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Heat Flux Estimates From a Synthesis of Satellite Observations and a Hydrodynamic Model (With Application to Long Island Sound).

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Title: Heat Flux Estimates From a Synthesis of Satellite Observations and a Hydrodynamic Model (With Application to Long Island Sound).
Authors: McCardell, Grant1 (AUTHOR) grant.mccardell@uconn.edu, Horwitz, Rachel2 (AUTHOR), Ilia, Amin1,3 (AUTHOR), Howard Strobel, M. Kay1 (AUTHOR), Fake, Todd1 (AUTHOR), O'Donnell, James1,4 (AUTHOR)
Source: Journal of Geophysical Research. Oceans. Feb2023, Vol. 128 Issue 2, p1-13. 13p.
Subject Terms: *Ocean temperature, Heat flux, Kalman filtering, Artificial satellites
Abstract: Estimating surface heat fluxes via direct covariance measurements or bulk formulae is observation‐intensive and costly. We present a methodology whereby we estimate net surface heat fluxes as the difference between the depth‐integrated heat tendencies and the depth‐integrated horizontal heat exchanges in a hydrodynamic model. We calibrate the model to achieve a good representation of mixing and advection and then assimilate satellite sea surface temperature (SST) observations into the model at an 8‐day scale. The SST data assimilation forces a good representation of observed temperatures and heat tendencies both at the surface and throughout the water column. We estimate the horizontal heat exchange directly from the model output and then infer the surface fluxes required to close the budget. When we apply this methodology to a model with prescribed surface heat fluxes and without data assimilation, we can recover the prescribed fluxes with an RMS error of ±10 W m−2 and an r2 of 0.998. When we compare our results to those estimated using Coupled Ocean‐Atmosphere Response Experiment bulk formulae with observations in western Long Island Sound, we find similarly good agreement. Plain Language Summary: We use satellite observations of sea surface temperatures in combination with a three‐dimensional simulation of the ocean to infer the air‐sea surface heat fluxes needed to create the observed surface temperatures. We use this methodology to quantify the annual cycle of warming and cooling fluxes in Long Island Sound (LIS). Our surface heat flux estimates compare well with estimates obtained from meteorological measurements in the western LIS. Key Points: We infer net air‐sea heat fluxes by assimilating satellite measurements of sea surface temperatures into a calibrated hydrodynamic modelWe estimate both surface heat fluxes and horizontal exchange fluxesWe describe the annual evolution of the heat budget in Long Island Sound, USA [ABSTRACT FROM AUTHOR]
Copyright of Journal of Geophysical Research. Oceans is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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PubTypeId: academicJournal
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Heat Flux Estimates From a Synthesis of Satellite Observations and a Hydrodynamic Model (With Application to Long Island Sound).
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  Data: <searchLink fieldCode="AR" term="%22McCardell%2C+Grant%22">McCardell, Grant</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> grant.mccardell@uconn.edu</i><br /><searchLink fieldCode="AR" term="%22Horwitz%2C+Rachel%22">Horwitz, Rachel</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ilia%2C+Amin%22">Ilia, Amin</searchLink><relatesTo>1,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Howard+Strobel%2C+M%2E+Kay%22">Howard Strobel, M. Kay</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Fake%2C+Todd%22">Fake, Todd</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22O'Donnell%2C+James%22">O'Donnell, James</searchLink><relatesTo>1,4</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Geophysical+Research%2E+Oceans%22">Journal of Geophysical Research. Oceans</searchLink>. Feb2023, Vol. 128 Issue 2, p1-13. 13p.
– Name: Subject
  Label: Subject Terms
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  Data: *<searchLink fieldCode="DE" term="%22Ocean+temperature%22">Ocean temperature</searchLink><br /><searchLink fieldCode="DE" term="%22Heat+flux%22">Heat flux</searchLink><br /><searchLink fieldCode="DE" term="%22Kalman+filtering%22">Kalman filtering</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+satellites%22">Artificial satellites</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Estimating surface heat fluxes via direct covariance measurements or bulk formulae is observation‐intensive and costly. We present a methodology whereby we estimate net surface heat fluxes as the difference between the depth‐integrated heat tendencies and the depth‐integrated horizontal heat exchanges in a hydrodynamic model. We calibrate the model to achieve a good representation of mixing and advection and then assimilate satellite sea surface temperature (SST) observations into the model at an 8‐day scale. The SST data assimilation forces a good representation of observed temperatures and heat tendencies both at the surface and throughout the water column. We estimate the horizontal heat exchange directly from the model output and then infer the surface fluxes required to close the budget. When we apply this methodology to a model with prescribed surface heat fluxes and without data assimilation, we can recover the prescribed fluxes with an RMS error of ±10 W m−2 and an r2 of 0.998. When we compare our results to those estimated using Coupled Ocean‐Atmosphere Response Experiment bulk formulae with observations in western Long Island Sound, we find similarly good agreement. Plain Language Summary: We use satellite observations of sea surface temperatures in combination with a three‐dimensional simulation of the ocean to infer the air‐sea surface heat fluxes needed to create the observed surface temperatures. We use this methodology to quantify the annual cycle of warming and cooling fluxes in Long Island Sound (LIS). Our surface heat flux estimates compare well with estimates obtained from meteorological measurements in the western LIS. Key Points: We infer net air‐sea heat fluxes by assimilating satellite measurements of sea surface temperatures into a calibrated hydrodynamic modelWe estimate both surface heat fluxes and horizontal exchange fluxesWe describe the annual evolution of the heat budget in Long Island Sound, USA [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Geophysical Research. Oceans is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1029/2022JC018463
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      – Code: eng
        Text: English
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        PageCount: 13
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      – SubjectFull: Heat flux
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      – SubjectFull: Kalman filtering
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      – SubjectFull: Artificial satellites
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      – TitleFull: Heat Flux Estimates From a Synthesis of Satellite Observations and a Hydrodynamic Model (With Application to Long Island Sound).
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            NameFull: McCardell, Grant
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            NameFull: Horwitz, Rachel
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            NameFull: Ilia, Amin
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            NameFull: Howard Strobel, M. Kay
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            NameFull: Fake, Todd
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              M: 02
              Text: Feb2023
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              Y: 2023
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              Value: 128
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            – TitleFull: Journal of Geophysical Research. Oceans
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