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The Indonesian throughflow (ITF) transports a significant amount of warm freshwater from the Pacific to the Indian Ocean, making it critical to the global climate system. This study examines decadal ITF variations using ocean reanalysis data as well as climate model simulations from the Coupled Model Inter-comparison Project Phase 5 (CMIP5). While the observed annual cycle of ITF transport is known to be correlated with the annual cycle of sea surface height (SSH) difference between the Pacific and Indian Oceans, ocean reanalysis data (1959–2015) show that the Pacific Ocean SSH variability controls more than 85% of ITF variation on decadal timescales. In contrast, the Indian Ocean SSH variability contributes less than 15%. While those observed contributions are mostly reproduced in the CMIP5 historical simulations, an analysis of future climate projections shows a 25–30% increase in the Indian Ocean SSH variability to decadal ITF variations and a corresponding decrease in the Pacific contribution. These projected changes in the Indian Ocean SSH variability are associated with a 23% increase in the amplitudes of negative zonal wind stress anomalies over the equatorial Indian Ocean, along with a 12º eastward shift in the center of action in these anomalies. This combined effect of the increased amplitude and eastward shift in the zonal wind stress increases the SSHA variance over the Indian Ocean, increasing its contribution to the ITF variation. The decadal ITF changes discussed in this study will be crucial in understanding the future global climate variability, strongly coupled to Indo-Pacific interactions.

The Indian summer monsoon rainfall (ISMR) exhibits significant variability, affecting the food and water security of the densely populated Indian subcontinent. The two dominant spatial modes of ISMR variability are associated with the El Niño Southern Oscillation (ENSO) and the strength of the semi-permanent monsoon trough and related variability in monsoon depressions, respectively. ENSO strongly influences the ISMR, but the temporal and regional variability of this teleconnection is not well understood. Our analysis shows that the teleconnection between ENSO and ISMR increased consistently between 1901 to 1940, from a moderate to substantially strong correlation, remained stable at a strong correlation during 1941 to 1980, and then decreased consistently again to a moderate correlation in the recent period, 1981 to 2020. We have also explored the regional variability based on the consistency in the ENSO–ISMR relationship. We identify three regions—namely north, central and south India, where the variability in ENSO–ISMR relationship is moderate, high and consistent —and investigate the mechanisms behind the varying teleconnections. The overall decrease in ISMR is related to warm SST anomalies in the eastern Pacific Ocean suggesting El Niño conditions. Meanwhile, the decrease of rainfall over the Indo-Gangetic Plains and an increase over the southern peninsula is associated with warm SST anomalies over the Indian Ocean. We find that the temporal changes in ENSO–ISMR relation in different regions of the country are due to the overlying influence of the monsoon trough and related variability in monsoon depressions.

There is still a significant lack of diversity and equity in geoscience education, even after decades of work and widespread calls for improvement and action. We join fellow community voices in calls for improved diversity, equity, inclusion, and justice in the geosciences. Here, in this manifesto, we present a list of opportunities for educators to bring about this cultural shift within higher education: (1) advocating for institutional change, (2) incorporating diverse perspectives and authors in curricula, (3) teaching historical and socio-political contexts of geoscience information, (4) connecting geoscience principles to more geographically diverse locations, (5) implementing different communication styles that consider different ways of knowing and learning, and (6) empowering learner transformation and agency.

Climatologically, the frequency of tropical cyclones (TCs) in the Bay of Bengal (BoB) is higher relative to that over the Arabian Sea (ARB). However, recent years exhibit a greater number of TCs forming in the ARB than in the BoB. During the study period (1982–2019), a significant increasing trend in the intensity, frequency, and duration of cyclonic storms (CS) and very severe CS (VSCS) is observed over the ARB. There is a 52% increase in the frequency of CS during the recent epoch (2001–2019) in the ARB, while there is a decrease of 8% in the BoB. Over the ARB, increment in CS duration is 80% and VSCS is almost threefold in the recent epoch as compared to the past epoch (1982–2000). Also, lifetime maximum intensity and accumulated cyclone energy have increased over the ARB implying an increase in the strength of TCs. The increase in TC duration over the ARB is prominent during May, June, and October and a decrease over the BoB is noted during November. The increase in the duration of TCs in the ARB is associated with an increase in mid-level relative humidity and column averaged (950-150 hPa) moist static energy, which is significantly correlated to an increase in sea surface temperatures and tropical cyclone heat potential in the basin. In the recent epoch, TC genesis is observed at lower latitudes (

In this study, we reexamine the effect of two types of El Niño Southern Oscillation (ENSO) modes on Madden Julian Oscillation (MJO) activity in terms of the frequency of MJO phases. Evaluating all-season data, we identify two dominant zonal patterns of MJO frequency exhibiting prominent interannual variability. These patterns are structurally similar to the Wheeler and Hendon (Mon. Weather Rev. 132:1917–1932, 2004) RMM1 and RMM2 spatial patterns. The first pattern explains a higher frequency of MJO activity over the Maritime Continent and a lower frequency over the central Pacific Ocean and the western Indian Ocean, or vice versa. The second pattern is associated with a higher frequency of MJO active days over the eastern Indian Ocean and a lower frequency over the western Pacific, or vice versa. We find that these two types of MJO frequency patterns are related to the central Pacific and eastern Pacific ENSO modes. From the positive to the negative ENSO (central Pacific or eastern Pacific) phases, the respective MJO frequency patterns change their sign. The MJO frequency patterns are the lag response of the underlying ocean state. The coupling between ocean and atmosphere is exceedingly complex. The first MJO frequency pattern is most prominent during the negative central-Pacific (CP-type) ENSO phases (specifically during September–November and December-February seasons). The second MJO frequency pattern is most evident during the positive eastern-Pacific (EP-type) ENSO phases (specifically during March–May, June–August and September–November). Different zonal circulation patterns during CP-type and EP-type ENSO phases alter the mean moisture distribution throughout the tropics. The horizontal convergence of mean background moisture through intraseasonal winds are responsible for the MJO frequency anomalies during the two types of ENSO phases. The results here show how the MJO activity gets modulated on a regional scale in the presence of two types of ENSO events and can be useful in anticipating the seasonal MJO conditions from a predicted ENSO state.

