Unraveling the Mystery of Indian Monsoon Failure During El Nino

Spatial diversity of atmospheric moisture transport and climate teleconnections over Indian subcontinent at different timescales

Regional weather and climate are generally impacted by global climatic phenomenon's. Understanding the impact of global climate phenomenon's on an atmospheric branch of the hydrological cycle is crucial to make advances in skillful precipitation forecast. The present study adopts a multiscale approach based on wavelets for unravelling the linkages between teleconnections and atmospheric moisture transport over homogeneous regions of Indian sub-continent. We investigated linkages between atmospheric moisture transport quantified as monthly integrated water vapor transport (IVT) during 1951-2022 over selected homogeneous regions and eight large scale climate oscillations using wavelet and global wavelet coherence. Our results indicate significant heterogeneity in linkages across different regions and across multiple timescales. In particular, the Indian Ocean Dipole (IOD) influence monthly IVT at intra-annual to inter-annual scale over all regions. The El Niño-Southern Oscillation (ENSO) have strong connection to monthly IVT at inter-annual scale whereas over west central region both IOD and ENSO strongly influence IVT at inter-decadal scale. While the Atlantic Multi-Decadal Oscillation and Pacific Decadal Oscillation have an impact on IVT in the north-east and southern regions, the Arctic Oscillation and North Atlantic oscillation have a strong inter-annual connection to IVT, majorly in the northwest and hilly regions. Overall, the methodology offers an effective approach for capturing the dynamics of atmospheric moisture transport in time-frequency space and provide a practical reference for prediction of atmospheric moisture transport linked precipitation over different regions of Indian subcontinent.

Amplified drying in South Asian summer monsoon precipitation due to anthropogenic sulfate aerosols

A declining trend in Indian summer monsoon precipitation (ISMP) in the latter half of the 20th century is a scientifically challenging and societally relevant research issue. Heavy aerosol loading over India is one of the key factors in modulating the ISMP. Using the state-of-the-state-of-the-art chemistry-climate model, ECHAM6-HAMMOZ, the impacts of South Asian anthropogenic sulfate aerosols on the Indian summer monsoon precipitation were investigated against: (1) 2010 La Niña (excess monsoon), (2) 2015 El Niño (deficit monsoon) in comparison to (3) normal monsoon 2016. Sensitivity simulations were designed with 48% enhancement in South Asian SO2 emissions based on a trend estimated from Ozone Monitoring Instrument (OMI) satellite observations during 2006-2017. The model simulations showed that sulfate aerosols reduce ISMP by 27.5%-43.3 %, while simulations without sulfate loading enhanced ISMP by 23% in 2010 La Niña and reduction by 35% in 2015 El Niño. This paper reports that sulfate aerosols loading over India reduce precipitation by aerosol-induced direct and indirect effects by inducing atmospheric cooling, weakening in the convection, and reduction in moisture transport to Indian landmass. This paper emphasizes the necessity of alternate use of energy to reduce sulfate aerosol emissions to solve water issues in South Asia.

Artificial intelligence predicts normal summer monsoon rainfall for India in 2023

Inaccuracy in the All Indian Summer Monsoon Rainfall (AISMR) forecast has major repercussions for India's economy and people's daily lives. Improving the accuracy of AISMR forecasts remains a challenge. An attempt is made here to address this problem by taking advantage of recent advances in machine learning techniques. The data-driven models trained with historical AISMR data, the Niño3.4 index, and categorical Indian Ocean Dipole values outperform the traditional physical models, and the best-performing model predicts that the 2023 AISMR will be roughly 790 mm, which is typical of a normal monsoon year.

Propagation pathways of Indo-Pacific rainfall extremes are modulated by Pacific sea surface temperatures

Intraseasonal variation of rainfall extremes within boreal summer in the Indo-Pacific region is driven by the Boreal Summer Intraseasonal Oscillation (BSISO), a quasi-periodic north-eastward movement of convective precipitation from the Indian Ocean to the Western Pacific. Predicting the spatiotemporal location of the BSISO is essential for subseasonal prediction of rainfall extremes but still remains a major challenge due to insufficient understanding of its propagation pathway. Here, using unsupervised machine learning, we characterize how rainfall extremes travel within the region and reveal three distinct propagation modes: north-eastward, eastward-blocked, and quasi-stationary. We show that Pacific sea surface temperatures modulate BSISO propagation - with El Niño-like (La Niña-like) conditions favoring quasi-stationary (eastward-blocked) modes-by changing the background moist static energy via local overturning circulations. Finally, we demonstrate the potential for early warning of rainfall extremes in the region up to four weeks in advance.

