DOI: 10.5281/zenodo.6977160
title: Processing and Data for "Estimating ocean net primary productivity from daily cycles of carbon biomass measured by profiling floats"

description: 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