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The study employs a hybrid Employing a hybrid ensemble empirical mode decomposition-temporal convolutional network (EEMD-TCN) machine learning approach to predict the IOD index and sea surface temperatures for various time spans (3, 6, 9, and 12 months ahead), and explores changes in the relationship between IOD and Indian summer monsoon rainfall (ISMR) across India from 1960 to 2020, considering risk and uncertainty. The methodology involves decomposing the IOD index and SST into consistent subcomponents using EEMD, followed by TCN modeling to forecast these subcomponents, resulting in predictions affected by risk and uncertainty. The IOD index's forecast precision surpasses that of SSTs, attributed to the higher number of high-frequency elements in the SST data, posing a greater challenge in prediction risk and uncertainty. The research also examines anomalies in rainfall, SST, and low-level wind circulation, highlighting the impact of IOD events. ISMR across India shows sensitivity to IOD events, with positive IOD (pIOD) events linked to increased rainfall and negative IOD (nIOD) events to decreased rainfall, except during the initial phase of the Indian summer monsoon, emphasizing the role of risk and uncertainty. Variations in SST, wind circulation, and moisture transport mechanisms in the Indian Ocean lead to notable precipitation changes during different IOD stages, especially from 1991 to 2020. Notably, a recent rise in the frequency of low-level equatorial jets (LEJs) in the Indian Ocean equatorial region and the Arabian Sea during pIOD events is observed, in contrast to the earlier decades of 1960–1990. [ABSTRACT FROM AUTHOR]

In this study, we investigate the connection between planetary equatorial waves, modulated by the Indian Ocean dipole (IOD) and El Niño Southern Oscillation (ENSO), and the interannual variabilities of the salinity distribution in the Bay of Bengal (BoB) in October–December (OND), along with its associated dynamics, using satellite and reanalysis datasets. In OND 2010 and 2016 (1994, 1997, 2006, and 2019), positive (negative) sea surface salinity anomalies (SSSAs) were distributed in the eastern equatorial Indian Ocean (EIO) and Andaman Sea. Moreover, the southward movement of negative (positive) SSSAs along the eastern Indian coast was observed. This phenomenon was caused by large-scale anomalous currents associated with zonal wind over the EIO. During OND 2010 and 2016 (1994, 1997, 2006, and 2019), due to anomalous westerlies (easterlies) over the EIO and anomalous downwelling (upwelling) Kelvin waves, the strengthened (weakened) Wyrtki jet and the basin-scale anomalous cyclonic (anticyclonic) circulation in the BoB gave rise to positive (negative) SSSAs within the eastern EIO and Andaman Sea. In addition, the intensified (weakened) eastern Indian coastal currents led to the southward movement of negative (positive) SSSAs. It is worth noting that downwelling Kelvin waves reached the western coast of India during OND 2010 and 2016, while upwelling Kelvin waves were only confined to the eastern coast of India during OND 1994, 1997, 2006, and 2019. Furthermore, westward salinity signals associated with reflected westward Rossby waves could modulate the spatial pattern of salinity. The distribution of salinity anomalies could potentially influence the formation of the barrier layer, thereby impacting the sea surface temperature variability and local convection. [ABSTRACT FROM AUTHOR]

The characteristics of terrestrial droughts are closely linked to simultaneous fluctuations in climatic factors, notably influenced by sea surface temperature (SST). This study explores the response of vegetation photosynthesis, indicated by solar-induced chlorophyll fluorescence (SIF), in India during the summer monsoon period (JJAS) under drought conditions. Notably, statistically significant associations between SST variations in the tropical Indian Ocean and land-based drought responses (precipitation, temperature, soil moisture, and SIF) were observed, which were attributed to atmospheric teleconnections. The positive phases of El Niño and the Indian Ocean Dipole (IOD) significantly impacted SST, triggering severe droughts in India in 2009 and 2015. The results revealed that positive SST anomalies weaken monsoon flow during the onset period, reducing moisture transmission to the Indian subcontinent. In 2009, the precipitation anomaly showed severe drought conditions (<−1.5) primarily in the northwest, central northeast, and west-central subregions, respectively, with soil moisture deficit and reduced photosynthetic activity (indicated by negative SIF anomalies) mirroring precipitation anomalies. In 2015, moderate to severe drought conditions affected regions primarily in the west-central and peninsular areas, with corresponding consistency in SIF anomalies and soil moisture deficits. These conditions led to decreased photosynthetic rates and negative SIF anomalies observed across India. The findings provide insights for predicting droughts and understanding ecosystem impacts across India amidst rapidly changing climate conditions in the Indian Ocean region. [ABSTRACT FROM AUTHOR]

An effort is made to understand the role of El Nino-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events on the malaria transmission intensity over India during the period 1951–2020 (70 years) with the help of a realistically simulated dynamical malaria model. The results suggest that the La Nina years pose a greater threat of malaria disease, especially in the densely populated Indian states. During El Nino years, the malaria transmission intensity and distribution over India greatly reduce, except in the regions such as Orissa, Chhattisgarh, Jharkhand, Western Ghats, parts of Madhya Pradesh, and Andhra Pradesh. It is found that in the positive IOD years, the malaria transmission intensity increases (decreases) over the entire central Indian region and along coastal regions of Tamil Nadu and Kerala (southern peninsular states of India and northeast India). An almost opposite behavior is seen during the negative IOD years. The malaria transmission variability over India is becoming increasingly heterogeneous in recent decades during the El Nino and La Nina years as a result of global warming. The period of 1986–2020 witnessed a substantial decrease (increase) in the malaria transmission intensity during the positive (negative) IOD years, except for a few regions of India. The implications of the results presented in the paper linking the ENSO and IOD signals with the intensity and distribution of malaria over India in a warming world are enormous, especially for the densely populated Indian states. [ABSTRACT FROM AUTHOR]

