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238 results for “Atmosphere modeling”
Water "Pump" in the Atmosphere of Mars: Modeling Vertical Transport to the Thermosphere
<p>Recent studies link the observed hydrogen escape in the Martian thermosphere to the water of lower atmospheric origin. However, the cold mesosphere hinders penetration of vapor into the upper atmosphere. We present results of simulations with the Max Planck Institute general circulation model (MPI-MGCM) implementing a state-of-the-art hydrological cycle scheme. The simulations reveal a seasonal water ``pump” mechanism responsible for the upward transport of vapor. It takes place in high latitudes of the southern hemisphere at perihelion, when the upward branch of the meridional circulation is particular strong. A combination of the mean vertical flux with variations induced by solar tides facilitates penetration of water across the “bottleneck” at approximately 60 km. The meridional circulation then transports water across the globe to the northern hemisphere. Since the intensity of the meridional cell is tightly controlled by airborne dust, the water abundance in the thermosphere strongly increases during dust storms.</p>
Data set for: "Model atmospheric aerosols convert to vesicles upon entry into aqueous solution"
<p>This document compiles raw data used in the aerosol to vesicle transformation study carried out by <strong>Serge Nader <em>et al.</em></strong><br> For detailed information and context, refer to the main article and its supplementary material published in ACS Earth and Space Chemistry.</p> <p>The Excel file contains data relevant to each figure in the main article and supporting information. The additional compressed file contains raw Transmission Electron Microscopy (TEM) photographs.</p>
Model output for analyses in Qian et al. (2023) "Region and cloud regime dependences of parametric sensitivity in E3SM Atmosphere Model".
<p>This archive contains post-processed data for analyses in Qian et al. (2023) "<strong>Region and cloud regime dependences of parametric sensitivity in E3SM Atmosphere Model</strong>". These data are model output from the Perturbed Parameters Ensemble (PPE) simulations conducted with DOE's E3SM Atmosphere Model Version 1 (EAMv1). There are 256x12 PPE simulations with each simulation run for 5 days following the approach of Cloud Associated Parameterization Testbed (CAPT) and transpose Atmosphere Model Intercomparison Project (AMIP) paradigm. The diagnostic variables associated with the parameterizations of turbulence and shallow convection, deep convection, cloud microphysics, and gravity wave drag at day 5 are saved and used for analyses in this paper. </p>
Preliminary DOI/Repository of ALPINE3D and SNOWPACK data of the submitted paper "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model"
<p>There are 2 zip folders in this repository.</p> <p>"a3d_jgr.zip" contains a folder structure that must be kept as it is in order to run the simulation in the current configuration.<br> The setup contains both input and output data as well as the model configuration as used in the submitted manuscript <br> "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".</p> <p>The zip file contains 3 main folders:</p> <ul> <li>base_setup_files</li> <li>a3d_jgr_alpha1</li> <li> a3d_jgr_alpha3</li> </ul> <p>The "base_setup_files" contains all input files that are necessary to run the reference (R) simulation ("a3d_jgr_alpha1" folder) and the comparison "C" scenario ("a3d_jgr_alpha3") folder. In the a3d_jgr_alpha1 and a3d_jgr_alpha3 folders you find the corresponding outputs as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each a3d_jgr_alphax/setup/io.ini file. The input data is already linked accordingly in each io.ini file.</p> <p>a3d_jgr_alpha1 also contains the detailed snow profiles for each point along the transects.</p> <p>To reproduce the results, download and compile the source code for the adjusted ALPINE3D model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/alpine3d.git under the "alpine3d_mosaic" branch. After installing, you can run the provided model setup uploaded here.</p> <p>_________________________________________________________________________________________________________<br> <br> "SNOWPACK_JGR.zip" contains both input and output data for SNOWPACK as well as the model configuration as used in the submitted manuscript "Towards a fully physical representation of snow on Arctic sea ice using a 3D snow-atmosphere model".