Periodic Reporting for period 4 - GOCART (Gauging Ocean organic Carbon fluxes using Autonomous Robotic Technologies)
Okres sprawozdawczy: 2021-05-01 do 2022-10-31
Climate change driven by CO2 emissions from human activities is a significant challenge facing mankind. An important component of Earth’s carbon (C) cycle is the ocean’s biological C pump; without it atmospheric CO2 would be ~50% higher than it is now. The pump consists of sinking organic matter which is remineralised back into CO2 in the deep ocean. The depth at which remineralisation occurs is the main factor affecting the amount of organic C stored in the ocean. Currently we do not understand how or why remineralisation depth varies in time, which limits our ability to make robust predictions of how the future C cycle, and hence our climate, will change into the future. This is mainly due to the challenges of measuring remineralisation depth using conventional methods– a barrier which autonomous underwater vehicles are poised to overcome by providing high frequency data over long periods. This technological innovation will revolutionise our understanding of this important planetary C flux.
GOCART is an ambitious project to address current uncertainties in remineralisation depth. GOCART encompasses new observations, obtained using cutting-edge technology and novel methodology, through to global climate modelling. Underwater glider deployments will be used to establish the characteristics and significance of temporal variability in organic C flux and remineralisation depth during the most dynamic period of the year. This will enable new insights into the factors driving variability in remineralisation depth, ultimately leading to development of a new model parameterisation incorporating temporal variability. Using an innovative modelling framework, this parameterisation will be tested for its potential to improve predictions of ocean C storage. GOCART represents a significant advance in quantifying temporal variability in remineralisation depth, which is key to reducing uncertainty in model predictions of ocean C storage, and yet currently almost entirely unknown.
GOCART is an ambitious project to address current uncertainties in remineralisation depth. GOCART encompasses new observations, obtained using cutting-edge technology and novel methodology, through to global climate modelling. Underwater glider deployments will be used to establish the characteristics and significance of temporal variability in organic C flux and remineralisation depth during the most dynamic period of the year. This will enable new insights into the factors driving variability in remineralisation depth, ultimately leading to development of a new model parameterisation incorporating temporal variability. Using an innovative modelling framework, this parameterisation will be tested for its potential to improve predictions of ocean C storage. GOCART represents a significant advance in quantifying temporal variability in remineralisation depth, which is key to reducing uncertainty in model predictions of ocean C storage, and yet currently almost entirely unknown.
GOCART successfully completed its first two pieces of planned fieldwork, with extended glider deployments at South Georgia and in the Benguela upwelling region. GOCART funds were also leveraged to add a glider mission in the Southeast Pacific (completed). A mission in the Northeast Atlantic was due to take place in May 2020 but was postponed due to the COVID-19 pandemic. The latter two missions are in collaboration with international partners from the US.
The semi-automated processing and calibration of the glider data streams has been established in ‘toolbox’ form by GOCART postdocs Nathan Briggs and Filipa Carvalho. This substantial piece of work at the start of the project allowed the later glider deployments to be more autonomously processed.
Nathan Briggs has advanced autonomous methods for measuring key areas of the biological carbon pump and applied these methods to the GOCART glider dataset. In 2018, Nathan published a method for estimating primary productivity from diel cycles in dissolved oxygen concentration (Briggs et al., 2018), and he has now generated primary productivity estimates from the first two GOCART deployments using this method. Nathan also published a method in 2020 for autonomously quantifying the role of particle fragmentation in the biological carbon pump (Briggs et al., 2020), which will be applied to the GOCART glider dataset. Nathan produced estimates of mean particle size in the surface mixed layer from the first two GOCART deployments and produced estimates of downward particulate organic carbon flux via sinking particles. He found a strong correlation between the two quantities, suggesting that changes in surface particle size (likely driven by aggregation) drive changes in carbon flux on sub-weekly timescales. Nathan presented these results at the 2018 Ocean Optics conference and the 2019 IMBER Open Science Conference. Nathan also estimated particle sinking velocities using glider data from the first GOCART deployment and found an increase in mean sinking velocity with depth. He repeated this analysis on a wider biogeochemical Argo dataset and found a similar result. He presented these findings at the 2020 Ocean Sciences Meeting. This work contributes to delivery of GOCART Objectives 1 and 2.
