Processing and Data for "Estimating ocean net primary productivity from daily cycles of carbon biomass measured by profiling floats"

Description: These files contain processed BGC-Argo float data, figure data, the radiocarbon productivity subset, bootstrapping results, and the associated Python/Matlab code to calculate net primary productivity from daily cycles of optical backscatter and dissolved oxygen. The raw float data used in this study are available from the Argo Global Data Assembly Centers in Brest, France (ftp://ftp.ifremer.fr/ifremer/argo/dac/coriolis) and Monterey, California (ftp://usgodae.org/pub/outgoing/argo/dac/coriolis). The raw MODIS satellite-based productivity data is available from the Oregon State University Ocean Productivity site (http://orca.science.oregonstate.edu/npp_products.php). The raw MODIS satellite-based euphotic depth estimates are available from the NASA L3 browser (https://oceancolor.gsfc.nasa.gov/l3/). The original ship-based estimates of net primary productivity are available from the Pangaea (https://doi.pangaea.de/10.1594/PANGAEA.932417) and the British Oceanography Data Centre (https://www.bco-dmo.org/dataset/814803). Please cite as: Stoer, A., and Fennel, K. 2022. Processing and Data for Estimating ocean net primary productivity from daily cycles of carbon biomass measured by profiling floats. Zenodo. doi: 10.5281/zenodo.6977161. Python/MATLAB Software Description: dielFit_GOPeqCR.m: This code is from Johnson and Bif (2021). We have added outputs for standard errors for linear and PvE models and sunrise/sunset times. To run this code with the associated Python software a MATLAB engine needs to be installed. Please see: https://www.mathworks.com/help/matlab/matlab-engine-for-python.html argo_so_processing_20220815.py: This code is the first of two pieces of software for estimating net primary productivity from floats in the Southern Ocean. The program below obtains the data from the BGC Argo database (Argo, 2021) and processes it. Simple data quality control, interpolation, biogeochemical calculations, and data binning occur. The processed float data is located in the folder 'Processed Argo Transects'. argo_daily_npp_20220815.py: This code using processed Argo float data that contains oxygen and particle backscatter measurements to infer net primary production. The code combines the float that meet the criteria of sampling at all local hours of the day throughout its lifetime. Then, it constructs diel cycles from this data by finding the median value of each hour and uses the code from Johnson and Bif (2021), which is a modified version from Barone et al. (2019). The algorithm used to convert particle backscatter to particulate organic carbon is from Graff et al. (2015). We assume that dissolved primary productivity accounts for 30% of total primary productivity (Moran et al., 2022). argo_daily_npp_bootstrap_20220815.py: This code using processed Argo float data that contains co-located oxygen and particle backscatter measurements to infer net primary production. This code is very similar to argo_daily_npp_20220815.py but randomly samples a subset of the co-located profiles at different sample sizes before calculating net primary productivity. Productivity is calculated at each sample size 1000 times. The results of this analysis is located in the folder 'Bootstrapped Results'. More details can be found in the code itself. Data Descriptions: Data from 'Processed Argo Transects' Folder | Description for each variable Variable Description Units depth Average depth of depth bin m mid_depth Center of depth bin m pressure Average pressure in depth bin dbar profile_index Profile number or index profile_longitude Average longitude of profile degE profile_latitude Average latitude of profile degN profile_time Average UTC time of profile yyyy-mm-dd hh:mm:ss profile_local_time Average local time of profile yyyy-mm-dd hh:mm:ss profile_local_hour The hour of the local timestamp salinity Seawater salinity PSU temperature Seawater temperature degC oxygen Dissolved oxygen concentration umol kg-1 oxygen_saturation Saturated dissolved oxygen concentration calculated from the Garcia and Gordon (1992) equation. umol