Indian Ocean Climate Research Articles

Emerging influence of the Australian Monsoon on Indian Ocean interannual variability in a warming climate

The Indian Ocean Dipole (IOD) and Tripole (IOT) represent primary modes of interannual variability in the Indian Ocean, impacting both regional and global climate. Unlike the IOD, which is closely related to the El Niño-Southern Oscillation (ENSO), our findings unveil a substantial influence of the Australian Monsoon on the IOT. An anomalously strong Monsoon induces local sea surface temperature (SST) variations via the wind-evaporation-SST mechanism, triggering atmospheric circulation anomalies in the eastern Indian Ocean. These circulation changes lead to changes in oceanic heat transport, facilitating the formation of the IOT. Our analysis reveals a strengthening connection between the Australian Monsoon and the IOT in recent decades, with a projected further strengthening under global warming. This contrasts with the diminished coupling between ENSO and IOD in recent decades from observations and model projections, illustrating evolving Indian Ocean dynamics under the warming climate.

Modeling individual growth reveals decreasing gray whale body length and correlations with ocean climate indices at multiple scales

AbstractChanges in body size have been documented across taxa in response to human activities and climate change. Body size influences many aspects of an individual's physiology, behavior, and ecology, ultimately affecting life history performance and resilience to stressors. In this study, we developed an analytical approach to model individual growth patterns using aerial imagery collected via drones, which can be used to investigate shifts in body size in a population and the associated drivers. We applied the method to a large morphological dataset of gray whales (Eschrichtius robustus) using a distinct foraging ground along the NE Pacific coast, and found that the asymptotic length of these whales has declined since around the year 2000 at an average rate of 0.05–0.12 m/y. The decline has been stronger in females, which are estimated to be now comparable in size to males, minimizing sexual dimorphism. We show that the decline in asymptotic length is correlated with two oceanographic metrics acting as proxies of habitat quality at different scales: the mean Pacific Decadal Oscillation index, and the mean ratio between upwelling intensity in a season and the number of relaxation events. These results suggest that the decline in gray whale body size may represent a plastic response to changing environmental conditions. Decreasing body size could have cascading effects on the population's demography, ability to adjust to environmental changes, and ecological influence on the structure of their community. This finding adds to the mounting evidence that body size is shrinking in several marine populations in association with climate change and other anthropogenic stressors. Our modeling approach is broadly applicable across multiple systems where morphological data on megafauna are collected using drones.

Modulation of Annual Rossby Waves on the Formation of Basin‐Wide Salinity Fronts

AbstractThis study reveals the formation mechanisms of a group of salinity fronts across the Arabian Sea (AS) and explores their associations with annual Rossby waves, utilizing Soil Moisture Active Passive (SMAP) satellite data and other relevant data sets. As low‐salinity water is transported westward and northward at varying rates between 6°N ∼ 20°N, substantial basin‐wide northeast‐southwest oriented salinity fronts emerge at its leading edge from March to May. Further analysis indicates a strong correlation between the transport of low‐salinity water and the westward‐propagating Rossby waves. The salinity fronts are primarily influenced by the geostrophic circulation, which significantly contributes to the transport of low‐salinity water. As a result, the low‐salinity water closely aligns with positive sea level anomaly (SLA), representing westward propagating downwelling Rossby waves. A continuously stratified linear ocean model (LOM) analysis suggests second mode baroclinic Rossby waves dominate seasonal sea level changes, surpassing the influence of the first mode. The spatial mean standard deviation of the first mode within the region of 56 ∼ 75°E, 9 ∼ 11°N is approximately 60% that of the second mode. Positive SLA is mainly caused by the annual downwelling Rossby waves radiating from the eastern boundary. Due to the latitudinal decrease in the phase speed of the annual Rossby waves, the sea level fronts manifest the northeast‐southwest direction, resembling the location of the sea surface salinity fronts. The salinity fronts highlight the crucial role of Rossby waves in shaping upper ocean water mass distribution in the AS, potentially impacting the broader Indian Ocean climate.