Filipa Carvalho has focused on understanding physical drivers of the phytoplankton bloom dynamics in the South Georgia dataset. The full glider mission has been carefully calibrated by intercalibrating the three available gliders and using shipboard measurements during the cruise. Recurrent thermal restratification events have been identified and linked to increased chlorophyll fluorescence in the water column. Using glider observations and atmospheric forcing model output, dissipation rates have been calculated and the predominant drivers of stratification evaluated. Wind forcing shows a high correlation with mixed layer dynamics and is two orders of magnitude more important in establishing stratification than buoyancy forces (i.e. heat fluxes). Phytoplankton net growth rates have been calculated and increased growth is linked to restratification periods. This work contributes to delivery of GOCART Objective 3.
Benoit Espinola has developed a method to understand the role of spatial variability in chlorophyll on estimates of flux attenuation (Ruhl et al., 2020). The method includes a stochastic modelling approach (a backtracking model with a Monte-Carlo method) to find possible statistical funnels for a particle with a constant sinking speed. He has also developed an approach to correct flux observation profiles for the possible influence of spatial variability, enabling more robust estimates of the remineralisation length scale. This work contributes to delivery of GOCART Objective 1.
Stephanie Henson is investigating the temporal variability in primary production, export efficiency and transfer efficiency, building on work published in Henson et al. (2019). Her analysis is focused now on the South Georgia glider mission, and incorporating the ship-board observations to understand how variability in biological processes, such as zooplankton abundance and bacterial productivity, may alter the remineralisation of organic carbon. Stephanie is also exploring the frequency and magnitude of sub-weekly scale variability in export flux by applying wavelet analysis to the time series of flux from the South Georgia mission. This work contributes to delivery of GOCART Objectives 1 and 2.
Francisco de Melo Virissimo has commenced foundational work to explore the sensitivity of global carbon storage to seasonal variability in the remineralisation length scale of organic carbon using the Transport Matrix Model approach. This work contributes to delivery of GOCART Objectives 4 and 5.
Elisa Lovecchio has established the modelling framework to enable an exploration of the influence of (sub)mesoscale variability on estimates of export flux and remineralisation length scale in the Benguela mission. Initial sensitivity runs of the model have been performed with parameter values obtained from the Benguela ship-board and glider datasets. This work contributes to delivery of GOCART Objectives 1 and 4.
The semi-automated processing and calibration of the glider data streams has been established in ‘toolbox’ form by GOCART postdocs Nathan Briggs and Filipa Carvalho. This substantial piece of work at the start of the project allowed the later glider deployments to be more autonomously processed.
Nathan Briggs has advanced autonomous methods for measuring key areas of the biological carbon pump and applied these methods to the GOCART glider dataset. In 2018, Nathan published a method for estimating primary productivity from diel cycles in dissolved oxygen concentration (Briggs et al., 2018), and he has now generated primary productivity estimates from the first two GOCART deployments using this method. Nathan also published a method in 2020 for autonomously quantifying the role of particle fragmentation in the biological carbon pump (Briggs et al., 2020), which will be applied to the GOCART glider dataset. Nathan produced estimates of mean particle size in the surface mixed layer from the first two GOCART deployments and produced estimates of downward particulate organic carbon flux via sinking particles. He found a strong correlation between the two quantities, suggesting that changes in surface particle size (likely driven by aggregation) drive changes in carbon flux on sub-weekly timescales. Nathan presented these results at the 2018 Ocean Optics conference and the 2019 IMBER Open Science Conference. Nathan also estimated particle sinking velocities using glider data from the first GOCART deployment and found an increase in mean sinking velocity with depth. He repeated this analysis on a wider biogeochemical Argo dataset and found a similar result. He presented these findings at the 2020 Ocean Sciences Meeting. This work contributes to delivery of GOCART Objectives 1 and 2.
Filipa Carvalho has focused on understanding physical drivers of the phytoplankton bloom dynamics in the South Georgia dataset. The full glider mission has been carefully calibrated by intercalibrating the three available gliders and using shipboard measurements during the cruise. Recurrent thermal restratification events have been identified and linked to increased chlorophyll fluorescence in the water column. Using glider observations and atmospheric forcing model output, dissipation rates have been calculated and the predominant drivers of stratification evaluated. Wind forcing shows a high correlation with mixed layer dynamics and is two orders of magnitude more important in establishing stratification than buoyancy forces (i.e. heat fluxes). Phytoplankton net growth rates have been calculated and increased growth is linked to restratification periods. This work contributes to delivery of GOCART Objective 3.
