Modeling the Recent Changes of Phytoplankton Blooms Dynamics in the Arctic Ocean

Abstract

and mostly due to a well-documented climate warming trend (Rantanen et al., 2022). However, the current spatial and temporal variations in AO stratification seem to be controlled not only by the sea-ice melting and ocean warming but also by the intensity of the wind and of the riverine freshwater runoff (Hordoir et al., 2022). Additionally, even the changes in advection of water masses from the subpolar regions (both Atlantic and Pacific) can modify the AO stratification (Polyakov et al., 2020). The seasonal cycle of sea-ice melt and accretion strongly regulates the life cycle of AO phytoplankton (Janout et al., 2016). Kahru et al. (2010Kahru et al. ( , 2016 used remote-sensing observations to show that in the surface AO the spring phytoplankton bloom (SPB) timing has occurred earlier in recent decades and hypothesized that this was due to the earlier break-up of sea ice driven by climate warming. In the temperate and high-latitude oceans the SPB usually starts its development because of the reduction in light limitation caused by the increased seasonal stratification of the water column (Siegel et al., 2002) induced by the reduction in convection-driven mixing (Mignot et al., 2018). These specific conditions of the physical ocean allow marine phytoplankton to spend enough time in the euphotic zone boosting their cell doubling rate and exceed their mortality rate. These environmental conditions can then trigger a SPB even in the polar oceans (Behrenfeld et al., 2017;Uchida et al., 2019) where the

Quantifying Regional Efficiency of Marine Carbon Dioxide Removal (mCDR) via Alkalinity Enhancement using the ECCO-Darwin Ocean Biogeochemistry State Estimate and an Idealized Vertical 1-D Model

“…For the pulse experiments, mCDR eff is evaluated using Equation 2, where the cumulative OAE additionality is estimated from the difference in simulated CO 2 flux between OAE and baseline/unperturbed simulations. This approach can be computation- The ECCO-Darwin model and data assimilation methods have been extensively described in the literature (e.g., Brix et al, 2015;Manizza et al, 2019Manizza et al, , 2023Carroll et al, 2020Carroll et al, , 2022Bertin et al, 2023). In particular, a technical description of the ECCO-Darwin model set-up, observational constraints, and optimization methodology is presented in Carroll et al (2020).…”

Revealing the seasonal cycles of Arctic phytoplankton: insights from year-round chlorophyll monitoring

“…For example, under dominant first-year ice in the Arctic Ocean, wider melt pond coverage has greater light transmission than bare ice, causing a change in the underwater light field (Kwok et al 2011, Stroeve and Notz 2018, Shu et al 2022. Early sea ice retreats or delayed sea ice advances have led to changes in the early phytoplankton and fall blooms in the Arctic Ocean (Kahru et al 2011, Ardyna et al 2014, Manizza et al 2023. Two factors contribute to primary production increase in the Arctic Ocean.…”