Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
238
datasets available to search
ShareScore release 0.9.0
Dataset results
238 results for “Atmosphere modeling”
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>
Data for "• Can we achieve atmospheric chemical environments in the laboratory? An integrated model-measurement approach to chamber SOA studies"
Open the record for dataset details and reuse information.
Wind profile in the wave boundary layer and its application in a coupled atmosphere-wave model
<p>The simulation data for the study</p>
Data for the article entitled "Strongly Coupled Data Assimilation of Ocean Observations into an Ocean-Atmosphere Model" by Tang et al. 2021, GRL
<p>We stored the output data for the free run and the data assimilation experiments. All the data is stored in netCDF format and named by XX1_ensmean_XX2_monmean.nc. The prefix XX1 indicates the simulation scenarios, where 'free_run' refers to the free run, 'wcda' the weakly coupled assimilation run, 'scda' the strongly coupled data assimilation run without vertical localization for atmosphere, and 'scda_vert' the strongly coupled assimilation run with vertical localization for atmosphere. The XX2 represents variables from the simulations, where 'temp2' refers to 2 meter temperature, 'u10' 10 metre U wind component, 'v10' 10 metre V wind component, 'st_p' temperature at pressure levels, 'uv_p' U and V component of wind at pressure levels, and 'q_p' specific humidity at pressure levels.</p>
Surrogate modelling for the forecast of Seveso-type atmospheric pollutant dispersion - Online Resource 1
<p>Online Resource 1: Test-data response of GIM model.</p>
Model's configuration for paper "Dynamic and Thermodynamic coupling between the Atmosphere and Ocean near the Kuroshio Current and Extension System"
<p>Here are the data used for the SKRIPS simulations. </p>
A Predictive Model for the Streamwise Velocity in the Near-neutral Atmospheric Surface Layer
<p>A Predictive Model for the Streamwise Velocity in the Near-neutral Atmospheric Surface Layer</p>
Advanced methods for uncertainty assessment and global sensitivity analysis of a Eulerian atmospheric chemistry transport model
<p>Atmospheric chemistry transport models (ACTMs) are extensively used to provide scientific support for the development of policies to mitigate against the detrimental effects of air pollution on human health and ecosystems. Therefore, it is essential to quantitatively assess the level of model uncertainty and to identify the model input parameters that contribute the most to the uncertainty. For complex process-based models, such as ACTMs, uncertainty and global sensitivity analyses are still challenging and are often limited by computational constraints due to the requirement of a large number of model runs. In this work, we demonstrate an emulator-based approach to uncertainty quantification and variance-based sensitivity analysis for the EMEP4UK model (regional application of the European Monitoring and Evaluation Programme Meteorological Synthesizing Centre-West). A separate Gaussian process emulator was used to estimate model predictions at unsampled points in the space of the uncertain model inputs for every modelled grid cell. The training points for the emulator were chosen using an optimised Latin hypercube sampling design. The uncertainties in surface concentrations of O<sub>3</sub>, NO<sub>2</sub>, and PM<sub>2.5</sub> were propagated from the uncertainties in the anthropogenic emissions of NO<sub>x</sub>, SO<sub>2</sub>, NH<sub>3</sub>, VOC, and primary PM<sub>2.5</sub> reported by the UK National Atmospheric Emissions Inventory. The results of the EMEP4UK uncertainty analysis for the annually averaged model predictions indicate that modelled surface concentrations of O<sub>3</sub>, NO<sub>2</sub>, and PM<sub>2.5</sub> have the highest level of uncertainty in the grid cells comprising urban areas (up to ± 7%, ± 9%, and ± 9% respectively). The uncertainty in the surface concentrations of O<sub>3 </sub>and NO<sub>2</sub> were dominated by uncertainties in NO<sub>x</sub> emissions combined from non-dominant sectors (i.e. all sectors excluding energy production and road transport) and shipping emissions. Additionally, uncertainty in O<sub>3</sub> was driven by uncertainty VOC emissions combined from sectors excluding solvent use. Uncertainties in the modelled PM<sub>2.5</sub> concentrations were mainly driven by uncertainties in primary PM<sub>2.5</sub> emissions and NH<sub>3</sub> emissions from the agricultural sector. Uncertainty and sensitivity analyses were also performed for five selected