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88 results for “Relative humidity”
Fig. 1 in Effects of relative humidity on the vector of rose rosette disease, Phyllocoptes fructiphilus (Eriophyidae), and incidence of disease symptoms
Fig. 1. Mean (± SE) number of Phyllocoptes fructiphilus under various relative humidity regimes (A) by wk and (B) for the duration of the experiment. The same letters within a wk afer infestation or bars are not significantly different (ANOVA followed by Tukey's HSD test; α = 0.05). Where no differences were observed, no letters are included.
Fig. 2 in Effects of relative humidity on the vector of rose rosette disease, Phyllocoptes fructiphilus (Eriophyidae), and incidence of disease symptoms
Fig. 2. Mean (± SE) (A) proportion of rose rosette disease symptomatic terminals and (B) value of the Horsfall-Barratt scale on the severity of rose rosette disease. The same letters within a wk afer infestation are not significantly different (ANOVA followed by Tukey's HSD test; α = 0.05). Where no differences were observed, no letters are included.
Fig 1 in The effects of relative humidity on Halyomorpha halys (Stål) (Hemiptera: Pentatomidae) egg hatch, nymph survival, and adult reproduction
Fig 1. Mean (± SE) percent egg hatch and nymphal survival of Halyomorpha halys from whole and divided egg clutches exposed to 15% to 90% RH. Means with the same letter are not significantly different (Tukey-Kramer test, P ≤ 0.05).
Fig 2 in The effects of relative humidity on Halyomorpha halys (Stål) (Hemiptera: Pentatomidae) egg hatch, nymph survival, and adult reproduction
Fig 2. Mean survival (± SE) of 6 second instar nymphs to the third, fourth, and fifh instar, and adult stage of Halyomorpha halys exposed to 15% to 90% RH. Means with the same letter are not significantly different (Tukey- Kramer test, P ≤ 0.05).
Air Temperature and Relative Humidity, San Marcos, CA, USA, March 2020 - June 2021
<p>Air temperature and relative humidity collected with MX2201 and MX2301A sensors/loggers (manufactured by Onset Computer Corporation ®) in San Marcos, CA, USA. Time series span March 2020 to June 2021. Support for equipment and data collection was provided by California State University San Marcos. See metadata in files for additional information.</p>
Temperature and Relative Humidity Time Series across 60 forest plots at Sagehen Creek Field Station, 2016-2019
Database contains data downloaded from HOBO loggers placed at 60 sites within the Sagehen Experimental Forest. These plots are a subset of 500+ forest monitoring plots established in 2004 and 2005 for the purpose of testing strategically-placed land area treatments (SPLATS) that impede forest fire progression (Vaillant 2008, UC Berkeley Doctoral Dissertation). HOBO loggers sampled dates between fall 2016 and spring 2019. Some sites have intermittent data due to deactivation for logging activities and some interference from being buried in snow or from wild animals. Please see comments in the plot information file (Logger_Plot_Data.csv) detailing all plot metadata. This monitoring is ongoing through the Sagehen Forest Monitoring Project. Contact the Tahoe National Forest for forest treatment dates, additional information and GIS data.
Murphy Dome: Hourly temperature of air and soil, PAR, relative humidity and soil moisture in three pairs of adjacent black spruce and birch stands 2012-2018
This dataset contains weather station data (air and soil temperature, relative humidity, moisture, and PAR) from 2012 to 2019. The data was collected in three blocks (A, B, and C) of adjacent black spruce and paper birch stands at Murphy Dome (access via Cache Creek road).
