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The mesoscale orography over one of the wettest regions of the world makes the Northeast India (NEI) vulnerable to hydrological disasters while sustaining a biodiversity "hotspot." The monsoon rainy season over the NEI is known to be longer than June–September (JJAS), but an objective definition has been lacking. Understanding the drivers and predictability of rainfall variability over the region is key for sustainable development planning and adaptation to increasing disasters in the backdrop of a warming climate but remained poor due to lack of a working definition of "summer monsoon season" over NEI. Here, using the relationship between rainfall over the region and winds at 850 hPa over North Bay of Bengal (BoB), we provide an objective definition of the monsoon season over NEI and argue that the "summer monsoon rainy season" over the NEI (NEIR) is from May to September (MJJAS). In contrast to a significant negative relationship between JJAS Central India (CI) rainfall and a JJAS El Niño–Southern Oscillation (ENSO) index, the MJJAS rainfall over the NEI has no relationship with MJJAS or JJAS ENSO. Instead, we unravel that (a) the tropical Northwest‐Pacific (TNWP) sea surface temperature (SST), (b) the South Equatorial Indian Ocean Dipole (SEIOD) and (c) the Atlantic Zonal mode (AZM) are potential drivers of the NEIR variability. Using a causal inference algorithm, namely the Peter and Clark Momentary Conditional Independence (PCMCI) method, we show that SEIOD directly influences NEIR while TNWP SST has a two‐way connection with the NEIR. While "internal variability" may be higher over the NEI, significant modulation of the variances of the subseasonal fluctuations by predictable drivers like the Atlantic Niño and North Atlantic water temperature provides optimism for seasonal prediction of the NEIR. [ABSTRACT FROM AUTHOR]

The significant multi-decadal mode (MDM) of the Indian summer monsoon rainfall (ISMR) during the past two millennia provides a basis for decadal predictability of the ISMR and has a strong association with the North-Atlantic (NA) variability with the Atlantic Multi-decadal Oscillation (AMO) as a potential external driver. It is also known that the annual cycles and interannual variability of ISMR and sea surface temperatures (SST) over the tropical Indian Ocean (IO) are strongly coupled. However, the role of local air–sea interactions in maintaining or modifying the ISMR MDM remains unknown. A related puzzle we identify is that the IO SST has an increasing trend during two opposite phases of the ISMR MDM, namely during an increasing phase of ISMR (1901–1957) as well as a decreasing phase of ISMR (1958–2007). Here, using a twentieth-century reanalysis (20CR), we examine the role of air-sea interactions in maintaining two opposite phases of the ISMR MDM and unravel that the Bjerknes feedback is at the heart of maintaining the ISMR MDM but cannot explain the increasing trend of SST in the tropical IO during the opposite phases. Large-scale low-level vorticity influence on SST and net heat flux changes through circulation and cloudiness changes associated with the two phases of the ISMR MDM together contribute to the SST trends. The decreasing trend of low-level wind convergence during the period between 1958 and 2007 is a determining factor for the decreasing trend of ISMR in the backdrop of an increasing trend of atmospheric moisture content. Consistent with the lead of the AMO with respect to ISMR by about a decade, the AMO drives the transition from one phase of ISMR MDM to another by changing its phase first and setting up low-level equatorial zonal winds conducive for the transition. [ABSTRACT FROM AUTHOR]