Recent studies have shown that the Atlantic zonal mode (AZM) can significantly influence the Indian summer monsoon (ISM). In an earlier study, we proposed that AZM influence propagates in tropospheric temperature as Kelvin wave-like features to the east to reach the Indian Ocean and influences the monsoon by modulating the mid-tropospheric land-sea thermal gradient and thereby the seasonal mean flow. The changes thus induced in the mean flow were shown to affect the monsoon depressions in the Bay of Bengal and rainfall over India. In the present study, we use the Coupled Forecast System version 2, which is utilized for seasonal prediction of ISM in India, to examine how well the model simulates this AZM-monsoon link. In the sensitivity experiment, a warm AZM SST anomaly is added over the tropical Atlantic in the boreal summer and the ISM response is studied. We find that the model simulates the important aspects of the AZM-monsoon link. The model also simulates a known dynamics-based mechanism wherein a warm AZM SST anomaly produces a Matsuno-Gill type response, which in turn induces a sinking motion over India causing a reduction in rainfall. However, some finer details of these mechanisms are not simulated due to mean state biases in the tropical Atlantic in the model, a problem common to many coupled models. Our study highlights the need for the improvement of mean state of model in the tropical Atlantic to better capture the AZM-ISM relationship which will ultimately improve the monsoon forecasts issued using this model.

The Indian Ocean Observing System (IndOOS), established in 2006, is a multinational network of sustained oceanic measurements that underpin understanding and forecasting of weather and climate for the Indian Ocean region and beyond. Almost one-third of humanity lives around the Indian Ocean, many in countries dependent on fisheries and rain-fed agriculture that are vulnerable to climate variability and extremes. The Indian Ocean alone has absorbed a quarter of the global oceanic heat uptake over the last two decades and the fate of this heat and its impact on future change is unknown. Climate models project accelerating sea level rise, more frequent extremes in monsoon rainfall, and decreasing oceanic productivity. In view of these new scientific challenges, a 3-yr international review of the IndOOS by more than 60 scientific experts now highlights the need for an enhanced observing network that can better meet societal challenges, and provide more reliable forecasts. Here we present core findings from this review, including the need for 1) chemical, biological, and ecosystem measurements alongside physical parameters; 2) expansion into the western tropics to improve understanding of the monsoon circulation; 3) better-resolved upper ocean processes to improve understanding of air–sea coupling and yield better subseasonal to seasonal predictions; and 4) expansion into key coastal regions and the deep ocean to better constrain the basinwide energy budget. These goals will require new agreements and partnerships with and among Indian Ocean rim countries, creating opportunities for them to enhance their monitoring and forecasting capacity as part of IndOOS-2.

Marine heatwaves (MHWs) are extreme oceanic warm water events (above 90th percentile threshold) that significantly impact the marine environment. Several studies have recently explored the genesis ...

Generally, a strong north India summer-monsoon rainfall (NISR) is associated with anomalous upper troposphere ridge over northwest of India. This ridge triggers anomalous northerly winds over Tibetan Plateau and easterlies over India. The easterly anomaly over India reduces the tropospheric wind shear, while the northerly at Tibetan plateau allows frequent intrusions of high-latitude dry and cold meridional winds to interact with the lower-level relatively warm and moist easterly monsoonal flow, enhancing the NISR. The current study, using a suite of observations, reanalysis products and numerical model sensitivity experiments, explores the changes in NISR, and its association with the warming in the equatorial Indian Ocean. In the recent two decades (1996-2017), the NISR has been exhibiting a decreasing trend with increased variability, much larger than the earlier period (1979-2000). A possible reason for this is due to the rise in warm sea surface temperature (SST) observed in the east equatorial Indian ocean, which shows a negative correlation to NISR. The current analysis indicates that the warmer SST induce strong convection and associated northward propagating off-equatorial Rossby gyres to the west of the equatorial eastern Indian ocean, spreading the tropospheric heating towards the northeast of India, thereby elevating the geopotential height. This creates upper troposphere low pressure anomaly at the northwest of India. These factors are consistent with the suppression of the NISR, resulting in the observed decreasing trend in the recent decades.

Cyclone Fani, in April 2019, was the strongest pre-monsoon cyclone to form in the Bay of Bengal after 1994. It underwent rapid intensification and intensified quickly to an extremely severe cyclone. It maintained a wind speed of ≥ 51 m s−1 (≥ 100 knots) for a record time period of 36 h. The total lifespan of the cyclone was double than the climatological lifespan. Also, the duration of the cyclone in its extremely severe phase and the accumulated cyclone energy were significantly larger than the climatological records for the pre-monsoon season. In the current study, we investigate the ocean-atmospheric conditions that led to its genesis, rapid intensification and long lifespan. Our analysis shows that the Madden Julian Oscillation and anomalous high sea surface temperatures provided conducive dynamic and thermodynamic conditions for the genesis of cyclone Fani, despite forming very close to the equator where cyclogenesis is generally unlikely. Further, favourable ocean subsurface conditions and the presence of a warm core eddy in the region led to its rapid intensification to an extremely severe cyclone. A large area of warm ocean surface and subsurface temperatures aided the cyclone to maintain very high wind speed for a record time period. The vital role of the ocean surface and the subsurface in the genesis and the intensification highlights the need to efficiently incorporate ocean initial conditions (surface and sub-surface) and ocean–atmosphere coupling in the operational cyclone forecasting framework.