</p> <p>The zip file contains 2 main folders: </p> <ul> <li>SNOWPACK_JGR_ALPHA1</li> <li>SNOWPACK_JGR_ALPHA3</li> </ul> <p>In the SNOWPACK_JGR_ALPHA1 (reference "SP_R" simulation) and SNOWPACK_JGR_ALPHA3 (comparison "SP_C" scenario) folders you find the corresponding inputs, outputs and configuration as used in the paper, as well as the settings used - which only differ by the changed "SCHMIDT_DRIFT_FUDGE" value that is found in each SNOWPACK_JGR_ALPHA/setup/io.ini file. The input data is already linked accordingly in each io.ini file.</p> <p>To reproduce the results, download and compile the source code for the adjusted SNOWPACK model first, which can be obtained from https://gitlabext.wsl.ch/snow-models/snowpack.git under the "snowpack_mosaic" branch. After installing, you can run the provided model setup uploaded here.</p>
Flexpart input/output data for "An optimisation method to improve modelling of wet deposition in atmospheric transport models: applied to FLEXPART v10.4"
<p>Flexpart input and output data for the manuscript/paper "An optimisation method to improve modelling of wet deposition in atmospheric transport models: applied to FLEXPART v10.4" by S. Van Leuven, P. De Meutter, J. Camps, P. Termonia and A. Delcloo.</p>
Dataset for JGR Atmospheres manuscript " An Observational Constraint of VOC Emissions for Air Quality Modeling Study in the Pearl River Delta Region"
<p>The file includes hourly observations of ground-level ozone (O<sub>3</sub>) and nitrogen dioxide (NO<sub>2</sub>) concentrations at 56 environmental monitoring stations in the Pearl River Delta (PRD) region in China during June 2018. The units are in μg/m<sup>3</sup>.</p>
Atmospheric and Coupled Model inter-comparison Study
<p>This repository contains software tools, model output datasets and plotting scripts that used for evaluations and figures presented in the study.</p>
Soil and atmospheric drought explain the biophysical conductance responses in diagnostic and prognostic evaporation models over two contrasting European forest sites
<p>This contains the datasets and codes that were used to generate the results and discussions in the manuscript.</p>
Model outputs associated with "Comprehensive multiphase chlorine chemistry in the box model CAABA/MECCA: Implications to atmospheric oxidative capacity"
<p>Model outputs associated with "Comprehensive multiphase chlorine chemistry in the box model CAABA/MECCA: Implications to atmospheric oxidative capacity”.</p>
Model data for: Drawdown of atmospheric pCO2 via dynamic particle export stoichiometry in the ocean twilight zone
Open the record for dataset details and reuse information.
Lagrangian Atmospheric Model output for the Control, Onset and Development experiments
Open the record for dataset details and reuse information.
Contrasting effects of Miocene and Anthropocene levels of atmospheric CO2 on silicon accumulation in a model grass
Open the record for dataset details and reuse information.
Methyl bromide atmosphere-ocean box model code, inputs, and outputs
Open the record for dataset details and reuse information.
Data for modelling spatial patterns and determinants of atmospheric carbon dioxide concentrations in Phoenix metro area
The purpose of this work is to describe determinants and spatial patterns of atmospheric carbon dioxide (CO2) in Phoenix, Arizona. Specifically, we use geographic information systems (GIS) and regression-based analyses to identify the human and biological factors that contribute to spatial and temporal variations in near-surface atmospheric CO2 levels. We use these factors to create estimated surfaces of CO2 for the urban area. We validate our surfaces using independently collected records of CO2 from several monitoring stations and transects. To investigate the temporal patterns and variations of CO2, we were able to generate CO2 surfaces for the early mornings and the afternoons, and on weekdays when traffic is heavy and spatially focused and on weekends when it is lighter and more spatially dispersed. Our findings suggest there is a distinct relationship between the structure of Phoenix CO2 levels and spatial patterns of human activities and vegetation densities. Morning CO2 levels are higher than afternoon levels and correspond closely to the density of traffic, population, and employment. The spatial structure of human activity explains the pattern of CO2 better on weekdays than on weekends. CO2 surfaces reflect declining densities of human activity with distance from the city center, the pattern of irrigated agriculture in the Phoenix area, and riparian habitats on the urban fringe. Spatial and temporal patterns of CO2 are useful in understanding urban climate and ecosystem processes.
