Seasonality of the North Pacific Ocean Desert area in the past two decades and a modelling perspective for the 21st century

Meng, Siyu; Gong, Xun; Webber, Benjamin; Joshi, Manoj; Ding, Xiaokun; Gong, Xiang; Gu, Mingliang; Gao, Huiwang

doi:10.5194/egusphere-2025-13

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https://doi.org/10.5194/egusphere-2025-13

Preprints

14 Mar 2025

| 14 Mar 2025

Seasonality of the North Pacific Ocean Desert area in the past two decades and a modelling perspective for the 21st century

Siyu Meng, Xun Gong, Benjamin Webber, Manoj Joshi, Xiaokun Ding, Xiang Gong, Mingliang Gu, and Huiwang Gao

Abstract. As the largest ocean desert, the North Pacific Ocean Desert (NPOD) exhibits pronounced variations across seasonal, decadal, and centennial time scales. Notably, changes in the seasonality of the NPOD are thought to have larger effects on marine ecosystems than variability in the annual-mean state of the NPOD. However, the interannual variability of NPOD seasonality and its response to climate processes remain unclear. Here, we investigate the amplitude of the seasonal cycle in NPOD area and its linkage with climate variability and change. Our results show that the El Niño - Southern Oscillation (ENSO) modulated the seasonal maximum of NPOD area in boreal summer, and thus the amplitude of the seasonal cycle during 1998–2021. This is primarily due to ENSO-induced changes in nutrient transport via equatorial upwelling and thermal stratification. Future projections based on Coupled Model Intercomparison Project Phase 5 (CMIP5) modelling results and an Elman neural network indicate a significant decrease in the seasonal amplitude of NPOD area by 2100, attributed to the growing seasonal minimum of NPOD area in winter along the anthropogenic increase in atmospheric CO₂. The findings highlight the importance of considering seasonal differences in future research on the interannual variability of ocean desert and underscore the need for models to distinguish between the effects of climate variability and change.

Received: 12 Jan 2025 – Discussion started: 14 Mar 2025

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02 Feb 2026

Seasonality of the North Pacific Oligotrophic Gyre area in the past two decades and a modelling perspective for the 21st century

Siyu Meng, Xun Gong, Benjamin G. M. Webber, Manoj Joshi, Xiaokun Ding, Xiang Gong, Mingliang Gu, and Huiwang Gao

Biogeosciences, 23, 867–879, https://doi.org/10.5194/bg-23-867-2026,https://doi.org/10.5194/bg-23-867-2026, 2026

Short summary

Siyu Meng, Xun Gong, Benjamin Webber, Manoj Joshi, Xiaokun Ding, Xiang Gong, Mingliang Gu, and Huiwang Gao

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-13', Anonymous Referee #1, 12 Jun 2025