The extreme wind climate and its trends and variability of the southwest coast of India, particularly the Kerala coast, are investigated using hourly reanalysis wind speeds for the period 1979–2021. The observed maximum wind speed and 99th percentile wind speed off Kerala coast are 21.0 and 11.3 m·s−1, respectively. The predominant direction of high wind speeds is in the SW–WNW sector, which accounts for 93.5% of the total high winds. Extreme wind speeds in this region are not due to tropical cyclones alone, but also due to seasonal high winds. Seasonally, the premonsoon and SW monsoon extreme winds are predominantly in the WSW–WNW directional sector, while postmonsoon strong winds are present in all directional sectors, but predominantly in the SSW–WNW sector, followed by the E–SSE sector. The 99th percentile wind speeds during premonsoon, SW monsoon and postmonsoon are 8.8, 12.3 and 8.9 m·s−1, respectively. A significant decreasing trend is observed in the 99th percentile wind speeds during 1979–2021, ranging from 3 to 6 cm·s−1·year−1 off Kerala coast. This is in contrast with global increasing extreme wind speeds, and it can be attributed to regional variability as well as weakening of the land–sea thermal gradients associated with rising surface temperature in the Arabian Sea in the light of global warming. In addition to the long‐term declining trend and monthly as well as seasonal features, distinct interannual variations are also noticed in the 99th percentile wind speeds. Analysis shows that the atmospheric teleconnections associated with El Niño–La Niña events and Indian Ocean Dipole have an important role in the variability of extreme wind speeds. The co‐occurrence of positive (negative) IOD with El Niño (La Niña) results in a sharp decline (increase) in extreme wind speeds. Significant decadal variations are also noticed in the 99th percentile wind speeds. [ABSTRACT FROM AUTHOR]

Previous studies suggest that the winter surface freshening in the southeastern Arabian Sea (SEAS) contributes to the development of very high Sea Surface Temperatures (SST) thereby influencing the following summer monsoon onset. Here, we use forced and coupled simulations with a regional ocean general circulation model to explore the SEAS Sea Surface Salinity (SSS) variability mechanisms and impact on the monsoon. Both configurations capture the main SEAS oceanographic features, and confirm that the winter SSS decrease results from horizontal advection of Bay of Bengal freshwater by the cyclonic circulation around India during fall. A coupled model sensitivity experiment where salinity has no effect on mixing indicates that the salinity stratification reduces the SEAS mixed layer cooling by vertical processes by 3 °C seasonally. Salinity however enhances mixed layer cooling by a similar amount through concentrating negative winter surface heat fluxes into a thinner mixed layer, resulting in no climatological impact on SST and summer monsoon rainfall. The Indian Ocean Dipole (IOD) is the main driver of the winter SEAS SSS interannual variability (r ~ 0.8). Salty anomalies generated in the western Bay of Bengal during fall by positive IOD events are indeed transported by the cyclonic climatological coastal circulation, reaching the SEAS in winter. By this time, warm IOD-induced SST anomalies in the SEAS are already decaying, and the SEAS SSS anomalies hence do not contribute to their development. Overall, our model results suggest a weak climatological and interannual impact of the SEAS winter freshening on local SST and following monsoon onset. [ABSTRACT FROM AUTHOR]

Wind climate along the southwest coast of India (Kerala coast) has been analysed using 41 years of Climate Forecast System Reanalysis (CFSR) winds to delineate long‐term trends and variability. The study reveals significant decreasing trends in annual mean wind speeds, of the order of −2.0 to −2.5 cm·s−1·year−1, for the period 1979–2019. Southwest monsoon has contributed the highest weakening trends (−3.0 to −4.0 cm·s−1·year−1) due to significant decrease in the southwesterly/westerly wind speeds. The wind climate and trends during the northeast monsoon and premonsoon seasons have been characterized largely by the prevalence of sea breeze and shamal–makran wind systems. We find that the intensity of both sea breeze and shamal–makran wind systems reduces from north to south along the Kerala coast, which is in consistent with the earlier studies. Decadal oscillations in wind speeds, driven by the decadal variability in large‐scale atmosphere–ocean circulations, are evident. Recent changes in the frequency of occurrence of Indian Ocean Dipole in the Indian Ocean have determined the overturning trends since 2010, and resulted in increasing trends in the current decade along the central and northern coasts of Kerala. Furthermore, interannual variability in wind speeds has been linked to the El Niño–Southern Oscillations (ENSO) and Indian Ocean Dipole (IOD). [ABSTRACT FROM AUTHOR]

The 2019 extreme positive Indian Ocean dipole drove climate extremes over Indian Ocean rim countries with unclear carbon‐cycle responses. We investigated its impact on net biome productivity (NBP) and its constituent fluxes, using the Global Carbon Assimilation System (GCASv2) product, process‐based model simulations from TRENDYv9, and satellite‐based gross primary productivity (GPP). By distinguishing two separate regions, the India‐Africa and Asia‐Pacific, GCASv2 indicated enhanced terrestrial carbon uptake of 0.23 ± 0.20 PgC and release of 0.38 ± 0.15 PgC, respectively, during September–December (SOND) 2019. These NBP anomalies had comparable magnitudes to those following the 2015 extreme El Niño which, however, caused the consistent carbon release in both regions. The TRENDYv9 model ensemble confirmed these NBP responses, albeit with smaller magnitudes. These regional NBP anomalies were related to soil moisture variations with a dominant role of GPP. Understanding the impact of IOD provides new insights into mechanisms driving interannual variations in regional carbon cycling. Plain Language Summary: The extreme Indian Ocean Dipole (IOD) can drive climate extremes, such as floods, heatwaves, droughts, and wildfires, over the Indian Ocean rim countries. However, responses of regional terrestrial carbon cycling to IOD remained unclear. We used the net biome productivity (NBP) from an atmospheric inversion and multiple terrestrial biosphere models to demonstrate an enhanced terrestrial carbon uptake and release over the India‐Africa and Asia‐Pacific regions, respectively, during the extreme positive IOD (September–December) in 2019. These IOD‐induced regional NBP anomalies showed comparable magnitudes but different patterns to those following the 2015 extreme El Niño. Along with the more frequent extreme IOD under future greenhouse warming, IOD will be an important mechanism driving interannual variations in regional carbon cycling. Key Points: The 2019 extreme positive Indian Ocean Dipole caused the enhanced land carbon uptake over India‐Africa and release over Asia‐Pacific during September–DecemberThese regional net biome productivity (NBP) anomalies were closely related to soil moisture variations with a dominant role of gross primary productivityThese Indian Ocean Dipole‐induced regional NBP anomalies showed comparable magnitudes but different patterns to those following the 2015 extreme El Niño [ABSTRACT FROM AUTHOR]

