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