Large-scale alignment of oceanic nitrate and density

Abstract

[1] By analyzing global data, we find that over large scales, surfaces of constant nitrate are often better aligned with isopycnals than with isobars, particularly below the euphotic zone. This is unexplained by the movement of isopycnal surfaces in response to eddies and internal waves, and is perhaps surprising given that the biological processes that alter nitrate distributions are largely depth dependent. We provide a theoretical framework for understanding the orientation of isonitrate surfaces in relation to isopycnals. In our model, the nitrate distribution results from the balance between depth-dependent biological processes (nitrate uptake and remineralization), and the along-isopycnal homogenization of properties by eddy fluxes (parameterized by eddy diffusivity). Where the along-isopycnal eddy diffusivity is relatively large, nitrate surfaces are better aligned with isopycnals than isobars. We test our theory by estimating the strength of the eddy diffusivity and biological export production from global satellite data sets and comparing their contributions. Indeed, we find that below the euphotic zone, the mean isonitrate surfaces are oriented along isopycnals where the isopycnal eddy diffusivity is large, and deviate where the biological export of organic matter is relatively strong. Comparison of nitrate data from profiling floats in different regions corroborates the hypothesis by showing variations in the nitrate-density relationship from one part of the ocean to another.Citation: Omand, M. M., and A. Mahadevan (2013), Large-scale alignment of oceanic nitrate and density,

Impact of decadal reversals of the north Ionian circulation on phytoplankton phenology

“…As previously demonstrated for the global ocean (While and Haine, 2010;Omand and Mahadevan, 2013), the depth of an isopycnal can be representative of the nitracline depth in the case of a stratified water column. This is confirmed in the north Ionian from the obtained linear relationship between the depth of the nitracline and the 28.9 kg m −3 isopycnal (Fig.…”

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 µ M , Figure a; almost constant around 4 µ M for [NO 3 ] at a fixed density, Figure b). 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 ., ; Omand and Mahadevan , ; While and Haines , ]. The variability of [NO 3 ] on isobars (Figure a) is, however, intriguing, as it informs on the increase/decrease of the availability of NO 3 in the enlightened layer.…”

The shape of the oceanic nitracline

“…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. The relationship between nitrate and density also extends to longer time-and space scales, leading to a large-scale alignment between the mean isopycnal and iso-nitrate surfaces (Omand and Mahadevan, 2015).…”

“…Algorithms that exploit the nitrate-temperature relationship have also been developed for remotely sensed sea surface temperature (SST) and ocean color (Dugdale et al, 1989;Goes et al, 2000;Switzer et al, 2003); however, the strong correlation between nitrate and temperature tends to break down near the surface as biological effects and upperocean heat fluxes alter the relationship (Garside and Garside, 1995). Biological processes challenge the predictive capacity of the empirical algorithms, and there are relatively few simple mechanistic models for oceanic-nitrate distribution in density coordinates (Kamykowski, 1987;Dugdale et al, 1989;Omand and Mahadevan, 2015).…”