On the Nature of Temporal Variability of the Gulf Stream Path from 75° to 55°W

The response of the Gulf Stream (GS) system to atmospheric forcing is generally linked either to the basin-scale winds on the subtropical gyre or to the buoyancy forcing from the Labrador Sea. This study presents a multiscale synergistic perspective to describe the low-frequency response of the GS system. The authors identify dominant temporal variability in the North Atlantic Oscillation (NAO), in known indices of the GS path, and in the observed GS latitudes along its path derived from sea surface height (SSH) contours over the period 1993-2013. The analysis suggests that the signature of interannual variability changes along the stream's path from 75 degrees to 55 degrees W. From its separation at Cape Hatteras to the west of 65 degrees W, the variability of the GS is mainly in the near-decadal (7-10 years) band, which is missing to the east of 60 degrees W, where a new interannual (4-5 years) band peaks. The latter peak (4-5 years) was missing to the west of 65 degrees W. The region between 65 degrees and 60 degrees W seems to be a transition region. A 2-3-yr secondary peak was pervasive in all time series, including that for the NAO. This multiscale response of the GS system is supported by results from a basin-scale North Atlantic model. The near-decadal response can be attributed to similar forcing periods in the NAO signal; however, the interannual variability of 4-5 years in the eastern segment of the GS path is as yet unexplained. More numerical and observational studies are warranted to understand such causality.

On the Nature of Temporal Variability of the Gulf Stream Path from 75° to 55°W

The response of the Gulf Stream (GS) system to atmospheric forcing is generally linked either to the basin-scale winds on the subtropical gyre or to the buoyancy forcing from the Labrador Sea. This study presents a multiscale synergistic perspective to describe the low-frequency response of the GS system. The authors identify dominant temporal variability in the North Atlantic Oscillation (NAO), in known indices of the GS path, and in the observed GS latitudes along its path derived from sea surface height (SSH) contours over the period 1993-2013. The analysis suggests that the signature of interannual variability changes along the stream's path from 75 degrees to 55 degrees W. From its separation at Cape Hatteras to the west of 65 degrees W, the variability of the GS is mainly in the near-decadal (7-10 years) band, which is missing to the east of 60 degrees W, where a new interannual (4-5 years) band peaks. The latter peak (4-5 years) was missing to the west of 65 degrees W. The region between 65 degrees and 60 degrees W seems to be a transition region. A 2-3-yr secondary peak was pervasive in all time series, including that for the NAO. This multiscale response of the GS system is supported by results from a basin-scale North Atlantic model. The near-decadal response can be attributed to similar forcing periods in the NAO signal; however, the interannual variability of 4-5 years in the eastern segment of the GS path is as yet unexplained. More numerical and observational studies are warranted to understand such causality.

Seasonal variability in microbial methanol utilisation in coastal waters of the western English Channel

Methanol is ubiquitous in seawater and the most abundant oxygenated volatile organic compound (OVOC) in the atmosphere where it influences oxidising capacity and ozone formation. Marine methylotrophic bacteria utilise methanol in seawater both as an energy and/or growth substrate. This work represents the first fully resolved seasonal study of marine microbial methanol uptake dynamics. Rates of microbial methanol dissimilation in coastal surface waters of the UK varied between 0.7 – 11.2 nmol l-1 h-1 and reached a maximum in February. Rates of microbial methanol assimilation varied between 0.04 – 2.64 x 10-2 nmol l-1 h-1 and reached a maximum in August. Temporal variability in microbial methanol uptake rates shows that methanol assimilation and dissimilation display opposing seasonal cycles, although overall <1% of methanol was assimilated. Correlative approaches with 16S rRNA pyrosequencing data suggested that bacteria of the SAR11 clade and Rhodobacterales could be significantly influencing rates of methanol dissimilation and assimilation, respectively, at station L4 in the western English Channel

Seasonal variability in microbial methanol utilisation in coastal waters of the western English Channel

Methanol is ubiquitous in seawater and the most abundant oxygenated volatile organic compound (OVOC) in the atmosphere where it influences oxidising capacity and ozone formation. Marine methylotrophic bacteria utilise methanol in seawater both as an energy and/or growth substrate. This work represents the first fully resolved seasonal study of marine microbial methanol uptake dynamics. Rates of microbial methanol dissimilation in coastal surface waters of the UK varied between 0.7 – 11.2 nmol l-1 h-1 and reached a maximum in February. Rates of microbial methanol assimilation varied between 0.04 – 2.64 x 10-2 nmol l-1 h-1 and reached a maximum in August. Temporal variability in microbial methanol uptake rates shows that methanol assimilation and dissimilation display opposing seasonal cycles, although overall <1% of methanol was assimilated. Correlative approaches with 16S rRNA pyrosequencing data suggested that bacteria of the SAR11 clade and Rhodobacterales could be significantly influencing rates of methanol dissimilation and assimilation, respectively, at station L4 in the western English Channel

