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Development of ocean measurement technologies can improve monitoring of the global Ocean Heat Content (OHC) and Heat Storage Rate (HSR) that serve as early-warning indices for climate-critical circulation processes such as the Atlantic Meridional Overturning Circulation and provide real-time OHC assessments for tropical cyclone forecast models. This paper examines the potential of remotely measuring ocean temperature profiles using a simulated Brillouin lidar for calculating ocean HSR. A series of data analysis ('Nature') and Observational Systems Simulation Experiments (OSSEs) were carried out using 26 years (1992–2017) of daily mean temperature and salinity outputs from the ECCOv4r4 ocean circulation model. The focus of this study is to compare various OSSEs carried out to measure the HSR using a simulated Brillouin lidar against the HSR calculated from the ECCOv4r4 model results. Brillouin lidar simulations are used to predict the probability of detecting a return lidar signal under varying sampling strategies. Correlations were calculated for the difference between sampling strategies. These comparisons ignore the measurement errors inherent in a Brillouin lidar. Brillouin lidar technology and instruments are known to contain numerous, instrument-dependent errors and remain an engineering challenge. A significant decrease in the ability to measuring global ocean HSRs is a consequence of measuring ocean temperature from nadir-pointing instruments that can only take measurements along-track. Other sources of errors include the inability to fully profile ocean regions with deep mixed layers, such as the Southern Ocean and North Atlantic, and ocean regions with high light attenuation levels. [ABSTRACT FROM AUTHOR]

Large marine ecosystems (LMEs) are highly productive regions of the world ocean under anthropogenic pressures; we analyzed trends in sea surface temperature (SST), cloud fraction (CF), and chlorophyll concentration (CHL) over the period 1998–2019. Trends in these parameters within LMEs diverged from the world ocean. SST and CF inside LMEs increased at greater rates inside LMEs, whereas CHL decreased at a greater rates. CHL declined in 86% of all LMEs and of those trends, 70% were statistically significant. Complementary analyses suggest phytoplankton functional types within LMEs have also diverged from those characteristic of the world ocean, most notably, the contribution of diatoms and dinoflagellates, which have declined within LMEs. LMEs appear to be warming rapidly and receiving less solar radiation than the world ocean, which may be contributing to changes at the base of the food chain. Despite increased fishing effort, fishery yields in LMEs have not increased, pointing to limitations related to productivity. These changes raise concerns over the stability of these ecosystems and their continued ability to support services to human populations. [ABSTRACT FROM AUTHOR]

Abstract: Ocean color remote sensing has provided the scientific community with unprecedented global coverage of chlorophyll a, an indicator of phytoplankton biomass. Together, satellite-derived chlorophyll a and knowledge of Phytoplankton Functional Types (PFTs) will improve our limited understanding of marine ecosystem responses to physiochemical climate drivers involved in carbon cycle dynamics and linkages. Using cruise data from the Gulf of Maine and the Middle Atlantic Bight (N=269 pairs of HPLC and phytoplankton absorption samples), two modeling approaches were utilized to predict phytoplankton absorption and pigments. Algorithm I predicts the chlorophyll-specific absorption coefficient ( (m2 mgchla−1)) using inputs of temperature, light, and chlorophyll a. Modeled r 2 values (400–700nm) ranged from 0.79 to 0.99 when compared to in situ observations with ∼25% lower r 2 values in the UV region. Algorithm II-a utilizes matrix inversion analysis to predict (m−1, 400–700nm) and r 2 values ranged from 0.89 to 0.99. The prediction of phytoplankton pigments with Algorithm II-b produced r 2 values that ranged from 0.40 to 0.93. When used in combination, Algorithm I, and Algorithm II-a are able to use satellite products of SST, PAR, and chlorophyll a (Algorithm I) to predict pigment concentrations and ratios to describe the phytoplankton community. The results of this study demonstrate that the spatial variation in modeled pigment ratios differ significantly from the 10-year SeaWiFS average chlorophyll a data set. Contiguous observations of chlorophyll a and phytoplankton biodiversity will elucidate ecosystem responses with unprecedented complexity. [Copyright &y& Elsevier]

Functional relationships which parameterize growth based on the Eppley temperature relationship for phytoplankton maximal growth rates are increasingly being used in marine and freshwater ecosystem models. In this paper, we demonstrate the effect of using such generalized relationships in modelling studies. Two suites of numerical experiments are carried out to investigate the sensitivity of models to generalized growth relationships. In each experiment, 100 individual species or groups of phytoplankton are allowed to compete under a variety of growth versus temperature relationships. One suite of experiments is carried out within a simple ‘chemostat’ type model that is forced with seasonally varying temperature and photosynthetically available radiation (PAR) fields. A second suite of experiments is carried out using a biogeochemical mixed-layer model to demonstrate the sensitivity of these models to various temperature versus growth relationships. The key difference in the biogeochemical mixed-layer simulations is in the timing of the ecosystem response to seasonal variability of the mixed-layer depth and temperature. The Eppley growth versus temperature relationship overestimates phytoplankton growth by as much as 80% during the spring when growth rates are crucial to the timing of the spring blooms. This decrease in growth rates causes a delay in the spring phytoplankton bloom which in turn results in significant changes in all other model constituents. The results from both suites of experiments show that it is important to resolve the intrinsic growth dynamics of a population in order to properly resolve the maximum growth rates of phytoplankton populations. The results also present a possible explanation for why phytoplankton are commonly found growing within water colder than their optimal temperature for growth. A dynamic growth versus temperature model is introduced that is capable of resolving the growth dynamics of a population of phytoplankton under a variety of temperature forcing scenarios. This new growth versus temperature model/relationship will be useful in global biogeochemical models and demonstrates the importance of underlying population dynamics in controlling bulk community growth estimates. [Copyright &y& Elsevier]

