Seasonal Sea Surface Temperature Variability Research Articles

Trends and drivers of CO2 parameters, from 2006 to 2021, at a time-series station in the Eastern Tropical Atlantic (6°S, 10°W)

The seawater fugacity of CO2 (fCO2) has been monitored hourly at an instrumented mooring at 6°S, 10°W since 2006. The mooring is located in the South Equatorial Current and is affected by the equatorial Atlantic cold tongue. This site is characterized by large seasonal sea surface temperature variations (>4°C). The fCO2 is measured by a spectrophotometric sensor deployed at about 1.5 meters deep. Measurements of seawater fCO2, sea surface temperature (SST) and sea surface salinity (SSS) are used to calculate total dissolved inorganic carbon (TCO2) and pH. Total alkalinity (TA) is calculated using an empirical relationship with SSS determined for this region. Satellite chlorophyll-a concentrations at 6°S, 10°W are low (<0.2 mg m-3) but some peaks over 0.8 mg m-3 are sometimes detected in August. Nevertheless, the site is a permanent source of CO2 to the atmosphere, averaging 4.7 ± 2.4 mmol m-2d-1 over 2006-2021. Despite the weakening of the wind, the CO2 flux increases significantly by 0.20 ± 0.05 mmol m-2d-1 yr-1. This suggests that the source of CO2 is increasing in this region. This is explained by seawater fCO2 increasing faster than the atmospheric increase during 2006-2021. Most of the seawater fCO2 increase is driven by the increase of TCO2, followed by SST. The fCO2 increase leads to a pH decrease of -0.0030 ± 0.0004 yr-1. The SST anomalies (SSTA) at 6°S, 10°W are correlated to the Tropical Southern Atlantic (TSA) index and to the Atlantic 3 region (ATL3) index with a correlation coefficient higher than 0.75. The strong positive phase of both ATL3 and TSA, observed towards the end of the time-series, is likely contributing to the strong increase of seawater fCO2.

Analysis of Spatiotemporal Variation of Oceanographic Parameters in the North Atlantic of Morocco

Analysis of the spatiotemporal evolution of oceanographic parameters such as sea surface temperature (SST) and chlorophyll concentration (CHL) in the North Atlantic between 2018 and 2022 revealed interesting seasonal and interannual trends. Seasonal variations in SST and CHL are associated with factors such as sunlight, winds, and ocean currents. These two parameters showed an inverse relationship caused by several factors, of which the coastal upwelling is the most important. Interannual variations are influenced by weather conditions, extreme climatic events, and changes in ocean currents. The study of the spatiotemporal evolution of these two parameters is essential to understand environmental changes, assess the state of health of marine ecosystems and predict future changes. It also contributes to the establishment of appropriate management measures for the conservation of ocean ecosystems and to assess the impact of environmental disturbances.

Metabolic Robustness to Growth Temperature of a Cold- Adapted Marine Bacterium.

Microbial communities experience continuous environmental changes, with temperature fluctuations being the most impacting. This is particularly important considering the ongoing global warming but also in the "simpler" context of seasonal variability of sea-surface temperature. Understanding how microorganisms react at the cellular level can improve our understanding of their possible adaptations to a changing environment. In this work, we investigated the mechanisms through which metabolic homeostasis is maintained in a cold-adapted marine bacterium during growth at temperatures that differ widely (15 and 0°C). We have quantified its intracellular and extracellular central metabolomes together with changes occurring at the transcriptomic level in the same growth conditions. This information was then used to contextualize a genome-scale metabolic reconstruction, and to provide a systemic understanding of cellular adaptation to growth at 2 different temperatures. Our findings indicate a strong metabolic robustness at the level of the main central metabolites, counteracted by a relatively deep transcriptomic reprogramming that includes changes in gene expression of hundreds of metabolic genes. We interpret this as a transcriptomic buffering of cellular metabolism, able to produce overlapping metabolic phenotypes, despite the wide temperature gap. Moreover, we show that metabolic adaptation seems to be mostly played at the level of few key intermediates (e.g., phosphoenolpyruvate) and in the cross talk between the main central metabolic pathways. Overall, our findings reveal a complex interplay at gene expression level that contributes to the robustness/resilience of core metabolism, also promoting the leveraging of state-of-the-art multi-disciplinary approaches to fully comprehend molecular adaptations to environmental fluctuations. IMPORTANCE This manuscript addresses a central and broad interest topic in environmental microbiology, i.e. the effect of growth temperature on microbial cell physiology. We investigated if and how metabolic homeostasis is maintained in a cold-adapted bacterium during growth at temperatures that differ widely and that match measured changes on the field. Our integrative approach revealed an extraordinary robustness of the central metabolome to growth temperature. However, this was counteracted by deep changes at the transcriptional level, and especially in the metabolic part of the transcriptome. This conflictual scenario was interpreted as a transcriptomic buffering of cellular metabolism, and was investigated using genome-scale metabolic modeling. Overall, our findings reveal a complex interplay at gene expression level that contributes to the robustness/resilience of core metabolism, also promoting the use of state-of-the-art multi-disciplinary approaches to fully comprehend molecular adaptations to environmental fluctuations.

