TY - JOUR
T1 - Coupling ecological concepts with an ocean-colour model
T2 - Parameterisation and forward modelling
AU - Sun, Xuerong
AU - Brewin, Robert J.W.
AU - Sathyendranath, Shubha
AU - Dall'Olmo, Giorgio
AU - Antoine, David
AU - Barlow, Ray
AU - Bracher, Astrid
AU - Kheireddine, Malika
AU - Li, Mengyu
AU - Raitsos, Dionysios E.
AU - Shen, Fang
AU - Tilstone, Gavin H.
AU - Vellucci, Vincenzo
N1 - Publisher Copyright:
© 2024 The Authors
PY - 2025/1/1
Y1 - 2025/1/1
N2 - In the first part of this paper series (Sun et al., 2023), we developed an ecological model that partitions the total chlorophyll-a concentration (Chl-a) into three phytoplankton size classes (PSCs), pico-, nano-, and microplankton. The parameters of this model are controlled by sea surface temperature (SST), intended to capture shifts in phytoplankton size structure independently of variations in total Chl-a. In this second part of the series, we present an Ocean Colour Modelling Framework (OCMF), building on the classical Case-1 assumption, that explicitly incorporates our ecological model. The OCMF assumes the presence of the three PSCs and the existence of an independent background of non-algal particles. The framework assumes each phytoplankton group resides in a distinct optical environment, assigning chlorophyll-specific inherent optical properties to each group, both directly (phytoplankton) and indirectly (non-algal particulate and dissolved substances). The OCMF is parameterised, validated, and assessed using a large global dataset of inherent and apparent optical properties. We use the OCMF to explore the influence of variations in temperature and Chl-a on phytoplankton size structure and its resulting effects on ocean colour. We also discuss applications of the OCMF, such as its potential for inverse modelling and phytoplankton climate trend detection, which will be explored further in subsequent papers.
AB - In the first part of this paper series (Sun et al., 2023), we developed an ecological model that partitions the total chlorophyll-a concentration (Chl-a) into three phytoplankton size classes (PSCs), pico-, nano-, and microplankton. The parameters of this model are controlled by sea surface temperature (SST), intended to capture shifts in phytoplankton size structure independently of variations in total Chl-a. In this second part of the series, we present an Ocean Colour Modelling Framework (OCMF), building on the classical Case-1 assumption, that explicitly incorporates our ecological model. The OCMF assumes the presence of the three PSCs and the existence of an independent background of non-algal particles. The framework assumes each phytoplankton group resides in a distinct optical environment, assigning chlorophyll-specific inherent optical properties to each group, both directly (phytoplankton) and indirectly (non-algal particulate and dissolved substances). The OCMF is parameterised, validated, and assessed using a large global dataset of inherent and apparent optical properties. We use the OCMF to explore the influence of variations in temperature and Chl-a on phytoplankton size structure and its resulting effects on ocean colour. We also discuss applications of the OCMF, such as its potential for inverse modelling and phytoplankton climate trend detection, which will be explored further in subsequent papers.
KW - Climate change
KW - Forward modelling
KW - Inherent and apparent optical properties
KW - Ocean colour modelling framework
KW - Ocean-colour remote sensing
KW - Phytoplankton size classes
UR - https://www.scopus.com/pages/publications/85208917355
U2 - 10.1016/j.rse.2024.114487
DO - 10.1016/j.rse.2024.114487
M3 - 文章
AN - SCOPUS:85208917355
SN - 0034-4257
VL - 316
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
M1 - 114487
ER -