Sea surface temperature (SST) and upper ocean heat content (OHC, upper 700 m) in the tropical Indian Ocean underwent rapid warming during 1950–2015, with the SSTs showing an average warming of about 1 °C. The SST and OHC trends are very likely to continue in the future, under different emission scenarios. Climate models project a rise in tropical Indian Ocean SST by 1.2–1.6 °C and 1.6–2.7 °C in the near (2040–2069) and far (2070–2099) future across greenhouse gas (GHG) emissions scenarios RCP4.5 and RCP8.5, relative to the reference period of 1976–2005. Indian Ocean warming has very likely resulted in decreasing trend in oxygen (O2) concentrations in the tropical Indian Ocean, and declining trends in pH and marine phytoplankton over the western Indian Ocean. The observed trends in O2, pH and marine phytoplankton are projected to increase in the future with continued GHG emissions.

Global climate models including the Climate Forecast System version 2, the operational model used for prediction of Indian summer monsoon rainfall by the India Meteorological Department, has dry precipitation bias, mostly over densely populated Ganga basin. This restricts the use of model output in hydrological simulations/forecasts. We use regional atmospheric Weather Research and Forecasting model coupled with land surface models, driven by the boundary conditions from Climate Forecast System version 2. We find significant reduction in the dry bias of Indian summer monsoon rainfall with regional land-atmosphere model and this attributes to (a) improved moisture transport from Western and Upper Indian Ocean to Ganga Basin and (b) improved precipitation recycling over the Ganga basin. We find that the smoothened topography in the global model allows advection of cold dry subtropical air into the Indian monsoon region, contributing to the cold temperature and dry precipitation bias. These results have important implications for monsoon simulations in developing operational hydroclimatic prediction system in India. Plain Language Summary The operational monsoon prediction model for India, Climate Forecast System version 2, has significant dry bias in precipitation over the Ganga basin, and this restricts the use of model output for hydrologic prediction. We attribute such bias to the lack of representation of land surface processes and characteristics in the model. We show that an improved representation of land characteristics in a regional coupled atmospheric-land model improves not only the land-atmosphere interactions but also the moisture contributions from distant oceanic sources. This finally results into improved simulations of monsoon.

We analyse the bias present in the Indian Summer Monsoon Rainfall (ISMR), as simulated by Climate Forecast System Model 2 (CFSv2), the operational model used for monsoon forecasts in India. In the simulations, the precipitation intensity is redistributed within the ITCZ band with southward shifts of precipitation maxima. We observe weakening of maximum intensity of precipitation over the region between 20°N and 14°N. In the simulations by CFSv2, there exists two rain bands: the northern one located slightly southward compared to reanalysis dataset and the southern one over the equator with intensified precipitation. This results in dry bias over land and wet bias over the ocean. We use a Dynamic Recycling Model, based on Lagrangian approach, to investigate the role of various moisture sources in generating these biases. We find that, the dry bias during June exists due to the delayed monsoon onset and reduced moisture flow from the Arabian Sea. As the monsoon progresses, deficiency in the simulated contributions from South Indian Ocean becomes the key source of bias. The reduced supply of moisture from oceanic sources is primarily attributed to the weaker northward transport of moisture flux from the Southern Ocean, associated with a weaker southward energy flux. Inefficiency of the model in simulating the heating in Tibetan plateau during the pre-monsoon period leads to this reduced cross equatorial energy flow. We also find that, towards the end of monsoon season, moisture contributions from land sources namely, Ganga Basin and North-Eastern forests become significant and underestimations of the same in the simulations by CFSv2 result into biases over Central and Eastern India.

The South Asian summer monsoon is a complex coupled human‐natural system that poses unique challenges for understanding its evolution alongside increasing anthropogenic activities. Rapid and substantial changes in land‐use, land‐management and industrial activities over the subcontinent, and warming in the Indian Ocean, have influenced the South Asian summer monsoon. These might continue to be significant drivers in the near‐term along with rising global greenhouse gas emissions. Deciphering the region's vulnerability to climate change requires an understanding of how these anthropogenic activities, acting on a range of spatial scales, have shaped the monsoon spatially and temporally. This review summarizes historical changes in monsoon rainfall characteristics, associated mechanisms, and the role of anthropogenic forcings, focusing on subseasonal variability and extreme events. Several studies have found intensified subseasonal extremes across parts of India and an increase in spatial variability of rainfall despite an overall weakening of seasonal rainfall in the monsoon core. However, understanding these changes remains challenging because of uncertainties in observations and climate models. The mechanisms and relative influences of various anthropogenic activities, particularly on subseasonal extremes, remain relatively underexplored. Large biases in the representation of relevant processes in global climate models limit the ability to attribute historical changes and make reliable projections. Nevertheless, recent advances in modeling these processes using higher‐resolution modeling frameworks provide new tools to investigate the Indian summer monsoon's response to various anthropogenic forcings. There is an urgent need to understand how these forcings interact to shape climate variability and change in this vulnerable region. This article is categorized under: Paleoclimates and Current Trends > Earth System Behavior