grid sells for monthly averaged model predictions to illustrate the seasonal change in the magnitude of uncertainty and change in the contribution of different model inputs to the overall uncertainty. Our study demonstrates the viability of a Gaussian process emulator-based approach for uncertainty and global sensitivity analyses, which can be applied to other ACTMs. Conducting these analyses helps to increase the confidence in model predictions. Additionally, the emulators created for these analyses can be used to predict the ACTM response for any other combination of perturbed input emissions within the ranges set for the original Latin hypercube sampling design without the need to re-run the ACTM, thus allowing fast exploratory assessments at significantly reduced computational costs.</p> <p>The upload contains the uncertainty and sensitivity data together with the analysis scripts.</p>
Simulations of Typhoon In-Fa (2106) and air-sea interactions using a coupled ocean-atmosphere-wave-sediment transport (COAWST) modeling system
<p>The Observation data supporting the result of our manucript submitted to JGR-Ocean.</p> <p> </p>
From atmospheric water isotopes measurement to firn core interpretation in Adelie Land: A case study for isotope-enabled atmospheric models in Antarctica: DATASET
<p>Thoses datasets are associated to the non-published study (at date): From atmospheric water isotopes measurement to firn core interpretation in Adelie Land: A case study for isotope-enabled atmospheric models in Antarctica.</p> <p>- date is in datetime format.</p> <p>- humidite is humidity (in ppmv)</p> <p>- d18 and dD are isotopic compositions (in per mil)</p> <p>- temp is 2-meters temperature in °C</p> <p>- pression is pressure (in mbar)</p> <p>- vitesse_vent is wind speed (in m/s)</p> <p>- direction_vent is wind direction (in °)</p> <p>- RH is relative humidity (in %)</p>
Data supporting "Modeling and evaluating the effects of irrigation on land-atmosphere interaction in southwestern Europe with the regional climate model REMO2020-iMOVE using a newly developed parameterization"
<p>This data supports the analysis of the manuscript Asmus et al. 2023 "Modeling and evaluating the effects of irrigation on land-atmosphere interaction in southwestern Europe with the regional climate model REMO2020-iMOVE using a newly developed parameterization".</p><p><strong>Simulation data</strong></p><p>The simulation data is created with REMO2020-iMOVE using the new irrigation parameterization. The results are saved as NetCDF files with monthly mean values and/or time series (hourly) of single variables for the analysis period. A list of the simulations can be found below.</p><p><strong>Observation data </strong></p><p>The observation data is published with the kind permission of ISPRA which hosts the SCIA database (www.scia.isprambiente.it). If you use this data, please make sure to include the following data source:<br>SCIA by ISPRA - Area Climatologia operativa - Via V. Brancati 48 00144 Roma. <br>We downloaded monthly mean values for the variables T2Max, T2Min and T2Mean from <a href="http://193.206.192.214/servertsutm/serietemporali100.php">http://193.206.192.214/servertsutm/serietemporali100.php </a>(last accessed on 14/10/2022) to verify the model results with and without irrigation parameterization. </p><p>By untarring the tarballs, the data structure is created that is necessary to execute the analysis scripts.</p><p>For more information or additional data please contact the author.</p><p> </p><p><strong>tarball | exp_number | description </strong></p><p>067015.tar.gz | 067015 | not irrigated</p><p>067016.tar.gz | 067016 | irrigated with "adaptive water application scheme"</p><p>067017.tar.gz | 067017 | irrigated with "adaptive water application scheme"</p><p>067019.tar.gz | 067019 | irrigated with "flexible time water application scheme"</p><p>067020.tar.gz | 067020 | irrigated with "prescribed water application scheme"</p><p>observation_scia.tar | - | observation data from SCIA </p><p> </p><p><strong>Data structure for simulation data</strong></p><p>\<exp_number><br> \monthly<br> \hourly<br> \var_series<br> \<variable><br><br>Note:<br>\067015 includes static variables<br> \irrifrac (irrigated fraction)<br> \bla (land-sea-mask)</p>
Data for "Supercells and Tornado-like Vortices in an Idealized Global Atmosphere Model"
<p>Data used in a manuscript on supercells and tornado-like vortices, for submission to ESS.</p>
Linking evapotranspiration, boundary-layer processes and atmospheric moisture using isotope tracer modeling and data
Open the record for dataset details and reuse information.
