Heat Extremes with Regionally Varying Impacts during Eastern vs Central Pacific Events
<p><span>Humid heat extremes, characterized by high wet bulb temperature (Tw), pose significant health risks. While strong El Niño events are known to affect the frequency of extreme Tw days, the distinct impacts of Central Pacific (CP) and Eastern Pacific (EP) El Niño events remain understudied. Using a 12-member CMIP6 ensemble at discrete global warming targets (+1.5˚C, 2˚C, 3˚C, 4˚C), this study shows progressively enhanced humid heat exposure during EP events primarily in Mainland Southeast Asia, while South Asia experiences regionally opposing effects from EP and CP events. EP and CP events expose distinct, regionally varying areas to dangerous Tw, yet both significantly amplify population and area exposure to humid heat extremes at all global warming levels. This amplification surpasses the impact of an additional degree of global warming, highlighting El Niño’s compounding effect on heat stress threats across warmer climates.</span> <br><a name="_msocom_1"></a></p>
Fig. 8 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences
Fig. 8. Ecological groups of carabids in terms of humidity (number of specimens).
Fig. 6 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences
Fig. 6. Proportions of the species according to the type of preferred habitat.
Fig. 7 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences
Fig. 7. Ecological groups of carabids in terms of humidity (number of species).
Fig. 5 in Ground beetles (Coleoptera: Carabidae) from the region of Cape Emine (Central Bulgarian Black sea coast). Part I. Taxonomic and zoogeographic structure, life forms, habitat and humidity preferences
Fig. 5. Proportions of the species according to their habitat preferendum.
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.