Using Existing Argo Trajectories to Statistically Predict Future Float Positions with a Transition Matrix

The Argo array provides nearly 4000 temperature and salinity profiles of the top 2000 m of the ocean every 10 days. Still, Argo floats will never be able to measure the ocean at all times, everywhere. Optimized Argo float distributions should match the spatial and temporal variability of the many so...

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Main Authors: Chamberlain, Paul, Talley, Lynne D., Mazloff, Matthew, Van Sebille, Erik, Gille, Sarah T., Tucker, Tyler, Scanderbeg, Megan, Robbins, Pelle
Other Authors: Sub Physical Oceanography, Marine and Atmospheric Research
Format: Article in Journal/Newspaper
Language:English
Published: 2023
Subjects:
Online Access:https://dspace.library.uu.nl/handle/1874/433020
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spelling ftunivutrecht:oai:dspace.library.uu.nl:1874/433020 2023-12-10T09:53:55+01:00 Using Existing Argo Trajectories to Statistically Predict Future Float Positions with a Transition Matrix Chamberlain, Paul Talley, Lynne D. Mazloff, Matthew Van Sebille, Erik Gille, Sarah T. Tucker, Tyler Scanderbeg, Megan Robbins, Pelle Sub Physical Oceanography Marine and Atmospheric Research 2023-09-01 application/pdf https://dspace.library.uu.nl/handle/1874/433020 en eng 0739-0572 https://dspace.library.uu.nl/handle/1874/433020 info:eu-repo/semantics/EmbargoedAccess Advection Buoy observations Lagrangian circulation/transport Large-scale motions Ocean Statistical forecasting Taverne Ocean Engineering Atmospheric Science Article 2023 ftunivutrecht 2023-11-15T23:22:11Z The Argo array provides nearly 4000 temperature and salinity profiles of the top 2000 m of the ocean every 10 days. Still, Argo floats will never be able to measure the ocean at all times, everywhere. Optimized Argo float distributions should match the spatial and temporal variability of the many societally important ocean features that they observe. Determining these distributions is challenging because float advection is difficult to predict. Using no external models, transition matrices based on existing Argo trajectories provide statistical inferences about Argo float motion. We use the 24 years of Argo locations to construct an optimal transition matrix that minimizes estimation bias and uncertainty. The optimal array is determined to have a 28° 3 28° spatial resolution with a 90-day time step. We then use the transition matrix to predict the probability of future float locations of the core Argo array, the Global Biogeochemical Array, and the Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) array. A comparison of transition matrices derived from floats using Argos system and Iridium communication methods shows the impact of surface displacements, which is most apparent near the equator. Additionally, we demonstrate the utility of transition matrices for validating models by comparing the matrix derived from Argo floats with that derived from a particle release experiment in the Southern Ocean State Estimate (SOSE). Article in Journal/Newspaper Southern Ocean Utrecht University Repository Southern Ocean
institution Open Polar
collection Utrecht University Repository
op_collection_id ftunivutrecht
language English
topic Advection
Buoy observations
Lagrangian circulation/transport
Large-scale motions
Ocean
Statistical forecasting
Taverne
Ocean Engineering
Atmospheric Science
spellingShingle Advection
Buoy observations
Lagrangian circulation/transport
Large-scale motions
Ocean
Statistical forecasting
Taverne
Ocean Engineering
Atmospheric Science
Chamberlain, Paul
Talley, Lynne D.
Mazloff, Matthew
Van Sebille, Erik
Gille, Sarah T.
Tucker, Tyler
Scanderbeg, Megan
Robbins, Pelle
Using Existing Argo Trajectories to Statistically Predict Future Float Positions with a Transition Matrix
topic_facet Advection
Buoy observations
Lagrangian circulation/transport
Large-scale motions
Ocean
Statistical forecasting
Taverne
Ocean Engineering
Atmospheric Science
description The Argo array provides nearly 4000 temperature and salinity profiles of the top 2000 m of the ocean every 10 days. Still, Argo floats will never be able to measure the ocean at all times, everywhere. Optimized Argo float distributions should match the spatial and temporal variability of the many societally important ocean features that they observe. Determining these distributions is challenging because float advection is difficult to predict. Using no external models, transition matrices based on existing Argo trajectories provide statistical inferences about Argo float motion. We use the 24 years of Argo locations to construct an optimal transition matrix that minimizes estimation bias and uncertainty. The optimal array is determined to have a 28° 3 28° spatial resolution with a 90-day time step. We then use the transition matrix to predict the probability of future float locations of the core Argo array, the Global Biogeochemical Array, and the Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) array. A comparison of transition matrices derived from floats using Argos system and Iridium communication methods shows the impact of surface displacements, which is most apparent near the equator. Additionally, we demonstrate the utility of transition matrices for validating models by comparing the matrix derived from Argo floats with that derived from a particle release experiment in the Southern Ocean State Estimate (SOSE).
author2 Sub Physical Oceanography
Marine and Atmospheric Research
format Article in Journal/Newspaper
author Chamberlain, Paul
Talley, Lynne D.
Mazloff, Matthew
Van Sebille, Erik
Gille, Sarah T.
Tucker, Tyler
Scanderbeg, Megan
Robbins, Pelle
author_facet Chamberlain, Paul
Talley, Lynne D.
Mazloff, Matthew
Van Sebille, Erik
Gille, Sarah T.
Tucker, Tyler
Scanderbeg, Megan
Robbins, Pelle
author_sort Chamberlain, Paul
title Using Existing Argo Trajectories to Statistically Predict Future Float Positions with a Transition Matrix
title_short Using Existing Argo Trajectories to Statistically Predict Future Float Positions with a Transition Matrix
title_full Using Existing Argo Trajectories to Statistically Predict Future Float Positions with a Transition Matrix
title_fullStr Using Existing Argo Trajectories to Statistically Predict Future Float Positions with a Transition Matrix
title_full_unstemmed Using Existing Argo Trajectories to Statistically Predict Future Float Positions with a Transition Matrix
title_sort using existing argo trajectories to statistically predict future float positions with a transition matrix
publishDate 2023
url https://dspace.library.uu.nl/handle/1874/433020
geographic Southern Ocean
geographic_facet Southern Ocean
genre Southern Ocean
genre_facet Southern Ocean
op_relation 0739-0572
https://dspace.library.uu.nl/handle/1874/433020
op_rights info:eu-repo/semantics/EmbargoedAccess
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