Air-sea fluxes of CO2 and CH4 from the Penlee Point Atmospheric Observatory on the south-west coast of the UK

We present air–sea fluxes of carbon dioxide (CO2), methane (CH4), momentum, and sensible heat measured by the eddy covariance method from the recently established Penlee Point Atmospheric Observatory (PPAO) on the south-west coast of the United Kingdom. Measurements from the south-westerly direction (open water sector) were made at three different sampling heights (approximately 15, 18, and 27m above mean sea level, a.m.s.l.), each from a different period during 2014–2015. At sampling heights ≥18ma.m.s.l., measured fluxes of momentum and sensible heat demonstrate reasonable (≤ ±20% in the mean) agreement with transfer rates over the open ocean. This confirms the suitability of PPAO for air–sea exchange measurements in shelf regions. Covariance air–sea CO2 fluxes demonstrate high temporal variability. Air-to-sea transport of CO2 declined from spring to summer in both years, coinciding with the breakdown of the spring phytoplankton bloom. We report, to the best of our knowledge, the first successful eddy covariance measurements of CH4 emissions from a marine environment. Higher sea-to-air CH4 fluxes were observed during rising tides (20±3; 38±3; 29±6 μmolem-2 d-1 at 15, 18, 27ma.m.s.l.) than during falling tides (14±2; 22±2; 21±5 μmolem-2 d-1), consistent with an elevated CH4 source from an estuarine outflow driven by local tidal circulation. These fluxes are a few times higher than the predicted CH4 emissions over the open ocean and are significantly lower than estimates from other aquatic CH4 hotspots (e.g. polar regions, freshwater). Finally, we found the detection limit of the air–sea CH4 flux by eddy covariance to be 20 μmolem-2 d-1 over hourly timescales (4 μmolem-2 d-1 over 24 h).

Air-sea fluxes of CO2 and CH4 from the Penlee Point Atmospheric Observatory on the south-west coast of the UK

We present air–sea fluxes of carbon dioxide (CO2), methane (CH4), momentum, and sensible heat measured by the eddy covariance method from the recently established Penlee Point Atmospheric Observatory (PPAO) on the south-west coast of the United Kingdom. Measurements from the south-westerly direction (open water sector) were made at three different sampling heights (approximately 15, 18, and 27m above mean sea level, a.m.s.l.), each from a different period during 2014–2015. At sampling heights ≥18ma.m.s.l., measured fluxes of momentum and sensible heat demonstrate reasonable (≤ ±20% in the mean) agreement with transfer rates over the open ocean. This confirms the suitability of PPAO for air–sea exchange measurements in shelf regions. Covariance air–sea CO2 fluxes demonstrate high temporal variability. Air-to-sea transport of CO2 declined from spring to summer in both years, coinciding with the breakdown of the spring phytoplankton bloom. We report, to the best of our knowledge, the first successful eddy covariance measurements of CH4 emissions from a marine environment. Higher sea-to-air CH4 fluxes were observed during rising tides (20±3; 38±3; 29±6 μmolem-2 d-1 at 15, 18, 27ma.m.s.l.) than during falling tides (14±2; 22±2; 21±5 μmolem-2 d-1), consistent with an elevated CH4 source from an estuarine outflow driven by local tidal circulation. These fluxes are a few times higher than the predicted CH4 emissions over the open ocean and are significantly lower than estimates from other aquatic CH4 hotspots (e.g. polar regions, freshwater). Finally, we found the detection limit of the air–sea CH4 flux by eddy covariance to be 20 μmolem-2 d-1 over hourly timescales (4 μmolem-2 d-1 over 24 h).

Spatio-temporal characteristics of Agulhas leakage: a model inter-comparison study

Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

Spatio-temporal characteristics of Agulhas leakage: a model inter-comparison study

Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.

Rationalizing spatial exploration patterns of wild animals and humans through a temporal discounting framework

Understanding the exploration patterns of foragers in the wild provides fundamental insight into animal behavior. Recent experimental evidence has demonstrated that path lengths (distances between consecutive turns) taken by foragers are well fitted by a power law distribution. Numerous theoretical contributions have posited that “Lévy random walks”—which can produce power law path length distributions—are optimal for memoryless agents searching a sparse reward landscape. It is unclear, however, whether such a strategy is efficient for cognitively complex agents, from wild animals to humans. Here, we developed a model to explain the emergence of apparent power law path length distributions in animals that can learn about their environments. In our model, the agent’s goal during search is to build an internal model of the distribution of rewards in space that takes into account the cost of time to reach distant locations (i.e., temporally discounting rewards). For an agent with such a goal, we find that an optimal model of exploration in fact produces hyperbolic path lengths, which are well approximated by power laws. We then provide support for our model by showing that humans in a laboratory spatial exploration task search space systematically and modify their search patterns under a cost of time. In addition, we find that path length distributions in a large dataset obtained from free-ranging marine vertebrates are well described by our hyperbolic model. Thus, we provide a general theoretical framework for understanding spatial exploration patterns of cognitively complex foragers.