scholarly journals Assessing the Skills of a Seasonal Forecast of Chlorophyll in the Global Pelagic Oceans

2021 ◽  
Vol 13 (6) ◽  
pp. 1051
Author(s):  
Cecile S. Rousseaux ◽  
Watson W. Gregg ◽  
Lesley Ott
Keyword(s):  
Ocean Circulation ◽  
North Atlantic ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Chlorophyll Concentration ◽  
Correlation Coefficients ◽  
Global Scale ◽  
Seasonal Forecasts ◽  
Mean Square Errors ◽  
Satellite Chlorophyll

While forecasts of atmospheric variables, and to a lesser degree ocean circulation, are relatively common, the forecast of biogeochemical conditions is still in its infancy. Using a dynamical ocean biogeochemical forecast forced by seasonal forecasts of atmospheric and physical ocean variables, we produce seasonal predictions of chlorophyll concentration at the global scale. Results show significant Anomaly Correlation Coefficients (ACCs) for the majority of regions (11 out of the 12 regions for the 1-month lead forecast). Root mean square errors are smaller (<0.05 µg chlorophyll (chl) L−1) in the Equatorial regions compared to the higher latitudes (range from 0.05 up to 0.13 µg chl L−1). The forecast for all regions except three (North Atlantic, South Pacific and North Indian) are within the Semi-Interquartile Range of the satellite chlorophyll concentration (Suomi-National Polar-orbiting Partnership (NPP), 27.9%). This suggests the potential for skillful global biogeochemical forecasts on seasonal timescales of chlorophyll, primary production and harmful algal blooms that could support fisheries management and other applications.

Viewpoints of Dominant Environmental Factors Influencing Algal Blooms

2011 ◽  
Vol 66-68 ◽  
pp. 155-159
Author(s):  
Di Guan ◽  
Da Wen Gao ◽  
Nan Qi Ren ◽  
Yi Fan Li
Keyword(s):  
Environmental Factors ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Meteorological Factors ◽  
Chlorophyll Concentration ◽  
Phytoplankton Growth ◽  
High Biomass ◽  
Coupling Effects ◽  
Factors Influencing

Harmful algal blooms (HABs) are generally known as excessive phytoplankton growth or rapidly concentrate to high biomass. This study summarized the situation of HABs in China, and discussed possible dominant factors stimulating algal blooms by analyzing several actual HABs cases. It was manifested nutrients may affect algae concentration principally, but such impact tended to decease with degradation of background water. Meanwhile the hydrological and meteorological factors expressed greater correlation to chlorophyll concentration under multiple coupling effects of complex environmental factors. For the complex mechanisms, the determination of principle factors which stimulate excessive algal blooms effectively still need further researches, which are suggested to conduct under overall considerations on 3 scales: macro dimension, medium dimension and micro dimension.

The North Atlantic Oscillation and the Arctic Oscillation favour harmful algal blooms in SW Europe

Harmful Algae ◽  
2014 ◽  
Vol 39 ◽  
pp. 121-126 ◽  
Author(s):  
José C. Báez ◽  
Raimundo Real ◽  
Victoria López-Rodas ◽  
Eduardo Costas ◽  
A. Enrique Salvo ◽  
...  
Keyword(s):  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Arctic Oscillation ◽  
The Arctic ◽  
The North ◽  
The North Atlantic ◽  
The Arctic Oscillation ◽  
The North Atlantic Oscillation

scholarly journals Harmful algal blooms in the Eastern North Atlantic Ocean

2017 ◽  
Vol 114 (46) ◽  
pp. E9763-E9764 ◽  
Author(s):  
Paul Dees ◽  
Eileen Bresnan ◽  
Andrew C. Dale ◽  
Martin Edwards ◽  
David Johns ◽  
...  
Keyword(s):  
Atlantic Ocean ◽  
North Atlantic ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
North Atlantic Ocean ◽  
Eastern North Atlantic ◽  
Eastern North Atlantic Ocean

scholarly journals Controllability of mixing errors in a coupled physical biogeochemical model of the North Atlantic: a nonlinear study using anamorphosis