Benoit Espinola has developed a method to understand the role of spatial variability in chlorophyll on estimates of flux attenuation (Ruhl et al., 2020). The method includes a stochastic modelling approach (a backtracking model with a Monte-Carlo method) to find possible statistical funnels for a particle with a constant sinking speed. He has also developed an approach to correct flux observation profiles for the possible influence of spatial variability, enabling more robust estimates of the remineralisation length scale. This work contributes to delivery of GOCART Objective 1.
Stephanie Henson is investigating the temporal variability in primary production, export efficiency and transfer efficiency, building on work published in Henson et al. (2019). Her analysis is focused now on the South Georgia glider mission, and incorporating the ship-board observations to understand how variability in biological processes, such as zooplankton abundance and bacterial productivity, may alter the remineralisation of organic carbon. Stephanie is also exploring the frequency and magnitude of sub-weekly scale variability in export flux by applying wavelet analysis to the time series of flux from the South Georgia mission. This work contributes to delivery of GOCART Objectives 1 and 2.
Francisco de Melo Virissimo has commenced foundational work to explore the sensitivity of global carbon storage to seasonal variability in the remineralisation length scale of organic carbon using the Transport Matrix Model approach. This work contributes to delivery of GOCART Objectives 4 and 5.
Elisa Lovecchio has established the modelling framework to enable an exploration of the influence of (sub)mesoscale variability on estimates of export flux and remineralisation length scale in the Benguela mission. Initial sensitivity runs of the model have been performed with parameter values obtained from the Benguela ship-board and glider datasets. This work contributes to delivery of GOCART Objectives 1 and 4.
GOCART has undertaken the first multi-month glider missions designed to quantify the sub-daily to seasonal variability in particulate organic carbon flux and remineralisation length scale. The semi-automated processing and calibration of the glider data streams has been established in ‘toolbox’ form by GOCART postdocs Nathan Briggs and Filipa Carvalho. This substantial piece of work at the start of the project allowed the later glider deployments to be more autonomously processed. The toolbox will be published in future allowing other groups worldwide working with glider data to semi-automate processing and calibration of their datastreams.
The dataset collected by GOCART will allow us to establish the characteristics and significance of temporal variability in organic carbon flux and remineralisation depth during the winter-to-spring transition period, i.e. the most dynamic period of the year. GOCART has already resulted in new insights into the factors driving variability in remineralisation depth (e.g. Briggs et al., 2020). Work is now underway that will ultimately lead to development of a new model parameterisation incorporating temporal variability. The innovative modelling framework for testing GOCART’s new parameterisation for its potential to improve predictions of ocean carbon storage has been established.
Expected results until the end of the project will target delivery of the GOCART objectives:
1. Quantify the variability in flux of particulate organic carbon through the TZ and its RLS on daily to sub-seasonal timescales
2. Determine the characteristics and significance of episodic pulses of flux
3. Investigate potential drivers of episodic flux pulses
4. Quantify the effect of temporal variability on uncertainty in RLS estimates
5. Establish and test a new empirical parameterisation of RLS that incorporates temporal variability
The dataset collected by GOCART will allow us to establish the characteristics and significance of temporal variability in organic carbon flux and remineralisation depth during the winter-to-spring transition period, i.e. the most dynamic period of the year. GOCART has already resulted in new insights into the factors driving variability in remineralisation depth (e.g. Briggs et al., 2020). Work is now underway that will ultimately lead to development of a new model parameterisation incorporating temporal variability. The innovative modelling framework for testing GOCART’s new parameterisation for its potential to improve predictions of ocean carbon storage has been established.
Expected results until the end of the project will target delivery of the GOCART objectives:
1. Quantify the variability in flux of particulate organic carbon through the TZ and its RLS on daily to sub-seasonal timescales
2. Determine the characteristics and significance of episodic pulses of flux
3. Investigate potential drivers of episodic flux pulses
4. Quantify the effect of temporal variability on uncertainty in RLS estimates
5. Establish and test a new empirical parameterisation of RLS that incorporates temporal variability