Sebastian Landwehr
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Sebastian Landwehr has a total of 102 co-authors. Here are the top co-authors by number of shared publications:
- Brian Ward
University of Galway, Ireland
14 shared publications - Julia Schmale
Extreme Environments Research Laboratory, École Polytechnique Fédérale de Lausanne, Sion, Switzerland
14 shared publications - Iris Thurnherr
Institute for Atmospheric and Climate Science, ETH Zürich, Switzerland
11 shared publications - Robin Lewis Modini
Paul Scherrer Institute
9 shared publications - Gang Chen
MRC Centre for Environment and Health, Environmental Research Group, Imperial College London, 86 Wood Lane, London W12 0BZ, UK
8 shared publications - Silvia Henning
Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
8 shared publications
Latest Publications
- Open Access
- 30 November 2021
- Published by Copernicus GmbH in Earth System Dynamics
- Vol. 12 (4) , 1295-1369
Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition
The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question.
- 30 November 2021
- Published by Copernicus GmbH in Earth System Dynamics
- Vol. 12 (4) , 1295-1369
Open AccessExploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition
The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question.
- Open Access
- 9 June 2021
- Published by American Geophysical Union (AGU) in Journal of Geophysical Research: Atmospheres
- Vol. 126 (11)
Sources, Occurrence and Characteristics of Fluorescent Biological Aerosol Particles Measured Over the Pristine Southern Ocean
In this study, we investigate the occurrence of primary biological aerosol particles (PBAP) over all sectors of the Southern Ocean (SO) based on a 90‐day data set collected during the Antarctic Circumnavigation Expedition (ACE) in austral summer 2016–2017. Super‐micrometer PBAP (1–16 µm diameter) were measured by a wide band integrated bioaerosol sensor (WIBS‐4). Low (3σ) and high (9σ) fluorescence thresholds are used to obtain statistics on fluorescent and hyper‐fluorescent PBAP, respectively. Our focus is on data obtained over the pristine ocean, that is, more than 200 km away from land. The results indicate that (hyper‐)fluorescent PBAP are correlated to atmospheric variables associated with sea spray aerosol (SSA) particles (wind speed, total super‐micrometer aerosol number concentration, chloride and sodium concentrations). This suggests that a main source of PBAP over the SO is SSA. The median percentage contribution of fluorescent and hyper‐fluorescent PBAP to super‐micrometer SSA was 1.6% and 0.13%, respectively. We demonstrate that the fraction of (hyper‐)fluorescent PBAP to total super‐micrometer particles positively correlates with concentrations of bacteria and several taxa of pythoplankton measured in seawater, indicating that marine biota concentrations modulate the PBAP source flux. We investigate the fluorescent properties of (hyper‐)fluorescent PBAP for several events that occurred near land masses. We find that the fluorescence signal characteristics of particles near land is much more variable than over the pristine ocean. We conclude that the source and concentration of fluorescent PBAP over the open ocean is similar across all sampled sectors of the SO.
- 9 June 2021
- Published by American Geophysical Union (AGU) in Journal of Geophysical Research: Atmospheres
- Vol. 126 (11)
Open AccessSources, Occurrence and Characteristics of Fluorescent Biological Aerosol Particles Measured Over the Pristine Southern Ocean
In this study, we investigate the occurrence of primary biological aerosol particles (PBAP) over all sectors of the Southern Ocean (SO) based on a 90‐day data set collected during the Antarctic Circumnavigation Expedition (ACE) in austral summer 2016–2017. Super‐micrometer PBAP (1–16 µm diameter) were measured by a wide band integrated bioaerosol sensor (WIBS‐4). Low (3σ) and high (9σ) fluorescence thresholds are used to obtain statistics on fluorescent and hyper‐fluorescent PBAP, respectively. Our focus is on data obtained over the pristine ocean, that is, more than 200 km away from land. The results indicate that (hyper‐)fluorescent PBAP are correlated to atmospheric variables associated with sea spray aerosol (SSA) particles (wind speed, total super‐micrometer aerosol number concentration, chloride and sodium concentrations). This suggests that a main source of PBAP over the SO is SSA. The median percentage contribution of fluorescent and hyper‐fluorescent PBAP to super‐micrometer SSA was 1.6% and 0.13%, respectively. We demonstrate that the fraction of (hyper‐)fluorescent PBAP to total super‐micrometer particles positively correlates with concentrations of bacteria and several taxa of pythoplankton measured in seawater, indicating that marine biota concentrations modulate the PBAP source flux. We investigate the fluorescent properties of (hyper‐)fluorescent PBAP for several events that occurred near land masses. We find that the fluorescence signal characteristics of particles near land is much more variable than over the pristine ocean. We conclude that the source and concentration of fluorescent PBAP over the open ocean is similar across all sampled sectors of the SO.
