This dataset includes the post-processed data and a demo MATLAB script used for the paper titled "Global trends of fronts in a warming ocean and impacts on phytoplankton productivity" SST_FRONT_data.zip contains maps of sea surface temperature (SST) fronts detected by the Cayula and Cornillon single image edge detection algorithm over global ocean warming hotspot regions and covering the period 2003-2020. The original data was obtained from NASA OB.DAAC MODIS sea surface temperature (SST) product (MODIS Aqua Level 3 SST MID-IR 8 Day 4km Nighttime V2019.0: https://podaac.jpl.nasa.gov/dataset/MODIS_AQUA_L3_SST_MID-IR_8DAY_4KM_NIGHTTIME_V2019.0?ids=&values=&search=MODIS%20Aqua&provider=POCLOUD). Fdens_Ffreq_Fstre_example.mlx is a MATLAB live script showing how to compute metrics of fronts based on frontal maps: frontal frequency (Ffreq), frontal density (Fdens), and frontal strength (Fstre).
Abstract Ocean temperature extreme events such as marine heatwaves are expected to intensify in coming decades due to anthropogenic global warming. Reported ecological and economic impacts of marine heatwaves include coral bleaching, local extinction of mangrove and kelp forests and elevated mortalities of invertebrates, fishes, seabirds and marine mammals. In contrast, little is known about the impacts of marine heatwaves on microbes that regulate biogeochemical processes in the ocean. Here we analyse the daily output of a near‐global ocean physical–biogeochemical model simulation to characterize the impacts of marine heatwaves on phytoplankton blooms in 23 tropical and temperate oceanographic regions from 1992 to 2014. The results reveal regionally coherent anomalies of shallower surface mixing layers and lower surface nitrate concentrations during marine heatwaves. These anomalies exert counteracting effects on phytoplankton growth through light and nutrient limitation. Consequently, the responses of phytoplankton blooms are mixed, but can be related to the background nutrient conditions of the study regions. The blooms are weaker during marine heatwaves in nutrient‐poor waters, whereas in nutrient‐rich waters, the heatwave blooms are stronger. The corresponding analyses of sea‐surface temperature, chlorophyll a and nitrate based on satellite observations and in situ climatology support this relationship between phytoplankton bloom anomalies and background nitrate concentration. Given that nutrient‐poor waters are projected to expand globally in the 21st century, this study suggests increased occurrence of weaker blooms during marine heatwaves in coming decades, with implications for higher trophic levels and biogeochemical cycling of key elements.
This dataset includes the post-processed data and a demo MATLAB script used for the paper titled "Global trends of fronts and chlorophyll in a warming ocean" SST_FRONT_data.zip contains maps of sea surface temperature (SST) fronts detected by the Cayula and Cornillon single image edge detection algorithm over global ocean warming hotspot regions and covering the period 2003-2020. The original data was obtained from NASA OB.DAAC MODIS sea surface temperature (SST) product (MODIS Aqua Level 3 SST MID-IR 8 Day 4km Nighttime V2019.0: https://podaac.jpl.nasa.gov/dataset/MODIS_AQUA_L3_SST_MID-IR_8DAY_4KM_NIGHTTIME_V2019.0?ids=&values=&search=MODIS%20Aqua&provider=POCLOUD). SST_FRONT_data.zip also contains Fdens_Ffreq_Fstre_example.mlx, whichis a MATLAB live script showing how to compute metrics of fronts based on frontal maps: frontal frequency (Ffreq), frontal density (Fdens), and frontal strength (Fstre). Fdens_Ffreq_Fstre_example.pdf is intended for quick viewing of the script above.
ABSTRACT The original at-launch SeaWiFS algorithm (OC2 for Ocean Chlorophyll 2-band algorithm) was derived fromthe SeaBAM data set (N = 919) which contains coincident remote sensing reflectance, /}rs, and in situ chlo-rophyll a, Ca, measurements from a variety of oceanic provinces. Following the SeaWiFS launch, the accuracyof SeaWiFS chlorophyll a estimates using the OC2 algorithm was evaluated against new in situ measurements.These new data indicated that OC2 was performing generally well in Case-1 waters with Ca concentration,between 0.03-1 mgm -a, but tended to overestimate (_a at higher concentrations. To strengthen the SeaBAMdata set at Ca > 1 mgm -3, 255 new stations were added to the original data set. These new data generallyshowed lower Rrs(490)/R,s(555) band ratios at C'a > 4mgm -3 than in the original SeaBAM data set, whichwould explain some of the overestimations observed with OC2. The new SeaBAM data set was used to refine thecoefficients for the OC2 MCP function. The updated algorithm (OC2v2) is presented along with its statisticalperformance and a Comparison with the original version of the algorithm.
Non-photochemical quenching (NPQ) within phytoplankton cells often causes the daytime suppression of chlorophyll fluorescence in the Southern Ocean. This is problematic and requires accurate correction when chlorophyll fluorescence is used as a proxy for chlorophyll-a concentration or phytoplankton abundance. In this study, we reveal that Southern Ocean subsurface chlorophyll maxima (SCMs) are the largest source of uncertainty when correcting for NPQ of chlorophyll fluorescence profiles. A detailed assessment of NPQ correction methods supports this claim by taking advantage of coincident chlorophyll fluorescence and chlorophyll concentration profiles. The best performing NPQ correction methods are conditional methods that consider the mixed layer depth (MLD), subsurface fluorescence maximum (SFM) and depth of 20% surface light. Compared to existing methods, the conditional methods proposed halve the bias in corrected chlorophyll fluorescence profiles and improve the success of replicating a SFM relative to chlorophyll concentration profiles. Of existing methods, the X12 and P18 methods, perform best overall, even when considering methods supplemented by beam attenuation or backscatter data. The widely-used S08 method, is more varied in its performance between profiles and its application introduced on average up to 2% more surface bias. Despite the significant improvement of the conditional method, it still underperformed in the presence of an SCM due to 1) changes in optical properties at the SCM and 2) large gradients of chlorophyll fluorescence across the pycnocline. Additionally, we highlight that conditional methods are best applied when uncertainty in chlorophyll fluorescence yields is within 50%. This highlights the need to better characterize the bio-optics of SCMs and chlorophyll fluorescence yields in the Southern Ocean, so that chlorophyll fluorescence data can be accurately converted to chlorophyll concentration in the absence of in situ water sampling.
In climate-ocean models, eddy mixing coefficients are often constant in space and time. However, observations, advances in theory, and high-resolution-eddy-resolving ocean models have revealed significant variability in the strength of isopycnal mixing both spatially and temporally. A theory that includes the effect of mean flow suppression has been developed by [1] it has a strong impact on tracer uptake and ventilation. This theory is used in offline calculations by [1, 2, 4] but has not been implemented as a parameterization in an ocean model and in this study we implement it for the first time in an ocean model [3]. The parameterization is tested in a non-eddy-resolving ocean model, demonstrating passive ventilation of a tracer as a function of depth and latitude. The first main result is this parameterization improves the mean state of the ocean. The other result is this parameterization improves the sensitivity of tracer uptake to changing winds.
Perturbations to phytoplankton biomass associated with the onset of the 1997–98 El Niño event are described and explained using physical and bio‐optical data from moorings in the central equatorial Pacific. The physical progression of El Niño onset is depicted, from reversal of the trade winds in the western equatorial Pacific, through eastward propagation of equatorially trapped Kelvin waves and advection of waters from the nutrient‐poor western equatorial warm pool. Fluctuations in chlorophyll and quantum yield of fluorescence are tightly coupled to thermocline variations.
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