Skillful prediction of the Indian summer monsoon rainfall (ISMR) at leads of 12–24 months are valuable for farmers and policymakers for water resource management and food security planning. While the ISMR is known to be highly predictable at short leads, estimates of long‐lead "potential skill" is lacking. Here, a new predictor discovery method taking into account simultaneous contributions from all potential drivers unravels a predictor based on the depth of the 20° isotherm (D20) to be best suited for estimating the "potential skill" significantly better than a sea surface temperature (SST)‐based predictor. We find high "potential skills" at 18–24‐months leads instead of at short leads, with the highest skill for 18‐months‐lead forecasts (r = 0.87). Investigation of the intriguing finding reveals that the initial errors for ISMR prediction as well as their growth are controlled by a global manifestation of the El Niño–Southern Oscillation (ENSO) oscillator. Phase‐locking of initial errors of D20 and their growth rates with the annual cycle ascertain that forecast errors are minimum and "potential skill" is maximum at leads of 18–24 months. While non‐linearity of small‐scale D20 anomalies may make realization of the potential predictability challenging, with improvements of coupled models and use of deep‐learning artificial‐intelligence techniques, our findings provide optimism for skillful long‐lead forecasts of ISMR in coming years. [ABSTRACT FROM AUTHOR]

While the El Niño-Southern Oscillation and Indian Summer Monsoon Rainfall (ISMR) relationship is weak in recent years, a strong correlation between May Southern Annular Mode Index (SAMI) and June–July (JJ) ISMR is a southern hemispheric source of ISMR predictability. Here, using observed and reanalysis data, we find that the SAMI–ISMR relationship is non-stationary with a potential multi-decadal variability. Both during high/low correlation periods (1980–2010)/(1949–1979), a Southern Indian Ocean Dipole (SIOD) pattern of JJ sea surface temperature anomaly is found to reverse sign during strong and weak SAMI years. The changes in the strength and location of the northern pole of SIOD during the two time blocks are consistent with corresponding changes in the cross equatorial flow and monsoon south-westerlies together with change in SAMI–ISMR correlations. Our analysis indicates teleconnection pathways through which the Atlantic Multidecadal Oscillation (AMO) may be responsible for the multi-decadal swings of SAMI–ISMR correlations through modulation of the SIOD. [ABSTRACT FROM AUTHOR]

Systematic biases in simulation of the mean and variability of Indian summer monsoon rainfall (ISMR) and its teleconnection with the El Nino and Southern Oscillation (ENSO) by climate models have proven to be roadblocks for improving the seasonal prediction skill of the ISMR. Yet, the improvements of these biases in simulating the ISMR by coupled ocean–atmosphere general circulation models (CGCMs) have been slow. Here, we investigate the progress made by the latest CMIP6 models in simulating the mean and variability of the ISMR including its multi-decadal variability in comparison to the earlier CMIP3 and CMIP5 models and unravel key common and persisting biases. That the number of models simulating the pattern of climatological mean summer rainfall over the region with fidelity has increased from less than 10% in CMIP3 to more than 50% in CMIP6 is a notable progress. The CMIP6 models also indicate notable progress in simulating the inter-annual, multi-decadal variability and marginal improvement in simulating the ENSO-ISMR correlations. In addition to consolidating these advances in simulating the ISMR in more climate models, future developments must focus on improving the following three persisting biases namely; (1) most models, including those in CMIP6, tend to simulate the mean location of the continental ITCZ during June–September (JJAS) about 10° south of the observed location of ~ 22° N, (2) with the ensemble mean 21-year moving correlation between ISMR and JJAS mean Nino3.4 sea surface temperature for all models being ~ − 0.3 compared to observed ~ − 0.65, almost all models simulate significantly weaker ENSO-monsoon relationship and (3) the number of models simulating the observed variance and periodicity of the multi-decadal variability of ISMR remains small even in CMIP6. We argue that the position bias in simulating the continental ITCZ may be related to the large and significant biases in simulating the JJAS SST over the tropical Indian Ocean, persistent even in the best of CMIP6 CGCMs making the improvement of SST biases (and associated heat transport across the equator) another area where future model developments need to focus. [ABSTRACT FROM AUTHOR]

