Assessing the Skill of a High-Resolution Marine Biophysical Model Using Geostatistical Analysis of Mesoscale Ocean Chlorophyll Variability From Field Observations and Remote Sensing
High-resolution ocean biophysical models are now routinely being conducted at basin and global-scale, opening opportunities to deepen our understanding of the mechanistic coupling of physical and biological processes at the mesoscale. Prior to using these models to test scientific questions, we need...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2021-04-01
|
| Series: | Frontiers in Marine Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2021.612764/full |
| _version_ | 1818603356002713600 |
|---|---|
| author | Rachel Eveleth David M. Glover Matthew C. Long Ivan D. Lima Alison P. Chase Scott C. Doney |
| author_facet | Rachel Eveleth David M. Glover Matthew C. Long Ivan D. Lima Alison P. Chase Scott C. Doney |
| author_sort | Rachel Eveleth |
| collection | DOAJ |
| description | High-resolution ocean biophysical models are now routinely being conducted at basin and global-scale, opening opportunities to deepen our understanding of the mechanistic coupling of physical and biological processes at the mesoscale. Prior to using these models to test scientific questions, we need to assess their skill. While progress has been made in validating the mean field, little work has been done to evaluate skill of the simulated mesoscale variability. Here we use geostatistical 2-D variograms to quantify the magnitude and spatial scale of chlorophyll a patchiness in a 1/10th-degree eddy-resolving coupled Community Earth System Model simulation. We compare results from satellite remote sensing and ship underway observations in the North Atlantic Ocean, where there is a large seasonal phytoplankton bloom. The coefficients of variation, i.e., the arithmetic standard deviation divided by the mean, from the two observational data sets are approximately invariant across a large range of mean chlorophyll a values from oligotrophic and winter to subpolar bloom conditions. This relationship between the chlorophyll a mesoscale variability and the mean field appears to reflect an emergent property of marine biophysics, and the high-resolution simulation does poorly in capturing this skill metric, with the model underestimating observed variability under low chlorophyll a conditions such as in the subtropics. |
| first_indexed | 2024-12-16T13:21:52Z |
| format | Article |
| id | doaj.art-e23b9a0255194a67a22f6ffb348b644f |
| institution | Directory Open Access Journal |
| issn | 2296-7745 |
| language | English |
| last_indexed | 2024-12-16T13:21:52Z |
| publishDate | 2021-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Marine Science |
| spelling | doaj.art-e23b9a0255194a67a22f6ffb348b644f2022-12-21T22:30:19ZengFrontiers Media S.A.Frontiers in Marine Science2296-77452021-04-01810.3389/fmars.2021.612764612764Assessing the Skill of a High-Resolution Marine Biophysical Model Using Geostatistical Analysis of Mesoscale Ocean Chlorophyll Variability From Field Observations and Remote SensingRachel Eveleth0David M. Glover1Matthew C. Long2Ivan D. Lima3Alison P. Chase4Scott C. Doney5Department of Geology, Oberlin College, Oberlin, OH, United StatesDepartment of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, United StatesClimate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, United StatesDepartment of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA, United StatesApplied Physics Laboratory, University of Washington, Seattle, WA, United StatesDepartment of Environmental Sciences, University of Virginia, Charlottesville, VA, United StatesHigh-resolution ocean biophysical models are now routinely being conducted at basin and global-scale, opening opportunities to deepen our understanding of the mechanistic coupling of physical and biological processes at the mesoscale. Prior to using these models to test scientific questions, we need to assess their skill. While progress has been made in validating the mean field, little work has been done to evaluate skill of the simulated mesoscale variability. Here we use geostatistical 2-D variograms to quantify the magnitude and spatial scale of chlorophyll a patchiness in a 1/10th-degree eddy-resolving coupled Community Earth System Model simulation. We compare results from satellite remote sensing and ship underway observations in the North Atlantic Ocean, where there is a large seasonal phytoplankton bloom. The coefficients of variation, i.e., the arithmetic standard deviation divided by the mean, from the two observational data sets are approximately invariant across a large range of mean chlorophyll a values from oligotrophic and winter to subpolar bloom conditions. This relationship between the chlorophyll a mesoscale variability and the mean field appears to reflect an emergent property of marine biophysics, and the high-resolution simulation does poorly in capturing this skill metric, with the model underestimating observed variability under low chlorophyll a conditions such as in the subtropics.https://www.frontiersin.org/articles/10.3389/fmars.2021.612764/fullgeostatistical analysisNorth Atlantic OceanCommunity Earth System Modelmodel validataionchlorophyll |
| spellingShingle | Rachel Eveleth David M. Glover Matthew C. Long Ivan D. Lima Alison P. Chase Scott C. Doney Assessing the Skill of a High-Resolution Marine Biophysical Model Using Geostatistical Analysis of Mesoscale Ocean Chlorophyll Variability From Field Observations and Remote Sensing Frontiers in Marine Science geostatistical analysis North Atlantic Ocean Community Earth System Model model validataion chlorophyll |
| title | Assessing the Skill of a High-Resolution Marine Biophysical Model Using Geostatistical Analysis of Mesoscale Ocean Chlorophyll Variability From Field Observations and Remote Sensing |
| title_full | Assessing the Skill of a High-Resolution Marine Biophysical Model Using Geostatistical Analysis of Mesoscale Ocean Chlorophyll Variability From Field Observations and Remote Sensing |
| title_fullStr | Assessing the Skill of a High-Resolution Marine Biophysical Model Using Geostatistical Analysis of Mesoscale Ocean Chlorophyll Variability From Field Observations and Remote Sensing |
| title_full_unstemmed | Assessing the Skill of a High-Resolution Marine Biophysical Model Using Geostatistical Analysis of Mesoscale Ocean Chlorophyll Variability From Field Observations and Remote Sensing |
| title_short | Assessing the Skill of a High-Resolution Marine Biophysical Model Using Geostatistical Analysis of Mesoscale Ocean Chlorophyll Variability From Field Observations and Remote Sensing |
| title_sort | assessing the skill of a high resolution marine biophysical model using geostatistical analysis of mesoscale ocean chlorophyll variability from field observations and remote sensing |
| topic | geostatistical analysis North Atlantic Ocean Community Earth System Model model validataion chlorophyll |
| url | https://www.frontiersin.org/articles/10.3389/fmars.2021.612764/full |
| work_keys_str_mv | AT racheleveleth assessingtheskillofahighresolutionmarinebiophysicalmodelusinggeostatisticalanalysisofmesoscaleoceanchlorophyllvariabilityfromfieldobservationsandremotesensing AT davidmglover assessingtheskillofahighresolutionmarinebiophysicalmodelusinggeostatisticalanalysisofmesoscaleoceanchlorophyllvariabilityfromfieldobservationsandremotesensing AT matthewclong assessingtheskillofahighresolutionmarinebiophysicalmodelusinggeostatisticalanalysisofmesoscaleoceanchlorophyllvariabilityfromfieldobservationsandremotesensing AT ivandlima assessingtheskillofahighresolutionmarinebiophysicalmodelusinggeostatisticalanalysisofmesoscaleoceanchlorophyllvariabilityfromfieldobservationsandremotesensing AT alisonpchase assessingtheskillofahighresolutionmarinebiophysicalmodelusinggeostatisticalanalysisofmesoscaleoceanchlorophyllvariabilityfromfieldobservationsandremotesensing AT scottcdoney assessingtheskillofahighresolutionmarinebiophysicalmodelusinggeostatisticalanalysisofmesoscaleoceanchlorophyllvariabilityfromfieldobservationsandremotesensing |