Coral Sr/Ca-derived seasonal sea surface temperature variations in the Qiongdong upwelling area of the northern South China Sea during the Medieval Climate Anomaly

Geological records of seasonal sea surface temperature (SST) records are useful for better understanding the past dynamics of coastal upwelling, and for inferring future scenarios. By using Sr/Ca records obtained from Porites lutea corals in the Qiongdong upwelling (QDU) area of the northern South China Sea (SCS), seasonal SST variations were reconstructed for the 1129–1263 CE interval of the Medieval Climate Anomaly (MCA). On an annual scale, summer SST is negatively correlated with the intensity of the East Asian Summer Monsoon (EASM), indicating a dominant role of the EASM on summer SST in the QDU area. The lack of correlation between winter SST and the East Asian Winter Monsoon (EAWM) may result from the dating errors of the climate archives and the low temporal resolution of EAWM records. Winter SST and summer SST played similarly affected the SST seasonality during the MCA. On the centennial scale, the differences in the averages of summer SST and winter SST in the QDU area between the MCA and the Current Warm Period were attributed to the different EASM and EAWM intensities. The consistent variations between the summer QDU and the winter Sumatra-Java upwelling during both climate intervals may imply that the SST variabilities in these two coastal upwelling systems responded to cross-equatorial winds originating from the Indian Ocean.

Nemo-Nordic 2.0: operational marine forecast model for the Baltic Sea

Abstract. This paper describes Nemo-Nordic 2.0, an operational marine model for the Baltic Sea. The model is used for both near-real-time forecasts and hindcast purposes. It provides estimates of sea surface height, water temperature, salinity, and velocity, as well as sea ice concentration and thickness. The model is based on the NEMO (Nucleus for European Modelling of the Ocean) circulation model and the previous Nemo-Nordic 1.0 configuration by Hordoir et al. (2019). The most notable updates include the switch from NEMO version 3.6 to 4.0, updated model bathymetry, and revised bottom friction formulation. The model domain covers the Baltic Sea and the North Sea with approximately 1 nmi resolution. Vertical grid resolution has been increased from 3 to 1 m in the surface layer. In addition, the numerical solver configuration has been revised to reduce artificial mixing to improve the representation of inflow events. Sea ice is modeled with the SI3 model instead of LIM3. The model is validated against sea level, water temperature, and salinity observations, as well as Baltic Sea ice chart data for a 2-year hindcast simulation (October 2014 to September 2016). Sea level root mean square deviation (RMSD) is typically within 10 cm throughout the Baltic basin. Seasonal sea surface temperature variation is well captured, although the model exhibits a negative bias of approximately −0.5 ∘C. Salinity RMSD is typically below 1.5 g kg−1. The model captures the 2014 major Baltic inflow event and its propagation to the Gotland Deep. The model assessment demonstrates that Nemo-Nordic 2.0 can reproduce the hydrographic features of the Baltic Sea.

Variability of SST and ILD in the Arabian Sea and Sea of Oman in Association with the Monsoon Cycle