How the Indian summer monsoon rainfall (ISMR) would change in future is of broader scientific interest and critical for adaptation to climate change and sustainable development for the vulnerable population of the region. An Emergent Constraint (EC), to correct the projections of ISMR by the Coupled Model Inter‐comparison Project‐6 (CMIP6) models for systematic model biases is urgently needed but has been lacking. Founded on an observed association between the multi‐decadal variability (MDV) of ISMR and North Atlantic (NA) sea surface temperature (SST), here we unravel a strong correlation between future changes in ISMR and biases in simulating the present‐day ISMR MDV. The new emergent constraint renders a 32% reduction in the multi‐model ensemble mean of projected ISMR increase, making the corrected future ISMR change (3.64 ± 2.5) %/K. The estimate based on this EC is robust and more reliable than previous estimates for basing policy interventions toward adaptation and mitigation. Plain Language Summary: Reliability of projections of ISMR to future, critical for developing policy for adaptation to climate change and sustainable development of the vulnerable population of the region is undermined by their biases in simulating the present climate. We unravel that the projections of ISMR by the models are uniquely related to biases in simulating the MDV of ISMR and associated north Atlantic SST. This present‐future relationship or emergent constraint allows us to correct the projections for model biases and make them more reliable. The confidence in the bias‐corrected ISMR change in the future is derived from the fact that the observed ISMR change during the historical period is close to this estimate indicating it to be a more fundamental property of the Indian monsoon system. Key Points: A new emergent constraint (EC) for projections of ISMR by the CMIP6 models is unraveledA present‐day association between ISMR MDV with NA SST in models is correlated with projected ISMR changesThe uncorrected ensemble mean projected ISMR change of 5.4%/K is corrected to 3.64%/K by the EC [ABSTRACT FROM AUTHOR]

A robust estimate of the ENSO-Indian summer monsoon rainfall (ISMR) relationship in a changing climate is critically important for projection of the ISMR predictability. In this study, we show that the increasing nonlinear trend of ISMR and global sea surface temperatures (SST) associated with the trend of the global warming mode leads to a 'long-term' component to the ENSO-ISMR relationship together with a 'short-range' component associated with the ENSO mode. Using historical and projected simulations by some state-of-the-art CMIP5 models, we separate the global warming mode from other oscillatory modes including the ENSO mode through a combined empirical orthogonal function (CEOF) analysis, supported by a signal-to-noise maximizing EOF analysis. We find that the 'short-term' ENSO-ISMR relationship, represented by significant negative correlation between JJAS NINO3.4 SST and ISMR does not change appreciably with increase in green-house gas (GHG) forcing while the 'long-term' relationship changes from weak to significantly positive. We demonstrate that in a warming environment, the global warming mode must be taken into account together with the 'natural' ENSO mode in order to predict ISMR with confidence and emphasize that predictability of ISMR at any given time must be reassessed taking into account contributions from both short and long-term ENSO-ISMR relationships. [ABSTRACT FROM AUTHOR]

A better understanding of the drivers and teleconnection mechanisms responsible for the multi decadal mode (MDM) of variability of the Indian summer monsoon rainfall (ISMR) with major socio-economic impacts in the region through clustering of large-scale floods or droughts is key to improving the poor simulation of ISMR MDM by most climate models. Here, using the longest instrumental record of ISMR available (1813–2006) and longest atmospheric and oceanic re-analyses, the global four dimensional (space–time) structures of atmospheric and oceanic fields of the multi-decadal mode of ISMR and sub-seasonal evolution of the teleconnection mechanism are brought out, essential for understanding underlying drivers but lacking so far. The relationships between the spatial structure of winds, Sea Surface Temperature (SST) and thermocline depth with the ISMR MDM indicate that the tropical ocean over the Indo-Pacific domain is passive responding primarily to the surface winds associated with the mode. A close association between the Atlantic Meridional Overturning Circulation (AMOC), north Atlantic (NA) SST, NA sea surface salinity (SSS) and the ISMR MDM indicate a slow oceanic pathway linking NA SST and the ISMR. In addition to strong correlation (~ 0.9) between global spatial patterns of JJAS SST associated with the MDMs of ISMR, NA SST and AMOC, strong temporal coherence (correlations ~ 0.9) between them is suggestive of regulation of the ISMR MDM (T ~ 65-years) by the NA SST associated with the Atlantic Multidecadal Oscillation (AMO) through a 'fast' atmospheric bridge. On a seasonal time scale, the atmospheric bridge manifests in the form of a stationary Rossby wave train generated by an anticyclonic (cyclonic) barotropic vorticity located above positive (negative) SST anomaly over NA in two phases of the AMO. That the AMO SST is the driver of the ISMR MDM is further supported when we unravel the sub-seasonal face of the teleconnection between the two. We show that phase locking of active (break) spells with annual cycle during positive (negative) phases of the ISMR MDM are forced by a similar phase locking of barotropic anticyclonic (cyclonic) vorticity over the NA SST with the annual cycle through the generation of a quasi-stationary Rossby wave train with an anticyclonic (cyclonic) vorticity at upper level over the Indian region with the NA columnar vorticity leading Indian monsoon rainfall by about a week. Our findings provide a basis for enhanced predictability of tropical climate through slow modulation by extra-tropical SST. [ABSTRACT FROM AUTHOR]