- Open Access
- 2 June 2021
- Published by Copernicus GmbH
- p. 1-114
Review of Landwehr et al., 2021, ESD
The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter term variations, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a sparse Principal Component Analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. More specifically, we identify: the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as source processes near “hotspots” for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper ocean layer light intensity, surface wind speed and relative humidity, played an important role in the majority of latent variables, highlighting their importance for a large variety of processes and the necessity for Earth System Models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.
- 2 June 2021
- Published by Copernicus GmbH
- p. 1-114
Open AccessReview of Landwehr et al., 2021, ESD
The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter term variations, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a sparse Principal Component Analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. More specifically, we identify: the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as source processes near “hotspots” for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper ocean layer light intensity, surface wind speed and relative humidity, played an important role in the majority of latent variables, highlighting their importance for a large variety of processes and the necessity for Earth System Models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.
- Open Access
- 1 June 2021
- Published by Copernicus GmbH
- p. 1-114
Comment on esd-2021-16
The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter term variations, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a sparse Principal Component Analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. More specifically, we identify: the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as source processes near “hotspots” for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper ocean layer light intensity, surface wind speed and relative humidity, played an important role in the majority of latent variables, highlighting their importance for a large variety of processes and the necessity for Earth System Models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.
- 1 June 2021
- Published by Copernicus GmbH
- p. 1-114
Open AccessComment on esd-2021-16
The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter term variations, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a sparse Principal Component Analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. More specifically, we identify: the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as source processes near “hotspots” for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper ocean layer light intensity, surface wind speed and relative humidity, played an important role in the majority of latent variables, highlighting their importance for a large variety of processes and the necessity for Earth System Models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.
- Open Access
- 28 May 2021
- Published by Copernicus GmbH
- p. 1-114
Comment on esd-2021-16
The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter term variations, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a sparse Principal Component Analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. More specifically, we identify: the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as source processes near “hotspots” for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper ocean layer light intensity, surface wind speed and relative humidity, played an important role in the majority of latent variables, highlighting their importance for a large variety of processes and the necessity for Earth System Models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.
- 28 May 2021
- Published by Copernicus GmbH
- p. 1-114
Open AccessComment on esd-2021-16
The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter term variations, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a sparse Principal Component Analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. More specifically, we identify: the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as source processes near “hotspots” for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper ocean layer light intensity, surface wind speed and relative humidity, played an important role in the majority of latent variables, highlighting their importance for a large variety of processes and the necessity for Earth System Models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.
- Open Access
- 21 April 2021
- Published by Copernicus GmbH
Supplementary material to "Biogeochemistry and Physics of the Southern Ocean-Atmosphere System Explored With Data Science"
- 21 April 2021
- Published by Copernicus GmbH
Open AccessSupplementary material to "Biogeochemistry and Physics of the Southern Ocean-Atmosphere System Explored With Data Science"
- Open Access
- 21 April 2021
- Published by Copernicus GmbH in EGUsphere
- Vol. 2021, 1-114
Biogeochemistry and Physics of the Southern Ocean-Atmosphere System Explored With Data Science
The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter term variations, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a sparse Principal Component Analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. More specifically, we identify: the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as source processes near “hotspots” for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper ocean layer light intensity, surface wind speed and relative humidity, played an important role in the majority of latent variables, highlighting their importance for a large variety of processes and the necessity for Earth System Models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.
- 21 April 2021
- Published by Copernicus GmbH in EGUsphere
- Vol. 2021, 1-114
Open AccessBiogeochemistry and Physics of the Southern Ocean-Atmosphere System Explored With Data Science
The Southern Ocean is a critical component of Earth’s climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the dynamic state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, ocean biogeochemistry and microbiology. This circumpolar cruise included visits to twelve remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter term variations, the geographic setting of environmental processes, and interactions between them over the duration of 90 days. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable, we applied a sparse Principal Component Analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. We identified temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction. Our results establish connections of oceanic, atmospheric, biological and terrestrial processes in an innovative way, while confirming many well known relations of the Southern Ocean system. More specifically, we identify: the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; that sea ice predominantly controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilization and reduced light limitation; and clear regional patterns of aerosol characteristics emerged, stressing the role of the sea state, atmospheric chemical processing, as well as source processes near “hotspots” for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper ocean layer light intensity, surface wind speed and relative humidity, played an important role in the majority of latent variables, highlighting their importance for a large variety of processes and the necessity for Earth System Models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean-atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. The sPCA processing code is available as open-access and we believe that our approach is widely applicable to other environmental field studies.