SiB3 Modeled Global 1-degree Hourly Biosphere-Atmosphere Carbon Flux, 1998-2006
The Simple Biosphere Model, Version 3 (SiB3) was used to produce a global data set of hourly carbon fluxes between the atmosphere and the terrestrial biosphere for the years 1998-2006. This data set represents the global net ecosystem exchange (NEE) of carbon between the atmosphere and the terrestrial biosphere; specifically, the flux of CO2 between the planetary boundary layer (PBL) and the surface vegetation layer. Following atmospheric convention, flux is defined as positive into the atmosphere and negative into the surface vegetation.The data reported are 9 years of estimated hourly carbon flux for 14637 land points. Units are moles C/m2/sec.Data are provided in two NetCDF formats: * The NetCDF format provided by the investigators -- format designed specifically to minimize disk storage volume that excludes water grid cells. * A CF Compliant NetCDF format -- generated by the ORNL DAAC that includes both land and water grid cells.The investigator provided NetCDF formatted files can be processed using the provided FORTRAN code (sib_process_flux.f90) and the land mask (sib_mask.nc) into hourly, daily-mean, or monthly-mean fluxes on a global 1x1 degree Cartesian grid. The monthly-mean SiB3 fluxes were compared to TransCom flux data available for years 2000-2005 (Gurney et al., 2008) as a means of evaluating overall behavior of the model. In general, SiB3 fluxes are within the error bars of the TransCom results.The CF compliant NetCDF format files have been processed by the ORNL DAAC and the hourly and summarized daily-mean and monthly-mean flux data files are provided. GeoTIFF format files:In addition, the CF convention NetCDF files were converted to GeoTIFF image files by the ORNL DAAC and are included with the data set. Companion file:Additional information about the data formats, methodology, and data quality is found in the companion file: SiB3_carbon_flux_readme.pdfAccess to GeoTIFF format files via WCS Interface:The ORNL DAAC also provides access to the GeoTIFF files via a Web Coverage Service Interface (WCS). The OpenGIS® Web Coverage Service Interface Standard (WCS) defines a standard interface and operations that enables interoperable access to geospatial coverages.These data are a carbon cycle reanalysis, which may be thought of as analogous to NCEP meteorological reanalysis products. Carbon fluxes have been used by a large community of atmospheric transport modelers to create reanalysis of CO2 concentrations and the results have been evaluated against observations. In addition, the reanalyzed flux and CO2 fields are important for designing future observing strategies for the global carbon cycle.
SAFARI 2000 ETA Atmospheric Model Data, Wet and Dry Seasons 2000
With modern computer power now capable of making mesoscale model output available in real time in the operational environment, increased attention has been given to utilizing these models in order to improve the forecasting ability of meteorologists. The National Centers for Environmental Prediction (NCEP) has developed a step-mountain eta coordinate model generally known as the ETA Model.This NCEP ETA data assimilation and prediction system (see Mesinger et al., 1988; Black, 1994) has been used by the South African Weather Bureau/Service (SAWS) to provide operational regional forecast guidance since November 1993. SAWS used this model to produce the basic meteorological data for the SAFARI project. The SAWS ETA model is a hydrostatic model with a horizontal grid spacing of approximately 48 km and 38 vertical levels, with layer depths that range from 20 m in the planetary boundary layer to 2 km at 50 mb. There have been several major ETA Model upgrades at SAWS: in March 1996, August 1998, November 1999, and August 2001.