Eurasian snow is one of the slowly varying boundary forcings known to have significant influences on the mean and variability of the Indian summer monsoon rainfall (ISMR). A multilayer complex snow scheme, incorporated into the state‐of‐the‐art coupled Climate Forecast System version 2 (CFSv2) showed significant improvements in the simulation of mean ISMR, snow, and Northern Hemisphere surface and tropospheric temperature. Here we show that a realistic simulation of high‐latitude snow decreases the north–south temperature gradient, which in turn decreases the meridional transport of energy from the Equator to the Pole, consequently affecting the tropical sea surface temperature (SST) and air–sea interactions. The global teleconnections of the ISMR with SST and 2 m temperature over land are also improved considerably in association with improved simulation of the oceanic natural modes of variability. Our findings provide new insights for the relationship between the winter Eurasian snow and the following ISMR, namely that the same relationship may be understood through a framework of meridional atmospheric energy transport and its effects on the tropical air–sea interactions. The improvements in the global teleconnection in the modified version of CFSv2 may have implications in the ISMR predictability and prediction skill. [ABSTRACT FROM AUTHOR]

The high propensity of deficient monsoon rainfall over the Indian sub-continent in the recent 3 decades (seven deficient monsoons against 3 excess monsoon years) compared to the prior 3 decades has serious implications on the food and water resources in the country. Motivated by the need to understand the high occurrence of deficient monsoon during this period, we examine the change in predictability of the Indian summer monsoon (ISM) and its teleconnections with Indo-Pacific sea surface temperatures between the two periods. The shift in the tropical climate in the late 1970s appears to be one of the major reasons behind this. We find an increased predictability of the ISM in the recent 3 decades owing to reduced 'internal' interannual variability (IAV) due to the high-frequency modes, while the 'external' IAV arising from the low-frequency modes has remained largely the same. The Indian Ocean Dipole–ISM teleconnection has become positive during the monsoon season in the recent period thereby compensating for the weakened ENSO–ISM teleconnection. The central Pacific El-Niño and the Indian Ocean (IO) warming during the recent 3 decades are working together to realise enhanced ascending motion in the equatorial IO between 70°E and 100°E, preconditioning the Indian monsoon system prone to a deficient state. [ABSTRACT FROM AUTHOR]