The changing relationship between Cholera and interannual climate variables in Kolkata over the past century

BACKGROUND

In the Bengal Delta, research has shown that climate and cholera are linked. One demonstration of this is the relationship between interannual ocean-atmospheric oscillations such as the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). What remains unclear in the present literature is the nature of this relationship in the specific context of Kolkata, and how this relationship may have changed over time.

RESULTS

In this study, we analyse the changing relationship between ENSO and IOD with cholera in Kolkata over recent (1999-2019) and historical (1897-1941) time intervals. Wavelet coherence analysis revealed significant non-stationary association at 2-4 year and 4-8 year periods between cholera and both interannual timeseries during both time intervals. However, coherence was notably weakened in the recent interval, particularly with regards to ENSO, a result supported by a complementary SARIMA analysis. Similar coherence patterns with temperature indicate it could be an important mediating factor in the relationship between cholera and oscillating climate phenomena in Kolkata.

CONCLUSIONS

This study reveals a shifting relationship between cholera and climate variables (ENSO and IOD) in Kolkata, suggesting a decoupling between environmental influences and cholera transmission in recent years. Our results therefore do not suggest that an intensification of ENSO is likely to significantly influence cholera in the region. We also find that the relationship between cholera and interannual climate variables is distinct to Kolkata, highlighting the spatial heterogeneity of the climate-cholera relationship even within the Bengal Delta.

The Western Himalayan fir tree ring record of soil moisture in Pakistan since 1855

Data on historical soil moisture is crucial for assessing and responding to droughts that commonly occur in climate change-affected countries. The Himalayan temperate forests in Pakistan are particularly at risk of climate change. Developing nations lack the means to gather surface soil moisture (SSM) information. Tree rings are one way to bridge this gap. Here, we employed dendrochronological methods on climate-sensitive tree rings from Abies pindrow to reconstruct the SSM in the Western Himalayan mountain region of Pakistan from 1855 to 2020. December (r = 0.41), May (r = 0.40), and June (r = 0.65) SSMs were found to be the limiting factors for A. pindrow growth. However, only the June SSM showed reconstruction possibility (coefficient of efficiency = 0.201 and reduction of error = 0.325). Over the studied period, we found 6 years (wet year) when June SSM was above the threshold of 32.04 (mean + 2 δ) and 1 year (dry year) when June SSM was below the threshold of 21.28 (mean - 2 δ). It was revealed that 1921 and 1917 were the driest and wettest SSM of all time, with means of 19.34 and 36.49, respectively. Our study shows that winter soil moisture is critical for the growing season in the context of climate change. Climate change has broad impacts on tree growth in the Western Himalayas. This study will assist various stakeholders in understanding and managing local and regional climate change.

The COVID-19 lockdown: a unique perspective into heterogeneous impacts of transboundary pollution on snow and ice darkening across the Himalayas

The Tibetan Plateau holds the largest mass of snow and ice outside of the polar regions. The deposition of light-absorbing particles (LAPs) including mineral dust, black carbon and organic carbon and the resulting positive radiative forcing on snow (RFSLAPs) substantially contributes to glacier retreat. Yet how anthropogenic pollutant emissions affect Himalayan RFSLAPs through transboundary transport is currently not well known. The COVID-19 lockdown, resulting in a dramatic decline in human activities, offers a unique test to understand the transboundary mechanisms of RFSLAPs. This study employs multiple satellite data from the moderate resolution imaging spectroradiometer and ozone monitoring instrument, as well as a coupled atmosphere-chemistry-snow model, to reveal the high spatial heterogeneities in anthropogenic emissions-induced RFSLAPs across the Himalaya during the Indian lockdown in 2020. Our results show that the reduced anthropogenic pollutant emissions during the Indian lockdown were responsible for 71.6% of the reduction in RFSLAPs on the Himalaya in April 2020 compared to the same period in 2019. The contributions of the Indian lockdown-induced human emission reduction to the RFSLAPs decrease in the western, central, and eastern Himalayas were 46.8%, 81.1%, and 110.5%, respectively. The reduced RFSLAPs might have led to 27 Mt reduction in ice and snow melt over the Himalaya in April 2020. Our findings allude to the potential for mitigating rapid glacial threats by reducing anthropogenic pollutant emissions from economic activities.