2009 ◽  
Vol 6 (2) ◽  
pp. 1289-1332 ◽  
Author(s):  
D. Béal ◽  
P. Brasseur ◽  
J.-M. Brankart ◽  
Y. Ourmières ◽  
J. Verron
Keyword(s):  
Ocean Circulation ◽  
North Atlantic ◽  
Estimation Error ◽  
Chlorophyll Concentration ◽  
Observation System ◽  
Biogeochemical Model ◽  
Significant Information ◽  
The North ◽  
Biogeochemical Models ◽  
The North Atlantic

Abstract. In biogeochemical models coupled to ocean circulation models, vertical mixing is an important physical process which governs the nutrient supply and the plankton residence in the euphotic layer. However, mixing is often poorly represented in numerical simulations because of approximate parameterizations of sub-grid scale turbulence, wind forcing errors and other mis-represented processes such as restratification by mesoscale eddies. Getting a sufficient knowledge of the nature and structure of these error sources is necessary to implement appropriate data assimilation methods and to evaluate their controllability by a given observation system. In this paper, Monte Carlo simulations are conducted to study mixing errors induced by approximate wind forcings in a three-dimensional coupled physical-biogeochemical model of the North Atlantic with a 1/4° horizontal resolution. An ensemble forecast involving 200 members is performed during the 1998 spring bloom, by prescribing realistic wind perturbations to generate mixing errors. It is shown that the biogeochemical response can be rather complex because of nonlinearities and threshold effects in the coupled model. In particular, the response of the surface phytoplankton depends on the region of interest and is particularly sensitive to the local stratification. We examine the robustness of the statistical relationships computed between the various physical and biogeochemical variables, and we show that significant information on the ecosystem can be obtained from observations of chlorophyll concentration or sea surface temperature. In order to improve the analysis step of sequential assimilation schemes, we propose to perform a simple nonlinear change of variables that operates separately on each state variable, by mapping their ensemble percentiles on the Gaussian percentiles. It is shown that this method is able to substantially reduce the estimation error with respect to the linear estimates computed by the Kalman filter.

scholarly journals Statistical–Dynamical Seasonal Forecast of North Atlantic and U.S. Landfalling Tropical Cyclones Using the High-Resolution GFDL FLOR Coupled Model

2016 ◽  
Vol 144 (6) ◽  
pp. 2101-2123 ◽  
Author(s):  
Hiroyuki Murakami ◽  
Gabriele Villarini ◽  
Gabriel A. Vecchi ◽  
Wei Zhang ◽  
Richard Gudgel
Keyword(s):  
High Resolution ◽  
Hybrid Model ◽  
North Atlantic ◽  
Large Scale ◽  
Linear Models ◽  
Climate Model ◽  
Coupled Model ◽  
Correlation Coefficients ◽  
Hybrid Models ◽  
Seasonal Forecasts

Abstract Retrospective seasonal forecasts of North Atlantic tropical cyclone (TC) activity over the period 1980–2014 are conducted using a GFDL high-resolution coupled climate model [Forecast-Oriented Low Ocean Resolution (FLOR)]. The focus is on basin-total TC and U.S. landfall frequency. The correlations between observed and model predicted basin-total TC counts range from 0.4 to 0.6 depending on the month of the initial forecast. The correlation values for U.S. landfalling activity based on individual TCs tracked from the model are smaller and between 0.1 and 0.4. Given the limited skill from the model, statistical methods are used to complement the dynamical seasonal TC prediction from the FLOR model. Observed and predicted TC tracks were classified into four groups using fuzzy c-mean clustering to evaluate the model’s predictability in observed classification of TC tracks. Analyses revealed that the FLOR model has the highest skill in predicting TC frequency for the cluster of TCs that tracks through the Caribbean and the Gulf of Mexico. New hybrid models are developed to improve the prediction of observed basin-total TC and landfall TC frequencies. These models use large-scale climate predictors from the FLOR model as predictors for generalized linear models. The hybrid models show considerable improvements in the skill in predicting the basin-total TC frequencies relative to the dynamical model. The new hybrid model shows correlation coefficients as high as 0.75 for basinwide TC counts from the first two lead months and retains values around 0.50 even at the 6-month lead forecast. The hybrid model also shows comparable or higher skill in forecasting U.S. landfalling TCs relative to the dynamical predictions. The correlation coefficient is about 0.5 for the 2–5-month lead times.