kg-1 oxygen_anom The difference between observed dissolved oxygen concentration and saturated oxygen umol kg-1 bbp470 Optical backscatter coefficient at 470 nm. Particulate organic carbon is calculated in argo_daily_npp_20220815.py m-1 Variable Description Units wmo WMO number of float profile_index Profile index or profile number taken by float profile_latitude Average profile latitude degN profile_longitude Average profile longitude degE Variable Description Units fod Fraction of day oxy Sinusoidal curve fit to oxygen mol m-3 poc Sinusoidal curve fit to particulate organic carbon mol m-3 oxy_med Hourly median oxygen mol m-3 oxy_sem Hourly standard error of oxygen mol m-3 poc_med Hourly median particulate organic carbon mol m-3 poc_sem Hourly standard error of particulate organic carbon mol m-3 region Name of data subset (e.g., 30-40 deg N, co-located) Variable Description Units region Name of data subset (e.g., 30-40 deg N) depth Depth of profile m zeu 1% euphotic depth from Lee et al. (2013) algorithm from NASA (2022) L3 satellite products. m n_profiles_bpp Number of backscatter profiles n_profiles_oxy Number of oxygen profiles n_floats_bbp Number of floats with backscatter measurements n_floats_oxy Number of floats with oxygen measurements gop_do Gross oxygen productivity estimated from dissolved oxygen mol m-3 yr-1 gop_do_serr Standard error of gross oxygen productivity estimated from dissolved oxygen mol m-3 yr-1 gop_do_p p-value of curve fit to hourly oxygen data gop_do_r2 r-squared value of curve to hourly oxygen data oxy_sr The calculated sunrise time as a fraction of the day oxy_ss The calculated sunset time as a fraction of the day gpp_bbp Gross carbon productivity estimated from optical backscatter mol m-3 yr-1 gpp_bbp_serr Standard error of gross carbon productivity estimated from optical backscatter mol m-3 yr-1 gop_do_p p-value of curve fit to hourly particulate organic carbon data gop_do_r2 r-squared value of curve to hourly particulate organic carbon data gop_bbp Gross oxygen productivity calculated from gross carbon productivity (gpp_bbp) mol m-3 yr-1 gop_bbp_serr Standard error of gross oxygen productivity calculated from gross carbon productivity (gpp_bbp_serr) mol m-3 yr-1 npp_bbp Net primary productivity calculated from backscatter-based gross oxygen productivity (gop_bbp) mol m-3 yr-1 npp_bbp_serr Standard error of net primary productivity calculated from backscatter-based gross oxygen productivity (gop_bbp_serr) mol m-3 yr-1 npp_do Net primary productivity calculated from oxygen-based gross oxygen productivity (gop_do) mol m-3 yr-1 npp_do_serr Standard error of net primary productivity calculated from oxygen-based gross oxygen productivity (gop_do_serr) mol m-3 yr-1 Data for Fig. S1 | Description for number_of_bbp_profiles_in_each_year.csv and number_of_oxy_profiles_in_each_year.csv Variable Description Units year Year bbp470 Number of backscatter profiles oxygen_anom Number of oxygen profiles Variable Description Units mid_depth Depth of NPP profile m mean Mean volumetric 14C-NPP at depth mmol m-3 yr-1 median Median volumetric 14C-NPP at depth mmol m-3 yr-1 min Minimum volumetric 14C-NPP at depth mmol m-3 yr-1 maximum Maximum volumetric 14C-NPP mmol m-3 yr-1 Variable Description Units subset Number of profiles randomly sampled from the co-located dataset int_npp_do Euphotic-depth-integrated net primary productivity calculated from oxygen-based gross oxygen productivity mol m-2 y-1 int_npp_bbp Euphotic-depth-integrated net primary productivity calculated from backscatter-based gross oxygen productivity mol m-2 y-1 gop_do_r2 R-squared of the sinusoidal curve to the diel cycle of oxygen anomaly gpp_bbp_r2 R-squared of sinusoidal curve to the diel cycle of particulate organic carbon Variable Description Units ROSE Topographic (negative values are below sea level) m ETOPO05_Y Latitude degN ETOPO05_X Longitude degE Variable Description Units database Database the data was extracted from Month Month of NPP measurement month of year npp_14c Net primary productivity estimated from the radiocarbon method mmol m-3 y-1 depth depth of 14C-NPP measurement m

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