| File(s) | Type | Description | Action |
|---|---|---|---|
| surface_n2o_compilation.csv (19.12 MB) | Comma Separated Values (.csv) | Primary data file for dataset ID 810032 | Add to Cart Download |
| n2oFlux-Yang2020.nc (357.95 MB) | NetCDF | We calculate the N2O air-sea flux using two wind-speed dependent parameterizations: an updated version of a commonly-used quadratic formulation, and a recent formulation that explicitly accounts for the effect of bubble-mediated . We apply each parameterization to two high-resolution wind products yielding four permutations of the piston velocity. In total, we obtain an ensemble of 400 global N2O air-sea flux estimates, from which we calculate a mean and uncertainty range. File contents: latitude_2d = center-cell latitude; degrees north longitude_2d =center-cell longitude; degrees east cellArea_m2 =Cell area in m^2 n2oFlux_EnsMean_g-pm2-pyr =n2o flux -- ensemble mean prediction; g m^(-2) y^(-1) n2oFlux_EnsStd_g-pm2-pyr =n2o flux -- ensemble standard-deviation; g m^(-2) y^(-1) n2oFluxSeas_g-pm2-pyr = n2o flux seasonality (sum of components); g m^(-2) y^(-1) n2oFluxSeas_fromWind_g-pm2-pyr = wind component of the n2o flux; g m^(-2) y^(-1) n2oFluxSeas_fromXn2o_g-pm2-pyr = dn2o component of the n2o flux; g m^(-2) y^(-1) n2oFluxSeas_fromIcePress_g-pm2-pyr = sea-ice and atmospheric pressure component of the n2o flux; g m^(-2) y^(-1) n2oFluxSeas_fromCovar_g-pm2-pyr = covariations component of the n2o flux; g m^(-2) y^(-1) biomes_masks =ocean biomes masks (1:Tropical ocean, 2:Coastal upwelling systems, 3:Polar ocean, 4: Mid-latitudes, 5: Deep mixed layer systems, 6: Subtropical gyres) coastal_upwellSys_masks = coastal upwelling systems masks (1:Peru, 2:Benguela, 3:Costa-Rica, 4:Chile, 5:California current, 6: Canary, 7:Arabian sea , 8: Bay of Bengal) | Add to Cart Download |
| n2oDataYang2020PNAS.mat (9.90 MB) | MATLAB Data (.mat) | Surface N2O Compilation in .mat format | Add to Cart Download |
| dn2o-mapped-Yang2020.nc (170.65 MB) | NetCDF | Predicted N2O disequilibrium. The N2O disequilibrium at the location of each measurement is estimated following: _DXN2O = XN2O_ocean − XN2O_atm . Here, XN2O_ocean is the ocean-side N2O measurement converted to mixing ratios, and XN2O_atm is the atmospheric N2O mixing ratio estimated by interpolating the National Oceanic and Atmospheric Administration atmospheric N2O flask dataset at the latitude and time of the oceanic measurements. To convert sparse observations to a global climatology, we trained 100 ensembles of regressions trees (Random Forests) to predict dN2O based on its relationship to well-sampled physical and biogeochemical predictors. File contents: latitude_2d = enter-cell latitude; degrees north longitude_2d = center-cell longitude; degrees east cellArea_m2 = Cell area in m^2 n2oFlux_EnsMean_g-pm2-pyr = dn2o_EnsMean_natm; natm n2oFlux_EnsStd_g-pm2-pyr = dn2o_EnsStd_natm; natm n2oFluxSeas_g-pm2-pyr = dn2o_griddedobs_mean_natm; natm atm-press = Sea Level Pressure -- ERA5 climatological average; atm biomes_masks = ocean biomes masks (1:Tropical ocean, 2:Coastal upwelling systems, 3:Polar ocean, 4: Mid-latitudes, 5: Deep mixed layer systems, 6: Subtropical gyres) coastal_upwellSys_masks = coastal upwelling systems masks (1:Peru, 2:Benguela, 3:Costa-Rica, 4:Chile, 5:California current, 6: Canary, 7:Arabian sea , 8: Bay of Bengal) | Add to Cart Download |
| Supplemental File(s) | Type | Description | Action |
| SuppCruiseTable_dec11.xlsx (24.25 KB) | Octet Stream | N2O data included in the compilation listed by cruise name, the associated year, number of observations, source and if relevant, a reference. See tag description qc1, qc2, and qc3 at the end of the table for a detailed description of the methods associated with new data. | Add to Cart Download |
©2020 Biological and Chemical Oceanography Data Management Office.Funded by the U.S. National Science Foundation