Recent Advances in Understanding Multi-scale Climate Variability of the Asian Monsoon

Studies of the multi-scale climate variability of the Asian monsoon are essential to an advanced understanding of the physical processes of the global climate system. In this paper, the progress achieved in this field is systematically reviewed, with a focus on the past several years. The achievements are summarized into the following topics: (1) the onset of the South China Sea summer monsoon; (2) the East Asian summer monsoon; (3) the East Asian winter monsoon; and (4) the Indian summer monsoon. Specifically, new results are highlighted, including the advanced or delayed local monsoon onset tending to be synchronized over the Arabian Sea, Bay of Bengal, Indochina Peninsula, and South China Sea; the basic features of the record-breaking mei-yu in 2020, which have been extensively investigated with an emphasis on the role of multi-scale processes; the recovery of the East Asian winter monsoon intensity after the early 2000s in the presence of continuing greenhouse gas emissions, which is believed to have been dominated by internal climate variability (mostly the Arctic Oscillation); and the accelerated warming over South Asia, which exceeded the tropical Indian Ocean warming, is considered to be the main driver of the Indian summer monsoon rainfall recovery since 1999. A brief summary is provided in the final section along with some further discussion on future research directions regarding our understanding of the Asian monsoon variability.

A predictable prospect of the South Asian summer monsoon

Prediction of the South Asian summer monsoon (SASM) has remained a challenge for both scientific research and operational climate prediction for decades. By identifying two dominant modes of the SASM, here we show that the unsatisfactory prediction may be due to the fact that the existing SASM indices are mostly related to the less predictable second mode. The first mode, in fact, is highly predictable. It is physically linked to the variation of the Indian monsoon trough coupled with large rainfall anomalies over core monsoon zone and the northern Bay of Bengal. An index is constructed as a physical proxy of this first mode, which can be well predicted one season in advance, with an overall skill of 0.698 for 1979-2020. This result suggests a predictable prospect of the SASM, and we recommend the new index for real-time monitoring and prediction of the SASM.

Emergence of changing Central-Pacific and Eastern-Pacific El Niño-Southern Oscillation in a warming climate

El Niño-Southern Oscillation (ENSO) features strong warm events in the eastern equatorial Pacific (EP), or mild warm and strong cold events in the central Pacific (CP), with distinct impacts on global climates. Under transient greenhouse warming, models project increased sea surface temperature (SST) variability of both ENSO regimes, but the timing of emergence out of internal variability remains unknown for either regime. Here we find increased EP-ENSO SST variability emerging by around 2030 ± 6, more than a decade earlier than that of CP-ENSO, and approximately four decades earlier than that previously suggested without separating the two regimes. The earlier EP-ENSO emergence results from a stronger increase in EP-ENSO rainfall response, which boosts the signal of increased SST variability, and is enhanced by ENSO non-linear atmospheric feedback. Thus, increased ENSO SST variability under greenhouse warming is likely to emerge first in the eastern than central Pacific, and decades earlier than previously anticipated.

Protracted Indian monsoon droughts of the past millennium and their societal impacts

Protracted droughts lasting years to decades constitute severe threats to human welfare across the Indian subcontinent. Such events are, however, rare during the instrumental period (ca. since 1871 CE). In contrast, the historic documentary evidence indicates the repeated occurrences of protracted droughts in the region during the preinstrumental period implying that either the instrumental observations underestimate the full spectrum of monsoon variability or the historic accounts overestimate the severity and duration of the past droughts. Here we present a temporally precise speleothem-based oxygen isotope reconstruction of the Indian summer monsoon precipitation variability from Mawmluh cave located in northeast India. Our data reveal that protracted droughts, embedded within multidecadal intervals of reduced monsoon rainfall, frequently occurred over the past millennium. These extreme events are in striking temporal synchrony with the historically documented droughts, famines, mass mortality events, and geopolitical changes in the Indian subcontinent. Our findings necessitate reconsideration of the region's current water resources, sustainability, and mitigation policies that discount the possibility of protracted droughts in the future.