The current manuscript describes spatial-temporal changes in surface chlorophyll concentrations in the oligotrophic north pacific gyre as observed using satellite remote sensing data and as assessed using Earth System Models. The work adds to a body of literature on this topic by evaluating higher temporal resolution data that climatological annual average patterns assessed in earlier studies. I have a few comments.
1) I think it would be beneficial for the science community to avoid using the term ‘ocean desert’. The oligotrophic central ocean gyres are not comparable to deserts on land. The gyres are actually very biologically active and their water column net primary production is not much lower than, for example, mesotrophic systems. I recommend replacing ‘ocean desert’ with ‘oligotrophic ocean gyre’.
2) One of my primary concerns with this manuscript is that the analysis is based on spatial-temporal changes in surface chlorophyll concentration, and these are interpreted as reflecting phytoplankton biomass. Chlorophyll concentration, however, reflects both phytoplankton biomass and physiology (i.e., Chl:C) and the latter element reflects both nutrient availability and mixed layer light conditions. Distinguishing these factors controlling chlorophyll concentration is important as it can fundamentally impact the interpretation of observations. For example, it should be assumed a priori that chlorophyll concentration will decrease in response to a shoaling of the mixed layer and/or increasing incident sunlight (even in the total absence of change in nutrient availability or phytoplankton biomass) simply because phytoplankton will adjust Chl:C in response to changing mixed layer light levels (i.e., photoacclimation). One can easily envision that the strong seasonal cycle in surface chlorophyll concentration reported in this manuscript is entirely due to this photoacclimation response and may have nothing to do with changes in phytoplankton biomass or nutrient vertical transport (see for example figure 2 in Behrenfeld et al. 2005 GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 19, GB1006, doi:10.1029/2004GB002299). It can also be easily envisioned that the observed relationships between chlorophyll concentration and ENSO cycles likewise primarily reflects changes in mixed layer light levels. It is worthwhile noting here that the ENN used in this model includes solar radiation as a primary input (i.e., photoacclimation, not nutrient stress) and that the other two inputs (SST and wind stress curl) are also linked to variations in mixed layer light levels. Unlike the photoacclimation response, it cannot be assumed a priori that mixed layer shoaling will result in a decrease in chlorophyll concentration due to a reduction in vertical nutrient transport (see for example: Lozier et al. 2011, GEOPHYSICAL RESEARCH LETTERS, VOL. 38, L18609, doi:10.1029/2011GL049414).
The accurate interpretation of mechanism driving observed surface chlorophyll concentrations is import throughout this manuscript. For example, a decrease in chlorophyll due to photoacclimation to higher mixed layer light levels is expected to be associated with either unchanged or increased primary production, not a decrease. Another example is that a photoacclimation-based chlorophyll response makes the evaluation of phytoplankton ‘blooms’ in the oligotrophic north pacific gyre very questionable. The term ‘bloom’ is usually associated with a significant change in phytoplankton biomass, not a seasonal change in light driven (or nutrient-driven for that matter) change in Chl:C. Thus, without carefully distinguishing light-, nutrient-, and biomass-driven changes in chlorophyll concentration, the section of the manuscript regarding bloom properties is compromised. It may also be noted here that the more common NPOD_WHY feature shown in figure 4 is consistent with photoacclimation to winter minima in mixed layer light levels and that the less common NPOD_SHY also corresponds (according to the authors) to regions where summer mixed layer depths are high (i.e., lower light). The importance of light- versus nutrient-driven chlorophyll changes also compromises the validity of the conceptual model presented in figure 7.
3) It is noteworthy that a decrease in surface chlorophyll concentration will correspond to a decrease in mixed layer light attenuation coefficients, causing submixed layer light levels to increase and thus submixed layer primary production to increase, again questioning the quantitative significance of surface chlorophyll concentration changes to overall productivity.
4) Figure 3 provides an interesting analysis of temporal trends in chlorophyll concentration, but it seems it would be useful to also show an overall time series of these trends. Figure 3b does this to a degree in a monthly-resolved manner, but there is no indication in this panel which of the monthly trends are statistically significant.
5) In figure 2 and as discussed in the text, changes in summer NPOD area between El Nino and La Nina conditions are not widespread but rather primarily isolated to the two regions indicated in figure 2. It is therefore not clear to me why the influence of ENSO was evaluated based on physical properties averaged over the entire NPOD (line 200). Why wasn’t this analysis focused on physical changes only in the areas where ENSO effects are seen? If the assessed changes in physical properties are representative of the entire NPOD, why are there no changes in chlorophyll concentration observed over the entire region?
6) It seems to me that the manuscript is a bit critical of the Earth System Model results without being equally critical of the ENN results. For example, how reliable are the ENN predictions about future change when the ENN is built from hindcast data that doesn’t take into account future changes in major ocean physical features (e.g., a potential northward movement in the location of the Kuroshio current) that provide critical constraints on the potential areal extent of the oligotrophic north pacific gyre? I think a more balanced evaluation of strengths and weakness of different approaches is warranted.