Skillful prediction of the "active" and "break" spells of monsoon intraseasonal oscillations during the South Asian monsoon season is crucial for the socio-economic fate of one-sixth of the world's population, yet it remains a grand challenge problem. The limited skill of our coupled weather and climate models is largely due to our inability to represent the complex multiscale interactions of the north Indian Ocean and the atmosphere. Air-sea interactions are at the heart of not only the climatological mean annual cycle of the South Asian monsoon but also its synoptic, subseasonal, interannual, and decadal variability. With high local monsoon precipitation and discharge from major rivers (Ganges-Brahmaputra, Irrawaddy), the Bay of Bengal (BoB) exhibits the lowest surface salinities in the tropics as well as unique thermal stratification, making it a natural laboratory for studying multiscale interactions ranging from planetary-scale monsoons to submesoscale mixing in freshwater pools. The current ocean component of coupled models is inadequate for simulating the BoB's upper-ocean thermal structure with fidelity. To further improve monsoon forecasts on intraseasonal and interannual time scales, we need new high-resolution and highfrequency observations over the BoB to fill the gap in our understanding of how the ocean mixes in highly fresh regions, and we need modeling of processes that will convert this understanding to parameterizations of mixing that can be used to improve large-scale ocean models. [ABSTRACT FROM AUTHOR]

Based on extensive analysis of observations and a series of climate model experiments, here we establish that slow variations of northern hemispheric extratropical sea-surface temperature (SST) anomalies can augment seasonal predictability of the south Asian monsoon. The SST conditions and performance of the south Asian monsoon during 2013 boreal summer months (June-September) led us to hypothesize that the strong extratropical SST anomalies in the North Pacific and North Atlantic in conjunction with weak tropical SST anomalies (weak La Niña) were responsible for the above-normal rainfall over India during 2013. We also argue that the 2013 SST pattern and above-normal monsoon condition are not unique but occurred on several occasions in the past. Further, we show that there is a complementary pattern of strong extratropical SST and weak tropical SST that is associated with below-normal south Asian monsoon rainfall. We also show that the extratropical SST pattern in the Northern Hemisphere is associated with a low-frequency interdecadal mode of variability indicating potential predictability associated with such extratropical SST forcing. Extensive experiments with an atmospheric general circulation model forced by such SST conditions elucidate the mechanism through which the extratropical SSTs influence the Indian monsoon. The SST anomalies affect the north-south temperature gradient and lead to a local displacement of the jet stream, setting up a quasi-stationary wave. Such a stationary wave, in turn, affects the tropospheric temperature (TT) over southern Eurasia, influencing the north-south TT gradient in the region and thereby the Indian monsoon. Our discovery of this additional source of potential predictability together with the fact that the new-generation coupled ocean-atmosphere models are capable of predicting the extratropical SST anomalies brightens the prospect of south Asian monsoon prediction. [ABSTRACT FROM AUTHOR]

Impact of bias correction of sea surface temperature (SST) forecast on extended range (ER, ∼3-4 weeks) prediction skill is studied using the bias-corrected forecasted SST from Climate Forecast System version 2 (CFSv2) as the boundary condition for running the Global Forecast System version 2 (GFSv2) model. Potential predictability limit is comparable (∼16 days) for both bias-corrected GFSv2 ( GFSv2bc) and CFSv2. Prediction skills of active and break spells and of low-frequency monsoon intraseasonal oscillations is higher for GFSv2bc at all lead pentads. Although initially same, predictability error after 14 days grows slightly faster for GFSv2bc compared to CFSv2. Bias correction in SST has minimal impact in short-to-medium range, while substantial influence is felt in ER between 12-18 days. [ABSTRACT FROM AUTHOR]

In spite of strong mean summer monsoon winds, the magnitudes of diurnal and intraseasonal oscillations (ISO) of the sea surface temperature (SST) in the Bay of Bengal (BoB) are as strong as the respective magnitudes in the western Pacific. Using continuous observations during the peak summer monsoon of 1998 at BoB buoy (DS4) located at (89^\circ\ \E, 19^ \circ\ \N), we show that the strong near-surface diurnal variation in the BoB during warming phases of the ISO leads to almost double the magnitude of the diurnal SST over the BoB as compared to that during the cooling phases. The simulation experiments with and without the diurnal cycle of surface fluxes indicate that more than one-third of the observed SST ISO amplitude could arise from the rectification of the diurnal cycle through the influence of late night and early daytime upper-ocean mixing processes during the warming phases. The rapid shoaling of the upper-ocean mixed layer occurs during afternoon while it deepens slowly during late night and early daytime which tends to retain the warm SSTs at the end of the nighttime cooling. The insight derived from these experiments on the influence of the diurnal cycle on ISOs of the SST underlines the need for a proper simulation of the diurnal cycle of the SST in climate models. [ABSTRACT FROM PUBLISHER]