Unraveling sub-seasonal precipitation variability in the Middle East via Indian Ocean sea surface temperature

This study examines sub-seasonal precipitation anomalies, challenging to predict yet vital for society and the environment. Focusing on October, we investigate correlations between the Indian Ocean Dipole Mode Index (DMI), West Tropical Indian Ocean Index (WTIO), and Middle Eastern precipitation. We find robust correlations (~ 0.7), up to a two-month lag, demonstrating strong links between these climate indices and rainfall patterns, potentially suggesting sub-seasonal precipitation predictability. Over the past four decades, DMI and WTIO have shown a significant upward trend of ~ 0.4 °C, intensifying their impact on precipitation dynamics. This trend signifies evolving Indian Ocean climate patterns with potential regional consequences and is projected to continue in the twenty-first century. Significant correlations also emerge between DMI, WTIO, and maximum daily precipitation, highlighting their role in extreme rainfall events. Finally, our study attributes most of October’s precipitation variability to Indian Ocean sea surface temperature variations. These temperature anomalies influence the Indian Ocean’s Walker circulation, affecting water vapor flux to the Middle East and shaping regional precipitation. Our findings underscore the importance of these indices in understanding and predicting Middle East climate variability, revealing intricate ocean–atmosphere interactions.

Assessment of thermocline depth bias in the Seychelles-Chagos Thermocline Ridge of the Southwestern Indian Ocean simulated by the CMIP6 models

The Seychelles-Chagos Thermocline Ridge (SCTR, 5°S-10°S, 50°E-80°E) is a unique open-ocean upwelling region in the southwestern Indian Ocean. Due to the negative wind stress curl between the equatorial westerlies and southeasterly trade winds, SCTR is known as a strong upwelling region with high biological productivity, providing a primary fishing zone for the surrounding countries. Given its importance in shaping the variability of the Indian Ocean climate by understanding the sea-air interaction and its dynamics, the simulation of SCTR is evaluated using outputs from the Coupled Model Intercomparison Project Phase Sixth (CMIP6). Compared to observations, 23 out of 27 CMIP6 models tend to simulate considerably deeper SCTR thermocline depth (defined as the 20°C isotherm depth (D20))– a common bias in climate models. The deep bias is related to the easterly wind bias in the equatorial to southern Indian Ocean, which is prominent in boreal summer and fall. This easterly wind bias produces a weak annual mean Ekman pumping, especially in the boreal fall. Throughout the year, the observed Ekman pumping is positive and is driven by two components: the curl term, is associated with the wind stress curl, leads to upwelling during boreal summer to fall; the beta term, is linked to planetary beta and zonal wind stress, contributes to downwelling during boreal spring to fall. However, the easterly wind bias in the CMIP6 increases both the positive curl and negative beta terms. The beta term bias offsets the curl term bias and reduces the upwelling velocity. Furthermore, the easterly wind bias is likely caused by the reduced east-west sea surface temperature (SST) difference associated with a pronounced warm bias in the western equatorial Indian Ocean, accompanied by the east-west mean sea level pressure gradient over the Indian Ocean. Furthermore, this study finds local wind-induced Ekman pumping to be a more dominant factor in thermocline depth bias than Rossby waves, despite CMIP6 models replicating Rossby wave propagation. This study highlights the importance of the beta term in the Ekman pumping simulation. Thus, reducing the boreal summer-to-fall easterly wind bias over the Indian Ocean region may improve the thermocline depth simulation over the SCTR region.

Numerical Investigation of Tropical Indian Ocean Barrier Layer Variability

AbstractThe barrier layer (BL) is part of the surface ocean isolated from the local air‐sea exchange processes despite it's great potential to store the heat beneath the mixed layer. The tropical oceans are known for the presence of BL. The interannual variability of the BL of the tropical Indian Ocean is examined in this study with a concomitant analysis of observations and outputs from an ocean general circulation model. The model faithfully reproduces the tropical variability of the dynamics and thermodynamics of the Indian Ocean when compared with observations and other studies. The BL thins (thickens) in the eastern (central‐to‐western) tropical Indian Ocean during the positive phase of the Indian Ocean Dipole Mode (IOD). The individual roles of five major forcing mechanisms on BL‐IOD coupling are examined. The thinning in the east is caused by upward heaving thermocline due to upwelling Kelvin waves during the positive phase of the IOD, causing the isothermal layer to shoal steeper than the mixed layer. The surface freshwater fluxes substantiate the thinning of BL in the east during this time, while the net heat fluxes thin the BL in the entire tropical Indian Ocean. The basin‐wide salinity (temperature) dynamics have widespread and complementary impacts, a BL thickening (thinning) in the equatorial and eastern tropical Indian Ocean during positive IOD years, with the former overwhelming the latter. The thickening of BL in the central‐to‐western tropical Indian Ocean during positive IOD is due to a combined action of salinity and freshwater forcing. The thermocline heaving, temperature and salinity dynamics and buoyancy forcing could explain the net variability of BL in the tropical Indian Ocean almost entirely in the model. The ocean‐only response shows that a BL weakens the shoaling (deepening) of the ocean mixed layer during positive (negative) IOD years in the eastern tropical Indian Ocean. As barrier layers store heat beneath the mixed layer, their role in Indian Ocean weather and climate needs to be examined with coupled model experiments.

