Sea Surface Temperature over the Bay of Bengal: A key driver for South Asian Summer Monsoon rainfall during past 31 kiloyears

IF 3.8 2区地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY

Climate of The Past Pub Date : 2024-06-25 DOI:10.5194/egusphere-2024-1566

Thamizharasan Sakthivel, Prosenjit Ghosh, Ravi Bhushan, Harsh Raj, Ankur J. Dabhi, Ajay Shivam, Senthilnathan D

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Abstract

Abstract. Warmer Sea Surface Temperature (SST) in the Bay of Bengal (BoB) is crucial for driving deep atmospheric convection, facilitating low-level south-westerly winds, and enhancing moisture transport, thereby intensifying South Asian Summer Monsoon (SASM) rainfall over South Asia. However, the specific impact of BoB SST on SASM rainfall during the Glacial-Interglacial periods remains poorly understood. In this study, we reconstructed SST and evaporation versus rainfall variability over the past 31 kiloyears by simultaneously analyzing the carbonate clumped isotopes and stable oxygen isotopic composition of surface-dwelling planktic foraminifera Globigerinoides ruber from the Central West BoB (CWBoB), a key moisture source region. Additionally, cloud cover index was inferred from the abundance ratio of planktic foraminifera Globigerina bulloides to Neogloboquadrina dutertrei. Our SST reconstruction reveals an 8 °C variability over the past 31 kyr, coinciding with shifts in the G. bulloides to N. dutertrei ratio during the Last Glacial period and deglaciation, suggesting SST regulation by variable cloud cover. The increase in SST from the Early Holocene is attributed to CO₂ radiative forcing. The stable oxygen isotope of seawater δ¹⁸O_sw strongly aligns with a proxy record of SASM wind intensity, indicating that changes in wind patterns drive the variable evaporation versus rainfall dynamics over CWBoB. Furthermore, we examined the temporal variation in SASM continental runoff and rainfall to the Northern BoB (NBoB) by assessing changes in δ¹⁸O_sw (∆¹⁸O_sw), a proxy for Sea Surface Salinity (ΔSSS), between the NBoB and CWBoB. Our analysis revealed a significant relationship between SASM rainfall and SST in the CWBoB, indicating a sensitivity of 0.9±0.1 psu drop in ΔSSS across the NBoB per 1 °C rise in SST. These findings enhance our understanding of the relationship between CWBoB SST and SASM rainfall, highlighting the intricate dynamics of monsoon variability and paving the way for improved predictability of SASM rainfall patterns.

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孟加拉湾海面温度：过去 31 千年南亚夏季季风降雨的关键驱动因素

摘要孟加拉湾（BoB）较高的海面温度（SST）对于推动深层大气对流、促进低层西南风和增强水汽输送，从而加强南亚夏季季风（SASM）降雨量至关重要。然而，人们对冰川-间冰期 BoB SST 对南亚夏季季风降雨的具体影响仍然知之甚少。在这项研究中，我们通过同时分析中西部渤海（CWBoB）这一关键水汽来源区的碳酸盐团块同位素和表栖浮游有孔虫 Globigerinoides ruber 的稳定氧同位素组成，重建了过去 31 千年的 SST 和蒸发量与降雨量的变化关系。此外，还根据浮游有孔虫 Globigerina bulloides 与 Neogloboquadrina dutertrei 的丰度比推断出云层覆盖指数。我们重建的海温显示，在过去的 31 千年中，海温的变化幅度为 8 ℃，这与末次冰川期和冰川消融期 G. bulloides 与 N. dutertrei 的比例变化相吻合，表明海温受云层变化的调节。全新世早期开始的海温上升归因于二氧化碳辐射强迫。海水的稳定氧同位素δ18Osw与SASM风强度的代用记录高度吻合，表明风模式的变化驱动着CWBoB上蒸发与降雨的动态变化。此外，我们还通过评估北部渤海湾（NBoB）和中西部渤海湾（CWBoB）之间海表盐度（ΔSSS）的代用指标δ18Osw（Δ18Osw）的变化，研究了SASM大陆径流和北部渤海湾（NBoB）降雨的时间变化。我们的分析表明，SASM 降水量与 CWBoB 的海表盐度之间存在明显的关系，表明海表盐度每上升 1 ℃，整个 NBoB 的 ΔSSS 就会下降 0.9±0.1 psu。这些发现加深了我们对 CWBoB SST 与 SASM 降雨量之间关系的理解，突出了季风变率的复杂动态，为提高 SASM 降雨模式的可预测性铺平了道路。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Climate of The Past 地学-气象与大气科学

CiteScore

7.40

自引率

14.00%

发文量

120

审稿时长

4-8 weeks

期刊介绍： Climate of the Past (CP) is a not-for-profit international scientific journal dedicated to the publication and discussion of research articles, short communications, and review papers on the climate history of the Earth. CP covers all temporal scales of climate change and variability, from geological time through to multidecadal studies of the last century. Studies focusing mainly on present and future climate are not within scope. The main subject areas are the following: reconstructions of past climate based on instrumental and historical data as well as proxy data from marine and terrestrial (including ice) archives; development and validation of new proxies, improvements of the precision and accuracy of proxy data; theoretical and empirical studies of processes in and feedback mechanisms between all climate system components in relation to past climate change on all space scales and timescales; simulation of past climate and model-based interpretation of palaeoclimate data for a better understanding of present and future climate variability and climate change.