Coastal hypoxia—harmfully low levels of oxygen—is a mounting problem that jeopardizes coastal ecosystems and economies. The northern Indian Ocean is particularly susceptible due to human‐induced impacts, vast naturally occurring oxygen minimum zones, and strong variability associated with the seasonal monsoons and interannual Indian Ocean Dipole (IOD). We assess how natural factors influence the risk of coastal hypoxia by combining a large set of oxygen measurements with satellite observations to examine how the IOD amplifies or suppresses seasonal hypoxia tied to the Asian Monsoon. We show that on both seasonal and interannual timescales hypoxia is controlled by wind‐ and coastal Kelvin wave‐driven upwelling of oxygen‐poor waters onto the continental shelf and reinforcing biological feedbacks (increased subsurface oxygen demand). Seasonally, the risk of hypoxia is highest in the western Arabian Sea in summer/fall (71% probability of hypoxia). Major year‐to‐year impacts attributed to the IOD occur during positive phases along the eastern Bay of Bengal (EBoB), where the risk of coastal hypoxia increases from moderate to high in summer/fall (21%–46%) and winter/spring (31%–42%), and along the eastern Arabian Sea (i.e., India, Pakistan) where the risk drops from high to moderate in summer/fall (53%–34%). Strong effects are also seen in the EBoB during negative IOD phases, when the risk reduces from moderate to low year‐round (∼25% to ∼5%). This basin‐scale mapping of hypoxic risk is key to aid national and international efforts that monitor, forecast, and mitigate the impacts of hypoxia on coastal ecosystems and ecosystem services. Plain Language Summary: Coastal "dead zones," with vanishingly low oxygen levels, stress marine organisms, compress their habitats, threaten the sustainability of fisheries, and can lead to mass mortality of marine life. The northern Indian Ocean is particularly vulnerable due to natural physical processes that bring oxygen‐poor water onto the continental shelf from vast offshore regions of low‐oxygen, and biological processes that can intensify coastal dead zones. Alongside these natural processes, coastal dead zones in the Indian Ocean are also influenced by human activity, such as fertilizer use and waste water management. In this study we use a large set of observations in the northern Indian Ocean to quantify how natural processes trigger coastal dead zones seasonally, and how they increase or decrease the risk of coastal dead zones from year‐to‐year. This information, on where and when coastal dead zones are most likely to occur, is key to anticipate and mitigate impacts on ecosystems and economies. Key Points: Regions at higher risk of coastal hypoxia in the northern Indian Ocean are identified using coastal oxygen observationsThe Indian Ocean Dipole (IOD) can amplify or suppress the seasonal risk of hypoxia by modulating coastal upwelling/downwellingThe risk is most amplified during positive IOD phases along the coast of the eastern Bay of Bengal [ABSTRACT FROM AUTHOR]

To find out how El Niño, the positive Indian Ocean Dipole (IOD), and the Madden-Julian Oscillation (MJO) affect the Indian Summer Monsoon Rainfall (ISMR), this study looks at two different monsoon years: 1997 (normal ISMR) and 2015 (below-normal ISMR). These two years were ideal for examining their combined effects on the performance of ISMR because they both experienced super El Niño conditions over the Pacific Ocean and positive IOD over the Indian Ocean. In these two years, spatial diversity associated with sea surface temperature (SST) was found over the Indian Ocean as well as the Pacific Ocean. The analysis of the large-scale circulation showed a distinct difference: the below-normal monsoon in 2015 was due to weak southwesterly flow toward the Indian landmass as well as anomalous subsidence compared to 1997. Analysis of rainy and dry days shows that 2015 had a greater (less) number of dry (rainy) days compared to 1997, contributing to a below-normal ISMR in 2015. The study also looked at the role of MJO in the observed rainfall anomalies over India during these two years, when there was both El Niño and positive IOD. This was done by looking at the composite of rainfall anomalies for different MJO phases. In 1997, during the monsoon season, MJO showed prolonged activity over the Indian Ocean (favorable MJO phases), which contributed to normal ISMR. However, in 2015, MJO was found active for many days over the western Pacific (unfavorable MJO phases), which contributed to below-normal ISMR. Overall, this case study highlights the complex interactions between El Niño, IOD, MJO, and monsoon dynamics, emphasizing the need for a comprehensive study of these factors to understand the behaviour of ISMR. • Combined influence of El Niño, positive IOD and MJO on Indian summer monsoon is analyzed • Indian summer monsoon was normal in 1997, whereas it was below normal in 2015 • The difference in seasonal rainfall was due to the anomalous SST and atmospheric circulations • MJO also plays an important role when both El Niño and positive IOD are present [ABSTRACT FROM AUTHOR]

This study presents a detailed analysis of the 2019 record-breaking seasonal (June–September) monsoon rainfall, since 1901, over large areas of Western India, which evolved in the backdrop of an intense positive Indian Ocean Dipole (pIOD) event. Analysis of ground-station-observed daily rainfall data revealed that the unusually excessive and flood-producing monsoonal rains of 2019 over Western India were driven by three intense rain episodes occurring between late June and September viz., 1) 28th June – 12th July 2) 24th July – 11th August 3) 2nd September – 13th September, characterized by large-scale bands of organized convection. We observed an abundance of stratiform precipitation from GPM Precipitation Radar swaths during the heavy-to-extreme rain events, indicating the presence of organized mesoscale convective systems with elevated heating over the region. Our findings suggest that the continual top-heavy stratiform heating forced a Rossby-wave pattern with regional stretching of mid-tropospheric potential vorticity across South and Southeast Asia, creating a favorable environment for sustaining widespread monsoon heavy-to-extreme rain events. Results reveal that the pIOD conditions that prevailed over tropical Indian Ocean during 2019 led to enhanced cross-equatorial moisture transport and were vital in fostering deep convection and heavy precipitation in this region. Interestingly, upon analyzing long-term data, we observed a 25% increase in the spatiotemporally aggregated rainfall over Western India contributed by seasonally abundant heavy rainfall events during pIOD years, as compared to non-pIOD years. Overall, this study underscores the potential hydrological consequences of intense pIOD manifestations on intense rain episodes and their impact on the monsoon-centric regions of South and Southeast Asia, particularly in a warming world. • Episodic spells of widespread intense rain events caused severe floods over Western India during 2019 summer monsoon. • A severe positive IOD and elevated stratiform heating within large-scale organized convective bands forced the events. • Strong cross-equatorial moisture flux and high mid-level potential vorticity creates an environment to sustain the events. • Spatiotemporal rainfall aggregation over Western India from abundant heavy rainfall seasons is 25% higher in pIOD years. [ABSTRACT FROM AUTHOR]

