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