Sea Surface Nitrate and Nitrate Based New Production - two innovative research products
from SGLI on board GCOM-C
ALGORITHM THEORETICAL BASIS DOCUMENT
Principal Investigator:
Joaquim I. Goes
Lamont Doherty Earth Observatory
Columbia University
Phone: 845-365-8988
Email: jig@ldeo.columbia.edu
Co -Investigators:
Helga do Rosario Gomes
Lamont Doherty Earth Observatory
Columbia University
Email: helga@ldeo.columbia.edu

Joji Ishizaka
Division for Land-Ocean Ecosystem ResearchInstitute for Space-Earth Environmental Research (ISEE)
Nagoya University
Furo-cho, Chikusa-ku, Nagoya, Aichi, Japan 464-8601
E-mail: jishizaka@nagoya-u.jp
Makio Honda
Department of Environmental Geochemical Research
Japan Agency for Marine-Earth Science and Technology (JAMSTEC)
Department of Environmental Geochemical Cycle Research
2-15 Natsushima, Yokosuka, Japan, 237-0061
hondam@jamstec.go.jp

I. Introduction:
Ocean ecosystems play a critical role in the Earth’s carbon (C) cycle through net primary
production (NPP) processes that fix dissolved CO2 into organic matter in the well-lit, surface
oceans, and C export into the deep ocean via the biological pump (Siegel et al., 2015). A major
fraction of this C transported (export carbon) into the oceans’ interior is associated withallochthonous nitrogen inputs, primarily inorganic nitrate into the euphotic zone (Eppley andPeterson, 1979; Dugdale and Goering, 1967). In oceanic regions outside of coastal marginal
zones, and away from the influence of terrestrial inputs, inorganic nitrate inputs from below theeuphotic zone represent a very important source of new nitrogen. Hence, understanding thespatial and temporal variations of inorganic nitrate in the euphotic layer over basin and global
scales is an important requirement for ocean biogeochemical process studies (Fasham et al.,2001).
Despite its importance, nitrate data obtainable by traditional shipboard techniques fall far
short of the spatial and temporal scales required for global climate research. This is especiallytrue for high latitude areas which continue to remain chronically under sampled, particularly in
winter when shipboard expeditions are difficult to conduct. Yet high latitude regions areimportant sinks for atmospheric CO2. Most observational and modeling studies of C export(Strass and Woods, 1991; Glover et al., 1994) rely on nitrate maps constructed using multi-year
data sets such as that of the NOAA National Oceanographic Data Centre (NODC) Atlas (Garciaet al., 2010). For climate-change and ocean C cycling studies, when the purpose is to study
interannual variations in C export, the utility of these climatological maps is rather limited.
Satellites have been suggested as a useful alternative, but although they can provide
frequent, large-scale, near surface views of several variables relevant to phytoplankton ecology
such as incident radiation, chlorophyll a and sea surface temperature (SST), nitratemeasurements from space have remained elusive as most nutrients including nitrate lack anelectro-magnetic signal that can be exploited from space.
This document presents the algorithm theoretical basis for deriving sea surface nitrate andnitrate based new production from satellite data.
II. Sea surface nitrate algorithm
There have been previous attempts to estimate seawater nitrate concentrations using proxies,
one being temperature which bears a strong inverse relationship with N (Kamykowski andZentara, 1986). This is because seawater temperature and nitrate concentrations are tightly
coupled as major inputs of nutrients into the euphotic zone occur through the intrusion of colder,nitrate-rich waters from deeper depths. Although empirical algorithms based on SST and nitrate
relationships have been in existence for quite a while (Chavez et al., 1996) their application overlarge temporal and spatial domains has been frustrated by the time and space varying nature of
the relationship (Garside and Garside, 1995; Chavez et al., 1996). One reason for thesevariations is that SST-nitrate relationships, is that the algorithms do not account for changes innitrate that arise from phytoplankton photosynthesis and growth (Goes et al., 1999; 2000;SilioCalzada et al., 2008; Hutahaean et al., 2010 ).
We have shown previously (Goes et al., 1999; 2000), that if biologically mediated changes in
the character of temperature-nitrate relationships are taken into account, remote sensing can beexploited to provide high-resolution maps of sea surface nitrate that are valid over much larger

scales than previously possible. Chlorophyll a was chosen as a predictor biological variable, largely,
because of its known relationship with sea surface nitrate in the euphotic zone, and its accessibility
from space in conjunction with SST. In our earlier studies we used data from several cruises to theNorth Pacific Ocean, covering different water types and different seasons were used to develop a setof algorithms that could predict SSN from T and Chl a.
The algorithms for nitrate take the general form as follows:
Sea surface nitrate = f1(SST) – f2(Chl a)III. Nitrate-based new production algorithm
In Goes et al. (2000), we show how SSN maps could be exploited to estimate new
production fueled by the supply of nitrate inputs during winter convective mixing in the subarctic
Pacific Ocean. In high latitude regions this input of nutrients supports the largest fraction of new
production occurring annually in the world’s major ocean basins (Strass and Woods, 1991;
Glover et al., 1994). By estimating the drawdown of nitrate within the euphotic zone over thegrowth season, we showed that it was possible to obtain estimates of C export that comparedwell with traditional shipboard sediment trap C export flux measurements. Although these newproduction estimates represent a lower bound estimate for total global ocean export production(as it does not account for C export that could result from other new nitrogen inputs into thesystem such as from N2 fixation or aerosol dust inputs into the ocean etc.), they do provide a
synoptic view of high-C export areas and regions where the dominant drivers are convective
overturning and coastal upwelling.
The algorithm for nitrate based new production, takes the following form
Nitrate based new production =[ED [NO3(0)- NO3(t)] * R]/t
Where =ED [NO3(0)- NO3(t)] is the amount of nitrate drawn down from the euphotic zone overthe growth season (for instance from the start of the spring bloom in March, to the end of thesummer bloom in Sept. in the North Atlantic or North Pacific ) of phytoplankton and R is thefactor for converting nitrogen into C units and t is the time interval over which nitrate drawdown
is calculated.
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