Subsurface temperature biases in coupled models can seriously impair their capability in generating skillful seasonal forecasts. The National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), coupled model, which is used for seasonal forecast in several countries including India, displays warm (cold) subsurface (surface) temperature bias in the tropical Indian Ocean (TIO), with deeper than observed mixed layer and thermocline. In the model, the maximum warm bias is reported between 150- and 200-m depth. Detailed analysis reveals that the enhanced vertical mixing by strong vertical shear of horizontal currents is primarily responsible for TIO subsurface warming. Weak upper-ocean stability corroborated by surface cold and subsurface warm bias further strengthens the subsurface warm bias in the model. Excess inflow of warm subsurface water from Indonesian Throughflow to the TIO region is partially contributing to the warm bias mainly over the southern TIO region. Over the north Indian Ocean, Ekman convergence and downwelling due to wind stress bias deepen the thermocline, which do favor subsurface warming. Further, upper-ocean meridional and zonal cells are deeper in CFSv2 compared to the Ocean Reanalysis System data manifesting the deeper mixing. This study outlines the need for accurate representation of vertical structure in horizontal currents and associated vertical gradients to simulate subsurface temperatures for skillful seasonal forecasts.

This study investigates the response of tropical Indian Ocean (TIO) sea surface temperature (SST) to El Nino decay phase and its impacts on South and East Asian summer monsoon in the National Centers for Environmental Prediction Climate Forecast System version 2 free run. The TIO basin-wide warming induced by El Nino at its peak phase (winter; DJF) and next spring (MAM + 1) are reasonably well captured by the model but with weak magnitude. This TIO basin-wide SST warming persists until summer (JJA + 1) and exert strong impact on summer monsoon rainfall and circulation as revealed in the observations. However, TIO SST anomalies are very weak in the model during the El Nino decaying summers. Though El Nino decay is delayed by 2 months in the model, decay of TIO SST warming is faster than the observations. Anomalous latent heat loss from ocean and a feeble southern TIO Rossby waves associated with weak wind response to El Nino are mainly accountable for rapid decay of TIO SST warming by mid-summer in the model. This suggests that JJA + 1 TIO SST response to El Nino decay phase in the model is poorly represented. The model is able to capture the SST anomalies associated with the northwest Pacific anticyclone at the peak phase of El Nino but fail to maintain that during the decay phase in MAM + 1 and JJA + 1. It is found that precipitation and circulation anomalies associated with TIO SST warming over the South and East Asian regions are disorganized in the model during the decay phase of El Nino. Rainfall anomalies over the southwest TIO, west coast of India, northern flank of northwest Pacific anticyclone and over Japan in JJA + 1 are poorly represented by the model. Analysis of lower troposphere stream function and rotational wind component reveals that northwest Pacific anticyclone shifted far eastward to the date line in the model during JJA + 1 unlike in the observations. Anomalous divergence observed over the western TIO and convergence in the northwest Pacific are absent in the model during JJA + 1. Extension of anomalous tropospheric warming from TIO region to equatorial western Pacific is also very weak in the model due to poor representation of TIO SSTs and the subsequent absence of any Kelvin wave response. Anomalous Walker circulation persisted from DJF to JJA + 1 due to El Nino late decay in the model unlike in the observations. This is also found to be responsible for the redundant changes in SST, rainfall and circulation over the Indo-western Pacific in the model. This study demonstrates that it is essential to represent the decay phase of El Nino and the associated TIO response accurately to have realistic simulations of summer monsoon in the decaying year.

With the goal of building an Earth system model appropriate for detection, attribution, and projection of changes in the South Asian monsoon, a state-of-the-art seasonal prediction model, namely the Climate Forecast System version 2 (CFSv2) has been adapted to a climate model suitable for extended climate simulations at the Indian Institute of Tropical Meteorology (IITM), Pune, India. While the CFSv2 model has been skillful in predicting the Indian summer monsoon (ISM) on seasonal time scales, a century-long simulation with it shows biases in the ocean mixed layer, resulting in a 1.5°C cold bias in the global mean surface air temperature, a cold bias in the sea surface temperature (SST), and a cooler-than-observed troposphere. These biases limit the utility of CFSv2 to study climate change issues. To address biases, and to develop an Indian Earth System Model (IITM ESMv1), the ocean component in CFSv2 was replaced at IITM with an improved version, having better physics and interactive ocean biogeochemistry. A 100-yr simulation with the new coupled model (with biogeochemistry switched off) shows substantial improvements, particularly in global mean surface temperature, tropical SST, and mixed layer depth. The model demonstrates fidelity in capturing the dominant modes of climate variability such as the ENSO and Pacific decadal oscillation. The ENSO–ISM teleconnections and the seasonal leads and lags are also well simulated. The model, a successful result of Indo–U.S. collaboration, will contribute to the IPCC’s Sixth Assessment Report (AR6) simulations, a first for India.

