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59 results for “Atmospheric effects”
Model Simulations of The Effects of Shifts in High-frequency Weather Variability (No Long-term Weather Trend) Control Carbon Loss from Land to the Atmosphere, Toolik Lake, Alaska, 2022-2122
Climate change is increasing extreme weather events, but effects on high-frequency weather variability and the resultant impacts on ecosystem function are poorly understood. We assessed ecosystem responses of arctic tundra to changes in day-to-day weather variability using a biogeochemical model and stochastic simulations of daily temperature, precipitation, and light. Changes in weather variability altered ecosystem carbon, nitrogen, and phosphorus stocks and cycling rates. Some responses of processes (e.g., respiration) were inconsistent with expectations, indicating that whole-ecosystem interactions and feedbacks moderate or even reverse responses to weather variability. More weather variability led to greater carbon losses from land to atmosphere, and less variability led to higher carbon sequestration on land. The magnitude of response to weather variability was similar to that predicted from climate mean trend effects. This dataset consists of the MEL parameter file, driver files and output files for simulations without a long term weather trend.
Model Simulations of The Effects of Shifts in High-frequency Weather Variability (With a Long-term Trend) on Carbon Loss from Land to the Atmosphere, Toolik Lake, Alaska, 2022-2122
Climate change is increasing extreme weather events, but effects on high-frequency weather variability and the resultant impacts on ecosystem function are poorly understood. We assessed ecosystem responses of arctic tundra to changes in day-to-day weather variability using a biogeochemical model and stochastic simulations of daily temperature, precipitation, and light. Changes in weather variability altered ecosystem carbon, nitrogen, and phosphorus stocks and cycling rates. Some responses of processes (e.g., respiration) were inconsistent with expectations, indicating that whole-ecosystem interactions and feedbacks moderate or even reverse responses to weather variability. More weather variability led to greater carbon losses from land to atmosphere, and less variability led to higher carbon sequestration on land. The magnitude of response to weather variability was similar to that predicted from climate mean trend effects. This dataset consists of the MEL parameter file, driver files and output files for simulations with a long-term weather trend.
Data for: Ring Current Electron Precipitation During the 17 March 2013 Geomagnetic Storm: Underlying Mechanisms and Their Effect on the Atmosphere
<p>All data are included as MATLAB figure files, png files and MATLAB MAT files.</p><p>File precipitated_flux.mat contains a 4-D array of values of precipitated electron flux in [1/(s cm^2 keV)] for 289 time points from 16 March 2013 to 19 March 2013, with a 15 min time step; 100 values of energy in a range from 10 keV to 1 MeV, with a 10 keV step; on a spatial grid of 28 by 49 (P, R).</p><p>netCDF data can be opened with a variety of software tools, including Matlab, Origin or Python.</p>
Atmospheric Effects on Neutron Star Parameter Constraints with NICER
<p>Posterior sample files associated with the publication "Atmospheric Effects on Neutron Star Parameter Constraints with NICER" by Salmi et al. (2023; <a href="https://doi.org/10.48550/arXiv.2308.09319">arXiv:2308.09319</a>; <a href="https://doi.org/10.3847/1538-4357/acf49d">https://doi.org/10.3847/1538-4357/acf49d</a>).</p><p>Also included are: the data products; the numeric model files including the telescope calibration products; model modules in the Python language using the X-PSI framework; and Jupyter analysis notebooks.</p><p>Please refer to the README for detailed information.</p>
On effective spectral wideband models for clear sky atmospheric emissivity and transmissivity