- Open Access
- 25 February 2021
- Published by Wiley in ESS Open Archive
Sources, Occurrence and Characteristics of Fluorescent Biological Aerosol Particles Measured over the Pristine Southern Ocean
In this study we investigate the occurrence of primary biological aerosol particles (PBAP) over all sectors of the Southern Ocean (SO) based on a 90-day dataset collected during the Antarctic Circumnavigation Expedition (ACE) in austral summer 2016-2017. Super-micrometer PBAP (1 to 16 µm diameter) were measured by a wide band integrated bioaerosol sensor (WIBS-4). Low (3σ) and high (9σ) fluorescence thresholds are used to obtain statistics on fluorescent and hyper-fluorescent PBAP, respectively. Our focus is on data obtained over the pristine ocean, i.e. more than 200 km away from land. The results indicate that (hyper-)fluorescent PBAP are correlated to atmospheric variables associated with sea spray aerosol (SSA) particles (wind speed, total super-micrometer aerosol number concentration, chloride and sodium concentrations). This suggests that a main source of PBAP over the SO is SSA. The median fraction of fluorescent and hyper-fluorescent PBAP to super-micrometer SSA is 1.6% and 0.13%, respectively. We demonstrate that the fraction of (hyper-)fluorescent PBAP to total super-micrometer particles positively correlates with concentrations of bacteria and several taxa of phytoplankton measured in seawater, indicating that marine biota concentrations modulate the PBAP source flux. We investigate the fluorescent properties of (hyper-)fluorescent PBAP for several events that occurred near land masses. We find that the fluorescence signal characteristics of particles near land is much more variable than over the pristine ocean. We conclude that the source and concentration of fluorescent PBAP over the open ocean is similar across all sectors of the SO.
- 25 February 2021
- Published by Wiley in ESS Open Archive
Open AccessSources, Occurrence and Characteristics of Fluorescent Biological Aerosol Particles Measured over the Pristine Southern Ocean
In this study we investigate the occurrence of primary biological aerosol particles (PBAP) over all sectors of the Southern Ocean (SO) based on a 90-day dataset collected during the Antarctic Circumnavigation Expedition (ACE) in austral summer 2016-2017. Super-micrometer PBAP (1 to 16 µm diameter) were measured by a wide band integrated bioaerosol sensor (WIBS-4). Low (3σ) and high (9σ) fluorescence thresholds are used to obtain statistics on fluorescent and hyper-fluorescent PBAP, respectively. Our focus is on data obtained over the pristine ocean, i.e. more than 200 km away from land. The results indicate that (hyper-)fluorescent PBAP are correlated to atmospheric variables associated with sea spray aerosol (SSA) particles (wind speed, total super-micrometer aerosol number concentration, chloride and sodium concentrations). This suggests that a main source of PBAP over the SO is SSA. The median fraction of fluorescent and hyper-fluorescent PBAP to super-micrometer SSA is 1.6% and 0.13%, respectively. We demonstrate that the fraction of (hyper-)fluorescent PBAP to total super-micrometer particles positively correlates with concentrations of bacteria and several taxa of phytoplankton measured in seawater, indicating that marine biota concentrations modulate the PBAP source flux. We investigate the fluorescent properties of (hyper-)fluorescent PBAP for several events that occurred near land masses. We find that the fluorescence signal characteristics of particles near land is much more variable than over the pristine ocean. We conclude that the source and concentration of fluorescent PBAP over the open ocean is similar across all sectors of the SO.
- Open Access
- 10 October 2020
- Published by Wiley in ESS Open Archive
Sea State and Boundary Layer Stability Limit Sea Spray Aerosol Lifetime over the Southern Ocean
A data set of concurrent measurements of sea spray aerosol concentration, wind speed, sea state, and air and water temperature was acquired across all sectors of the Southern Ocean during the Antarctic Circumnavigation Expedition (Austral summer 2016/2017). In addition to the established dependence on wind speed, our observations demonstrate that sea spray aerosol concentrations depend on sea state and the stability of the marine boundary layer. Besides driving sea spray emissions, wind speed and sea state strongly influence the deposition onto the ocean surface and thus aerosol lifetime even for smaller particles. Stable atmospheric conditions allow a typical lifetime of up to 4 days, while tropospheric air entrainment in unstable conditions reduces the residence time of sea spray aerosol in the marine boundary layer to less than 2 days.
- 10 October 2020
- Published by Wiley in ESS Open Archive
Open AccessSea State and Boundary Layer Stability Limit Sea Spray Aerosol Lifetime over the Southern Ocean
A data set of concurrent measurements of sea spray aerosol concentration, wind speed, sea state, and air and water temperature was acquired across all sectors of the Southern Ocean during the Antarctic Circumnavigation Expedition (Austral summer 2016/2017). In addition to the established dependence on wind speed, our observations demonstrate that sea spray aerosol concentrations depend on sea state and the stability of the marine boundary layer. Besides driving sea spray emissions, wind speed and sea state strongly influence the deposition onto the ocean surface and thus aerosol lifetime even for smaller particles. Stable atmospheric conditions allow a typical lifetime of up to 4 days, while tropospheric air entrainment in unstable conditions reduces the residence time of sea spray aerosol in the marine boundary layer to less than 2 days.