Seasonal and Interannual Variability of Tidal Mixing Signatures in Indonesian Seas from High-Resolution Sea Surface Temperature

With their complex narrow passages and vigorous mixing, the Indonesian seas provide the only low-latitude pathway between the Pacific and Indian Oceans and thus play an essential role in regulating Pacific-Indian Ocean exchange, regional air-sea interaction, and ultimately, global climate phenomena. While previous investigations using remote sensing and numerical simulations strongly suggest that this mixing is tidally driven, the impacts of monsoon and El Niño Southern Oscillation (ENSO) on tidal mixing in the Indonesian seas must play an important role. Here we use high-resolution sea surface temperature from June 2002 to June 2021 to reveal monsoon and ENSO modulations of mixing. The largest spring-neap (fortnightly) signals are found to be localized in the narrow passages/straits and sills, with more vigorous tidal mixing during the southeast (boreal summer) monsoon and El Niño than that during the northwest (boreal winter monsoon) and La Niña. Therefore, tidal mixing, which necessarily responds to seasonal and interannual changes in stratification, must also play a feedback role in regulating seasonal and interannual variability of water mass transformations and Indonesian throughflow. The findings have implications for longer-term variations and changes of Pacific–Indian ocean water mass transformation, circulation, and climate.

The Intersection of Marine and Coastal Conservation and Nature-Based Solutions to Climate Change: Governance Insights from Indian Ocean Climate Change Commitments 1

The Intersection of Marine and Coastal Conservation and Nature-Based Solutions to Climate Change: Governance Insights from Indian Ocean Climate Change Commitments 1

Warming trend during millennial-scale cold events in the northern Indian Ocean and potential atmospheric CO2 forcing during the past 40 kyr

• Millennial-scale climate variability in the Bay of Bengal is reconstructed by TEX 86 . • Warming trend during millennial-scale cold events is revealed in the northern Indian Ocean. • Atmospheric CO 2 force SST change during the millennial-scale cold events over the past 40 kyr. To better understand the process of hydrographic and temperature changes in the Indian Ocean, we present Glycerol dialkyl glycerol tetraether data on core BoB-56 from the Bay of Bengal to reconstruct the sea surface temperature (SST) variability during the last glaciation. The results indicate that the TEX 86 -derived SST ranged from 22.00 to 28.30 °C with several fluctuations since 40 ka BP and that the evolution pattern matched well with the marine isotope stage (MIS). During MIS 3, the SST kept around 24.60 °C with some small amplitudes. The SST showed more significant fluctuations during MIS 2 and increased gradually with a ~3 °C cooling during the Last Glacial Maximum (LGM). After the Younger Dryas (YD) stage, Holocene SST values exhibited miniscule variations. During the last glaciation climate variability process, the cold signals of the YD and Heinrich events were recorded well in our core SST series, revealing a regional response to global climate changes. The warming trend during these millennial-scale cold events in the northern Indian Ocean was also identified, and SST increased in the range of 2 °C. A comparison of SST records and atmospheric CO 2 concentration shows that the warming process during the YD, LGM, and Heinrich (1–4) events matched the gradual increase in atmospheric CO 2 concentration in the northern Indian Ocean. Hence, this study implies millennial-scale hydroclimate change linked with atmospheric CO 2 forcing that could improve our knowledge of the role of atmospheric CO 2 in triggering abrupt Indian Ocean climate changes.