While many of the previous positive Indian Ocean dipole (IOD) years were associated with above (below)-normal monsoon rainfall over central (southern) India during summer monsoon months [June-September (JJAS)], the IOD event in 2008 is associated with below (above)-normal rainfall in many parts of central (southern peninsular) India. Because understanding such regional organization is a key for success in regional prediction, using different datasets and atmospheric model simulations, the reasons for this abnormal behavior of the monsoon in 2008 are explored. Compared to normal positive IOD events, sea surface temperature (SST) and rainfall in the southern tropical Indian Ocean (STIO) in JJAS 2008 were abnormally high. Downwelling Rossby waves and oceanic heat advection played an important role in warming SST abnormally in the STIO. It was also found that the combined influence of a linear warming trend in the tropical Indian Ocean and warming associated with the IOD have resulted in abnormal warming of the STIO. This abnormal SST warming resulted in enhancement of convection in the southwest tropical Indian Ocean and forced anticyclonic circulation anomalies over the Bay of Bengal and central India, leading to suppressed rainfall over this region in JJAS 2008. The above mechanism is tested by conducting several model sensitivity experiments with an atmospheric general circulation model (AGCM). These experiments confirmed that the subsidence over central India and the Bay of Bengal was forced mainly by the anomalous warming in the STIO region driven by coupled ocean-atmosphere processes. This study provides the first evidence of combined Indian Ocean warming, associated with global warming, and IOD-related warming influence on Indian summer monsoon rainfall. The combined influence may force below-normal rainfall over central India by inducing strong convection in the STIO region. The conventional seesaw in convection between the Indian subcontinent and the eastern equatorial Indian Ocean may shift to the central equatorial Indian Ocean and the Bay of Bengal if the central Indian Ocean consistently warms in the global warming scenario. [ABSTRACT FROM AUTHOR]

New satellite and in situ observations show large intraseasonal (10–60 day) variability of surface winds and upper-ocean current in the equatorial Indian Ocean, particularly in the east. An ocean model forced by the Quick Scatterometer (QuikSCAT) wind stress is used to study the dynamics of the intraseasonal zonal current. The model has realistic upper-ocean currents and thermocline depth variabilities on intraseasonal to interannual scales. The quality of the simulation is directly attributed to the accuracy of the wind forcing. At the equator, moderate westerly winds are punctuated by strong 10–40-day westerly wind bursts. The wind bursts force swift, intraseasonal (20–50 day) eastward equatorial jets in spring, summer, and fall. The zonal momentum balance is between local acceleration, stress, and pressure, while nonlinearity deepens and strengthens the eastward current. The westward pressure force associated with the thermocline deepening toward the east rapidly arrests eastward jets and, subsequently, generates (weak) westward flow. Thus, in accord with direct observations in the east, the spring jet is a single intraseasonal event, there are intraseasonal jets in summer, and the fall jet is long lived but strongly modulated on an intraseasonal scale. The zonal pressure force is almost always westward in the upper 120 m, and changes sign twice a year in the 120–200-m layer. Transient eastward equatorial undercurrents in early spring and late summer are associated with semiannual Rossby waves generated at the eastern boundary following thermocline deepening by the spring and fall jets. An easterly wind stress is not necessary to generate the undercurrents. Experiments with a single westerly wind burst forcing show that apart from the intraseasonal response, the zonal pressure force and current in the east have an intrinsic 90-day time scale that arises purely from equatorial adjustment. [ABSTRACT FROM AUTHOR]