The present study examines the relationship between the tropical Indian Ocean (TIO) significant wave height (SWH) and Indian Ocean dipole (IOD) during boreal summer season (June through August) in the latest version of European Centre for Medium‐Range Weather Forecasts reanalysis (ERA5) and wave simulations forced with surface winds and sea‐ice fields from the Coupled Model Intercomparison Project version‐5 (CMIP5) models. The interannual variability of SWH shows a significant negative correlation with the IOD over TIO. SWH anomalies display meridional tripole pattern with significant negative (positive) anomalies over eastern equatorial Indian Ocean caused by anomalous easterlies (westerlies), and positive (negative) anomalies over southeastern TIO and the north Bay of Bengal during positive (negative) phase of IOD. The strong wave heights along the east coast of India during positive IOD and the south and southwest coast of India during negative IOD are noticed. CMIP5 models GFDL‐CM3, MRI‐CGCM3 and the multi‐model mean display considerable skill in capturing these teleconnections with substantial magnitude differences. A thorough understanding of the teleconnections between IOD and TIO wave heights is a significant prerequisite for the accurate forecast of surface waves in the Indian Ocean. Hence, this study advocates the importance evaluating the ability of models in representing the SWH and IOD interactions and its implications on Indian coastal regions in the form of inundation, coastal flooding and other vulnerabilities in a changing climate scenario. [ABSTRACT FROM AUTHOR]

Using reanalysis data and observations, interannual variations and long-term trends in the Somali Jet (hereafter, the Jet) and Indian Summer Monsoon Rainfall (ISMR) are characterized for drought vs flood, El Niño vs La Niña, and positive vs negative Indian Ocean Dipole (IOD) summer monsoon seasons. In flood years, the Jet is stronger over the upstream sector (i.e., Arabian Sea) and weaker over the downstream (i.e., Bay of Bengal), resulting in additional convergence and enhanced moisture transport over India, whereas the reverse occurs during drought years. The Jet and ISMR characteristics for El Niño (La Niña) years are similar to drought (flood) years, despite only around half of dry (wet) years, being associated with El Niño (La Niña). In +IOD years, the Jet shifts northward and intensifies over central and northern India, bringing more moisture and rainfall to those regions, while the −IOD has an opposite but relatively weak impact on ISMR. Over the last century, the Jet has become weaker over peninsular India, with reductions in rainfall across east India. Future projections under the SSP585 scenario from the CMIP6 multi-model mean suggest that the Jet will progressively shift northward and strengthen over the Arabian Sea, with associated rainfall increases over entire Indian region. The long-term changes in the Jet over the twentieth century are of comparable magnitude to interannual variations; however, the absolute magnitude of projected future changes is smaller than interannual variations observed in the past. [ABSTRACT FROM AUTHOR]

The positive Indian Ocean Dipole (IOD) event in 2019 was among the strongest on record, while the Indian Summer monsoon (ISM) was anomalously dry in June then very wet by September. We investigated the relationships between the IOD, Pacific sea surface temperature (SST), and ISM rainfall during 2019 with an atmospheric general circulation model forced by observed SST anomalies. The results show that the extremely positive IOD was conducive to a wetter‐than‐normal ISM, especially late in the season when the IOD strengthened and was associated with anomalous low‐level divergence over the eastern equatorial Indian Ocean and convergence over India. However, a warm SST anomaly in the central equatorial Pacific contributed to low‐level divergence and decreased rainfall over India in June. These results help to better understand the influence of the tropical SST anomalies on the seasonal evolution of ISM rainfall during extreme IOD events. Plain Language Summary: A prominent pattern of variability in the Indian Ocean is a seesaw in sea surface temperature (SST) between the eastern and western sides of the Ocean basin, called the Indian Ocean Dipole (IOD). Its influence on the regional weather and climate is not yet fully established, but the extremely strong IOD event in 2019 provided us the opportunity to consider its impact on the Indian Summer Monsoon. By simulating the response to the anomalous SST patterns that occurred in 2019, and by observation‐based analyses, we find evidence that the IOD did influence the monsoon rainfall in 2019, but that SST anomalies in the Pacific Ocean were also important. Our simulations show that the positive IOD was conducive to wetter‐than‐normal conditions throughout and especially at the end of the monsoon season, but that anomalous warmth in the central equatorial Pacific may have contributed to reduced rainfall in June over India. The results from this study help to understand the role of SST anomalies within and outside the Indian Ocean in affecting ISM rainfall intensity and seasonal evolution during extreme IOD events. Key Points: The positive Indian Ocean Dipole event that occurred in 2019 was among the strongest in the modern instrumental recordThe 2019 Indian Summer monsoon was drier than usual in June then wetter in the following months, resulting in above‐normal seasonal rainfallThe seasonal evolution of ISM was partly driven by a combination of equatorial Pacific and Indian Ocean sea surface temperature anomalies [ABSTRACT FROM AUTHOR]