Predicting the impact of marine ecosystem warming on the timing and magnitude of phytoplankton production is challenging. For example, warming can advance the progression of stratification thereby changing the availability of nutrients to surface phytoplankton, or influence the surface mixed layer depth, thus affecting light availability. Here, we use a time series of sea surface temperature (SST) and chlorophyll remote sensing products to characterize the response of the phytoplankton community to increased temperature in the Northeast US Shelf Ecosystem. The rate of change in SST was higher in the summer than in winter in all ecoregions resulting in little change in the timing and magnitude of the spring thermal transition compared to a significant change in the autumn transition. Along with little phenological shift in spring thermal conditions, there was also no evidence of a change in spring bloom timing and duration. However, we observed a change in autumn bloom timing in the Georges Bank ecoregion, where bloom initiation has shifted from late September to late October between 1998 and 2020—on average 33 d later. Bloom duration in this ecoregion also shortened from ∼7.5 to 5 weeks. The shortened autumn bloom may be caused by later overturn in stratification known to initiate autumn blooms in the region, whereas the timing of light limitation at the end of the bloom remains unchanged.  These changes in bloom timing and duration appear to be related to the change in autumn thermal conditions and the significant shift in autumn thermal transition. These results suggest that the spring bloom phenology in this temperate continental shelf ecosystem may be more resilient to thermal climate change effects than blooms occurring in other times of the year. [ABSTRACT FROM AUTHOR]

Abstract: We study the dynamics of the planktonic ecosystem in the coastal upwelling zone within the California Current System using a three-dimensional (3-D), eddy-resolving circulation model coupled to an ecosystem/biogeochemistry model. The physical model is based on the Regional Oceanic Modeling System (ROMS), configured at a resolution of 15km for a domain covering the entire US West Coast, with an embedded child grid covering the central California upwelling region at a resolution of 5km. The model is forced with monthly mean boundary conditions at the open lateral boundaries as well as at the surface. The ecological/biogeochemical model is nitrogen based, includes single classes for phytoplankton and zooplankton, and considers two detrital pools with different sinking speeds. The model also explicitly simulates a variable chlorophyll-to-carbon ratio. Comparisons of model results with either remote sensing observations (AVHRR, SeaWiFS) or in-situ measurements from the CalCOFI program indicate that our model is capable of replicating many of the large-scale, time-averaged features of the coastal upwelling system. An exception is the underestimation of the chlorophyll levels in the northern part of the domain, perhaps because of the lack of short-term variations in the atmospheric forcing. Another shortcoming is that the modeled thermocline is too diffuse, and that the upward slope of the isolines toward the coast is too small. Detailed time-series comparisons with observations from Monterey Bay reveal similar agreements and discrepancies. We attribute the good agreement between the modeled and observed ecological properties in large part to the accuracy of the physical fields. In turn, many of the discrepancies can be traced back to our use of monthly mean forcing. Analysis of the ecosystem structure and dynamics reveal that the magnitude and pattern of phytoplankton biomass in the nearshore region are determined largely by the balance of growth and zooplankton grazing, while in the offshore region, growth is balanced by mortality. The latter appears to be inconsistent with in situ observations and is a result of our consideration of only one zooplankton size class (mesozooplankton), neglecting the importance of microzooplankton grazing in the offshore region. A comparison of the allocation of nitrogen into the different pools of the ecosystem in the 3-D results with those obtained from a box model configuration of the same ecosystem model reveals that only a few components of the ecosystem reach a local steady-state, i.e. where biological sources and sinks balance each other. The balances for the majority of the components are achieved by local biological source and sink terms balancing the net physical divergence, confirming the importance of the 3-D nature of circulation and mixing in a coastal upwelling system. [Copyright &y& Elsevier]

Satellite and in situ observations are used to test model dynamics for the California Current System (CCS). The model and data are combined to reconstruct the mesoscale ocean structure during a given three-week period. The resulting physical flow field is used to drive a 3D ecosystem model to interpret SeaWiFS and in situ chlorophyll- a (chl- a ) variations. With this approach a more complete and consistent picture of the physical and ecosystem processes of the CCS is obtained, providing the basis for addressing fundamental questions about dynamics and predictability of the coastal ocean. [ABSTRACT FROM AUTHOR]