<p><strong>Overview</strong></p> <p>The HDF5 file contains primary measurement data and secondary processing data that was used to assess clear sky effective emissivity and transmissivity estimates and generate the results in the associated manuscript (accepted and forthcoming).</p> <p>Data is indexed by solar time and provided per site for years 2010 through 2015. Sample Python code is provided to reconstruct training and validation sets by concatenating all 'tra' or 'val' samples across sites. Results can be explored by modifying choice of filters and constructing new training and validation sets.</p> <p><strong>Data usage</strong></p> <p>The usage of the data presented here is intended for research and development purposes only and implies explicit reference to the paper:<br><em>Matsunobu, L. M., & Coimbra, C. F. M. (2024). On effective spectral wideband models for clear sky atmospheric emissivity and transmissivity. Journal of Geophysical Research: Atmospheres, 129, e2023JD039798. https://doi.org/10.1029/2023JD039798</em></p> <p><strong>Data description</strong></p> <p>Column names and descriptions are as follows:<br>- dlw_m: measured downwelling longwave [W/m^2]<br>- ghi_m: measured global horizontal irradiance [W/m^2]<br>- dni_m: measured direct normal irradiance [W/m^2]<br>- dhi_m: measured diffuse horizontal irradiance [W/m^2]<br>- rh_m: measured relative humidity [%]<br>- pa_m: measured atmospheric pressure [hPa]<br>- t_m: measured temperature [K]<br>- sza: solar zenith angle [deg]<br>- ghi_c: clear sky global horizontal irradiance [W/m^2]<br>- dni_c: clear sky direct normal irradiance [W/m^2]<br>- dhi_c: clear sky diffuse horizontal irradiance [W/m^2]<br>- cs1: clear sky filter 1<br>- cs2: clear sky filter 2<br>- site_elev: station elevation [m]<br>- clr_pct: fraction of samples identified as clear for the given site and day<br>- clr_num: number of samples identified as clear for the given site and day<br>- pw_hpa: water vapor partial pressure [hPa]<br>- alt_correction: altitude correction<br>- tra: indicate if sample is included in training set<br>- val: indicate if sample is included in validation set<br>- sqrt_pw: square root of non-dimensional water vapor partial pressure<br>- e_sky: effective clear sky emissivity</p> <p>The last two columns, 'sqrt_pw' and 'e_sky' represent the input and target for linear regression, i.e. e_sky = c_1 + (c_2 * sqrt_pw).<br>Altitude corrected sky emissivity, or expected emissivity for a station at sea-level, is found by e_sky - alt_correction.</p> <p><strong>Sample code (Python v3.8)</strong></p> <pre>import pandas as pd site = "GWC" # or other station code df = pd.read_hdf("data.h5", key=site) # import single site</pre> <p>Training and validation sets can be reconstructed as below. Linear regression on 'sqrt_pw' to predict 'e_sky' - 'alt_correction' in the resultant training set will reproduce results in the associated manuscript.</p> <pre>training = [] validation = [] surfrad_sites = ['BON', 'DRA', 'FPK', 'GWC', 'PSU', 'SXF', 'TBL'] for site in surfrad_sites: # loop through sites df = pd.read_hdf("data.h5", key=site) df["site"] = site # add site name training.append(df.loc[df.tra]) # append samples marked as training validation.append(df.loc[df.val]) # append samples marked as validation # join respective set samples across sites training = pd.concat(training, ignore_index=False) validation = pd.concat(validation, ignore_index=False)</pre> <p>Reproduce regression results</p> <pre>from sklearn.linear_model import LinearRegression c1 = 0.6 # set intercept (c1 constant) x = training.sqrt_pw.to_numpy().reshape(-1, 1) y = training.e_sky - training.alt_correction - c1 # adjust for altitude and c1 y = y.to_numpy().reshape(-1, 1) model = LinearRegression(fit_intercept=False) model.fit(x, y) c2 = model.coef_[0][0] print(f"c1={c1:.3f}, c2={c2:.3f}") # output: c1=0.600, c2=1.652</pre>
Subgrid-scale effects in cloud-like atmospheric flows: Colliding thermals - volume 2
<p>Datasets to perform surrogate modeling of subgrid-scale effects in cloud-like atmospheric flows. Please see README.md file for detailed description and metadata.</p>
Data in Support of Effects of Urbanization and Forest Fragmentation on Atmospheric Nitrogen Inputs and Ambient Nitrogen Oxide and Ozone Concentrations in Mixed Temperate Forests.