North Indian Ocean witnesses varied dynamical response due to independent climate modes such as Indian Ocean Dipole (IOD)/El Niño Southern Oscillations (ENSO) and their co-occurrences. These modes have a significant impact on ocean productivity, which in turn shows feedback for the strengthening of these patterns. Keeping this in view, the present work attempts to analyze the biological activity during the combined influence of positive IOD with El Niño during 2006–2007 event. To divulge the biological variability along with the dynamical response, the study includes intra-annual variability surface chlorophyll anomaly with D20 anomaly using satellite observations. Here, the individual role of IOD and ENSO on both surface chlorophyll and D20 is segregated through partial regression analysis for a period of 25 years (1993–2017). By the regression method, it can be seen varied chlorophyll response for the 2006–2007 event with the IOD forcing leads to the major spatial and temporal variability with positive anomalies in Eastern Equatorial Indian Ocean (EEIO) (generally oligotrophic), Northwestern Bay of Bengal (NWBoB), and Northwestern Arabian Sea (NAS2) where production begins in fall intermonsoon and peaks up during November. On the other hand, negative anomalies are observed around the southern tip of India (SBoB) and the Northern Arabian Sea (NAS1). While ENSO depicts the high surface chlorophyll variability in the Western Indian Ocean (WIO1, WIO2) with negative anomalies of surface chlorophyll. This study observed an asymmetric response of chlorophyll variability over the North Indian Ocean during the 1997–1998 and 2006–2007 events with a major influence of IOD mode compared with the El Niño. Therefore, understanding the chlorophyll anomalies during different climate modes will help us to better understand the interannual variability and improve the predictability of chlorophyll productivity regions. [ABSTRACT FROM AUTHOR]

The present study assess the potential predictability of boreal summer (June through September, JJAS) tropical sea surface temperature (SST) and Indian summer monsoon rainfall (ISMR) using high resolution climate forecast system (CFSv2-T382) hindcasts. Potential predictability is computed using relative entropy (RE), which is the combined effect of signal strength and model spread, while the correlation between ensemble mean and observations represents the actual skill. Both actual and potential skills increase as lead time decreases for Niño3 index and equatorial East Indian Ocean (EEIO) SST anomaly and both the skills are close to each other for May IC hindcasts at zero lead. At the same time the actual skill of ISMR and El Niño Modoki index (EMI) are close to potential skill for Feb IC hindcasts (3 month lead). It is interesting to note that, both actual and potential skills are nearly equal, when RE has maximum contribution to individual year’s prediction skill and its relationship with absolute error is insignificant or out of phase. The major contribution to potential predictability is from ensemble mean and the role of ensemble spread is limited for Pacific SST and ISMR hindcasts. RE values are able to capture the predictability contribution from both initial SST and simultaneous boundary forcing better than ensemble mean, resulting in higher potential skill compared to actual skill for all ICs. For Feb IC hindcasts at 3 month lead time, initial month SST (Feb SST) has important predictive component for El Niño Modoki and ISMR leading to higher value of actual skill which is close to potential skill. This study points out that even though the simultaneous relationship between ensemble mean ISMR and global SST is similar for all ICs, the predictive component from initial SST anomalies are captured well by Feb IC (3 month lead) hindcasts only. This resulted in better skill of ISMR for Feb IC (3 month lead) hindcasts compared to May IC (0 month lead) hindcasts. Lack of proper contribution from initial SST and teleconnections induces large absolute error for ISMR in May IC hindcasts resulting in very low actual skill. Thus the use of potential predictability skill and actual skill collectively help to understand the fidelity of the model for further improvement by differentiating the role of initial SST and simultaneous boundary forcing to some extent. [ABSTRACT FROM AUTHOR]

Variations in Indian summer rainfall pose a threat to water security that can cause widespread socio-economic impacts. Summer rainfall is affected by both tropical and extratropical circulation anomalies owing to India's particular geographical location. Using observational, reanalysis, and CMIP6 model datasets, this study reveals the individual and joint effects of the Indian Ocean Dipole (IOD) and Silk Road Pattern (SRP) on the interannual variability of Indian rainfall during the summer to autumn transition (i.e., September). The results indicate that there is a consistent positive correlation between the IOD and SRP and the second mode of the Indian rainfall anomaly, which features a north–south inverse dipole pattern. During the positive phase of the IOD, the zonal sea surface temperature anomaly (SSTA) gradient of warm west and cold east in the equatorial Indian Ocean drives a Gill-type response, with an anticyclonic anomaly over southern India. This suppresses local convection and results in precipitation deficit across southern India. The SRP exhibits a baroclinic structure over west-central Asia, with an upper (lower) tropospheric anticyclonic (cyclonic) anomaly over west-central Asia (northern India) during its positive phase. This lower-level cyclonic anomaly is drastically amplified under the easterly vertical shear condition, favoring stronger moisture convergence and increased precipitation over northern India. The joint effect of the IOD and SRP explain s nearly 29% of the Indian rainfall anomaly, higher than the individual contributions of the IOD (17%) or SRP (12%). These results highlight the need to consider the joint effects of tropical and mid-latitude anomalous drivers on precipitation patterns and provide the basis for more accurate simulation and prediction of Indian rainfall. • Second mode of Indian rainfall (IR) anomaly features a north-south inverse dipole pattern in September. • The dipolar IR anomaly is affected by both the IOD and SRP. • Joint effects of the IOD and SRP explain nearly 29% of IR anomaly, i.e., much more than the contribution of any single factor. [ABSTRACT FROM AUTHOR]