Minor comments:
7) the light colored symbols and lines in figure 1 are nearly impossible to see. I suggest bolder colors. Same issue in figure 2 regarding the La Nina lines.
8) the black contours in figure 4 are not defined in the caption.

Citation: https://doi.org/10.5194/egusphere-2025-13-RC1
- AC1: 'Reply on RC1', Siyu Meng, 24 Aug 2025
  
  We thank the reviewer for these constructive comments on our work which have improved the manuscript. In this version, we have
  1）included phytoplankton carbon data and calculated light conditions within the mixed layer, and further discussed how El Niño - Southern Oscillation (ENSO) modifies light availability in the mixed layer, thereby leading to phytoplankton photoacclimation responses and affecting the variation of the North Pacific oligotrophic ocean gyre.
  2）redefined the key study region, and analyzed how chlorophyll variations in this region alter the interannual variability of the North Pacific oligotrophic ocean gyre.
  3）provided a more balanced comparison between the Earth System Models (ESMs) and the Elman Neural Network (ENN) model, highlighting that the latter does not account for dynamical and biological processes, such as phytoplankton growth and grazing.
  4）revised several figures for clarity.
  Please see the Supplement PDF for point-by-point response.
  On behalf on all authors.
  
  Citation: https://doi.org/10.5194/egusphere-2025-13-AC1
RC2:
'Comment on egusphere-2025-13', Emmanuel Boss, 15 Jun 2025

This paper provide a bottom-up (nutrient/stratification) analysis to the dynamics of phytoplankton in the North Pacific subtropical gyre.
The premise of this paper is that this region is a desert that is modulated by nutrient dynamics.
This premise is wrong for many reason which I will detail below:
1. As Ed Laws has shown in his ARMS review, phytoplankton cells in this and similar (surface) area divide once a day. If this is the case, why call it a desert?
2. The designation of desert is based on surface. [chl a]. [Chl a] is a problematic biomass indicator due to photoacclimation. what about phytoplanton carbon or nitrogen, and in particular, depth integrated? Shouldn't the depth integrated value be what we look at when considering the contribution to the ecosystem rather than surface concentrations?
3. Phytoplankton accumulation, e.g. the change of concentration with time, is one to two order of magnitude smaller than their growth-rate, indicating that loss processes (e.g. grazing and viruses) are just as important as growth inducing processes in the dynamics of phytoplankton. While I do understand that it is hard to study these processes, ignoring them will not help in understanding their accumulation dynamics. In the least one has to acknowledge the equal importance of these processes and the assumption models do when parametrizing them (e.g. tuning to get correctly the average chlorophyll, etc').
Dear authors: I am often wrong. If you feel that the major comments above are not reasonable or plainly wrong, I urge you to contact me directly and if convinced, I would be more than happy to change my review. All the best, Emmanuel Boss

Citation: https://doi.org/10.5194/egusphere-2025-13-RC2
- AC2: 'Reply on RC2', Siyu Meng, 24 Aug 2025
  
  We thank the reviewer for the constructive comments, which have helped us improve the manuscript. In response, we have
  1) replaced the term North Pacific Ocean Desert (NPOD) with North Pacific oligotrophic ocean gyre (NPOG) and clarified the ecological significance of phytoplankton in this region.
  2) made a clear distinction between surface chlorophyll, phytoplankton biomass, and primary productivity, and incorporated POC-based phytoplankton carbon estimates and mixed-layer light availability.
  3) expanded the analysis of ENSO impacts on NPOG variability by highlighting the role of phytoplankton photoacclimation.
  4) added discussion acknowledging the equal importance of phytoplankton loss processes (e.g., grazing) alongside growth, clarifying how such processes are represented in models, and noting the empirical nature of the Elman Neural Network (ENN)-based reconstruction.
  Please see the Supplement PDF for point-by-point response.
  On behalf on all authors.
  