Sea surface temperature (SST) and isothermal layer depth (ILD) are important oceanic parameters and could play a significant role in understanding the upper thermal structure as well as improve the predictive capability of monsoons in the tropical oceans. In a disparate departure from the past research, the present study investigates the seasonal variability of SST and ILD in association with the monsoon cycle in the Arabian Sea and Sea of Oman regions by examination of Argo datasets for 2016-17. In this study, the ILD climatology is determined from temperature profiles provided by the Argo floats based on a threshold technique T z ≥ SST − 1 ° C to investigate the region of stronger and weaker monsoon wind forcing. For SST, values of temperature are used nearest to the sea surface (depth z ≤ 5 m). The region is split into four distinct zones for an accurate description of the monsoon cycle: the south Arabian Sea, the central Arabian Sea, the north Arabian Sea, and the Sea of Oman. It is observed that summer monsoon is more pronounced in the south-central basin of the Arabian Sea, where ILD is deepening (>100 m in September 2016) mainly due to stronger wind forcing in this region. On the contrary, the Sea of Oman region is displayed with smaller ILD amplitude (<10 m in June 2016) with larger SST, meaning that this region is weakly influenced by the summer monsoon. The seasonal relationship established between ILD variability and monsoon cycle for 2016-17 shows that ILD could be a useful indicator for predicting summer monsoon in the Arabian Sea regions. Our analysis results indicate that the dynamics for SST variability are different in these regions and are influenced either by large-scale atmospheric forcing, such as the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), or by the effects of mesoscale variations occurring along the Oman-Arabian coast.

Seasonal Predictability of Global and North American Coastal Sea Surface Temperature and Height Anomalies

AbstractA Linear Inverse Model (LIM) is constructed to evaluate predictability of seasonal sea surface temperature (SST) and sea surface height (SSH) anomalies over the ice‐free global ocean. Its ensemble‐mean hindcast skill is also compared to that of the North American Multi‐Model Ensemble (NMME) for 1982–2010. Both have similar skill for dominant modes of SST variability, but regional NMME SST skill is somewhat higher in many locations. However, the LIM has considerably more Atlantic and Southern Ocean SSH skill. Skill is generally comparable along the North American coastline, but LIM skill is greater for several highly productive coastal zones and East Coast tide gauge stations. Diverse, often predictable ENSO events drive teleconnections providing predictability in the North Pacific and along the US West Coast. Predictability in the Atlantic and along the US East Coast is associated with Gulf Stream strength modulation. Overall, the LIM shows potential for seasonal prediction of coastal ocean conditions.

Temporal variability of economic fish assemblage of the Northern Bay of Bengal in relation to its environment

The Northern Bay of Bengal (NBoB) contributes largely towards the fish production of India and its neighboring countries. A pioneering attempt was made to understand temporal variability of the fish assemblage (exclusively to those of fisheries interest) of the NBoB (20°20ʹ–21°30ʹN and 87°30ʹ–89°E) in relation to sea surface temperature (SST) (°C), sea surface salinity (SSS), and chlorophyll-a (Chl- a ) (mg/l) changes. Between 2006 and 2015, the inter-annual variations of SST, SSS, and Chl- a were minor. Seasonal variability of SST, SSS, and Chl- a was observed and a yearly bi-modal peak of Chl- a production was evident. Inter-annual variability of the species dominance (D) was most plausibly explained by the SST*Chl- a (Δ AIC = 0) model. Variation of evenness index (J) was explained most plausibility by the Chl- a (Δ AIC = 0) model. Seasonal variability of SST and Chl- a levels, possibly influence the fish community of the NBoB, therefore, a regular monitoring programme is suggested for understanding the long-term changes of the fish assemblage of the NBoB.

CMIP5-Based Projection of Decadal and Seasonal Sea Surface Temperature Variations in East China Shelf Seas

The East China Shelf Seas, comprising the Bohai Sea, the Yellow Sea, and the shelf region of East China Sea, play significant roles among the shelf seas of the Western North Pacific Ocean. The projection of sea surface temperature (SST) changes in these regions is a hot research topic in marine science. However, this is a very difficult task due to the lack of available long-term projection data. Recently, with the high development of simulation technology based on numerical models, the model intercomparison projects, e.g., Phase 5 of the Climate Model Intercomparison Project (CMIP5), have become important ways of understanding climate changes. CMIP5 provides multiple models that can be used to estimate SST changes by 2100 under different representative concentration pathways (RCPs). This paper developed a CMIP5-based SST investigation framework for the projection of decadal and seasonal variation of SST in East China Shelf Seas by 2100. Since the simulation results of CMIP5 models may have degrees of errors, this paper uses hydrological observation data from World Ocean Atlas 2018 (WOA18) for model validation and correction. This paper selects seven representative ones including ACCESS1.3, CCSM4, FIO-ESM, CESM1-CAM5, CMCC-CMS, NorESM1-ME, and Max Planck Institute Earth System Model of medium resolution (MPI-ESM-MR). The decadal and seasonal SST changes in the next 100 years (2030, 2060, 2090) are investigated by comparing with the present analysis in 2010. The experimental results demonstrate that SST will increase significantly by 2100: the decadal SST will increase by about 1.55 °C, while the seasonal SST will increase by 1.03–1.95 °C.