Impact of global-scale hydroclimatic patterns on surface water-groundwater interactions in the climatically vulnerable Ganges river delta of the Sundarbans

The global climate patterns like El Niño Southern Oscillation (ENSO) cycle and Indian Ocean Dipole (IOD) have impacts on surface water quality and groundwater recharge patterns. But the ENSO and IOD impacts on surface water-groundwater (SW-GW) interaction in terms of quality have not been studied. Therefore, the present study was conducted to delineate the impacts of ENSO and IOD on the SW-GW interaction process-induced groundwater quality of coastal aquifers of Sundarbans, by the application of isotopic signature, salinity content of groundwater and seawater in relation to rainfall variability. Study results revealed that the declining trend of rainfall potentially increases the seawater salinity. The rainfall pattern also positively correlates with the groundwater level (GWL) at a 5% level of significance observed from the wavelet analysis. The deficit in rainfall due to the El Niño is the possible reason for the declining GWL, which is giving rise to groundwater salinity. El Niño also affected the nearshore seawater salinity which was increased from 19 to 24 ppT. The study provides a surrogate understanding of the potential impact of El Niño in one of the most climatically vulnerable parts of the planet, while IOD impacts are not conclusive. In the scenario of depleted rainfall amount, groundwater abstraction practices need to be managed, otherwise, it could create a potential threat to the available drinking water resources in the present and future climate change scenarios.

Investigation of Forest Fire Activity Changes Over the Central India Domain Using Satellite Observations During 2001-2020

Recurrent and large forest fires negatively impact ecosystem, air quality, and human health. Moderate Resolution Imaging Spectroradiometer fire product is used to identify forest fires over central India domain, an extremely fire prone region. The study finds that from 2001 to 2020, ∼70% of yearly forest fires over the region occurred during March (1,857.5 counts/month) and April (922.8 counts/month). Some years such as 2009, 2012, and 2017 show anomalously high forest fires. The role of persistent warmer temperatures and multiple climate extremes in increasing forest fire activity over central India is comprehensively investigated. Warmer period from 2006 to 2020 showed doubling and tripling of forest fire activity during forest fire (February-June; FMAMJ) and non-fire (July-January; JASONDJ) seasons, respectively. From 2015 JASONDJ to 2018 FMAMJ, central India experienced a severe heatwave, a rare drought and an extremely strong El Niño, the combined effect of which is linked to increased forest fires. Further, the study assesses quinquennial spatiotemporal changes in forest fire characteristics such as fire count density and average fire intensity. Deciduous forests of Jagdalpur-Gadchiroli Range and Indravati National Park in Chhattisgarh state are particularly fire prone (>61 fire counts/grid) during FMAMJ and many forest fires are of high intensity (>45 MW). Statistical associations link high near surface air temperature and low precipitation during FMAMJ to significantly high soil temperature, low soil moisture content, low evapotranspiration and low normalized difference vegetation index. This creates a significantly drier environment, conducive for high forest fire activity in the region.

Spatiotemporal Variation in Rainfall Erosivity and Correlation with the ENSO on the Tibetan Plateau since 1971

Soil erosion is a serious ecological problem in the fragile ecological environment of the Tibetan Plateau (TP). Rainfall erosivity is one of the most important factors controlling soil erosion and is associated with the El Niño southern oscillation (ENSO). However, there is a lack of studies related to the spatial distribution and temporal trends of rainfall erosivity on the TP as a whole. Additionally, the understanding of the general influence of ENSO on rainfall erosivity across the TP remains to be developed. In this study, long-term (1971-2020) daily precipitation data from 91 meteorological stations were selected to calculate rainfall erosivity. The analysis combines co-kriging interpolation, Sen's slope estimator, and the Mann-Kendall trend test to investigate the spatiotemporal patten of rainfall erosivity across the TP. The Oceanic Niño Index (ONI) and multivariate ENSO Index (MEI) were chosen as ENSO phenomenon characterization indices, and the relationship between ENSO and rainfall erosivity was explored by employing a continuous wavelet transform. The results showed that an increasing trend in annual rainfall erosivity was detected on the TP from 1971 to 2020. The seasonal and monthly rainfall erosivity was highly uneven, with the summer erosivity accounting for 60.36%. The heterogeneous spatial distribution of rainfall erosivity was observed with an increasing trend from southeast to northwest. At the regional level, rainfall erosivity in the southeastern TP was mainly featured by a slow increase, while in the northwest was more destabilizing and mostly showed no significant trend. The rainfall erosivity on the whole TP was relatively high during non-ENSO periods and relatively low during El Niño/La Niña periods. It is worth noting that rainfall erosivity in the northwest TP appears to be more serious during the La Niña event. Furthermore, there were obvious resonance cycles between the rainfall erosivity and ENSO in different regions of the plateau, but the cycles had pronounced discrepancies in the occurrence time, direction of action and intensity. These findings contribute to providing references for soil erosion control on the TP and the formulation of future soil conservation strategies.