Urban ecosystems around the globe experience greater atmospheric nitrogen (N) deposition compared to rural areas and are particularly vulnerable to fragmentation due to land-use change. However, while the influences of urbanization and forest fragmentation on atmospheric inputs to temperate forests have been determined separately, the combined effects of the two changes on temperate forest ecosystems have yet to be assessed. To investigate these combined effects, we deployed throughfall collectors to measure atmospheric N inputs and passive samplers to measure nitrogen oxides (NOx) and ozone (O3) throughout the 2018 and 2019 growing seasons in seven temperate forest sites along an urbanization gradient from Boston to central Massachusetts. We found a positive relationship between the amount of impervious surface area surrounding each site (% ISA) and throughfall nitrate (NO3-) inputs at the forest edge, with urban edge NO3- inputs nearly double the rate at rural edge sites. There were higher rates of NO3- inputs in the rural forest interior than edge sites. Urban sites experienced significantly higher concentrations of NOx and O3 both in the interior and at the edge compared to rural sites. Atmospheric N inputs were significantly elevated in the early (May-July) compared to the late (August-November) growing season and concentrations of NOx and O3 were also elevated in the mid-growing season (June-September). Our results demonstrate that together, urbanization and forest fragmentation lead to greater rates of atmospheric N inputs and ambient pollutant concentrations of NOx and O3 in temperate forests of the northeastern U.S.
Dataset for "Air-sea interactions on Titan: effect of radiative transfer on the lake evaporation and atmospheric circulation"
<p>These documents are supplements to the "Air-sea interactions on Titan: effect of radiative transfer on the lake evaporation and atmospheric circulation" paper published by the same authors in The Planetary Science Journal in 2022.</p> <p>Are made available:</p> <p>-the Supporting Information document on the performed sensitivity study,<br> "paper_mtWRF_lake_RT_220825_SI.pdf"</p> <p>-the Fortran source code of the radiative transfer module developed for this work,<br> "module_ra_gray.F"</p> <p>-all the netCDF simulation outputs and a list describing their parameters,<br> "run-##.nc.gz"<br> "list_simulations_2D_paper2022_RT_zenodo.pdf"</p> <p>-the Python codes to plot figures from the netCDF output files,<br> "mtwrf_analysis_#D_#.py"</p>
Data associated with: Emergence of the physiological effects of elevated CO2 on land-atmosphere exchange of carbon and water
<p>Elevated atmospheric CO<sub>2</sub> (eCO<sub>2</sub>) influences the carbon assimilation rate and stomatal conductance of plants and thereby can affect the global cycles of carbon and water. Yet, the detection of these physiological effects of eCO<sub>2</sub> in observational data remains challenging, because natural variations and confounding factors (e.g., warming) can overshadow the eCO<sub>2</sub> effects in observational data of real-world ecosystems. In this study, we aim at developing a method to detect the emergence of the physiological CO<sub>2</sub> effects on various variables related to carbon and water fluxes. We mimic the observational setting in ecosystems using a comprehensive process-based land surface model QUINCY to simulate the leaf-level effects of increasing atmospheric CO<sub>2</sub> concentrations and their century-long propagation through the terrestrial carbon and water cycles across different climate regimes and biomes. We then develop a statistical method based on the signal-to-noise ratio to detect the emergence of the eCO<sub>2</sub> effects. The signal in gross primary production (GPP) emerges at relatively low CO<sub>2</sub> increase (Δ[CO<span>2</span>] ~ 20 ppm) where the leaf area index is relatively high. Compared to GPP, the eCO<sub>2</sub> effect causing reduced transpiration water flux (normalized to leaf area) emerges only at relatively high CO<sub>2</sub> increase (Δ[CO<sub>2</sub>] >> 40 ppm), due to the high sensitivity to climate variability and thus lower signal-to-noise ratio. In general, the response to eCO<sub>2</sub> is detectable earlier for variables of the carbon cycle than the water cycle, when plant productivity is not limited by climatic constraints, and stronger in forest-dominated rather than in grass-dominated ecosystems. Our results provide a step toward when and where we expect to detect physiological CO<sub>2</sub> effects in in-situ flux measurements, how to detect them and encourage future efforts to improve the understanding and quantification of these effects in observations of terrestrial carbon and water dynamics.</p>
Effects Of Atmospheric Attenuation On The Lightning Spectrum