Model and observational dataset used in Tsiringakis, A. , Holtslag, A.A.M., Grimmond, S. and Steeneveld, G.J. Surface and atmospheric driven variability of the single-layer urban canopy model under clear sky conditions over London, Journal of Geophysical Research: Atmospheres
<p>This dataset contains:</p> <p>- Model output from the single-column version of the Weather Research and Forecasting model v3.8.1.</p> <p>- Observations from the KSSW tower (King's College London, United Kingdom) used for model evaluation.</p> <p>- The Single-column Urban Boundary Layer Inter-comparison Model Experiment (SUBLIME) case study description and external forcing file for the single-column version of Weather Research and Forecasting model.</p> <p>This dataset is used in :</p> <p>~Tsiringakis, A., Holtslag, A.A.M., Grimmond, S. and Steeneveld, G.J. Surface and atmospheric driven variability of the single-layer urban canopy model under clear sky conditions over London. Journal of Geophysical Research: Atmospheres</p>
Improved representation of clouds in the atmospheric component LMDZ6A of the IPSL Earth system model IPSL-CM6A : Source codes and supporting files
<p>Source codes and supporting files of the paper by J-B Madeleine et al., 2020, entitled "Improved representation of clouds in the atmospheric component LMDZ6A of the IPSL Earth system model IPSL-CM6A" published in the Journal of Advances in Modeling Earth Systems. See the README file for more information.</p>
Dataset for: "The ARCiS framework for Exoplanet Atmospheres: Modelling Philosophy and Retrieval"
<p>This is the data package accompanying the publication: The ARCiS framework for Exoplanet Atmospheres: Modelling Philosophy and Retrieval</p> <p>Accepted for publication in A&A</p>
Contrasting aerosol effects on longwave cloud forcing in South East Asia and Amazon simulated with Community Atmosphere Model version 5.3
<p>Aerosols modify cloud microphysical and radiative properties and thus impact the shortwave (SW) and longwave cloud forcing (LWCF). This study first reports the finding of contrasting aerosol effects on LWCF in South East Asia and Amazon in the Community Atmosphere Model version 5.3 (CAM5.3), which corresponds to the sum of LW indirect and semi-direct effects investigated in Ghan et al., (2012). A series of numerical experiments is conducted to decompose the complex aerosol effects on LWCF. Our analysis indicates that the cooling (negative aerosol effects on LWCF) in Amazon is due mainly to the aerosol effects on warm clouds and the inhibition of vertical motion by the aerosol-induced radiative cooling. In contrast, the warming (positive aerosol effects on LWCF) in South East Asia is due mainly to the aerosol effect on homogeneous freezing, thus reducing the ice particle size and prolonging the existence of ice cloud. Our results emphasize that a comprehensive analysis of integrated aerosol effects on both warm and ice clouds is necessary for better understanding the aerosol effects on LWCF.</p>
Impact of horizontal resolution and model time step on European precipitation extremes in the OpenIFS 43r3 atmosphere model
<p>Python scripts used for GMD paper</p>
Fractal geometry features of aerosol particle and its contribution to atmospheric optical property: development of Fractal Aerosol Cluster Model and its validation of atmospheric visibility during a heavy haze event
<p>-------------------------<br>Content of the dataset<br>-------------------------<br>****** the experiment case (EXP) ; the control case (CTR) ******</p> <p>1. Meteorological elements.tar contains observational and simulated data for T2, WS, RH, and PM2.5 time series, which can be used to plot Figure 4 and build Table 2</p> <p>2. Planar distribution.tar contains the horizontal spatial distribution data of aerosol extinction coefficients simulated by CTR and EXP for the four typical moments selected in this paper, which can be used to plot Figures 5, 6, and 7</p> <p>3. PM.rar contains the vertical profile data of simulated Particulate Matter concentrations by CTR and EXP during the study period in the paper, which can be utilized for drawing Fig. 11.</p> <p>4. Timeseries.tar contains observational and simulated data for time series of atmospheric visibility and surface shortwave radiation, which can be used to plot Figures 5, 6, 7, 8, S1, and build Table 3</p> <p>5. wrfbiochemi.rar contains the biogenic emissions data for simulation both for CTR and EXP.</p> <p>6. wrffirechemi.rar contains the biomass burning emissions data for simulation both for CTR and EXP.</p> <p>7. wrfchemi.rar contains the Anthropogenic emissions data for simulation both for CTR and EXP.</p> <p>8. The file module_optical_averaging.F contains the main code of the improved visibility model, the Fractal Aerosol Cluster Model</p> <p>(FACM), which is coupled to WRF-Chem and used by EXP. It is located in the chem/ directory and called by optical_driver.F.</p> <pre> </pre> <p> </p> <p>-------------------------</p> <p>Contact information</p> <p>-------------------------</p> <p> </p> <p>Zhenxin Liu</p> <p>liuzhenxin@nuist.edu.cn</p> <p> </p> <p> </p>
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.