Decoding the Karakoram Anomaly

The 'Karakoram Anomaly' is termed as the stability or anomalous growth of glaciers in the central Karakoram, in contrast to the retreat of glaciers in other nearby mountainous ranges of Himalayas and other mountainous ranges of the world. It remains an intriguing scientific question to the researchers. An attempt is made to provide mechanisms leading to such a process and thus 'affirming' it. In view of this, meteorological and cryospheric processes, viz., glacial-atmosphere coupled interactions in tandem with temperature-moisture interactions and radiative balance- on glaciated regions are simultaneously argued over the Karakoram and the adjacent Ladakh. Ladakh is deliberately chosen to compare the weaknesses, lacuna and gaps in the observations/reanalyzes- so that similar forcings are investigated over both regions. It is important to mention that both regions are data sparse. Findings show that geographical and elevation positioning of the Karakoram makes its environmental conditions conducive for glacier stability and/or growth which otherwise is not the case in the Ladakh region. Indian winter monsoon, western disturbances (WDs) embedded within upper level subtropical westerly jet moving eastwards, provides higher moisture incursion which in association with lowered lifting condensation level dumps higher moisture/mass over Karakoram than Ladakh. In addition, role of 2 m surface (T2m) and skin temperature (Ts) is one of the leading driving mechanisms. Difference (T2m-Ts) illustrates inversion which provides stable atmosphere leading to dump all the available moisture/mass over Karakoram, which is contrary over Ladakh.

Regional and Local Impacts of the ENSO and IOD Events of 2015 and 2016 on the Indian Summer Monsoon—A Bhutan Case Study

The Indian Summer Monsoon (ISM) plays a vital role in the livelihoods and economy of those living on the Indian subcontinent, including the small, mountainous country of Bhutan. The ISM fluctuates over varying temporal scales and its variability is related to many internal and external factors including the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). In 2015, a Super El Niño occurred in the tropical Pacific alongside a positive IOD in the Indian Ocean and was followed in 2016 by a simultaneous La Niña and negative IOD. These events had worldwide repercussions. However, it is unclear how the ISM was affected during this time, both at a regional scale over the whole ISM area and at a local scale over Bhutan. First, an evaluation of data products comparing ERA5 reanalysis, TRMM and GPM satellite, and GPCC precipitation products against weather station measurements from Bhutan, indicated that ERA5 reanalysis was suitable to investigate ISM change in these two years. The reanalysis datasets showed that there was disruption to the ISM during this period, with a late onset of the monsoon in 2015, a shifted monsoon flow in July 2015 and in August 2016, and a late withdrawal in 2016. However, this resulted in neither a monsoon surplus nor a deficit across both years but instead large spatial-temporal variability. It is possible to attribute some of the regional scale changes to the ENSO and IOD events, but the expected impact of a simultaneous ENSO and IOD events are not recognizable. It is likely that 2015/16 monsoon disruption was driven by a combination of factors alongside ENSO and the IOD, including varying boundary conditions, the Pacific Decadal Oscillation, the Atlantic Multi-decadal Oscillation, and more. At a local scale, the intricate topography and orographic processes ongoing within Bhutan further amplified or dampened the already altered ISM.

Restored relationship between ENSO and Indian summer monsoon rainfall around 1999/2000

El Niño–Southern Oscillation (ENSO) was identified as the dominant predictor for the Indian summer monsoon rainfall (ISMR) in the early 1900s. An apparent weakening of the ENSO–ISMR relationship has been observed since the 1970s. Here, we found a clear restoration of the ENSO–ISMR relationship since 1999/2000. This restoring relationship is closely linked to the interdecadal transition of ENSO evolution and the associated sea surface temperature anomalies (SSTAs) over the tropical Atlantic. During 1979–1997, summer ENSO events mainly continued from the previous winter, which can drive apparent Atlantic Niña SSTAs to offset ENSO's impact on ISMR and weaken the ENSO–ISMR relationship. In contrast, when ENSO events newly emerge from late spring, as they have done more recently during 2000–2018, the associated tropical Atlantic SSTAs are weak and shift to the tropical North Atlantic, which can offset the contribution of Atlantic Niña and reinforce the ENSO–ISMR relationship. We identified that the diversity of ENSO's evolution, continuing from the previous winter or emerging from late spring, is the dominant factor perturbing the ENSO–ISMR relationship in recent epochs, with tropical Atlantic SSTAs as the crucial bridge. This finding should be considered in our efforts to improve ISMR prediction.