The diurnal data of the aerosol extinction coefficient of the Mount Qomolangma lidar, as well as precipitation, low cloud cover, relative humidity of three adjacent stations (Tingri, Lazi, Nyalam) of the Mount Qomolangma
<p><strong>The diurnal data of the the vertical average aerosol extinction coefficient of 0.15-2.5 km of the Mount Qomolangma lidar, as well as precipitation, low cloud cover, relative humidity of three adjacent stations (Tingri, Lazi, Nyalam) of the Mount Qomolangma in July 2018 and July 2019.</strong></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>
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>
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>
Acoustic activity of bats at power lines correlates with relative humidity: A potential role for corona discharges
<p><span>With the ever-increasing dependency on electric power, electrical grid networks are expanding worldwide. Bats exhibit a wide diversity of foraging and flight behaviours, and their sensitivity to anthropogenic stressors suggests this group is very likely to be affected by power lines in a myriad of ways. Yet the effects of power lines on bats remain unknown. Here we assessed the responses of insectivorous bats to very-high-voltage power lines (>220 kV, VHVPL). We implemented a paired sampling design and monitored bats acoustically at 25 pairs, one pair consisting of one forest edge near to VHVPL matched with one control forest edge. Relative humidity mediates the effects of power lines on bats: we detected bat attraction to VHVPL at high relative humidity levels and avoidance of VHVPL by bats at low relative humidity levels. We argue that the former could be explained by insect attraction to the light emitted by VHVPL due to corona discharges while the latter may be due to the physical presence of pylons/cables at foraging height and/or because of electromagnetic fields. Our work highlights the response of bats to power lines at foraging habitats, providing new insight into the interactions between power lines and biodiversity.</span></p>
Great Basin National Park, NV air temperature and relative humidity
<p><span class="TextRun SCXW69589011 BCX0"><span class="NormalTextRun SCXW69589011 BCX0">Hourly air temperature and relative humidity data has been collected </span><span class="NormalTextRun SCXW69589011 BCX0">from a network of</span><span class="NormalTextRun SCXW69589011 BCX0"> 29 </span><span class="NormalTextRun SCXW69589011 BCX0">data-logging sensors </span><span class="NormalTextRun SCXW69589011 BCX0">installed within</span><span class="NormalTextRun SCXW69589011 BCX0"> radiation shields </span><span class="NormalTextRun SCXW69589011 BCX0">~</span><span class="NormalTextRun SCXW69589011 BCX0">1.5 m above ground level</span> <span class="NormalTextRun SCXW69589011 BCX0">at</span><span class="NormalTextRun SCXW69589011 BCX0"> discrete </span><span class="NormalTextRun SCXW69589011 BCX0">sites </span><span class="NormalTextRun SCXW69589011 BCX0">within the Great Basin National Park</span><span class="NormalTextRun SCXW69589011 BCX0"> (GBNP)</span><span class="NormalTextRun SCXW69589011 BCX0">, NV, USA</span><span class="NormalTextRun SCXW69589011 BCX0"> from August 2006 to August 20</span><span class="NormalTextRun SCXW69589011 BCX0">2</span><span class="NormalTextRun SCXW69589011 BCX0">3.</span> <span class="NormalTextRun SCXW69589011 BCX0">The</span><span class="NormalTextRun SCXW69589011 BCX0"> sensors are</span><span class="NormalTextRun SCXW69589011 BCX0"> "embedded</span><span class="NormalTextRun SCXW69589011 BCX0">" –</span><span class="NormalTextRun SCXW69589011 BCX0"> suspended in trees or atop wooden stakes – </span><span class="NormalTextRun SCXW69589011 BCX0">within </span><span class="NormalTextRun SCXW69589011 BCX0">diverse</span><span class="NormalTextRun SCXW69589011 BCX0"> ecosystem</span><span class="NormalTextRun SCXW69589011 BCX0"> types</span><span class="NormalTextRun SCXW69589011 BCX0"> spanning over </span><span class="NormalTextRun AdvancedProofingIssueV2Themed SCXW69589011 BCX0">2,000</span> <span class="NormalTextRun AdvancedProofingIssueV2Themed SCXW69589011 BCX0">m</span><span class="NormalTextRun SCXW69589011 BCX0"> of </span><span class="NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW69589011 BCX0">elevation</span><span class="NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW69589011 BCX0">,</span><span class="NormalTextRun ContextualSpellingAndGrammarErrorV2Themed SCXW69589011 BCX0"> and</span> <span class="NormalTextRun SCXW69589011 BCX0">are </span><span class="NormalTextRun SCXW69589011 BCX0">m</span><span class="NormalTextRun SCXW69589011 BCX0">aintained</span><span class="NormalTextRun SCXW69589011 BCX0">/</span><span class="NormalTextRun SCXW69589011 BCX0">downloaded during</span> <span class="NormalTextRun SCXW69589011 BCX0">annual visitations by </span><span class="NormalTextRun SCXW69589011 BCX0">collaborating </span><span class="NormalTextRun SCXW69589011 BCX0">teams of </span><span class="NormalTextRun SCXW69589011 BCX0">students and staff from </span><span class="NormalTextRun SCXW69589011 BCX0">the Ohio State University</span><span class="NormalTextRun SCXW69589011 BCX0">,</span> <span class="NormalTextRun SCXW69589011 BCX0">University of Georgia, and Sinclair </span><span class="NormalTextRun SCXW69589011 BCX0">Community College, </span><span class="NormalTextRun SCXW69589011 BCX0">a</span><span class="NormalTextRun SCXW69589011 BCX0">ssisted</span> <span class="NormalTextRun SCXW69589011 BCX0">by GBNP</span><span class="NormalTextRun SCXW69589011 BCX0"> staff</span><span class="NormalTextRun SCXW69589011 BCX0">.