Archives Serving Science: Historic Maritime Records as Sources for Indian Ocean Climate Change Research: Potential and Problems

Climate scientists have identified the establishment of historical baseline data from which to determine degrees of climate change as a significant challenge. In this article the use of ships’ logbooks and other sources for maritime history, to provide evidence of weather and climatic conditions pre-dating the era of modern meteorological data measurements, is discussed. The CLIWOC and TANAP projects utilising international archival resources to provide climatological and related information are examined. The discussion is then focused on the Indian Ocean rim countries and the archival and historical resources that may yield similar information. The article concentrates on sources in the Republic of South Africa, and sources in the Sultanate of Oman and Western Australia are discussed for comparative purposes. Utilising archival sources to provide historical climate-change related data aligns archivists and information scientists with the major imperatives of the South African Government. A beginning can also be made with developing south-south scientific and archival co-operation that can unlock new sources of historical and climatological knowledge.

Impact of Large-Scale Climate Indices on Meteorological Drought of Coastal Ghana

The devastating effects of drought on agriculture, water resources, and other socioeconomic activities have severe consequences on food security and water resource management. Understanding the mechanism that drives drought and predicting its variability is important for enhancing early warning and disaster risk management. In this study, meteorological droughts over six coastal synoptic stations were investigated using three-month Standardized Precipitation Index (SPI). The dry seasons of November-December-January (NDJ), December-January-February (DJF), and January-February-March (JFM) were the focal seasons for the study. Trends of dry seasons SPIs were evaluated using seasonal Mann–Kendall test. The relationship between drought SPI and ocean-atmosphere climate indices and their predictive ability were assessed using Pearson correlation and Akaike Information Criterion (AIC) stepwise regression method to select best climate indices at lagged timestep that fit the SPI. The SPI exhibited moderate to severe drought during the dry seasons. Accra exhibited a significant increasing SPI trend in JFM, NDJ, and DJF seasons. Besides, Saltpond during DJF, Tema, and Axim in NDJ season showed significant increasing trend of SPI. In recent years, SPIs in dry seasons are increasing, an indication of weak drought intensity, and the catchment areas are becoming wetter in the traditional dry seasons. Direct (inverse) relationship was established between dry seasons SPIs and Atlantic (equatorial Pacific) ocean's climate indices. The significant climate indices modulating drought SPIs at different time lags are a combination of either Nino 3.4, Nino 4, Nino 3, Nino 1 + 2, TNA, TSA, AMM, or AMO for a given station. The AIC stepwise regression model explained up to 48% of the variance in the drought SPI and indicates Nino 3.4, Nino 4, Nino 3, Nino 1 + 2, TNA, TSA, AMM, and AMO have great potential for seasonal drought prediction over Coastal Ghana.

Origin of Indian Ocean multidecadal climate variability: role of the North Atlantic Oscillation

The multidecadal variability of Indian Ocean sea surface temperature (IOSST) has an important impact on both the regional Indian Ocean climate and the global climate. Here, we explore multidecadal variability in the annual IOSST. Observational analysis shows that the annual IOSST multidecadal variability is not only related to the Pacific Decadal Oscillation (PDO), but also to the North Atlantic Oscillation (NAO). The NAO leads by 15–20 years the detrended annual IOSST in which the PDO signal of the same period has been removed. Further analysis reveals that the NAO leads the annual IOSST multidecadal variability through its leading effect on the Atlantic Multidecadal Oscillation (AMO). The AMO affects the vertical wind anomaly in the Indian Ocean region through the Atlantic–Indian Ocean multidecadal teleconnection (AIMT), which in turn affects the net longwave radiation in the Indian Ocean region, thus driving the annual IOSST multidecadal variability. A Hasselmann model based on NAO and PDO further verify the joint influence of the NAO and PDO on the multidecadal variability of the IOSST. A PDO-based linear model and a climate model that incorporates the NAO signal are also constructed for the annual IOSST. Results show that the climate model with the NAO signal can better simulate the annual IOSST. This again verifies that the NAO is part of the annual IOSST multidecadal variability source, indicating that the annual IOSST variability may be due to the combined influences of the NAO and PDO.