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The relationship between ENSO and ISMR has been restoring since 1999/2000

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The transition of ENSO's evolution, continuing or emerging, is the dominant factor

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The response of tropical Atlantic SSTAs to ENSO's evolution are the crucial bridge

Global-scale massive feature extraction from monthly hydroclimatic time series: Statistical characterizations, spatial patterns and hydrological similarity

Hydroclimatic time series analysis focuses on a few feature types (e.g., autocorrelations, trends, extremes), which describe a small portion of the entire information content of the observations. Aiming to exploit a larger part of the available information and, thus, to deliver more reliable results (e.g., in hydroclimatic time series clustering contexts), here we approach hydroclimatic time series analysis differently, i.e., by performing massive feature extraction. In this respect, we develop a big data framework for hydroclimatic variable behaviour characterization. This framework relies on approximately 60 diverse features and is completely automatic (in the sense that it does not depend on the hydroclimatic process at hand). We apply the new framework to characterize mean monthly temperature, total monthly precipitation and mean monthly river flow. The applications are conducted at the global scale by exploiting 40-year-long time series originating from over 13 000 stations. We extract interpretable knowledge on seasonality, trends, autocorrelation, long-range dependence and entropy, and on feature types that are met less frequently. We further compare the examined hydroclimatic variable types in terms of this knowledge and, identify patterns related to the spatial variability of the features. For this latter purpose, we also propose and exploit a hydroclimatic time series clustering methodology. This new methodology is based on Breiman's random forests. The descriptive and exploratory insights gained by the global-scale applications prove the usefulness of the adopted feature compilation in hydroclimatic contexts. Moreover, the spatially coherent patterns characterizing the clusters delivered by the new methodology build confidence in its future exploitation. Given this spatial coherence and the scale-independent nature of the delivered feature values (which makes them particularly useful in forecasting and simulation contexts), we believe that this methodology could also be beneficial within regionalization frameworks, in which knowledge on hydrological similarity is exploited in technical and operative terms.

Interdecadal Variability in Myanmar Rainfall in the Monsoon Season (May–October) Using Eigen Methods

In this study, we investigated the interdecadal variability in monsoon rainfall in the Myanmar region. The gauge-based gridded rainfall dataset of the Global Precipitation Climatology Centre (GPCC) and Climatic Research Unit version TS4.0 (CRU TS4.0) were used (1950–2019) to investigate the interdecadal variability in summer monsoon rainfall using empirical orthogonal function (EOF), singular value decomposition (SVD), and correlation approaches. The results reveal relatively negative rainfall anomalies during the 1980s, 1990s, and 2000s, whereas strong positive rainfall anomalies were identified for the 1970s and 2010s. The dominant spatial variability mode showed a dipole pattern with a total variance of 47%. The power spectra of the principal component (PC) from EOF revealed a significant peak during decadal timescales (20–30 years). The Myanmar summer monsoon rainfall positively correlated with Atlantic multidecadal oscillation (AMO) and negatively correlated with Pacific decadal oscillation (PDO). The results reveal that extreme monsoon rainfall (flood) events occurred during the negative phase of the PDO and below-average rainfall (drought) occurred during the positive phase of the PDO. The cold phase (warm phase) of AMO was generally associated with negative (positive) decadal monsoon rainfall. The first SVD mode indicated the Myanmar rainfall pattern associated with the cold and warm phase of the PDO and AMO, suggesting that enhanced rainfall for about 53% of the square covariance fraction was related to heavy rain over the study region except for the central and eastern parts. The second SVD mode demonstrated warm sea surface temperature (SST) in the eastern equatorial Pacific (El Niño pattern) and cold SST in the North Atlantic Ocean, implying a rainfall deficit of about 33% of the square covariance fraction, which could be associated with dry El Niño conditions (drought). The third SVD revealed that cold SSTs in the central and eastern equatorial Pacific (La Niña pattern) caused enhance rainfall with a 6.7% square covariance fraction related to flood conditions. Thus, the extra-subtropical phenomena may affect the average summer monsoon trends over Myanmar by enhancing the cross-equatorial moisture trajectories into the North Atlantic Ocean.