  Citation: https://doi.org/10.5194/egusphere-2025-13-AC2

Interactive discussion

Status: closed

RC1:
'Comment on egusphere-2025-13', Anonymous Referee #1, 12 Jun 2025

The current manuscript describes spatial-temporal changes in surface chlorophyll concentrations in the oligotrophic north pacific gyre as observed using satellite remote sensing data and as assessed using Earth System Models. The work adds to a body of literature on this topic by evaluating higher temporal resolution data that climatological annual average patterns assessed in earlier studies. I have a few comments.
1) I think it would be beneficial for the science community to avoid using the term ‘ocean desert’. The oligotrophic central ocean gyres are not comparable to deserts on land. The gyres are actually very biologically active and their water column net primary production is not much lower than, for example, mesotrophic systems. I recommend replacing ‘ocean desert’ with ‘oligotrophic ocean gyre’.
2) One of my primary concerns with this manuscript is that the analysis is based on spatial-temporal changes in surface chlorophyll concentration, and these are interpreted as reflecting phytoplankton biomass. Chlorophyll concentration, however, reflects both phytoplankton biomass and physiology (i.e., Chl:C) and the latter element reflects both nutrient availability and mixed layer light conditions. Distinguishing these factors controlling chlorophyll concentration is important as it can fundamentally impact the interpretation of observations. For example, it should be assumed a priori that chlorophyll concentration will decrease in response to a shoaling of the mixed layer and/or increasing incident sunlight (even in the total absence of change in nutrient availability or phytoplankton biomass) simply because phytoplankton will adjust Chl:C in response to changing mixed layer light levels (i.e., photoacclimation). One can easily envision that the strong seasonal cycle in surface chlorophyll concentration reported in this manuscript is entirely due to this photoacclimation response and may have nothing to do with changes in phytoplankton biomass or nutrient vertical transport (see for example figure 2 in Behrenfeld et al. 2005 GLOBAL BIOGEOCHEMICAL CYCLES, VOL. 19, GB1006, doi:10.1029/2004GB002299). It can also be easily envisioned that the observed relationships between chlorophyll concentration and ENSO cycles likewise primarily reflects changes in mixed layer light levels. It is worthwhile noting here that the ENN used in this model includes solar radiation as a primary input (i.e., photoacclimation, not nutrient stress) and that the other two inputs (SST and wind stress curl) are also linked to variations in mixed layer light levels. Unlike the photoacclimation response, it cannot be assumed a priori that mixed layer shoaling will result in a decrease in chlorophyll concentration due to a reduction in vertical nutrient transport (see for example: Lozier et al. 2011, GEOPHYSICAL RESEARCH LETTERS, VOL. 38, L18609, doi:10.1029/2011GL049414).
The accurate interpretation of mechanism driving observed surface chlorophyll concentrations is import throughout this manuscript. For example, a decrease in chlorophyll due to photoacclimation to higher mixed layer light levels is expected to be associated with either unchanged or increased primary production, not a decrease. Another example is that a photoacclimation-based chlorophyll response makes the evaluation of phytoplankton ‘blooms’ in the oligotrophic north pacific gyre very questionable. The term ‘bloom’ is usually associated with a significant change in phytoplankton biomass, not a seasonal change in light driven (or nutrient-driven for that matter) change in Chl:C. Thus, without carefully distinguishing light-, nutrient-, and biomass-driven changes in chlorophyll concentration, the section of the manuscript regarding bloom properties is compromised. It may also be noted here that the more common NPOD_WHY feature shown in figure 4 is consistent with photoacclimation to winter minima in mixed layer light levels and that the less common NPOD_SHY also corresponds (according to the authors) to regions where summer mixed layer depths are high (i.e., lower light). The importance of light- versus nutrient-driven chlorophyll changes also compromises the validity of the conceptual model presented in figure 7.
3) It is noteworthy that a decrease in surface chlorophyll concentration will correspond to a decrease in mixed layer light attenuation coefficients, causing submixed layer light levels to increase and thus submixed layer primary production to increase, again questioning the quantitative significance of surface chlorophyll concentration changes to overall productivity.
4) Figure 3 provides an interesting analysis of temporal trends in chlorophyll concentration, but it seems it would be useful to also show an overall time series of these trends. Figure 3b does this to a degree in a monthly-resolved manner, but there is no indication in this panel which of the monthly trends are statistically significant.
5) In figure 2 and as discussed in the text, changes in summer NPOD area between El Nino and La Nina conditions are not widespread but rather primarily isolated to the two regions indicated in figure 2. It is therefore not clear to me why the influence of ENSO was evaluated based on physical properties averaged over the entire NPOD (line 200). Why wasn’t this analysis focused on physical changes only in the areas where ENSO effects are seen? If the assessed changes in physical properties are representative of the entire NPOD, why are there no changes in chlorophyll concentration observed over the entire region?
6) It seems to me that the manuscript is a bit critical of the Earth System Model results without being equally critical of the ENN results. For example, how reliable are the ENN predictions about future change when the ENN is built from hindcast data that doesn’t take into account future changes in major ocean physical features (e.g., a potential northward movement in the location of the Kuroshio current) that provide critical constraints on the potential areal extent of the oligotrophic north pacific gyre? I think a more balanced evaluation of strengths and weakness of different approaches is warranted.