The changing physical and ecological meanings of North Pacific Ocean climate indices

Climate change is likely to change the relationships between commonly used climate indices and underlying patterns of climate variability, but this complexity is rarely considered in studies using climate indices. Here, we show that the physical and ecological conditions mapping onto the Pacific Decadal Oscillation (PDO) index and North Pacific Gyre Oscillation (NPGO) index have changed over multidecadal timescales. These changes apparently began around a 1988/1989 North Pacific climate shift that was marked by abrupt northeast Pacific warming, declining temporal variance in the Aleutian Low (a leading atmospheric driver of the PDO), and increasing correlation between the PDO and NPGO patterns. Sea level pressure and surface temperature patterns associated with each climate index changed after 1988/1989, indicating that identical index values reflect different states of basin-scale climate over time. The PDO and NPGO also show time-dependent skill as indices of regional northeast Pacific ecosystem variability. Since the late 1980s, both indices have become less relevant to physical-ecological variability in regional ecosystems from the Bering Sea to the southern California Current. Users of these climate indices should be aware of nonstationary relationships with underlying climate variability within the historical record, and the potential for further nonstationarity with ongoing climate change.

Weakened Impact of the Developing El Niño on Tropical Indian Ocean Climate Variability under Global Warming

Abstract El Niño induces an anomalous easterly wind along the equator and a pair of anomalous anticyclones straddling the equator over the tropical Indian Ocean (TIO) during the autumn of its developing phase. Based on 30 coupled models participating in CMIP5, these atmospheric circulation anomalies over TIO are substantially weakened by about 12%–13% K−1 under global warming scenarios, associated with a weakened zonal gradient of the sea surface temperature (SST) anomaly. The mechanism for the response is investigated based on a hierarchy of model experiments. Based on stand-alone atmospheric model experiments under uniform and patterned mean-state SST warming, the atmospheric circulation anomaly over TIO during the autumn of the developing El Niño is also substantially weakened by about 8% K−1 even if the interannual variability of SST remains exactly unchanged, suggesting that the primary cause resides in the atmosphere rather than the SST anomaly. The tropospheric static stability is robustly enhanced under global warming, and experiments performed by a linear baroclinic model show that a much weaker atmospheric circulation anomaly over TIO is stimulated by an unchanged diabatic heating anomaly under a more stable atmosphere. The weakened atmospheric circulation anomaly due to enhanced static stability weakens the zonal gradient of the SST anomaly within TIO through local air–sea interaction, and it acts to further weaken the atmospheric circulation anomaly. The enhanced static stability of the troposphere is probably the primary cause and the air–sea interaction within TIO is a secondary cause for the weakened impact of the developing El Niño on atmospheric circulation variability over TIO.

Influence of Natural Climate Variability on the Extreme Ocean Surface Wave Heights Over the Indian Ocean

AbstractExtreme ocean waves are part of the climate system but responsible for significant impacts on coastal and offshore environments, structures, and populations. In the Indian Ocean (IO), the wind and wave climate can be significantly influenced by natural climate variability, such as the El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Southern Annular Mode (SAM), yet our understanding on their regional influence is limited, particularly for seasonal extremes. Here, seasonal extreme significant wave heights (SWHs) and winds in the IO are examined over the period 1957–2010 utilizing ERA‐20C reanalysis data and the nonstationary generalized extreme value distribution to understand climatic extremes, by considering climate indices as covariates. ENSO influence on extreme SWHs include increases in the Bay of Bengal, southwest tropical IO (TIO), southern IO (SIO; a broad extension south of Australia), and South China and Philippine (SCP) Seas, and decreases in the Arabian Sea in boreal summer during El Niño. Extreme SWH responses to the IOD include increases in the eastern TIO, southwest TIO, and SIO in boreal autumn during its positive phase. Lastly, Southern Annular Mode not only significantly affects the SIO year round but has a weak influence in the northern and tropical IO. Composite analysis of ENSO and IOD events further highlight in phase combinations display less significant influence than out of phase combinations during summer, but not autumn. Mean and extreme wind responses are consistent with SWH responses to natural climate variability, and climate mode teleconnection patterns help explain the seasonal variations.