Statistical physics approaches to the complex Earth system

Global warming, extreme climate events, earthquakes and their accompanying socioeconomic disasters pose significant risks to humanity. Yet due to the nonlinear feedbacks, multiple interactions and complex structures of the Earth system, the understanding and, in particular, the prediction of such disruptive events represent formidable challenges to both scientific and policy communities. During the past years, the emergence and evolution of Earth system science has attracted much attention and produced new concepts and frameworks. Especially, novel statistical physics and complex networks-based techniques have been developed and implemented to substantially advance our knowledge of the Earth system, including climate extreme events, earthquakes and geological relief features, leading to substantially improved predictive performances. We present here a comprehensive review on the recent scientific progress in the development and application of how combined statistical physics and complex systems science approaches such as critical phenomena, network theory, percolation, tipping points analysis, and entropy can be applied to complex Earth systems. Notably, these integrating tools and approaches provide new insights and perspectives for understanding the dynamics of the Earth systems. The overall aim of this review is to offer readers the knowledge on how statistical physics concepts and theories can be useful in the field of Earth system science.

Proportional Trends of Continuous Rainfall in Indian Summer Monsoon

A comprehensive study on the Indian summer monsoonal rainfall (ISMR) is performed in the light of decadal changes in the continuous rainfall events and the number of rainy days using 68 years (1951–2018) of gridded rain gauge data. Non-parametric Mann–Kendall’s test is applied on total rainfall amount, the number of rainy days, number of continuous rainfall events, and rainfall magnitude to find trends over different climatic zones of India for the two periods, 1951–1984 and 1985–2018. Our results found a decreasing trend for more than 4-days of continuous rainfall events during the recent 34 years (1985–2018) compared to 1951–1984. The rate of increase/decrease in extreme/continuous rainfall events does not follow a similar trend in number of continuous rainfall events and magnitude. Moreover, the rainfall is shifted towards a lesser number of continuous rainfall days with higher magnitudes during 1985–2018. During the crop’s sow season (i.e., the first 45 days from the onset date of Indian monsoon), the total number of rainy days decreased by a half day during the last 34 years. Over the Central and North East regions of India, the number of rainfall days decreased by ~0.1 days/yr and ~0.3 days/yr, respectively, during 1985–2018. Overall, the decreasing trends in continuous rainfall days may escalate water scarcity and lead to lower soil moisture over rain-fed irrigated land. Additionally, an upsurge in heavy rainfall episodes will lead to an unexpected floods. On a daily scale, rainfall correlates with soil moisture and evaporation up to 0.87 over various land cover and land use regions of India. Continuous light-moderate rainfall seems to be a controlling factor for replenishing soil moisture in upper levels. A change in rainfall characteristics may force the monsoon-fed rice cultivation period to adopt changing rainfall patterns.

Hydrological regulation of Vibrio dynamics in a tropical monsoonal estuary: a classification and regression tree approach

Dynamics of Vibrio populations in aquatic environments are of concern, as they encompass members pathogenic to humans as well as marine flora and fauna. Spatiotemporal distribution of its culturable abundance for a range of physicochemical and biological parameters in the Cochin estuary (CE), one of the largest tropical monsoonal estuary along the southwest coast of India, witnessed a proliferation of this bacterial group (707 ± 196 CFU ml^-1) in downstream stations during a relative dry period. The study for the first time employed classification and regression tree (CART) along with multiple linear regression (MLR) based approaches to explore the nonlinear and linear interactions, respectively, among environmental variables regulating Vibrio abundance in CE. Both the techniques were on consensus to ascertain salinity as the primary determinant of Vibrio dynamics, during the entire sampling period regardless of the seasons, viz., dry and wet. Nevertheless, CART outperformed MLR in performance index, suggesting that in a dynamic system like estuaries, usage of the latter is limited by complex nonlinear relationships among environmental variables. According to CART, Vibrio proliferation observed in downstream stations of the estuary (salinity ≥ 13.4 psu) during a relative dry period was driven by eutrophication (dissolved inorganic phosphate ≥ 1.48 μM L^-1) associated with reduced flushing resulting in an oxygen-limited environment (dissolved oxygen < 4.56 ml L^-1), wherein phytoplankton production diverts to support microbes. Our results imply that anthropogenic activities and sea level rise in future may prompt Vibrio proliferation, to be a concern for public health and impinge on fisheries yield from tropical estuaries.