International audience; The impact of the Indian and Atlantic oceans variability on El Niño–Southern-Oscillation (ENSO) phenomenon is investigated through sensitivity experiments with the SINTEX-F2 coupled model. For each experiment, we suppressed the sea surface temperature (SST) variability in either the Indian or Atlantic oceans by applying a strong nudging of the SST toward a SST climatology computed either from a control experiment or observations. In the sensitivity experiments where the nudging is done toward a control SST climatology, the Pacific mean state and seasonal cycle are not changed. Conversely, nudging toward an observed SST climatology in the Indian or Atlantic domain significantly improves the mean state and seasonal cycle, not only in the nudged domain, but also in the whole tropics. These experiments also demonstrate that decoupling the Indian or Atlantic variability modifies the phase-locking of ENSO to the annual cycle, influences significantly the timing and processes of ENSO onset and termination stages, and, finally, shifts to lower frequencies the main ENSO periodicities. Overall, these results suggest that both the Indian and Atlantic SSTs have a significant damping effect on ENSO variability and promote a shorter ENSO cycle. The reduction of ENSO amplitude is particularly significant when the Indian Ocean is decoupled, but the shift of ENSO to lower frequencies is more pronounced in the Atlantic decoupled experiments. These changes of ENSO statistical properties are related to stronger Bjerknes and thermocline feedbacks in the nudged experiments. During the mature phase of El Niño events, warm SST anomalies are found over the Indian and Atlantic oceans in observations or the control run. Consistent with previous studies, the nudged experiments demonstrate that these warm SSTs induce easterly surface wind anomalies over the far western equatorial Pacific, which fasten the transition from El Niño to La Niña and promote a shorter ENSO cycle in the control run. These results may be explained by modulations of the Walker circulation induced directly or indirectly by the Indian and Atlantic SSTs. Another interesting result is that decoupling the Atlantic or Indian oceans change the timing of ENSO onset and the relative role of other ENSO atmospheric precursors such as the extra-tropical Pacific Meridional Modes or the Western North Pacific SSTs.

Seasonal, interannual, and multidecadal variability of seawater pCO2 and air-sea CO2 fluxes in the equatorial Pacific Ocean for the past 45 years (1961–2005) are examined using a suite of experiments performed with an offline biogeochemical model driven by reanalysis ocean products. The processes we focus on are: (a) the evolution of seasonal cycle of pCO2 and air-sea CO2 fluxes during the dominant interannual mode in the equatorial Pacific, i.e., the El Nino-Southern Oscillation (ENSO), (b) its spatiotemporal characteristics, (c) the combined and individual effects of wind and ocean dynamics on pCO2 and CO2 flux variability and their relation to canonical (eastern Pacific) and central Pacific (Modoki) ENSOs and (d) the multidecadal variability of carbon dynamics in the equatorial Pacific and its association with the Pacific Decadal Oscillations (PDO). The simulated mean and seasonal cycle of pCO2 and CO2 fluxes are comparable with the observational estimates and with other model results. A new analysis methodology based on the traditional Empirical Orthogonal Functions (EOF) applied over a time-time domain is employed to elucidate the dominant mode of interannual variability of pCO2 and air-sea CO2 fluxes at each longitude in the equatorial Pacific. The results show that the dominant interannual variability of CO2 fluxes in the equatorial Pacific (averaged over 5°N–10°S) coevolves with that of ENSO. Generally a reduced CO2 source in the central-to-eastern equatorial Pacific evident during June–July of the El Nino year (Year:0) peaks through September of Year:0 to February of Year:+1 and recovers to a normal source thereafter. In the region between 160°W and 110°W, the canonical El Nino controls the dominant variability of CO2 fluxes (mean and RMS of anomaly from 1961 to 2005 is 0.43±0.12 PgC yr−1). However, in the western (160°E–160°W) and far eastern (110°W–90°W) equatorial Pacific, CO2 flux variability is dominantly influenced by the El Nino-Modoki (0.3±0.06 and 0.11±0.04 PgC yr−1, respectively). On the other hand, the interannual variability of pCO2 is correlated with the canonical El Nino mostly to the east of 140°W and with El Nino-Modoki to the west of 140°W. Decoupling of CO2 flux and pCO2 variability at various locations in the equatorial Pacific is attributable to the differences in the combined and individual effects of ocean dynamics and winds associated with these two types of ENSO. A multidecadal variability in the equatorial Pacific sea-air CO2 fluxes and pCO2 exhibits a positive phase during the 1960s, a negative phase during the 1980s, and then positive again by the 2000s. Within the ocean, the dissolved inorganic carbon (DIC) anomalies are traceable to the northern Pacific via thermocline pathways at decadal timescales. The multidecadal variability of equatorial Pacific CO2 fluxes and pCO2 are determined by the phases of the PDO and the corresponding scale of the El Nino-Modoki variability, whereas canonical El Nino's contribution is to mainly determine the variability at interannual timescales. This study segregates the impacts of different types of ENSOs on the equatorial Pacific carbon cycle and sets the framework for analysing its spatiotemporal variability under global warming.

Socioeconomic challenges continue to mount for half a billion residents of central India because of a decline in the total rainfall and a concurrent rise in the magnitude and frequency of extreme rainfall events. Alongside a weakening monsoon circulation, the locally available moisture and the frequency of moisture-laden depressions from the Bay of Bengal have also declined. Here we show that despite these negative trends, there is a threefold increase in widespread extreme rain events over central India during 1950–2015. The rise in these events is due to an increasing variability of the low-level monsoon westerlies over the Arabian Sea, driving surges of moisture supply, leading to extreme rainfall episodes across the entire central subcontinent. The homogeneity of these severe weather events and their association with the ocean temperatures underscores the potential predictability of these events by two-to-three weeks, which offers hope in mitigating their catastrophic impact on life, agriculture and property., Against the backdrop of a declining monsoon, the number of extreme rain events is on the rise over central India. Here the authors identify a threefold increase in widespread extreme rains over the region during 1950–2015, driven by an increasing variability of the low-level westerlies over the Arabian Sea.