A Sustained Ocean Observing System in the Indian Ocean for Climate Related Scientific Knowledge and Societal Needs

The Indian Ocean is warming faster than any of the global oceans and its climate is uniquely driven by the presence of a landmass at low latitudes, which causes monsoonal winds and reversing currents. The food, water, and energy security in the Indian Ocean rim countries and islands are intrinsically tied to its climate, with marine environmental goods and services, as well as trade within the basin, underpinning their economies. Hence, there are a range of societal needs for Indian Ocean observation arising from the influence of regional phenomena and climate change on, for instance, marine ecosystems, monsoon rains, and sea-level. The Indian Ocean Observing System (IndOOS), is a sustained observing system that monitors basin-scale ocean-atmosphere conditions, while providing flexibility in terms of emerging technologies and scientific and societal needs, and a framework for more regional and coastal monitoring. This paper reviews the societal and scientific motivations, current status, and future directions of IndOOS, while also discussing the need for enhanced coastal, shelf, and regional observations. The challenges of sustainability and implementation are also addressed, including capacity building, best practices, and integration of resources. The utility of IndOOS ultimately depends on the identification of, and engagement with, end-users and decision-makers and on the practical accessibility and transparency of data for a range of products and for decision-making processes. Therefore we highlight current progress, issues and challenges related to end user engagement with IndOOS, as well as the needs of the data assimilation and modeling communities. Knowledge of the status of the Indian Ocean climate and ecosystems and predictability of its future, depends on a wide range of socio-economic and environmental data, a significant part of which is provided by IndOOS.

Influence of the Pacific and Indian Ocean climate drivers on the rainfall in Vietnam

Rainfall in Vietnam is strongly influenced by climate drivers which are caused by anomalies in sea surface temperature (SST), sea level pressure (SLP) or geopotential height in the Pacific and the Indian Ocean. This paper analyses the rainfall records at different sites in various regions of Vietnam to determine the influence of the three major climate drivers, the ENSO (El Niño–Southern Oscillation), IPO (Interdecadal Pacific Oscillation) and IOD (Indian Ocean Dipole) and their interaction on the rainfall at each of these sites. A statistical technique called Bayesian model averaging (BMA) is used to discuss and address the uncertainties problem in model and variable selection when fitting observed rainfall data with climate drivers' indices. The results show that the ENSO, IPO and IOD and their interaction overall have very minor roles in influencing the rainfall in Northern Vietnam but they have some influences on the rainfall in the central and southern parts of Vietnam. Furthermore, seasonality analysis shows the spring rainfall in Vietnam is strongly influenced by the ENSO, IOD and ENSO*IOD interaction, with ENSO*IOD interaction strongest in the north. The situation in summer is similar but the IOD is most dominant compared to the ENSO and ENSO*IOD interaction. In autumn, the IOD and ENSO influences on rainfall are weaker while the IPO has strong influence in the Central and Southern Vietnam and no climate driver has any influence in the north. And during winter, the IPO, ENSO and IPO*ENSO interaction are associated with rainfall variability across Vietnam while the IOD influence is insignificant. The results also confirm the previous studies on the teleconnection roles of SST in the Pacific and Indian Oceans on rainfall variability in Vietnam.

Signals from the south; humpback whales carry messages of Antarctic sea-ice ecosystem variability.

Southern hemisphere humpback whales (Megaptera novaeangliae) rely on summer prey abundance of Antarctic krill (Euphausia superba) to fuel one of the longest-known mammalian migrations on the planet. It is hypothesized that this species, already adapted to endure metabolic extremes, will be one of the first Antarctic consumers to show measurable physiological change in response to fluctuating prey availability in a changing climate; and as such, a powerful sentinel candidate for the Antarctic sea-ice ecosystem. Here, we targeted the sentinel parameters of humpback whale adiposity and diet, using novel, as well as established, chemical and biochemical markers, and assembled a time trend spanning 8 years. We show the synchronous, inter-annual oscillation of two measures of humpback whale adiposity with Southern Ocean environmental variables and climate indices. Furthermore, bulk stable isotope signatures provide clear indication of dietary compensation strategies, or a lower trophic level isotopic change, following years indicated as leaner years for the whales. The observed synchronicity of humpback whale adiposity and dietary markers, with climate patterns in the Southern Ocean, lends strength to the role of humpback whales as powerful Antarctic sea-ice ecosystem sentinels. The work carries significant potential to reform current ecosystem surveillance in the Antarctic region.