The present study assesses the ability of the World Climate Research Programme's Coupled Model Intercomparison Project-6 (CMIP6) models in simulating the Indian Summer Monsoon (ISM) rainfall variability and its symmetric or asymmetric relationship with the El Niño–Southern Oscillation (ENSO) decay phase. The El Niño decays are classified into three categories based on their transition characteristics (rapid/slow) with respect to the subsequent boreal summer season, namely El Niño early-decay, El Niño mid-decay, and El Niño no-decay. Similarly, La Niña decays are also classified into the La Niña early-decay, La Niña mid-decay, and La Niña no-decay. In the case of El Niño and La Niña early-decay events, the observed summer rainfall anomalies over India are similar in spatial distribution and amplitude but opposite in sign, suggesting the symmetric rainfall response. This symmetric response is mainly due to the influence of the westward extension of western north Pacific (WNP) anomalous anticyclone/cyclone accompanied by tropical Indian Ocean (TIO) warming/cooling. In contrast to this, summers of El Niño and La Niña mid-decay events exhibited asymmetric rainfall anomaly pattern over India. This asymmetry in rainfall pattern between these two summers is attributed to differences mainly in the moisture divergence and low-level circulation over the Indo-Western Pacific region. Similar to El Niño and La Niña mid-decay cases, the summers of observed El Niño and La Niña no-decay events displayed ISM rainfall asymmetry. Differences in spatial distribution and magnitude of Sea surface temperature anomalies and related atmospheric circulation between these events mainly responsible for ISM rainfall asymmetry. Analysis of CMIP6 revealed that only ∼ 14% of selected CMIP6 models have simulated the rainfall anomalies somewhat correctly compared to observations during summers of different decay phases of ENSO. Further, symmetric/asymmetric response of summer rainfall anomalies over India between decay phases of El Niño and La Niña are not well captured by CMIP6 models. It is also noted that the CMIP6 models have displayed a tendency to simulate positive (negative) Indian Ocean Dipole conditions during the summers of El Niño no-decay (La Niña no-decay) events unlike in the observations. • CMIP6 models could simulate differences in decay phases of El Niño and La Niña well. • Models showed limited skills in capturing ISM rainfall related decay phases of ENSO. • Models tend to simulate unrealistic IOD pattern in summers of ENSO no-decay events. [ABSTRACT FROM AUTHOR]

Indo-Pacific sea surface temperature dynamics play a prominent role in Asian summer monsoon variability. Two interactive climate modes of the Indo-Pacific-the El Niño/Southern Oscillation (ENSO) and the Indian Ocean dipole mode-modulate the amount of precipitation over India, in addition to precipitation over Africa, Indonesia, and Australia. However, this modulation is not spatially uniform. The precipitation in southern India is strongly forced by the Indian Ocean dipole mode and ENSO. In contrast, across northern India, encompassing the Ganges and Brahmaputra basins, the climate mode influence on precipitation is much less. Understanding the forcing of precipitation in these river basins is vital for food security and ecosystem services for over half a billion people. Using 28 years of remote sensing observations, we demonstrate that (i) the tropical west-east differential heating in the Indian Ocean influences the Ganges precipitation and (ii) the north-south differential heating in the Indian Ocean influences the Brahmaputra precipitation. The El Niño phase induces warming in the warm pool of the Indian Ocean and exerts more influence on Ganges precipitation than Brahmaputra precipitation. The analyses indicate that both the magnitude and position of the sea surface temperature anomalies in the Indian Ocean are important drivers for precipitation dynamics that can be effectively summarized using two new indices, one tuned for each basin. These new indices have the potential to aid forecasting of drought and flooding, to contextualize land cover and land use change, and to assess the regional impacts of climate change. [ABSTRACT FROM AUTHOR]

The Indian Ocean Dipole (IOD) can affect the El Niño-Southern Oscillation (ENSO) state of the following year, in addition to the well-known preconditioning by equatorial Pacific Warm Water Volume (WWV), as suggested by a study based on observations over the recent satellite era (1981-2009). The present paper explores the interdecadal robustness of this result over the 1872-2008 period. To this end, we develop a robust IOD index, which well exploits sparse historical observations in the tropical Indian Ocean, and an efficient proxy of WWV interannual variations based on the temporal integral of Pacific zonal wind stress (of a historical atmospheric reanalysis). A linear regression hindcast model based on these two indices in boreal fall explains 50 % of ENSO peak variance 14 months later, with significant contributions from both the IOD and WWV over most of the historical period and a similar skill for El Niño and La Niña events. Our results further reveal that, when combined with WWV, the IOD index provides a larger ENSO hindcast skill improvement than the Indian Ocean basin-wide mode, the Indian Monsoon or ENSO itself. Based on these results, we propose a revised scheme of Indo-Pacific interactions. In this scheme, the IOD-ENSO interactions favour a biennial timescale and interact with the slower recharge-discharge cycle intrinsic to the Pacific Ocean. [ABSTRACT FROM AUTHOR]

It is now well known that there is a strong association of the extremes of the Indian summer monsoon rainfall (ISMR) with the El Niño and southern oscillation (ENSO) and the Equatorial Indian Ocean Oscillation (EQUINOO), later being an east-west oscillation in convection anomaly over the equatorial Indian Ocean. So far, the index used for EQUINOO is EQWIN, which is based on the surface zonal wind over the central equatorial Indian Ocean. Since the most important attribute of EQUINOO is the oscillation in convection/precipitation, we believe that the indices based on convection or precipitation would be more appropriate. Continuous and reliable data on outgoing longwave radiation (OLR), and satellite derived precipitation are now available from 1979 onwards. Hence, in this paper, we introduce new indices for EQUINOO, based on the difference in the anomaly of OLR/precipitation between eastern and western parts of the equatorial Indian Ocean. We show that the strong association of extremes of the Indian summer monsoon with ENSO and EQUINOO is also seen when the new indices are used to represent EQUINOO. [ABSTRACT FROM AUTHOR]

This paper examines an issue concerning the simulation of anomalously wet Indian summer monsoons like 1994 which co-occurred with strong positive Indian Ocean Dipole (IOD) conditions in the tropical Indian Ocean. Contrary to observations it has been noticed that standalone atmospheric general circulation models (AGCM) forced with observed SST boundary condition, consistently depicted a decrease of the summer monsoon rainfall during 1994 over the Indian region. Given the ocean-atmosphere coupling during IOD events, we have examined whether the failure of standalone AGCM simulations in capturing wet Indian monsoons like 1994 can be remedied by including a simple form of coupling that allows the monsoon circulation to dynamically interact with the IOD anomalies. With this view, we have performed a suite of simulations by coupling an AGCM to a slab-ocean model with spatially varying mixed-layer-depth (MLD) specified from observations for the 1994 IOD; as well as four other cases (1983, 1997, 2006, 2007). The specification of spatially varying MLD from observations allows us to constrain the model to observed IOD conditions. It is seen that the inclusion of coupling significantly improves the large-scale circulation response by strengthening the monsoon cross-equatorial flow; leading to precipitation enhancement over the subcontinent and rainfall decrease over south-eastern tropical Indian Ocean-in a manner broadly consistent with observations. A plausible physical mechanism is suggested to explain the monsoonal response in the coupled frame-work. These results warrant the need for improved monsoon simulations with fully coupled models to be able to better capture the observed monsoon interannual variability. [ABSTRACT FROM AUTHOR]

The article presents a study which investigates the impact of the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) on the north-east monsoon rainfall (NEMR) in Tamil Nadu, India. It states that NEMR had significant positive correlation with Niño-3 sea surface temperatures (SST) in July, in which the statistical relationships between the IOD and NEMR were much weaker compared to those between ENSO and NEMR. It discusses the composites of the circulation field for the extreme El Niño/La Niña years with the mean state for July, September and November.