Minor comments:
7) the light colored symbols and lines in figure 1 are nearly impossible to see. I suggest bolder colors. Same issue in figure 2 regarding the La Nina lines.
8) the black contours in figure 4 are not defined in the caption.

Citation: https://doi.org/10.5194/egusphere-2025-13-RC1
- AC1: 'Reply on RC1', Siyu Meng, 24 Aug 2025
  
  We thank the reviewer for these constructive comments on our work which have improved the manuscript. In this version, we have
  1）included phytoplankton carbon data and calculated light conditions within the mixed layer, and further discussed how El Niño - Southern Oscillation (ENSO) modifies light availability in the mixed layer, thereby leading to phytoplankton photoacclimation responses and affecting the variation of the North Pacific oligotrophic ocean gyre.
  2）redefined the key study region, and analyzed how chlorophyll variations in this region alter the interannual variability of the North Pacific oligotrophic ocean gyre.
  3）provided a more balanced comparison between the Earth System Models (ESMs) and the Elman Neural Network (ENN) model, highlighting that the latter does not account for dynamical and biological processes, such as phytoplankton growth and grazing.
  4）revised several figures for clarity.
  Please see the Supplement PDF for point-by-point response.
  On behalf on all authors.
  
  Citation: https://doi.org/10.5194/egusphere-2025-13-AC1
RC2:
'Comment on egusphere-2025-13', Emmanuel Boss, 15 Jun 2025

This paper provide a bottom-up (nutrient/stratification) analysis to the dynamics of phytoplankton in the North Pacific subtropical gyre.
The premise of this paper is that this region is a desert that is modulated by nutrient dynamics.
This premise is wrong for many reason which I will detail below:
1. As Ed Laws has shown in his ARMS review, phytoplankton cells in this and similar (surface) area divide once a day. If this is the case, why call it a desert?
2. The designation of desert is based on surface. [chl a]. [Chl a] is a problematic biomass indicator due to photoacclimation. what about phytoplanton carbon or nitrogen, and in particular, depth integrated? Shouldn't the depth integrated value be what we look at when considering the contribution to the ecosystem rather than surface concentrations?
3. Phytoplankton accumulation, e.g. the change of concentration with time, is one to two order of magnitude smaller than their growth-rate, indicating that loss processes (e.g. grazing and viruses) are just as important as growth inducing processes in the dynamics of phytoplankton. While I do understand that it is hard to study these processes, ignoring them will not help in understanding their accumulation dynamics. In the least one has to acknowledge the equal importance of these processes and the assumption models do when parametrizing them (e.g. tuning to get correctly the average chlorophyll, etc').
Dear authors: I am often wrong. If you feel that the major comments above are not reasonable or plainly wrong, I urge you to contact me directly and if convinced, I would be more than happy to change my review. All the best, Emmanuel Boss