CLPX-Model: Local Analysis and Prediction System: 4-D Atmospheric Analyses, Version 1
The Local Analysis and Prediction System (LAPS), run by the NOAA's Forecast Systems Laboratory (FSL), combines numerous observed meteorological data sets into a collection of atmospheric analyses.
MAPSS: Mapped Atmosphere-Plant-Soil System Model, Version 1.0
MAPSS (Mapped Atmosphere-Plant-Soil System) is a landscape to global vegetation distribution model that was developed to simulate the potential biosphere impacts and biosphere-atmosphere feedbacks from climatic change. Model output from MAPSS has been used extensively in the Intergovernmental Panel on Climate Change's (IPCC) regional and global assessments of climate change impacts on vegetation and in several other projects.
Land Surface Model (LSM 1.0) for Ecological, Hydrological, Atmospheric Studies
The NCAR LSM 1.0 is a land surface model developed by Gordon Bonan to examine biogeophysical and biogeochemical land-atmosphere interactions, especially the effects of land surfaces on climate and atmospheric chemistry. It can be run coupled to an atmospheric model or uncoupled, in a stand-alone mode, if an atmospheric forcing is provided. The model runs on a spatial grid that can range from one point to global. The model was designed for coupling to atmospheric numerical models. Consequently, there is a compromise between computational efficiency and the complexity with which the necessary atmospheric, ecological, and hydrologic processes are parameterized. The model is not meant to be a detailed micrometeorological model, but rather a simplified treatment of surface fluxes that reproduces at minimal computational cost the essential characteristics of land-atmosphere interactions important for climate simulations. The model is a complete executable code with its own time-stepping driver, initialization (subroutine lsmini), and main calling routine (subroutine lsmdrv). When coupled to an atmospheric model, the atmospheric model is the time-stepping driver. There is one call to subroutine lsmini during initialization to initialize all land points in the domain; there is one call per time step to subroutine lsmdrv to calculate surface fluxes and update the ecological, hydrological, and thermal state for all land points in the domain. The model writes its own restart and history files. These can be turned off if appropriate.Available for downloading from the ORNL DAAC are the LMS Model Documentation and User's Guide (ftp://daac.ornl.gov/data/model_archive/LSM/lsm_1.0/comp/NCAR_LSM_Users_Guide.pdf ), the model source code, input data set, and scripts for running the model. Applications of the model are described in two additional companion files (ftp://daac.ornl.gov/data/model_archive/LSM/lsm_1.0/comp/NCAR_LSM_Bckgrnd_Application_Info.pdf and ftp://daac.ornl.gov/data/model_archive/LSM/lsm_1.0/comp/NCAR_LSM_Analyzed-Data.pdf.
CARVE: Monthly Atmospheric CO2 Concentrations (2009-2013) and Modeled Fluxes, Alaska
This data set reports monthly averages of atmospheric CO2 concentration from satellite and airborne observations between 2009 and 2013 and simulated present and future monthly concentrations and land-atmosphere CO2 flux for periods between 1990 and 2200. Atmospheric CO2 concentration measurements were obtained from Carbon in Arctic Reservoirs Vulnerability Experiment (CARVE) and NOAA Arctic Coast Guard (ACG) flights, the Greenhouse Gases Observing Satellite (GOSAT), and NOAA/ESRL vertical profile measurements at Poker Flat, Alaska (PFA). Present and future monthly CO2 concentrations and fluxes were simulated using the GEOS-Chem global tracer model and the Community Land Model, Version 4.5, for multiple regional flux and permafrost thaw scenarios.
Cold atmospheric plasma affects stem cell renewal and differentiation and is associated with a regeneration process in an intestinal organoid culture model
GEO Series GSE178148. Mus musculus. 22 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
Understand access before you commit
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.