The article presents a study on the atmospheric balance over South Peninsular India and Sri Lanka during the northeast monsoon season. The study uses computed moisture convergence (C) and residual evaporation (E) from the National Centers for Environment Prediction or National Center for Atmospheric Research (NCEP/NCAR) reanalysis data and Global Precipitation and Climatology Project (GPCP) precipitation data. It discusses the spatial and temporal characteristics of the hydrological cycle and the contribution of evaporation (E) dominates during the entire monsoon months. It notes that the positive northeast monsoon rainfall (NEMR) is associated with El Niño coupled with Indian Ocean dipole, but negative NEMR is associated with only La Niña.

• Reasons for the intraseasonal variability of the 2019 monsoon rainfall over India. • The presence of an El Niño Modoki event adversely affected timely monsoon onset. • The Walker cell linked to El Niño intensified the Indan Ocean Dipole (IOD). • The unusually strong IOD strengthened the monsoon circulation during July-September. The year 2019 experienced an excess monsoon season over the Indian region, with the seasonal rainfall being 110 % of the long period average (LPA). Several zones across the country suffered multiple extreme rainfall events and flood situations resulting in a massive loss of life and property. The first half of 2019 experienced a moderate El Niño Modoki event that lasted till mid-summer. Another important feature of 2019 was the strongest recorded positive Indian Ocean Dipole (IOD) that lasted approximately seven months from May to November. This study has examined the reasons for the intra-seasonal variability of rainfall over India during the 2019 monsoon using available remote sensing and reanalysis data. Our analysis has shown that the presence of El Niño and the formation of a very severe cyclonic storm (VSCS) in the Arabian Sea were unfavorable for the monsoon onset and its northward advancement during June. However, the Walker circulation associated with El Niño helped strengthen the IOD developed early in the Indian Ocean, much before the monsoon onset. The anomalously strong IOD strengthened the monsoon circulation during July-September and resulted in excess rainfall over India. [ABSTRACT FROM AUTHOR]

Variations of energy fluxes with ENSO, IOD, and Intra-Seasonal Variability of Indian Summer Monsoon Rainfall (ISMR) over the Indian monsoon region are examined using ECMWF Era Interim reanalysis over a period of 1979–2013. The composite anomalies of radiative fluxes, viz. shortwave and longwave, latent, and sensible heat as well as precipitation and winds are analyzed for the years associated with El Niño, La Niña, positive and negative IOD phases, active, and break phases of ISMR with respect to the normal years. It is observed that, the lesser (more) precipitation over the region in the El Niño (La Niña) years is accompanied with enhanced (reduced) top of the atmosphere absorbed solar radiation and outgoing long wave radiation, as well as more (less) surface absorbed solar radiation, and surface sensible heat flux. During the positive IOD phase, enhanced convective activity and precipitation rainfall over the western Equatorial Indian Ocean, Arabian Sea, and west coast of India, with reduced rainfall over the eastern equatorial Indian ocean is accompanied with enhanced shortwave and long wave radiative fluxes over most parts of the Indian subcontinent. The conditions during the negative IOD phases are largely the opposite. • This study examines the relative influences of ENSO and IOD events on the energy budget during ISM season of 1979‐2013. • Less(more) rainfall during ElNiño(LaNiña) years associated with less(more) absorbed SW & LW radiation fluxes over ISM region. • Strong +ve IOD events enhance SW & LW fluxes over the Indian region whereas the -ve IOD events show the reversed conditions. [ABSTRACT FROM AUTHOR]

Monsoon rain and rivers bring large freshwater input to the Northern Bay of Bengal (BoB), yielding low Sea Surface Salinity (SSS) after the monsoon. The resulting sharp upper-ocean salinity stratification is thought to influence tropical cyclones intensity and biological productivity by inhibiting vertical mixing. Despite recent progresses, the density of in situ data is far from sufficient to monitor the BoB SSS variability, even at the seasonal timescale. The advent of satellite remotely-sensed SSS (SMOS, Aquarius, SMAP) offers a unique opportunity to provide synoptic maps of the BoB SSS every ~8 days. Previous SMOS SSS retrievals did not perform well in the BoB. Here, we show that improved systematic error corrections and quality control procedures yield a much better performance of the new "debiased v4" CATDS level-3 SSS from SMOS (~0.8 correlation, 0.04 bias and 0.64 root-mean-square difference to more than 28,000 collocated in situ data points over 2010–2019). The SMOS product now performs equivalently to Aquarius, and is slightly inferior to SMAP over the BoB. In particular, SMAP and SMOS are able to capture salinity variations close to the east coast of India (r > 0.8 within 75–150 km of the coast). They thus capture the seasonal freshening there, associated with equatorward advection of the Northern BoB low-salinity water by the East Indian Coastal Current (EICC) after the summer monsoon. The 10-year long SMOS record further allows to describe the BoB interannual SSS variability, which is strongest in boreal fall in relation with the Indian Ocean Dipole (IOD). Positive IOD events induce a weakening of the southward export of freshwater by the EICC, and hence negative SSS anomalies in the Northern BoB and positive ones along the East Indian coast. This confirms results from earlier studies based on modelling, sparse in situ data, or shorter satellite records, but this time from a 10-year long SSS record. Overall, our study indicates that the new SMOS retrieval can be confidently used to monitor the BoB SSS and to study its mechanisms. We end by a brief description of the BoB SSS anomalies associated with the extreme 2019 IOD event and highlight the very good performance over the BoB of a new multi-satellite product developed by the European Space Agency merging SMOS, Aquarius and SMAP data. • The new debiased CATDS SMOS SSS product resolves major issues in the Bay of Bengal. • New SMOS has a comparable quality with SMAP and Aquarius, but over a full decade. • Confirms the post-monsoon southward transport of low saline water by the EICC. • Confirms that this transport is interannually modulated by the Indian Ocean Dipole. [ABSTRACT FROM AUTHOR]