<p>Spectrum carries important information reflecting atomic and molecular processes inside a light source. Accurate spectral diagnosis is vital in revealing the microscopic physical mechanism of the lightning discharge process. Spectral correction was applied considering the influence of atmospheric attenuation, grating efficiency, and camera response on the observed spectrum, thereby solving the problems of atmospheric attenuation in long distance lightning spectrum observations. Based on the restored spectrum, the temperature of the lightning return stroke channel was calculated by the ionic and atomic lines respectively. The result showed that corrected temperature at the initial stage of the return stroke, calculated by the ionic line, could reach up to 40,000 K, which was about 10,000 K higher than the values directly obtained from the observed spectrum. Atmospheric attenuation of the atomic spectral line in the nearinfrared band is relatively weak; therefore, atmospheric attenuation was inferred to have a relatively less effect on the channel temperature that was calculated by the atomic spectral lines. This work provided the attenuation ratio of the characteristic lines in lightning spectra with distance, and can used for more precisely quantitative investigation on the physical characteristics of the lightning process. It also has application value for improving the spectral diagnostic techniques on celestial body and other natural luminous process.<br> </p>
Model simulation data used in "The global impact of the transport sectors on the atmospheric aerosol and the resulting climate effects under the Shared Socioeconomic Pathways (SSPs)" (Righi et al., Earth Syst. Dynam., 2023)
<p>This dataset contains the output of the EMAC global model simulations analysed and discussed in Righi et al. (<i>Earth Syst. Dynam.</i>, 2023). For details see the README.md file.</p>
Simulated top-of-atmosphere (120 km) downward and upward solar and thermal-infrared irradiances and ice cloud optical thickness; calculated solar, TIR and net cloud radiative effect. Simulated with ice crystal properties for aggregates, droxtals, and plates based on Yang (2013).
<p>This dataset consists of three .nc files for ice crystal shapes of aggregates, plates, and droxtals. The files include ice cloud optical thickness <span class="math-tex">\(\tau\)</span> (550nm), the simulated upward and downward irradiances <span class="math-tex">\(F\)</span> at the top-of-atmosphere (with and without the presence of the ice cloud), and the calculated ice cloud radiative effect <span class="math-tex">\(\Delta F\)</span> (solar [0.3-3.5 <span class="math-tex">\(\mu\)</span>m], thermal-infrared [3.5-75 <span class="math-tex">\(\mu\)</span>m], and net). The data set allows the user to extract <span class="math-tex">\(\Delta F\)</span> values for their parameter combinations. The available cloudy and cloud-free irradiances further allow to calculate the cirrus radiative effect (RE) by scaling the 'cloudy' RE with the required cloud cover. This serves as a first-approximation because, as 3D effects are neglected.</p>
PALM Model System v 6.0 input and configuration files for coupled large eddy simulations of land surface heterogeneity effects and diurnal evolution of late summer and early autumn atmospheric boundary layers during the CHEESEHEAD19 field campaign
<p>Namelist, configuration and forcing files for the PALM Model System 6.0 revision number 21.10-rc.2 used for the numerical simulations Coupled Large Eddy Simulations of land surface heterogeneity induced atmospheric boundary layer response during the CHEESEHEAD19 field campaign.</p>
Data associated with: Emergence of the physiological effects of elevated CO2 on land-atmosphere exchange of carbon and water
Open the record for dataset details and reuse information.
Meta-analytical data on soil organic, particulate organic, and mineral-associated organic carbon under nitrogen fertilization, elevated atmospheric carbon dioxide, atmospheric warming, increased precipitation, drought, and their combined effects
Data were harvested from journal articles found on the Web of Science Core Collection and the ProQuest Agricultural and Environmental Database that studied soil organic matter fraction carbon responses to global changes (nitrogen fertilization, elevated atmospheric carbon dioxide, atmospheric warming, increased and decreased precipitation, and combined effects). Soil organic carbon fractions were designated as particulate organic carbon or mineral-associated organic carbon based on size and density cutoffs. Relevant metadata, including article information (authors, publication year), environmental information (soil type, climate, and land use), and experiment information (rates, methods) were also added to the dataset.