Comparing the Performance of Turbulent Kinetic Energy and K-Profile Parameterization Vertical Parameterization Schemes over the Tropical Indian Ocean

The performance of vertical parameterization schemes, namely, turbulent kinetic energy (TKE) and K-profile parameterization (KPP), is evaluated over the domain [30E-120E; 20S-30N] in the Indian Ocean using the Nucleus for European Modeling of the Ocean (NEMO) regional model. The surface and sub-surface hydrography and mixed layer depth (MLD) of the simulations using TKE and KPP schemes have been compared. The KPP scheme produces higher bias (∼0.5 °C) of sea surface temperature (SST) in monsoon and post-monsoon seasons, which reduces on using the TKE scheme. The maximum surface salinity difference (0.45 psu) between TKE and KPP simulations is obtained over the head Bay of Bengal (BoB) in the post-monsoon months. The KPP scheme also overestimates MLD of the region. Barring highly convective regions as well as regions marked with very low and rapidly changing salinity, the TKE scheme performs better than KPP scheme in simulating the hydrography and MLD of the region. The differences between TKE and KPP simulations in the vertical stability and mixing are studied using buoyancy frequency, vertical shear of horizontal currents and energy required for mixing as quantifiers. The mixed layer heat budget analysis explains seasonal variability of SST and differences in vertical mixing parameterizations.

Does Sea Surface Temperature Affect Solubility of Iron in Mineral Dust? The Gulf of California as a Case Study

AbstractEolian transport of mineral dust is one of the main inputs of iron (Fe) to the global ocean; however, the magnitude and biogeochemical impact of this supply depends on the solubility of the deposited dust. In particular, the effect of temperature on Fe‐bearing dust solubility has been scarcely investigated even though a seasonal gradient of sea surface temperature (SST) is a common feature in coastal zones adjacent to the major dust source regions of the world. In this work, the effect of temperature on the fractional solubility of Fe (FFeS) was evaluated experimentally using sieved soils (as a dust proxy) from the Baja California Peninsula and surface seawater from the Gulf of California (GC). Two incubations were performed at 17°C (winter) and 29°C (summer) considering the seasonal variability of SST in the GC. Differences in FFeS up to 3 orders of magnitude (0.003–4.49%) were linked to incubation temperature, dust load, and contact time between seawater and dust. After 72 hr of incubation, the effect of temperature was statistically significant (p < 0.05) for all dust treatments, with FFeS higher (4–24 times) at 29°C. High FFeS in warmer waters are a result of increased Fe‐bearing dust dissolution and decreased scavenging of Fe by dust particles. Since temperature appears to control the magnitude of FFeS in the GC, we suggest that this factor could have an effect on the atmospheric inputs of soluble Fe in marginal seas with similar seasonal SST contrasts; including the global ocean, where well‐defined latitudinal temperature gradients exist.

Change the Annual Amplitude of Sea Surface Temperature due to Climate Change in a Recent Decade around the Korean Peninsula

We examined long-term variations in sea surface temperature (SST) and annual amplitudes of SST around the Korean Peninsula. Two SST data sets with data periods of approximately 51 years and longer than 100 years, respectively, were obtained from the National Institute of Fisheries Science and Japan Meteorological Agency. SST of Korean waters clearly increased during last 51 years (1968-2018), which was 2.5 times higher than the global trend. This significant increasing trend was caused by the dominant increasing SST trend during winter. However, a negative and positive SST anomaly frequently appeared during winter and summer, respectively, in a recent decade. These features of seasonal SST variation have changed the annual amplitude of SST, and resulted in a drastically increasing trend after 2009. Using the longer SST data set, it was revealed that the decreasing SST trend in winter began in the 2000s and the increasing SST trend in summer bagan in the 1990s. During a recent decade, there was a distinctive SST increase in summer, whereas a clear decrease in winter. In summary, the annual amplitude of SST around the Korean Peninsula significantly changed from a decreasing trend to an increasing trend during a recent decade.