Current study presents an integrated approach to assess the hydroclimatic teleconnections of large-scale coupled oceanic-atmospheric circulations on basin-scale extreme rainfall and streamflow indices for climatologically sensitive Tapi basin, India. The trend analysis of rainfall extremes revealed spatial heterogeneity across the basin. The coastal and mountainous regions of Lower and Upper Tapi basins respectively experienced wet conditions, while the plains of Middle and Upper Tapi (Purna sub-catchment) basins exhibited drier conditions during the analysis. The decreasing trend in high streamflow indices (except for Burhanpur sub-catchment) and significant increasing trend in low flow days (except for Lower Tapi basin) are observed, indicating the dominance of drier and moisture deficient conditions across Tapi basin. The hydroclimatic teleconnections of large-scale oceanic-atmospheric circulations of tropical Pacific and equatorial Indian Ocean regions, i.e., El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) respectively, with hydrometeorological extremes in Tapi basin for the concurrent period are investigated. As Indian summer monsoon rainfall (ISMR) and Tapi basin monsoon rainfall (TBMR) shows explained variance of around 42%, the influences of ENSO and IOD circulations on TBMR may be asymmetric with ISMR. The anomalous warming of the Indian Ocean, i.e., positive IOD (pIOD), and co-occurrence of pIOD and weak El Niño conditions, are associated with higher flood risk across the basin vis-à-vis other ENSO and IOD conditions. On other hand, the effects of ENSO and IOD are not apparent on low flow days, as the anthropogenic changes in the basin including streamflow regulations have considerably influenced the low flow regimes. The time interlocking between ENSO-IOD conditions and streamflow extremes in Tapi basin is further envisaged by performing a lead-lag correlation analysis. Unlabelled Image • Teleconnections of climate modes of Pacific and Indian Oceans are explored. • Spatially heterogenous trends in extreme rainfall and streamflow are detected. • Predominance of drier and moisture deficient conditions are observed in the basin. • ENSO and IOD have asymmetric influences on ISMR and TBMR. • Increased flood risk in Tapi basin during positive IOD conditions. [ABSTRACT FROM AUTHOR]

Background: Dengue is rapidly expanding climate-sensitive mosquito-borne disease worldwide. Outbreaks of dengue occur in various parts of India as well but there is no tool to provide early warning. The current study was, therefore, undertaken to find out the link between El Niño, precipitation, and dengue cases, which could help in early preparedness for control of dengue., Methods: Data on Oceanic Niño Index (ONI) was extracted from CPC-IRI (USA) while the data on monthly rainfall was procured from India Meteorological Department. Data on annual dengue cases was taken from the website of National Vector Borne Disease Control Programme (NVBDCP). Correlation analysis was used to analyse the relationship between seasonal positive ONI, rainfall index and dengue case index based on past 20 years' state-level data. The dengue case index representing 'relative deviation from mean' was correlated to the 3 months average ONI. The computed r values of dengue case index and positive ONI were further interpreted using generated spatial correlation map. The short-term prediction of dengue probability map has been prepared based on phase-wise (El Niño, La Niña, and Neutral) 20 years averaged ONI., Results: A high correlation between positive ONI and dengue incidence was found, particularly in the states of Arunachal Pradesh, Chhattisgarh, Haryana, Uttarakhand, Andaman and Nicobar Islands, Delhi, Daman and Diu. The states like Assam, Himachal Pradesh, Meghalaya, Manipur, Mizoram, Jammu & Kashmir, Uttar Pradesh, Orissa, and Andhra Pradesh shown negative correlation between summer El Niño and dengue incidence. Two - three month lag was found between monthly 'rainfall index' and dengue cases at local-scale analysis., Conclusion: The generated map signifies the spatial correlation between positive ONI and dengue case index, indicating positive correlation in the central part, while negative correlation in some coastal, northern, and north-eastern part of India. The findings offer a tool for early preparedness for undertaking intervention measures against dengue by the national programme at state level. For further improvement of results, study at micro-scale district level for finding month-wise association with Indian Ocean Dipole and local weather variables is desired for better explanation of dengue outbreaks in the states with 'no association'.

North Indian Ocean witnesses varied dynamical response due to independent climate modes such as Indian Ocean Dipole (IOD)/El Niño Southern Oscillations (ENSO) and their co-occurrences. These modes have a significant impact on ocean productivity, which in turn shows feedback for the strengthening of these patterns. Keeping this in view, the present work attempts to analyze the biological activity during the combined influence of positive IOD with El Niño during 2006-2007 event. To divulge the biological variability along with the dynamical response, the study includes intra-annual variability surface chlorophyll anomaly with D20 anomaly using satellite observations. Here, the individual role of IOD and ENSO on both surface chlorophyll and D20 is segregated through partial regression analysis for a period of 25 years (1993-2017). By the regression method, it can be seen varied chlorophyll response for the 2006-2007 event with the IOD forcing leads to the major spatial and temporal variability with positive anomalies in Eastern Equatorial Indian Ocean (EEIO) (generally oligotrophic), Northwestern Bay of Bengal (NWBoB), and Northwestern Arabian Sea (NAS2) where production begins in fall intermonsoon and peaks up during November. On the other hand, negative anomalies are observed around the southern tip of India (SBoB) and the Northern Arabian Sea (NAS1). While ENSO depicts the high surface chlorophyll variability in the Western Indian Ocean (WIO1, WIO2) with negative anomalies of surface chlorophyll. This study observed an asymmetric response of chlorophyll variability over the North Indian Ocean during the 1997-1998 and 2006-2007 events with a major influence of IOD mode compared with the El Niño. Therefore, understanding the chlorophyll anomalies during different climate modes will help us to better understand the interannual variability and improve the predictability of chlorophyll productivity regions.