</span><span class="NormalTextRun SCXW69589011 BCX0"> </span> <span class="NormalTextRun SCXW69589011 BCX0">T</span><span class="NormalTextRun SCXW69589011 BCX0">his dataset can be </span><span class="NormalTextRun SCXW69589011 BCX0">u</span><span class="NormalTextRun SCXW69589011 BCX0">tilized</span> <span class="NormalTextRun SCXW69589011 BCX0">to </span><span class="NormalTextRun SCXW69589011 BCX0">assess the</span> <span class="NormalTextRun SCXW69589011 BCX0">microclimates</span><span class="NormalTextRun SCXW69589011 BCX0"> and weather patterns</span> <span class="NormalTextRun SCXW69589011 BCX0">within the </span><span class="NormalTextRun SCXW69589011 BCX0">GBNP</span><span class="NormalTextRun SCXW69589011 BCX0">.</span> <span class="NormalTextRun SCXW69589011 BCX0">Th</span><span class="NormalTextRun SCXW69589011 BCX0">e</span><span class="NormalTextRun SCXW69589011 BCX0"> dataset </span><span class="NormalTextRun SCXW69589011 BCX0">comprises</span><span class="NormalTextRun SCXW69589011 BCX0"> daily mean, maximum, and minimum </span><span class="NormalTextRun SCXW69589011 BCX0">temperature</span><span class="NormalTextRun SCXW69589011 BCX0"> and relative humidity </span><span class="NormalTextRun SCXW69589011 BCX0">collect</span><span class="NormalTextRun SCXW69589011 BCX0">ed</span><span class="NormalTextRun SCXW69589011 BCX0"> between Aug 2006 – Aug 2023</span><span class="NormalTextRun SCXW69589011 BCX0">.</span><span class="NormalTextRun SCXW69589011 BCX0"> Hourly, raw data </span><span class="NormalTextRun CommentStart ContextualSpellingAndGrammarErrorV2Themed SCXW69589011 BCX0">are</span><span class="NormalTextRun SCXW69589011 BCX0"> available upon request.</span></span><span class="EOP SCXW69589011 BCX0"> </span></p>
Influence of Relative Humidity on the Heterogeneous Oxidation of Secondary Organic Aerosol
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Great Basin National Park, NV air temperature and relative humidity
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High relative humidity and temperature limit disease development and mortality in golden frogs of Panama, Atelopus zeteki, infected with Batrachochytrium dendrobatidis
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Acoustic activity of bats at power lines correlates with relative humidity: A potential role for corona discharges
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Longitudinal assessment of thermal and perceived air quality acceptability in relation to temperature, humidity, and CO2 exposure in Singapore
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Daily mean iButton soil and air temp, air relative humidity:BAC: Biodiversity and Climate
Climate changes forecast for our region by GCM???s and shifts in biodiversity and composition each have the potential to alter ecosystem functioning; their interactive effects are unknown. The "BAC" experiment is designed to determine the direct and interactive effects of plant species numbers, plant community composition, temperature, and precipitation on 11 productivity, C and N dynamics, stability, and plant, microbe, and insect species abundances in CDR grassland ecosystems.
McMurdo Dry Valleys Glacier melt modeling: Relative Humidity 1996-2011
This is the data and metatada for modeled Relative Humidity - part of six modeled parameters that comprise the Taylor Valley Galcier Melt modeling Data contained and described in this document correspond to the physically-based surface energy balance model for the glaciers of Taylor Valley developed by the dataset owners. The spatial variability in ablation (ice melt and sublimation), runoff, and climate sensitivity of the glaciers was modeled using 16 years of meteorological and surface mass balance (the net mass gain or loss of ice on the surface of the glacier) observations collected in Taylor Valley (see figure).  An unusual aspect of the model is the inclusion of transmission of solar radiation into the ice and subsequent drainage of some subsurface melt .  Melt model was applied to the ablation zones of the glaciers of Taylor Valley, identified by colored areas. Mass balance stakes, meteorological stations, and stream gages shown for reference. This dataset package is part of a 6-pack multi-set, which you can find at http://mcmlter.org The input files, parameters and examples are found in this package: http://mcmlter.org/content/glacier-melt-modeling-inputs-and-example-m-fi... Â
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