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31 results for “Air-sea flux”
A Numerical Study of Tropical Cyclone and Ocean Responses to Air-sea Momentum Flux at High Winds
<p>The simulation data output from FIO-AOW for tropical cyclone study</p>
Coastal Upwelling Modulates Winds and Air-Sea Fluxes, Impacting Offshore Wind Energy
<p>Model Output supporting the paper "Coastal Upwelling Modulates Winds and Air-Sea Fluxes, Impacting Offshore Wind Energy"</p> <p>The dataset includes four WRF runs, with upwelling (labeled 'operational') and with upwelling removed (labeled 'experimental'). Two of the runs have parameterized wind turbines, labeled "Fitch". </p> <p>This work was supported by NJ Board of Public Utilities. </p> <p> </p>
Data for ''A note on systematic biases in the ocean due to the air-sea flux calculation in coupled models''
<p>Data used to in a JAMES publication.</p> <p> </p> <p>Plotting routines can be found at: https://github.com/RafaelAbel/Coarse_Graining</p> <p>Manuscript DOI: tba</p>
WOMBAT v2.0 estimates of global GPP, respiration, and air-sea fluxes
These files contain estimates of global CO2 fluxes, split into GPP, respiration, and air-sea components produced by the WOMBAT v2.0 flux-inversion system (see https://arxiv.org/abs/2210.10479). These fluxes are further decomposed into trend and seasonality. The file WOMBAT_v2_CO2_gridded_climatology_samples.nc4 contains the estimated spatial fields for each beta in the paper that define the trend/seasonality of the fluxes. The bottom-up estimates are provided for each beta, as well as samples from the posterior distribution. A second file, WOMBAT_v2_CO2_gridded_flux_samples.nc4, contains bottom-up estimates and posterior samples for the flux component fields. These are split into components and the parts of the decomposition, so for example the linear component of GPP is in gpp_linear_bottom_up/gpp_linear_posterior for the bottom-up/posterior. The different fields can be summed to get meaningful quantities, such as the NEE (sum of all GPP and respiration parts), or the net flux (sum of all parts). The final file, samples-LNLGIS.rds, contains samples from the posterior distribution of the model parameters. This file format may be read using the readRDS function in the R programming language.
Southern Ocean Air-Sea Carbon Fluxes from Aircraft Observations: Modeling Datasets
The Southern Ocean plays an important role in determining atmospheric CO2, yet estimates of air-sea CO2 flux for the region diverge widely. We constrain Southern Ocean air-sea CO2 exchange by relating fluxes to horizontal and vertical CO2 gradients in atmospheric transport models and then apply atmospheric observations of these gradients to estimate fluxes. Aircraft-based measurements of the vertical atmospheric CO2 gradient provide robust flux constraints. We find an annual-mean flux of –0.55±0.23 Pg C yr–1 (net uptake) south of 45°S during 2009–2018. This is consistent with the mean of atmospheric-inversion estimates and surface-ocean pCO2-based products, but our data indicate stronger annual-mean uptake than suggested by recent interpretations of profiling-float observations.
A detectable change in the air-sea CO2 flux estimate from sailboat measurements
<p>This repository contains files and scripts used to generate figures for the paper titled "A detectable change in the air-sea CO2 flux estimate from sailboat measurements". The study quantifies the impact of pCO2 observations measured by the sailboat "Seaexplorer" on the air-sea CO2 flux estimate.</p><p><strong> Overview:</strong></p><p>We used pCO2 measurements sourced from SOCAT (www.socat.info), along with other environmental variables. We applied the 2-step neural network method SOM-FFN (Landschützer et al., 2013) to reconstruct air-sea CO2 flux estimates.</p><p>Four sets of air-sea CO2 flux estimates were reconstructed, each with 40 ensemble members to account for random errors in the neural network. These are the four sets:</p><p>E1) fluxesA - Based on SOCATv2022 including Seaexplorer data</p><p>E2) fluxesB - Based on SOCATv2022 excluding Seaexplorer data.</p><p>E3) fluxesC - Based on SOCATv2022 data, including Seaexplorer data, but introducing a random uncertainty of ± 5 μatm to the Seaexplorer data.</p><p>E4) fluxesD - Based on SOCATv2022 data, including Seaexplorer data, but introducing a constant measurement offset of 5 μatm to the Seaexplorer data.</p><p>These air-sea CO2 flux density estimates are 4-dimensional, represented in mol C m-2 yr-1, with the following dimensions:</p><p>- Ensemble size of flux reconstructions (40)</p><p>- Time (months from 1982 to 2021, totaling 480 months)</p><p>- Latitude (1-degree intervals, totaling 180 latitudes)</p><p>- Longitude (1-degree intervals, totaling 360 longitudes)</p>
The bulk parameterizations of turbulent air-sea fluxes in NEMO4: the origin of Sea Surface Temperature differences in a global model study
<p>This repository contains the code and the data used to produce the results of "The bulk parameterizations of turbulent air-sea fluxes in NEMO4: the origin of Sea Surface Temperature differences in a global model study" a discussion paper by G. Bonino, D. Iovino, L. Brodeau, S. Masina submitted to Geoscientific Model Development.</p> <p>- DATA.tar contains the 5 days model outputs to produce the figures in the manuscript.</p> <p>- CODE.tar contains the code and the namelists to run the experiments. The namelists and the modified code for run each experiments are available in the subfolder CODE/cfgs/. </p>
The 4-km monthly global air-sea carbon flux density dataset from 2000 to 2018
<p>We combined 24.6 million ocean observation data points, terabyte-level remote sensing images, and petabyte-level reanalysis data to create a standardized sample set containing more than 3 million records. We proposed a spatiotemporal feature-embedding machine-learning method to solve the issues of sparse data, missing data, and discontinuous changes existing in most current research. Our approach enables efficiently exploiting these massive datasets, leading to the first fully continuous and monthly global ocean partial pressure dataset covering the years 2000 to 2018. Based on the dataset, we presented a depiction of the 4-km monthly global air-sea carbon flux density that encompassed coastal oceans and characterized the ocean carbon budget for the period of 2000 to 2018 by integrating open datasets, including atmosphere partial pressure, wind speed, sea surface temperature, sea surface salinity.</p>
Ocean Surface pCO2 and Air-Sea CO2 Flux in the Northern Gulf of America, 2006-2010
This dataset provides 1 km gridded monthly estimates of surface ocean partial pressure of CO2 (pCO2) and air-sea flux of CO2 (CO2 flux) for the northern Gulf of America for the period 2006 through 2010. Estimates of pCO2 were derived from MODIS/Aqua satellite imagery in combination with ship-based observations. Estimates of CO2 flux were derived from estimates of seawater pCO2, wind fields, and atmospheric pCO2.
The impacts of sub-grid physical processes on SEP air-sea fluxes
<p>Model outputs from CAM5_CLUBB when parameters of ZM deep convection and CLUBB scheme are disturbed in SEP, ITCZ and SPCZ, respectively. And observations of surface energy fluxes. </p>
Ocean Surface pCO2 and Air-Sea CO2 Flux in the Northern Gulf of Mexico, 2006-2010
This dataset provides 1 km gridded monthly estimates of surface ocean partial pressure of CO2 (pCO2) and air-sea flux of CO2 (CO2 flux) for the northern Gulf of Mexico for the period 2006 through 2010. Estimates of pCO2 were derived from MODIS/Aqua satellite imagery in combination with ship-based observations. Estimates of CO2 flux were derived from estimates of seawater pCO2, wind fields, and atmospheric pCO2.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.