Seasonal Sea Surface Temperature Variability over Tropical Indo-Pacific Region Simulated by FIO-ESM Model Under Global Warming

The long-term trend and seasonal variability of sea surface temperature (SST) over tropical Indo-Pacific region under the global warming projection simulated by FIO-ESM model are analyzed. At seasonal time scale, significant warming trend over Indo-Pacific area is well captured by FIO-ESM model over the warm pool region under RCP8.5 scenario. The La Nina-like warming pattern is dominant in the tropical Pacific and the negative Indian Ocean Dipole warming pattern takes place in the Indian Ocean in global warming projection separately. The strength of SST warming trend is found to be seasonal dependent over Indo-Pacific region. The spatial distribution of calendar month where fastest/slowest SST warming trend take place in tropical Indo-Pacific has been assessed in FIO-ESM simulation, which is corresponded with the distribution of SST climatology closely in Pacific but not in Indian Ocean.

VARIABILITY OF CHLOROPHYLL-A DISTRIBUTION AROUND BELITUNG ISLAND WATERS OBSERVED BY AQUA-MODIS SATELLITE DATA

<p>Belitung Island has a strategic geographical location, which is directly bordered with Sumatera and Kalimantan also Karimata and Malacca Straits. Those conditions make the waters productivity being high due to the support from the biogeochemical cycle, nutrient runoff, and upwelling. This study aims to determine the seasonal variability of chlorophyll-a (Chl-a) around Belitung waters. The method used in this study was spatial analysis with IDW (inverse distance weighted) to interpolate the Chl-a surface distribution. Sea Surface Temperature (SST) acquired from Aqua-MODIS were retrieved from NASA (National Aeronautics and Space Administration) and wind data were obtained from ECMWF (European Centre for Medium-Range Weather Forecasts), data were analyzed statistically and spatially. The Chl-a concentration in the northeast monsoon ranged 0.38-3.5 mg.m-3, in the southwest monsoon ranged 0.15-18.7 mg.m-3, and in the transitional season ranged 0.29-9.04 mg.m-3. The Chl-a concentration during southwest and 1st transitional monsoons were higher due to the maximum sunlight intensity stimulating photosynthesis of autotroph biota. The condition of SST is indicating the upwelling event that involves wind-driven motion of dense, cooler, and usually nutrient-rich water towards the ocean surface. Seasonal SST variability ranged 22.6-28.3oC, 27.3-32.1oC, 30.7-32.3oC, and 29.1-32.8oC during northeast, 1st transitional, southwest, and 2nd transitional monsoons respectively. The existence of ENSO (El-Nino Southern Oscillation) contributes to enhance the Chl-a concentration. During ENSO years, the Chl-a concentration was higher than non-ENSO years due to the great impact of ENSO inducing upwelling and higher nutrient availability. Chl-a and SST conditions can be used to predict fishing ground and upwelling area. </p>

The role of sea surface temperature in the atmospheric seasonal cycle of the equatorial Atlantic

We investigate the role of sea surface temperature (SST) and land surface temperature (LST) in driving the seasonal cycle of the atmosphere (surface winds and precipitation) in the tropical Atlantic. For this we compare three atmospheric general circulation model (AGCM) experiments for the historical period 1982–2013 forced by different SST: (1) observed daily-climatological SST, (2) globally annual-mean SST, and (3) annual-mean SST in the equatorial Atlantic and daily-climatological SST elsewhere. Seasonal variations in SST strongly influence the seasonal evolution of the West African Monsoon (WAM) and ITCZ over the equatorial Atlantic Ocean. Forcing the model with annual mean SST (globally and in the equatorial Atlantic) considerably reduces the seasonal variance in the atmosphere, except for the zonal winds in the eastern equatorial Atlantic. Equatorial Atlantic SST contributes to the seasonal cycle in precipitation and meridional winds over the entire equatorial Atlantic, but only strongly influences zonal winds in the western equatorial Atlantic and has little influence on the northward penetration of the WAM. The leading modes of coupled SST–LST-atmosphere co-variability are identified by multivariate analysis. The analysis shows that both LST and SST drive seasonal variations in precipitation over equatorial Atlantic, with the LST being a larger contributor to the continental rainfall in West Africa. The coupling between ocean and atmosphere is stronger in the western than in the eastern equatorial Atlantic. The pressure adjustment mechanism is the main driver of the surface meridional wind convergence in the eastern tropical Atlantic.

Variability of Sea Surface Temperature in Indonesia Based on Aqua Modis Satellite Data

Sea surface temperature (SST) is one of the oceanographic factor in seawater. Its value depends on several factors. In indonesia, SST value depend on season and location. The aims of this study are to analyze the spatial and temporal variability of SST using 10-years (2007-2016) Aqua Modis satellite data. The result shows that the average of SST in Indonesia ranges from 27 – 31 °C depending on location. SST in equator area range from 30 – 31 °C and in nonequator area range from 27 – 30 °C. Monthly and seasonal variation of SST also show different value for each area in the indonesian region.