International audience; The relationship between the Indian Ocean and the Indian summer monsoon (ISM) and their respective influence over the Indo-Western North Pacific (WNP) region are examined in the absence of El Niño Southern Oscillation (ENSO) in two partially decoupled global experiments. ENSO is removed by nudging the tropical Pacific simulated sea surface temperature (SST) toward SST climatology from either observations or a fully coupled control run. The control reasonably captures the observed relationships between ENSO, ISM and the Indian Ocean Dipole (IOD). Despite weaker amplitude, IODs do exist in the absence of ENSO and are triggered by a boreal spring ocean–atmosphere coupled mode over the South-East Indian Ocean similar to that found in the presence of ENSO. These pure IODs significantly affect the tropical Indian Ocean throughout boreal summer, inducing a significant modulation of both the local Walker and Hadley cells. This meridional circulation is masked in the presence of ENSO. However, these pure IODs do not significantly influence the Indian subcontinent rainfall despite overestimated SST variability in the eastern equatorial Indian Ocean compared to observations. On the other hand, they promote a late summer cross-equatorial quadrupole rainfall pattern linking the tropical Indian Ocean with the WNP, inducing important zonal shifts of the Walker circulation despite the absence of ENSO. Surprisingly, the interannual ISM rainfall variability is barely modified and the Indian Ocean does not force the monsoon circulation when ENSO is removed. On the contrary, the monsoon circulation significantly forces the Arabian Sea and Bay of Bengal SSTs, while its connection with the western tropical Indian Ocean is clearly driven by ENSO in our numerical framework. Convection and diabatic heating associated with above-normal ISM induce a strong response over the WNP, even in the absence of ENSO, favoring moisture convergence over India.

Over the tropical oceans, higher sea surface temperatures (SST, above 26 °C) in summer are generally accompanied by increased precipitation. However, it has been argued for the last three decades that, any monotonic increase in precipitation with respect to SST is limited to an upper threshold of 28–29.5 °C, and beyond this, the relationship fails. Based on this assessment it has often been presumed that, since the mean SSTs over the Asian monsoon basins (Indian Ocean and north-west Pacific) are mostly above the threshold, SST does not play an active role on the summer monsoon variability. It also implies that increasing SSTs due to a changing climate need not result in increasing monsoon precipitation. The current study shows that the response of precipitation to SST has a time lag, that too with a spatial variability over the monsoon basins. Taking this lag into account, the results here show that enhanced convection occurs even up to the SST maxima of 31 °C averaged over these basins, challenging any claim of an upper threshold for the SST-convection variability. The study provides us with a novel method to quantify the SST-precipitation relationship. The rate of increase is similar across the basins, with precipitation increasing at ~2 mm day−1 for an increase of 1 °C in SST. This means that even the high SSTs over the monsoon basins do play an active role on the monsoon variability, challenging previous assumptions. Since the response of precipitation to SST variability is visible in a few days, it would also imply that including realistic ocean–atmosphere coupling is crucial even for short term monsoon weather forecasts. Though recent studies suggest a weakening of the monsoon circulation over the last few decades, results here suggest an increased precipitation over the tropical monsoon regions, in a global warming environment with increased SSTs. Thus the signature of SST is found to be significant for the Asian summer monsoon, in a quantifiable manner, seamlessly through all the timescales—from short-term intraseasonal to long-term climate scales.

Atmospheric dynamical mechanisms have been prevalently used to explain the characteristics of the sum- mer monsoon intraseasonal oscillation (MISO), which dictates the wet and dry spells of the monsoon rainfall. Recent studies show that ocean-atmosphere coupling has a vital role in simulating the observed amplitude and rela- tionship between precipitation and sea surface temperature (SST) at the intraseasonal scale. However it is not clear whether this role is simply 'passive' response to the atmospheric forcing alone, or 'active' in modulating the northward propagation of MISO, and also whether the extent to which it modulates is considerably noteworthy. Using coupled NCEP-Climate Forecast System (CFSv2) model and its atmospheric component the Global Forecast System (GFS), we investigate the relative role of the atmospheric dynamics and the ocean-atmosphere coupling in the initiation, maintenance, and northward propagation of MISO. Three numerical simulations are performed including (1) CFSv2 coupled with high frequency inter- active SST, the GFS forced with both (2) observed monthly SST (interpolated to daily) and (3) daily SST obtained from the CFSv2 simulations. Both CFSv2 and GFS simulate MISO of slightly higher period (*60 days) than observations (*45 days) and have reasonable seasonal rainfall over India. While MISO simulated by CFSv2 has realistic northward propagation, both the GFS model experiments show standing mode of MISO over India with no northward propagation of convection from the equator. The improvement in northward propagation in CFSv2, therefore, may not be due to improvement of the model physics in the atmospheric component alone. Our analysis indicates that even with the presence of conducive vertical wind shear, the absence of meridional humidity gradient and moistening of the atmosphere column north of con- vection hinders the northward movement of convection in GFS. This moistening mechanism works only in the pres- ence of an 'active' ocean. In CFSv2, the lead-lag rela- tionship between the atmospheric fluxes, SST and convection are maintained, while such lead-lag is unreal- istic in the uncoupled simulations. This leads to the con- clusion that high frequent and interactive ocean- atmosphere coupling is a necessary and crucial condition for reproducing the realistic northward propagation of MISO in this particular model.