Dataset of "Effects of latitude-dependent gravity wave source variations on the middle and upper atmosphere"
<p>This is a dataset for three 60-day simulations with the CMAT2-GCM for June-July 2010 conditions, using the Whole atmosphere gravity wave parameterization by Yiğit et al. (2008).</p> <p>Dimensions: 66 vertical levels, 24 longitudes, and 91 latitudes. The bottom level is at 100 mb. </p> <p>Variables: There are seven physical variables. Daily-averaged zonal wind, temperature, geopotential height, zonal drag, gravity wave total heating/cooling rate, gravity wave-induced temperature fluctuations, and gravity wave absolute momentum flux. </p> <p>Simulations: A benchmark run "00n", a run with latitude-dependent gravity wave source spectrum with 50% increased flux at the lower boundary in both hemispheres "51n"; same as "52n" but 100% increased flux in the Southern Hemisphere only. </p>
Data and GrADS scripts for "Effect of atmospheric circulation on surface air temperature trends in years 1979-2018" (forthcoming in Climate Dynamics)
<p>Data and GrADS scripts associated with "Effect of atmospheric circulation on surface air temperature trends in years 1979-2018", forthcoming in Climate Dynamics.</p> <p>The README file, the scripts and the GrADS data descriptor files are in the file "circulation.zip". Unpacking this with "unzip circulation.zip" creates the directory "circulation" together with the individual files.</p> <p>The three netcdf data files (T_anomalies_ERA5_1979-2018.nc, T_anomalies_circ_1979-2018.nc and T_trends_CMIP5_42mod_1979-2018.nc) must be downloaded to the same "circulation" directory for the GrADS scripts to work.</p> <p>See the README file within "circulation.zip" for further information.</p> <p> </p>
Data and code for "On the Effects of the Ocean on Atmospheric CFC-11 Lifetimes And Emissions" (Wang et al. 2021, PNAS)
<p>Data directory includes prescribed emission in MITgcm for CFC-11 and CFC-12, and MITgcm output under different forcing runs. Code directory includes all the code used to generate plots in the paper entitled "On the Effects of the Ocean on Atmospheric CFC-11 Lifetimes And Emissions" (Wang et al. 2021, PNAS). </p>
Critical PO2 as a diagnostic biomarker for the effects of low-oxygen modified and controlled atmospheres on phytosanitary irradiation treatments in the Cabbage Looper Trichoplusia ni (Hübner)
<p>BACKGROUND: Phytosanitary irradiation is a sustainable alternative to chemical fumigants for disinfesting fresh commodities from insect pests. However, irradiating insects in modified atmospheres with very low oxygen (<1 kPa O2) has repeatedly been shown to increase radioprotective response. Thus, there is a concern that modified atmosphere packaging could reduce the efficacy of phytosanitary irradiation. One hurdle slowing the widespread application of phytosanitary irradiation is a lack of knowledge about how moderate levels of hypoxia relevant to modified atmosphere packaging of most fresh commodities (3-10 kPa O2) may affect phytosanitary irradiation treatments. Therefore, we hypothesize that critical PO2 (Pcrit), the level of oxygen at which an insect's metabolism becomes impaired, can be used as a diagnostic biomarker to predict the induction of a radioprotective response. RESULTS: Using the cabbage looper Trichoplusia ni (Hübner), we show that there is a substantial increase in radiation resistance when larvae are irradiated in atmospheres more hypoxic than their Pcrit (3.3 kPa O2). These data are consistent with our hypothesis that Pcrit could be used as a diagnostic biomarker for what levels of hypoxia may induce radioprotective effects that could impact phytosanitary irradiation treatments. CONCLUSION: We propose that the relationship between Pcrit and radioprotective effects could allow us to build a framework for predicting the effects of low-oxygen atmospheres on the efficacy of phytosanitary irradiation. However, more widespread studies across pest species are still needed to test the generality of this idea.</p>
Global Catastrophic Effects on Future Climate due to Increasing Total Solar Irradiance. A General Atmospheric Circulation Analysis.
<p>10-yr CESM run with standard TSI (BGCN_T31_g37.cam.h0*)</p> <p>10-yr CESM run with TSI +10% (BGCN_T31_g37_TSI10p.cam.h0*)</p>
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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.