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Aluminum and manganese are both key parameters in the GEOTRACES program. Data on dissolved aluminum (dAl) and dissolved manganese (dMn) relative to their geochemical behavior remain limited in the northeastern Indian Ocean (IO; including the Bay of Bengal (BoB) and equatorial Indian Ocean (Eq. IO)). Seawater samples collected in the BoB and Eq. IO during the spring inter-monsoon period (7 March to 9 April) of 2017 were analyzed to investigate the behavior and main processes controlling the distributions of dAl and dMn in the northeastern IO. The average concentrations of dAl and dMn in the mixed layer of the BoB were 16.6 and 6.7 nM, respectively. A modified 1-D box-model equation was utilized to estimate the contributions of different sources to dAl and dMn in the mixed layer. Al released from the desorption of and/or dissolution of the lithogenic sediments discharged by the Ganga-Brahmaputra (G-B) river system predominantly controlled the dAl distributions in the mixed layer of the BoB, while the desorption from the lithogenic sediments only contributed approximately 13%-21% dMn. Additional dMn input from the advection of Andaman Sea water and photo-reduction-dissolution of particulate Mn(IV) contributed more than 60% dMn in the mixed layer of the BoB. dAl and dMn in the surface mixed layer of the Eq. IO were mainly affected by the mixing of dAl- and dMn-enriched BoB surface water and low-dAl, low-dMn southern Arabian Sea surface water. Considering water mass properties and dAl concentrations, the distributions of dAl in the intermediate water (750-1,500 m) of northeastern IO were controlled by the mixing of Red Sea Intermediate Water, Indonesian Intermediate Water, and intermediate water of the BoB. Different from dAl, the apparent oxygen utilization relationship with dMn concentrations indicated that the regeneration of lithogenic particles under hypoxic conditions played a more important role than the remineralization of settling organic particles in co

Most climate forecast agencies failed to make successful predictions of the strong 2020/2021 La Niña event before May 2020. The western equatorial Pacific warm water volume (WWV) before the 2020 spring failed to predict this La Niña event because of the near neutral state of the equatorial Pacific Ocean in the year before. A strong Indian Ocean Dipole (IOD) event took place in the fall of 2019, which is used as a precursor for the La Niña prediction in this study. We used observational data to construct the precursory relationship between negative sea level anomalies (SLA) in the southeastern tropical Indian Ocean (SETIO) in boreal fall and negative Niño 3.4 sea surface temperature anomalies index one year later. The application of the above relation to the prediction of the 2020/2021 La Niña was a great success. The dynamics behind are the Indo-Pacific "oceanic channel" connection via the Indian Ocean Kelvin wave propagation through the Indonesian seas, with the atmospheric bridge playing a secondary role. The high predictability of La Niña across the spring barrier if a positive IOD should occur in the previous year suggests that the negative SETIO SLA in fall is a much better and longer predictor for this type of La Niña prediction than the WWV. In comparison, positive SETIO SLA lead either El Niño or La Niña by one year, suggesting uncertainty of El Niño predictions.

The Indo-Pacific warm pool is the warmest ocean in the world and is known as "the global heat engine," which plays an important role in the climate system.

The southeastern Indian Ocean (SEIO) exhibits prominent decadal variability in sea surface salinity (SSS), showing salinity decreases during 1995-2000 and 2005-2011 and increases during 2000-2005 and after 2011. These salinity changes are linked to the Indo-Pacific climate and have impacts on the regional marine environment. Yet, the underlying mechanism has not been firmly established. In this study, decadal SSS variability of the SEIO is successfully simulated by a high-resolution regional ocean model, and the mechanism is explored through a series of sensitivity experiments. The results suggest that freshwater transport of the Indonesian throughflow (ITF) and local precipitation are two major drivers for the SSS decadal variability. They mutually cause most of the variability, with a generally larger contribution of precipitation. Other processes, such as evaporation and advection driven by local winds, play a minor role. Further analysis shows that the decadal precipitation in the SEIO is mainly associated with the decadal variability of Ningaloo Niño. Ocean dynamic processes significantly modify the relationship between SSS and precipitation, greatly shortening their lag time. The changes in both volume transport and salinity of the ITF water can cause large salinity changes in the SEIO region. Although local wind forcing gives rise to considerable changes in evaporation rate and ocean current advection, its overall contribution to decadal SSS variability is small compared to local precipitation and the ITF.

In the summer of 2022, like in many other regions of the world, an unprecedented period of continuous high-temperature weather occurred in eastern China. The degree and duration of this event far exceeded normal standards. Between 2020 and 2022, the tropical Pacific experienced the most significant three-year consecutive La Nina event recorded in recent decades. We investigate linkages between these events: the high-temperature response in eastern China and Asia under the background of such La Nina events. Development of summer La Nina events contributed to a high-temperature heat wave during the summer of 2022. Rapid development of these events in the third year exacerbated negative Indian Ocean Dipole phases because of energy accumulation from abnormal easterly winds. The combined effects of the negative Indian Ocean Dipole phase and La Nina provided background field support that strengthened the West Pacific Subtropical High (WPSH) and the Iranian High, leading to high terrestrial temperature anomalies. An empirical orthogonal function (EOF) analysis of the vertical velocity in the middle and low latitudes of the tropical Indian Ocean and the Asian continent reveals the first two empirical orthogonal function modes to be conducive to the strengthening of Walker circulation in 2022. These two main modes jointly reflect the rising movement of the equatorial East Indian Ocean and South China Sea in 2022, and the sinking movement to the west of the Tibet Plateau and eastern China, which was conducive to generating high temperatures in eastern China. Finally, the South Asian High was affected by the La Nina event that lasted for three years, showing a strong trend towards the north, thus making an important contribution to this high temperature.