Preprints
https://doi.org/10.5194/bg-2021-351
https://doi.org/10.5194/bg-2021-351
 
24 Jan 2022
24 Jan 2022
Status: this discussion paper is a preprint. It has been under review for the journal Biogeosciences (BG). The manuscript was not accepted for further review after discussion.

Reviews and syntheses: Assessment of Biogeochemical Models in the Marine Environment

Kaltham Ismail and Maryam Rashed Al-Shehhi Kaltham Ismail and Maryam Rashed Al-Shehhi
  • Department of Civil, Infrastructure and Environmental Engineering, Khalifa University, Abu Dhabi, UAE

Abstract. Marine biogeochemical models are key tools utilized to quantify numerous aspects of biogeochemistry including primary productivity, cycling of nutrients, redistribution of plankton, and variability of the carbon cycle in the ocean. These models are typically coupled to physical models with a horizontal resolution varying from few kilometers to more than 400 kilometers. Many of the existing biogeochemical models are commonly based on the NPZD model structure however, these models differ in their complexity determined by the number of state variables and the functional forms. Therefore, this review illustrates the types of the common biogeochemical models categorized based on the complexity levels and the governing equations. Then, applications of these models in several ecosystems of the world ocean are presented through a comprehensive assessment and evaluation of their performance in reproducing biogeochemical parameters such as chlorophyll-a, nutrients, as well as carbon and oxygen. In general, models based on functional group approach when coupled to high-resolution physical models show good estimates of surface nutrients such as nitrogen (N), phosphorous (P), silica (S) in global oceans with correlation coefficients (r) of ≥ 0.85, ≥ 0.9, and ≥ 0.78 respectively. Similarly, NPZD based models coupled to suitable physical models are found to accurately reproduce N, P, and oxygen (O) with coefficients of determination (R2) around 0.9 (for N & P) and ~ > 0.9 (for O) particularly in the Indian and Pacific waters. In addition, highest performance for iron prediction in global oceans is found with r values between 0.7 and 0.86 particularly by functional group approach models. However, chlorophyll-a prediction has shown varying performances by all types of models with r ranging from 0.55 and 0.9. So, applications of biogeochemical models are dependent on the features of the ecosystem and the purpose of the study. Therefore, the functional group approach models are mainly applied to investigate biogeochemical cycles while NPZD models are mainly used for physical-biological investigation.

Kaltham Ismail and Maryam Rashed Al-Shehhi

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2021-351', Anonymous Referee #1, 22 Feb 2022
  • RC2: 'Comment on bg-2021-351', Anonymous Referee #2, 03 Mar 2022

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2021-351', Anonymous Referee #1, 22 Feb 2022
  • RC2: 'Comment on bg-2021-351', Anonymous Referee #2, 03 Mar 2022

Kaltham Ismail and Maryam Rashed Al-Shehhi

Kaltham Ismail and Maryam Rashed Al-Shehhi

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Short summary
This review illustrates the types of common biogeochemical models categorized based on the complexity levels and the governing equations. A comprehensive assessment of their performances in reproducing biogeochemical parameters such as chlorophyll-a, nutrients, carbon and oxygen are presented herein based on reviewing more than 100 research papers.
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