The climate change experiments under the fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), namely the twentieth century simulations (20C3M) and Special Report on Emissions Scenarios (SRES) A1B, are revisited to study whether these models can reproduce the ENSO and ENSO Modoki patterns as the two important modes from statistical linear analysis as observed. The capability of the models in simulating realistic ENSO/ENSO Modoki teleconnections with the Indian summer monsoon, and also the implications for the future are also explored. Results from the study indicate that only ~ 1/4th of the models from 20C3M capture either ENSO or ENSO Modoki pattern in JJAS. Of this 1/4th, only two models simulate both ENSO and ENSO Modoki as important modes. Again, out of these two, only one model simulates both ENSO and ENSO Modoki as important modes during both summer and winter. It is also shown that the two models that demonstrate ENSO Modoki as well as ENSO associated variance in both 20C3M and SRESA1B represent the links of the ISMR with ENSO reasonably in 20C3M, but indicate opposite type of impacts in SREA1B. With the limited skills of the models in reproducing the monsoon, the ENSO and ENSO Modoki, it is difficult to reconcile that the teleconnections of a tropical driver can change like that. All these indicate the challenges associated with the limitations of the models in reproducing the variability of the monsoons and ENSO flavors, not to speak of failing in capturing the potential impacts of global warming as they are expected to. More research in improving the current day simulations, improving model capacity to simulate better by improving the Green House Gases (GHG) and aerosols in the models are some of the important and immediate steps that are necessary.

Tropical Indian Ocean is warming at a faster rate compared to other tropical oceans. The warming trends show a basin-scale surface warming with peak warming in the central equatorial Indian Ocean. This warming is favourable for weakening the monsoon Hadley circulation and strengthening the trade winds in the Pacific. In addition to this, the cross-equatorial flow also weakens in the recent years to reduce the moisture supply to Indian subcontinent. The associated strengthening of westerly winds along the equator and the resultant eastward surface currents transport warm water mass towards eastern equatorial region and Bay of Bengal. This is confirmed from different ocean reanalysis products. It is also found that the upper north Indian Ocean is gaining heat during the recent 60 years or so at an alarming rate. The ocean circulation and dynamics play favourably for such warming.

International audience; Among the tropical oceans, the western Indian Ocean hosts one of the largest concentrations of marine phytoplankton blooms in summer. Interestingly, this is also the region with the largest warming trend in sea surface temperatures in the tropics during the past century—although the contribution of such a large warming to productivity changes has remained ambiguous. Earlier studies had described the western Indian Ocean as a region with the largest increase in phytoplankton during the recent decades. On the contrary, the current study points out an alarming decrease of up to 20% in phytoplankton in this region over the past six decades. We find that these trends in chlorophyll are driven by enhanced ocean stratification due to rapid warming in the Indian Ocean, which suppresses nutrient mixing from subsurface layers. Future climate projections suggest that the Indian Ocean will continue to warm, driving this productive region into an ecological desert.

This study focuses on analyses and validation of 1 month forecasts (OMFs) of weak Indian monsoons based on 10 member ensemble hindcasts (retrospective forecasts) of the NCEP Climate Forecast System (CFS) model for the period 1981–2008. The weak monsoon episodes chosen for the analysis correspond to summer monsoon months which were characterized by significant deficits in the All-India monthly rainfall of − 20% of the climatological normal. Examination of the CFS-OMFs shows poor skill of the model in capturing the observed rainfall and circulation anomalies during weak monsoons. The present analysis suggests that deficiencies in realistically capturing the ocean-atmosphere coupling in the tropical Indian Ocean (IO) introduces biases in simulating sea surface temperature and rainfall anomalies in the equatorial region, which in turn affects the monsoon precipitation forecasts over the sub-continent. In particular, the mean thermocline in the near-equatorial IO is found to be practically flat in the CFS model, so that the near-equatorial anomalies in the model are not strong enough to weaken the summer monsoon circulation and reduce the monsoon precipitation over India. By examining a 100 year free run of the CFS model, it is seen that moderate monsoon-droughts simulated by the model have weak teleconnections with the equatorial IO dynamics. On the other hand, intense monsoon-droughts in the CFS-model are found be remarkably linked with the equatorial IO anomalies. It is suggested that improving the slope of the equatorial IO thermocline and allowing for more realistic IO-monsoon coupling in the CFS-model would be an important step for improving the skill of extended-range monsoon forecasts. Copyright © 2012 Royal Meteorological Society

A weakening land–ocean temperature difference, owing to a rapidly warming Indian Ocean, has seen the Indian monsoon trending downward since the 1950s. New research gives hope for a revival in monsoon rainfall as land warming catches up with, and exceeds, ocean warming.

The objective of this study is to examine, based on recently available high resolution satellite and observational data, the evolution and role of sea surface temperature (SST) in influencing the intraseasonal variability of the South China Sea (SCS) summer monsoon (SM). The study focuses on the 30–60 day timescale when the northward propagating anomalies are dominant over the SCS. Composite analysis of the SST maximum events during SCS SM shows that increased SST anomalies over the SCS are significantly influenced by the downward shortwave radiation flux anomalies, with the suppressed surface latent heat flux anomalies supplementing to it. A thermal damping of the positive SST anomalies induces positive upward heat fluxes, which then destabilize the lower atmosphere between 1,000 and 700 hPa. The positive SST anomalies lead the positive precipitation anomalies over the SCS by 10 days, with a significant correlation (r = 0.44) between the SST-precipitation anomalies. The new findings here indicate an ocean-to-atmosphere effect over the SCS, where underlying SST anomalies tend to form a favorable condition for convective activity and sustain enhanced precipitation during the SCS SM. It is also argued, based on our observations, that the negative sea level pressure anomalies induced by the positive SST anomalies play a role in enhancing the northward propagation of the intraseasonal anomalies over the SCS.