Time-series analysis of chlorophyll-a, sea surface temperature, and sea surface height anomalies during 2003–2014 with special reference to El Niño, La Niña, and Indian Ocean Dipole (IOD) Years

ABSTRACTThe present study was carried out to find the variability of chlorophyll-a (chl-a) concentration, sea surface temperature (SST), and sea surface height anomalies (SSHa) during 2003–2014, covering the Bay of Bengal (BoB) and Arabian Sea (AS) waters. These parameters were linked with El Niño, La Niña, and Indian Ocean Dipole (IOD) years. The observed results during 2003–2014 were evaluated and it was found that the monthly mean value for 12-year data ranged as follows: chl-a (0.11–0.46 mg m−3), SST (27–31 °C), and SSHa (−0.2 to 20 cm). The annual mean range of chl-a for 12-year data was 0.1–0.23 mg m−3, the SST range was 27–28 °C, and the SSHa range was 2.14–13.91 cm. It has been observed that with the SST range of 27–28 °C and the SSHa range of 7–9 cm, the chl-a concentration enhanced to 0.20–0.23 mg m−3. With a higher SST range of 28–29 °C and with a positive SSHa range of 11–14 cm, the chl-a concentration appeared to be low (0.17–0.18 mgm−3). During normal years, SSHa was positive with the >5 to <10 cm range during the months of April–June, which coincided with an increase in SST, >2 to <4 °C. During the normal years, SSHa (>−0.2 to <−10 cm) was observed to be negative during October–December, with a decrease in SST (<3 °C) observed. The high monthly mean chl-a concentration (>0.3 to <0.5 mg m−3) was noticed during December–February in the BoB and AS. Compared to the BoB chl-a range (<0.4 mg m−3), a high chl-a concentration was observed in AS (>0.4 mg m−3). However, during the phenomenon years, the study area had experienced low chl-a (<0.2 mg m−3), high SST (>5 °C), and more positive SSHa (>10 to <20 cm) during January–March and October–December in AS and BoB. The present study infers that a positive IOD leads to low chl-a concentration (<2 mg m−3) and low primary productivity in AS. El Niño caused the down-welling process, it results in a low chl-a concentration (<1 mg m−3) in BoB and AS. La Niña caused the upwelling process, and it results in a high chl-a concentration (>2.0 mg m−3) in BoB and AS. In the recent past years (2003–2014), the intensity and frequency of El Niño, La Niña, and IOD have been increasing, evidenced with few studies, and have impacts on the Indian Ocean climate. Therefore, the influences of the relative changes of these phenomena on the BoB and AS need to be understood for productivity assessment and ocean state monitoring.

The response of the southwest Western Australian wave climate to Indian Ocean climate variability

Knowledge of regional wave climates is critical for coastal planning, management, and protection. In order to develop a regional wave climate, it is important to understand the atmospheric systems responsible for wave generation. This study examines the variability of the southwest Western Australian (SWWA) shelf and nearshore wind wave climate and its relationship to southern hemisphere climate variability represented by various atmospheric indices: the southern oscillation index (SOI), the Southern Annular Mode (SAM), the Indian Ocean Dipole Mode Index (DMI), the Indian Ocean Subtropical Dipole (IOSD), the latitudinal position of the subtropical high-pressure ridge (STRP), and the corresponding intensity of the subtropical ridge (STRI). A 21-year wave hindcast (1994–2014) of the SWWA continental shelf was created using the third generation wave model Simulating WAves Nearshore (SWAN), to analyse the seasonal and inter-annual wave climate variability and its relationship to the atmospheric regime. Strong relationships between wave heights and the STRP and the STRI, a moderate correlation between the wave climate and the SAM, and no significant correlation between SOI, DMI, and IOSD and the wave climate were found. Strong spatial, seasonal, and inter-annual variability, as well as seasonal longer-term trends in the mean wave climate were studied and linked to the latitudinal changes in the subtropical high-pressure ridge and the Southern Ocean storm belt. As the Southern Ocean storm belt and the subtropical high-pressure ridge shifted southward (northward) wave heights on the SWWA shelf region decreased (increased). The wave height anomalies appear to be driven by the same atmospheric conditions that influence rainfall variability in SWWA.