Citation: https://doi.org/10.5194/egusphere-2025-13-RC2
- AC2: 'Reply on RC2', Siyu Meng, 24 Aug 2025
  
  We thank the reviewer for the constructive comments, which have helped us improve the manuscript. In response, we have
  1) replaced the term North Pacific Ocean Desert (NPOD) with North Pacific oligotrophic ocean gyre (NPOG) and clarified the ecological significance of phytoplankton in this region.
  2) made a clear distinction between surface chlorophyll, phytoplankton biomass, and primary productivity, and incorporated POC-based phytoplankton carbon estimates and mixed-layer light availability.
  3) expanded the analysis of ENSO impacts on NPOG variability by highlighting the role of phytoplankton photoacclimation.
  4) added discussion acknowledging the equal importance of phytoplankton loss processes (e.g., grazing) alongside growth, clarifying how such processes are represented in models, and noting the empirical nature of the Elman Neural Network (ENN)-based reconstruction.
  Please see the Supplement PDF for point-by-point response.
  On behalf on all authors.
  
  Citation: https://doi.org/10.5194/egusphere-2025-13-AC2

Peer review completion

AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload

ED: Reconsider after major revisions (05 Sep 2025) by Steven Bouillon

AR by Siyu Meng on behalf of the Authors (10 Oct 2025) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (31 Oct 2025) by Steven Bouillon

RR by Anonymous Referee #1 (04 Nov 2025)

RR by Emmanuel Boss (17 Nov 2025)

ED: Publish subject to minor revisions (review by editor) (17 Nov 2025) by Steven Bouillon

AR by Siyu Meng on behalf of the Authors (25 Nov 2025) Author's response Author's tracked changes Manuscript

ED: Publish subject to technical corrections (21 Dec 2025) by Steven Bouillon

AR by Siyu Meng on behalf of the Authors (28 Dec 2025) Author's response Manuscript

Journal article(s) based on this preprint

02 Feb 2026

Seasonality of the North Pacific Oligotrophic Gyre area in the past two decades and a modelling perspective for the 21st century

Siyu Meng, Xun Gong, Benjamin G. M. Webber, Manoj Joshi, Xiaokun Ding, Xiang Gong, Mingliang Gu, and Huiwang Gao

Biogeosciences, 23, 867–879, https://doi.org/10.5194/bg-23-867-2026,https://doi.org/10.5194/bg-23-867-2026, 2026

Short summary

Siyu Meng, Xun Gong, Benjamin Webber, Manoj Joshi, Xiaokun Ding, Xiang Gong, Mingliang Gu, and Huiwang Gao

Supplement

https://doi.org/10.5194/egusphere-2025-13-supplement

Data sets

Data for "Seasonality of the North Pacific Ocean Desert area in the past two decades and a modelling perspective for the 21st century" Siyu Meng https://zenodo.org/records/14632256

Siyu Meng, Xun Gong, Benjamin Webber, Manoj Joshi, Xiaokun Ding, Xiang Gong, Mingliang Gu, and Huiwang Gao

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The North Pacific Ocean Desert (NPOD), with low phytoplankton biomass, covers about 40 % of the North Pacific. The variations in NPOD seasonal cycle, which have a greater impact than its annual mean changes, are influenced by the El Niño-Southern Oscillation from 1998 to 2021. However, from 2021 to 2100, a weakened NPOD seasonal cycle is expected due to climate change. These changes in NPOD seasonal cycle could affect fisheries and marine ecosystems.


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Seasonality of the North Pacific Ocean Desert area in the past two decades and a modelling perspective for the 21st century

Journal article(s) based on this preprint

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Interactive discussion

Peer review completion

Suggestions for revision or reasons for rejection

Journal article(s) based on this preprint

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