An Overview of the Indian Monsoon Using Micropaleontological, Geochemical, and Artificial Neural Network (ANN) Proxies During the Late Quaternary

Atmospheric pressure gradients determine the dynamics of the southwest monsoon (SWM) and northeast monsoon (NEM), resulting in rainfall in the Indian subcontinent. Consequently, the surface salinity, mixed layer, and thermocline are impacted by the seasonal freshwater outflow and direct rainfall. Moreover, seasonally reversing monsoon gyre and associated currents govern the northern Indian Ocean surface oceanography. This study provides an overview of the impact of these dynamic changes on sea surface temperature, salinity, and productivity by integrating more than 3000 planktonic foraminiferal censuses and bulk sediment geochemical data from sediment core tops, plankton tows, and nets between 25° N and 10° S and 40° E and 110° E of the past six decades. These data were used to construct spatial maps of the five most dominant planktonic foraminifers and illuminate their underlying environmental factors. Moreover, the cured foraminiferal censuses and the modern oceanographic data were used to test the newly developed artificial neural network (ANN) algorithm to calculate the relationship with modern water column temperatures (WCTs). Furthermore, the tested relationship between the ANN derived models was applied to two foraminiferal censuses from the northern Bay of Bengal core MGS29-GC02 (13°31′59″ N; 91°48′21″ E) and the southern Bay of Bengal Ocean Drilling Program (ODP) Site 758 (5°23.05′ N; 90°21.67′ E) to reconstruct the WCTs of the past 890 ka. The reconstructed WCTs at the 10 m water depth of core GC02 suggest dramatic changes in the sea surface during the deglacial periods (i.e., Bolling–Allerǿd and Younger Dryas) compared to the Holocene. The WCTs at Site 758 indicate a shift in the mixed-layer summer temperature during the past 890 ka at the ODP Site, in which the post-Mid-Brunhes period (at 425 ka) was overall warmer than during the prior time. However, the regional alkenone-derived sea-surface temperatures (SSTs) do not show such a shift in the mixed layer. Therefore, this study hypothesizes that the divergence in regional SSTs is most likely due to differences in seasonality and depth habitats in the paleo-proxies.

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Publication Details

Journal
Geosciences
Published
2025-06-24
DOI
https://doi.org/10.3390/geosciences15070241
Citations
2
Primary Topic
Geology and Paleoclimatology Research
Type
article
Field-Weighted Citation Impact
2.60

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article

An Overview of the Indian Monsoon Using Micropaleontological, Geochemical, and Artificial Neural Network (ANN) Proxies During the Late Quaternary

C. K. Shum, Harunur Rashid, Ming Zeng, Yang Wang et al.
2 citations
Geosciences
Geology and Paleoclimatology Research
2.60
article

An Overview of the Indian Monsoon Using Micropaleontological, Geochemical, and Artificial Neural Network (ANN) Proxies During the Late Quaternary

C. K. Shum, Harunur Rashid, Ming Zeng, Yang Wang, Xiaohui He
article en
2 citations

Abstract

Atmospheric pressure gradients determine the dynamics of the southwest monsoon (SWM) and northeast monsoon (NEM), resulting in rainfall in the Indian subcontinent. Consequently, the surface salinity, mixed layer, and thermocline are impacted by the seasonal freshwater outflow and direct rainfall. Moreover, seasonally reversing monsoon gyre and associated currents govern the northern Indian Ocean surface oceanography. This study provides an overview of the impact of these dynamic changes on sea surface temperature, salinity, and productivity by integrating more than 3000 planktonic foraminiferal censuses and bulk sediment geochemical data from sediment core tops, plankton tows, and nets between 25° N and 10° S and 40° E and 110° E of the past six decades. These data were used to construct spatial maps of the five most dominant planktonic foraminifers and illuminate their underlying environmental factors. Moreover, the cured foraminiferal censuses and the modern oceanographic data were used to test the newly developed artificial neural network (ANN) algorithm to calculate the relationship with modern water column temperatures (WCTs). Furthermore, the tested relationship between the ANN derived models was applied to two foraminiferal censuses from the northern Bay of Bengal core MGS29-GC02 (13°31′59″ N; 91°48′21″ E) and the southern Bay of Bengal Ocean Drilling Program (ODP) Site 758 (5°23.05′ N; 90°21.67′ E) to reconstruct the WCTs of the past 890 ka. The reconstructed WCTs at the 10 m water depth of core GC02 suggest dramatic changes in the sea surface during the deglacial periods (i.e., Bolling–Allerǿd and Younger Dryas) compared to the Holocene. The WCTs at Site 758 indicate a shift in the mixed-layer summer temperature during the past 890 ka at the ODP Site, in which the post-Mid-Brunhes period (at 425 ka) was overall warmer than during the prior time. However, the regional alkenone-derived sea-surface temperatures (SSTs) do not show such a shift in the mixed layer. Therefore, this study hypothesizes that the divergence in regional SSTs is most likely due to differences in seasonality and depth habitats in the paleo-proxies.

GeosciencesVol. 15(7)
University of Ottawa (CA), Jiangxi Science and Technology Normal University (CN), Shanghai Ocean University (CN), The Ohio State University (US)
National Natural Science Foundation of China, Atlantic Canada Opportunities Agency
Life below water
Openalex Percentile: Top 11%
Geology and Paleoclimatology Research
2.60
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