Variability of Sea Surface Temperature in Indonesia Based on Aqua Modis Satellite Data

Sea surface temperature (SST) is one of the oceanographic factor in seawater. Its value depends on several factors. In indonesia, SST value depend on season and location. The aims of this study are to analyze the spatial and temporal variability of SST using 10-years (2007-2016) Aqua Modis satellite data. The result shows that the average of SST in Indonesia ranges from 27 – 31 °C depending on location. SST in equator area range from 30 – 31 °C and in nonequator area range from 27 – 30 °C. Monthly and seasonal variation of SST also show different value for each area in the indonesian region.

Seasonal Variation of SST in Mediterranean Sea

The study of sea surface temperature (SST) is fairly essential for solving many meteorological
 and oceanographic problem and climate system of the earth. The aim of this study is to explore
 the variation of SST of Mediterranean Sea during the period (1980-2009) by using statistical
 analysis technique such as time series and trend. The data obtained from the Europe center
 (ECMWF) and the resolution of the grid of the variable is 0.5°*0.5° and selects three locations
 (points) in the Mediterranean Sea. The seasonal variation of SST has the highest value of trend in
 summer season (0.06) for the points I, II, III, while the lowest value in the transition season, i.e. in
 spring (0.01) for point I and III and in Autumn (0.04) for point III.

Mesoscale wind stress–SST coupling in the Kuroshio extension and its effect on the ocean

Mesoscale perturbations (with a size of 100–1000 km) of wind stress magnitude, divergence and curl in the Kuroshio Extension (KE) are observed to tightly link to those of sea surface temperature (SST), and downwind and crosswind SST gradients, respectively. Based on long-term satellite observational data, their empirical relationships are established, which are further used to represent mesoscale wind stress–SST coupling in an ocean model that is based on the Regional Oceanic Modelling Systems (ROMS). The strength of mesoscale perturbations of wind stress and SST is observed to display a consistent seasonal variability, with the maximum appeared in winter while the minimum appeared in summer. This seasonal variability characteristic is also successfully simulated by ROMS with high resolution. Through comparing two experiments with and without the mesoscale wind stress–SST coupling, it is found that the mesoscale wind stress perturbation (τ MS) has a negative feedback on SST perturbation (SSTMS). Analyses of sensitivity experiments suggest that the τ MS acts to inhibit SSTMS mainly by means of surface heat flux. The τ MS –SSTMS coupling also exerts influences on the ocean mean state and seasonal variability of SST in the KE. The effect of τ MS on the SST is distinct in autumn and winter when the mesoscale perturbations are most active. Analyses of sensitivity experiments demonstrate that the τ MS can affect the long term mean SST through either way of surface heat flux or momentum flux.

Biogeography of dinoflagellate cysts in northwest Atlantic estuaries.

Few biogeographic studies of dinoflagellate cysts include the near‐shore estuarine environment. We determine the effect of estuary type, biogeography, and water quality on the spatial distribution of organic‐walled dinoflagellate cysts from the Northeast USA (Maine to Delaware) and Canada (Prince Edward Island). A total of 69 surface sediment samples were collected from 27 estuaries, from sites with surface salinities >20. Dinoflagellate cysts were examined microscopically and compared to environmental parameters using multivariate ordination techniques. The spatial distribution of cyst taxa reflects biogeographic provinces established by other marine organisms, with Cape Cod separating the northern Acadian Province from the southern Virginian Province. Species such as Lingulodinium machaerophorum and Polysphaeridinium zoharyi were found almost exclusively in the Virginian Province, while others such as Dubridinium spp. and Islandinium? cezare were more abundant in the Acadian Province. Tidal range, sea surface temperature (SST), and sea surface salinity (SSS) are statistically significant parameters influencing cyst assemblages. Samples from the same type of estuary cluster together in canonical correspondence analysis when the estuaries are within the same biogeographic province. The large geographic extent of this study, encompassing four main estuary types (riverine, lagoon, coastal embayment, and fjord), allowed us to determine that the type of estuary has an important influence on cyst assemblages. Due to greater seasonal variations in SSTs and SSSs in estuaries compared to the open ocean, cyst assemblages show distinct latitudinal trends. The estuarine context is important for understanding present‐day species distribution, the factors controlling them, and to better predict how they may change in the future.