- Open Access
- 30 June 2020
- Published by Copernicus GmbH in Atmospheric Measurement Techniques
- Vol. 13 (6) , 3487-3506
Using global reanalysis data to quantify and correct airflow distortion bias in shipborne wind speed measurements
At sea, wind forcing is responsible for the formation and development of surface waves and represents an important source of near-surface turbulence. Therefore, processes related to near-surface turbulence and wave breaking, such as sea spray emission and air–sea gas exchange, are often parameterised with wind speed. Thus, shipborne wind speed measurements provide highly relevant observations. They can, however, be compromised by flow distortion due to the ship's structure and objects near the anemometer that modify the airflow, leading to a deflection of the apparent wind direction and positive or negative acceleration of the apparent wind speed. The resulting errors in the estimated true wind speed can be greatly magnified at low wind speeds. For some research ships, correction factors have been derived from computational fluid dynamic models or through direct comparison with wind speed measurements from buoys. These correction factors can, however, lose their validity due to changes in the structures near the anemometer and, thus, require frequent re-evaluation, which is costly in either computational power or ship time. Here, we evaluate if global atmospheric reanalysis data can be used to quantify the flow distortion bias in shipborne wind speed measurements. The method is tested on data from the Antarctic Circumnavigation Expedition onboard the R/V Akademik Tryoshnikov, which are compared to ERA-5 reanalysis wind speeds. We find that, depending on the relative wind direction, the relative wind speed and direction measurements are biased by −37 % to +22 % and to respectively. The resulting error in the true wind speed is +11.5 % on average but ranges from −4 % to +41 % (5th and 95th percentile). After applying the bias correction, the uncertainty in the true wind speed is reduced to ±5 % and depends mainly on the average accuracy of the ERA-5 data over the period of the experiment. The obvious drawback of this approach is the potential intrusion of model biases in the correction factors. We show that this problem can be somewhat mitigated when the error propagation in the true wind correction is accounted for and used to weight the observations. We discuss the potential caveats and limitations of this approach and conclude that it can be used to quantify flow distortion bias for ships that operate on a global scale. The method can also be valuable to verify computational fluid dynamic studies of airflow distortion on research vessels.- 30 June 2020
- Published by Copernicus GmbH in Atmospheric Measurement Techniques
- Vol. 13 (6) , 3487-3506
Open AccessUsing global reanalysis data to quantify and correct airflow distortion bias in shipborne wind speed measurements
At sea, wind forcing is responsible for the formation and development of surface waves and represents an important source of near-surface turbulence. Therefore, processes related to near-surface turbulence and wave breaking, such as sea spray emission and air–sea gas exchange, are often parameterised with wind speed. Thus, shipborne wind speed measurements provide highly relevant observations. They can, however, be compromised by flow distortion due to the ship's structure and objects near the anemometer that modify the airflow, leading to a deflection of the apparent wind direction and positive or negative acceleration of the apparent wind speed. The resulting errors in the estimated true wind speed can be greatly magnified at low wind speeds. For some research ships, correction factors have been derived from computational fluid dynamic models or through direct comparison with wind speed measurements from buoys. These correction factors can, however, lose their validity due to changes in the structures near the anemometer and, thus, require frequent re-evaluation, which is costly in either computational power or ship time. Here, we evaluate if global atmospheric reanalysis data can be used to quantify the flow distortion bias in shipborne wind speed measurements. The method is tested on data from the Antarctic Circumnavigation Expedition onboard the R/V Akademik Tryoshnikov, which are compared to ERA-5 reanalysis wind speeds. We find that, depending on the relative wind direction, the relative wind speed and direction measurements are biased by −37 % to +22 % and to respectively. The resulting error in the true wind speed is +11.5 % on average but ranges from −4 % to +41 % (5th and 95th percentile). After applying the bias correction, the uncertainty in the true wind speed is reduced to ±5 % and depends mainly on the average accuracy of the ERA-5 data over the period of the experiment. The obvious drawback of this approach is the potential intrusion of model biases in the correction factors. We show that this problem can be somewhat mitigated when the error propagation in the true wind correction is accounted for and used to weight the observations. We discuss the potential caveats and limitations of this approach and conclude that it can be used to quantify flow distortion bias for ships that operate on a global scale. The method can also be valuable to verify computational fluid dynamic studies of airflow distortion on research vessels.