scholarly journals A novel random forest approach to revealing interactions and controls on chlorophyll concentration and bacterial communities during coastal phytoplankton blooms

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yiwei Cheng ◽  
Ved N. Bhoot ◽  
Karl Kumbier ◽  
Marilou P. Sison-Mangus ◽  
James B. Brown ◽  
...  
Keyword(s):  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Chlorophyll Concentration ◽  
Ecosystem Structure ◽  
Monterey Bay ◽  
Phytoplankton Abundance ◽  
Abundance Patterns ◽  
Machine Learning Model ◽  
Marine Algal ◽  
Coastal Phytoplankton

AbstractIncreasing occurrence of harmful algal blooms across the land–water interface poses significant risks to coastal ecosystem structure and human health. Defining significant drivers and their interactive impacts on blooms allows for more effective analysis and identification of specific conditions supporting phytoplankton growth. A novel iterative Random Forests (iRF) machine-learning model was developed and applied to two example cases along the California coast to identify key stable interactions: (1) phytoplankton abundance in response to various drivers due to coastal conditions and land-sea nutrient fluxes, (2) microbial community structure during algal blooms. In Example 1, watershed derived nutrients were identified as the least significant interacting variable associated with Monterey Bay phytoplankton abundance. In Example 2, through iRF analysis of field-based 16S OTU bacterial community and algae datasets, we independently found stable interactions of prokaryote abundance patterns associated with phytoplankton abundance that have been previously identified in laboratory-based studies. Our study represents the first iRF application to marine algal blooms that helps to identify ocean, microbial, and terrestrial conditions that are considered dominant causal factors on bloom dynamics.

National coastal management challenges and needs

Shore & Beach ◽  
2020 ◽  
pp. 34-43
Author(s):  
Nicole Elko ◽  
Tiffany Roberts Briggs
Keyword(s):  
Coastal Management ◽  
Harmful Algal Blooms ◽  
Algal Blooms ◽  
Local Community ◽  
Extreme Event ◽  
Technical Information ◽  
Interdisciplinary Approach ◽  
Beach Erosion ◽  
The U.S

In partnership with the U.S. Geological Survey Coastal and Marine Hazards and Resources Program (USGS CMHRP) and the U.S. Coastal Research Program (USCRP), the American Shore and Beach Preservation Association (ASBPA) has identified coastal stakeholders’ top coastal management challenges. Informed by two annual surveys, a multiple-choice online poll was conducted in 2019 to evaluate stakeholders’ most pressing problems and needs, including those they felt most ill-equipped to deal with in their day-to-day duties and which tools they most need to address these challenges. The survey also explored where users find technical information and what is missing. From these results, USGS CMHRP, USCRP, ASBPA, and other partners aim to identify research needs that will inform appropriate investments in useful science, tools, and resources to address today’s most pressing coastal challenges. The 15-question survey yielded 134 complete responses with an 80% completion rate from coastal stakeholders such as local community representatives and their industry consultants, state and federal agency representatives, and academics. Respondents from the East, Gulf, West, and Great Lakes coasts, as well as Alaska and Hawaii, were represented. Overall, the prioritized coastal management challenges identified by the survey were: Deteriorating ecosystems leading to reduced (environmental, recreational, economic, storm buffer) functionality, Increasing storminess due to climate change (i.e. more frequent and intense impacts), Coastal flooding, both Sea level rise and associated flooding (e.g. nuisance flooding, king tides), and Combined effects of rainfall and surge on urban flooding (i.e. episodic, short-term), Chronic beach erosion (i.e. high/increasing long-term erosion rates), and Coastal water quality, including harmful algal blooms (e.g. red tide, sargassum). A careful, systematic, and interdisciplinary approach should direct efforts to identify specific research needed to tackle these challenges. A notable shift in priorities from erosion to water-related challenges was recorded from respondents with organizations initially formed for beachfront management. In addition, affiliation-specific and regional responses varied, such as Floridians concern more with harmful algal blooms than any other human and ecosystem health related challenge. The most common need for additional coastal management tools and strategies related to adaptive coastal management to maintain community resilience and continuous storm barriers (dunes, structures), as the top long-term and extreme event needs, respectively. In response to questions about missing information that agencies can provide, respondents frequently mentioned up-to-date data on coastal systems and solutions to challenges as more important than additional tools.

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