A comparison of the variability of biological nutrients against depth and potential density

Abstract

Abstract. The main biogeochemical nutrient distributions, along with ambient ocean temperature and the light field, control ocean biological productivity. Observations of nutrients are much sparser than physical observations of temperature and salinity, yet it is critical to validate biogeochemical models against these sparse observations if we are to successfully model biological variability and trends. Here we use data from the Bermuda Atlantic Time-series Study and the World Ocean Database 2005 to demonstrate quantitatively that over the entire globe a significant fraction of the temporal variability of phosphate, silicate and nitrate within the oceans is correlated with water density. The temporal variability of these nutrients as a function of depth is almost always greater than as a function of potential density, with he largest reductions in variability found within the main pycnocline. The greater nutrient variability as a function of depth occurs when dynamical processes vertically displace nutrient and density fields together on shorter timescales than biological adjustments. These results show that dynamical processes can have a significant impact on the instantaneous nutrient distributions. These processes must therefore be considered when modeling biogeochemical systems, when comparing such models with observations, or when assimilating data into such models.

Large-scale alignment of oceanic nitrate and density

“…[42] Oceanic nitrate is known to correlate more strongly with density than with depth, though the biological pump tends to redistribute nitrate in a depth dependent fashion. Reduced variance of nitrate on isopycnals, as compared to isobars, is often ascribed to the vertical movement of isopycnal surfaces [While and Haines, 2010;Ascani et al, 2013]. We show in fact, a significant alignment between isonitrate and isopycnal surfaces persists in time-averaged data at large scales.…”

“…[22] In general, we find that the time-averaged NO 3 in the twilight zone is closely related to isopycnals. A similar analysis by While and Haines [2010] computed the spatial variance of NO 3 , and found that the ratio between the NO 3 variance on isobars and isopycnals was larger than 1 for more than 79% of the global 5 Â5 grid cells analyzed. Ascani et al [2013] also used APEX profiling floats in the subtropical Pacific to explore the variance of NO 3 on iso-pycnals.…”

“…[4] Recent studies have analyzed the variability of nitrate on isobars and isopycnals. While and Haines [2010] calculate the variance of the measured nitrate from profiles that constitute the World Ocean Atlas within 28Â2 bins.…”

The shape of the oceanic nitracline

“…Strickland (1970) was probably the first to find that over weeks, density could be used to predict nitrate to almost within experimental accuracy irrespective of the depth of the nutrient measurement. Recent studies (McGillicuddy et al, 1999;While and Haines, 2010;Ascani et al, 2013) have confirmed that nitrate is better correlated with density than with depth in the ocean. By relating isopycnal excursions with sea surface height, Ascani et al (2013) used the data from profiling floats to show that a higher variability of nitrate along isobars, as compared to isopycnals, on timescales ranging from hours to weeks, can be ascribed to the movement of isopycnal surfaces by internal waves and eddies.…”

Seasonal variability of nutrient concentrations in the Mediterranean Sea: Contribution of Bio‐Argo floats

“…In particular, it is up to 32 times smaller in the LEV, where the [NO 3 ] variability is the highest (i.e., [NO 3 ] values at 300 m depth vary from around 2 to 6 mM, Figure 7a; almost constant around 4 mM for [NO 3 ] at a fixed density, Figure 7b). Such a coorientation of [NO 3 ] with density is often observed because dynamical processes that vertically displace water masses with their properties are generally strong, compared to the biological pump [Ascani et al, 2013;Omand and Mahadevan, 2013;While and Journal of Geophysical Research: Oceans 10.1002/2015JC011103 Haines, 2010]. The variability of [NO 3 ] on isobars (Figure 7a) is, however, intriguing, as it informs on the increase/decrease of the availability of NO 3 in the enlightened layer.…”