dans commentaires/nouvelles; International audience

International audience; There are large uncertainties looming over the status and fate of the South Asian summer monsoon, with several studies debating whether the monsoon is weakening or strengthening in a changing climate. Our analysis using multiple observed datasets demonstrates a significant weakening trend in summer rainfall during 1901–2012 over the central-east and northern regions of India, along the Ganges-Brahmaputra-Meghna basins and the Himalayan foothills, where agriculture is still largely rain-fed. Earlier studies have suggested an increase in moisture availability and land-sea thermal gradient in the tropics due to anthropogenic warming, favouring an increase in tropical rainfall. Here we show that the land-sea thermal gradient over South Asia has been decreasing, due to rapid warming in the Indian Ocean and a relatively subdued warming over the subcontinent. Using long-term observations and coupled model experiments, we provide compelling evidence that the enhanced Indian Ocean warming potentially weakens the land-sea thermal contrast, dampens the summer monsoon Hadley circulation, and thereby reduces the rainfall over parts of South Asia.

International audience; The SST-precipitation relationship in the intraseasonal variability (ISV) over the Asian monsoon region is examined using recent high quality satellite data and simulations from a state of the art coupled model, the climate forecast system version 2 (CFSv2). CFSv2 demonstrates high skill in reproducing the spatial distribution of the observed climatological mean summer monsoon precipitation along with its interannual variability, a task which has been a conundrum for many recent climate coupled models. The model also exhibits reasonable skill in simulating coherent northward propagating monsoon intraseasonal anomalies including SST and precipitation, which are generally consistent with observed ISV characteristics. Results from the observations and the model establish the existence of spatial variability in the atmospheric convective response to SST anomalies, over the Asian monsoon domain on intraseasonal timescales. The response is fast over the Arabian Sea, where precipitation lags SST by ~5 days; whereas it is slow over the Bay of Bengal and South China Sea, with a lag of ~12 days. The intraseasonal SST anomalies result in a similar atmospheric response across the basins, which consists of a destabilization of the bottom of the atmospheric column, as observed from the equivalent potential temperature anomalies near the surface. However, the presence of a relatively strong surface convergence over the Arabian Sea, due to the presence of a strong zonal gradient in SST, which accelerates the upward motion of the moist air, results in a relatively faster response in terms of the local precipitation anomalies over the Arabian Sea than over the Bay of Bengal and South China Sea. With respect to the observations, the ocean-atmosphere coupling is well simulated in the model, though with an overestimation of the intraseasonal SST anomalies, leading to an exaggerated SST-precipitation relationship. A detailed examination points to a systematic bias in the thickness of the mixed layer of the ocean model, which needs to be rectified. A too shallow (deep) mixed layer enhances (suppress) the amplitude of the intraseasonal SST anomalies, thereby amplifying (lessening) the ISV and the active-break phases of the monsoon in the model.

The seasonal change in the relationship between El Nino and Indian Ocean dipole (IOD) is examined using the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40), and the twentieth century simulations (20c3m) from the Geophysical Fluid Dynamics Laboratory Coupled Model, version 2.1. It is found that, both in ERA-40 and the model simulations, the correlation between El Nino (Nino3 index) and the eastern part of the IOD (90-110 degrees E; 10 degrees S-equator) is predominantly positive from January to June, and then changes to negative from July to December. Correlation maps of atmospheric and oceanic variables with respect to the Nino3 index are constructed for each season in order to examine the spatial structure of their seasonal response to El Nino. The occurrence of El Nino conditions during January to March induces low-level anti-cyclonic circulation anomalies over the southeastern Indian Ocean, which counteracts the climatological cyclonic circulation in that region. As a result, evaporation decreases and the southeastern Indian Ocean warms up as the El Nino proceeds, and weaken the development of a positive phase of an IOD. This warming of the southeastern Indian Ocean associated with the El Nino does not exist past June because the climatological winds there develop into the monsoon-type flow, enhancing the anomalous circulation over the region. Furthermore, the development of El Nino from July to September induces upwelling in the southeastern Indian Ocean, thereby contributing to further cooling of the region during the summer season. This results in the enhancement of a positive phase of an IOD. Once the climatological circulation shifts from the boreal summer to winter mode, the negative correlation between El Nino and SST of the southeastern Indian Ocean changes back to a positive one.

Monsoon rainfall has profound economic and societal impacts for more than two-thirds of the global population. Here we provide a review on past monsoon changes and their primary drivers, the projected future changes, and key physical processes, and discuss challenges of the present and future modeling and outlooks. Continued global warming and urbanization over the past century has already caused a significant rise in the intensity and frequency of extreme rainfall events in all monsoon regions (high confidence). Observed changes in the mean monsoon rainfall vary by region with significant decadal variations. Northern Hemisphere land monsoon rainfall as a whole declined from 1950 to 1980 and rebounded after the 1980s, due to the competing influences of internal climate variability and radiative forcing from greenhouse gases and aerosol forcing (high confidence); however, it remains a challenge to quantify their relative contributions. The CMIP6 models simulate better global monsoon intensity and precipitation over CMIP5 models, but common biases and large intermodal spreads persist. Nevertheless, there is high confidence that the frequency and intensity of monsoon extreme rainfall events will increase, alongside an increasing risk of drought over some regions. Also, land monsoon rainfall will increase in South Asia and East Asia (high confidence) and northern Africa (medium confidence), decrease in North America, and be unchanged in the Southern Hemisphere. Over the Asian–Australian monsoon region, the rainfall variability is projected to increase on daily to decadal scales. The rainy season will likely be lengthened in the Northern Hemisphere due to late retreat (especially over East Asia), but shortened in the Southern Hemisphere due to delayed onset.