Indian monsoon derailed by a North Atlantic wavetrain

The forecast of Indian monsoon droughts has been predicated on the notion of a season-long rainfall deficit linked to a warm equatorial Pacific. Here we show that nearly half of all droughts over the past century differ from this paradigm in that they (i) occur when Pacific temperatures are near-neutral and (ii) are subseasonal phenomena, characterized by an abrupt decline in late-season rainfall. This severe subseasonal rainfall deficit can be associated with a Rossby wave from mid-latitudes. Specifically, we find that the interaction of upper-level winds with an episodic North Atlantic vorticity anomaly results in a wavetrain that curves toward East Asia, disrupting the monsoon. This atmospheric teleconnection offers an avenue for improved predictability of droughts, especially in the absence of telltale signatures in the Pacific.

Multiple livelihood strategies and high floristic diversity increase the adaptive capacity and resilience of Sri Lankan farming enterprises

Globally farmers are challenged by increasing climate variability and frequency of extreme events. However, traditional farming enterprises demonstrate resilience. To understand the underlying reasons, traditional farming enterprises in Sri Lanka were explored. Eighty-five farming enterprises were sampled across nine locations of the Intermediate agroecological zone using mixed methods. Farming enterprises incorporate On- and Off-farm livelihood components (graphical abstract). On-farm refers to landholdings with land uses including tree-dominant forest gardens (FGs), paddy, cash crops, swidden plots (chenas), plantations and livestock. Off-farm includes employment, trading and grants. We investigated how farming enterprises remained resilient, and which land use had the greatest adaptive capacity and best fulfilled household needs? Farming enterprises were assessed with respect to water availability, farmers' perspectives of climate variability, their socioeconomic characteristics, and land uses in landholdings. Land uses were characterised and compared by floristic diversity, crop: utility benefits, food functions, and those consumed and sold. Results revealed that most respondents were women, had primary school education and engaged full-time in farming. Cultivation was mainly rainfed. Farmers' perceptions of climate variability were supported by meteorological data showing that interannual and seasonal rainfall variability prevailed in the reference and preceding years. Farmers withstood these challenges owing to FGs, which were the oldest and dominant of all land uses, with larger area, highest plant and crop species richness, and crop diversity. Greater numbers of primary and secondary FG crops and products provided multiple household benefits. High floristic diversity, tree-dominance and multifunctionality gave FGs strong adaptive capacity. Nevertheless, farmers adopted multiple land uses with diverse landscape designs and Off-farm livelihood strategies simultaneously because this combination offered greater opportunities, buffered risk and increased resilience in farming enterprises. A clear implication of this study is that policymakers should engage with farmers when planning for a resilient agriculture in a variable climate scenario.

El Niño Southern Oscillation as an early warning tool for dengue outbreak in India

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'.

Fingerprint of volcanic forcing on the ENSO-Indian monsoon coupling

Coupling of the El Niño-Southern Oscillation (ENSO) and Indian monsoon (IM) is central to seasonal summer monsoon rainfall predictions over the Indian subcontinent, although a nonstationary relationship between the two nonlinear phenomena can limit seasonal predictability. Radiative effects of volcanic aerosols injected into the stratosphere during large volcanic eruptions (LVEs) tend to alter ENSO evolution; however, their impact on ENSO-IM coupling remains unclear. Here, we investigate how LVEs influence the nonlinear behavior of the ENSO and IM dynamical systems using historical data, 25 paleoclimate reconstructions, last-millennium climate simulations, large-ensemble targeted climate sensitivity experiments, and advanced analysis techniques. Our findings show that LVEs promote a significantly enhanced phase-synchronization of the ENSO and IM oscillations, due to an increase in the angular frequency of ENSO. The results also shed innovative insights into the physical mechanism underlying the LVE-induced enhancement of ENSO-IM coupling and strengthen the prospects for improved seasonal monsoon predictions.

Developing a Remote Sensing-Based Combined Drought Indicator Approach for Agricultural Drought Monitoring over Marathwada, India

The increasing drought severities and consequent devastating impacts on society over the Indian semi-arid regions demand better drought monitoring and early warning systems. Operational agricultural drought assessment methods in India mainly depend on a single input parameter such as precipitation and are based on a sparsely located in-situ measurements, which limits monitoring precision. The overarching objective of this study is to address this need through the development of an integrated agro-climatological drought monitoring approach, i.e., combined drought indicator for Marathwada (CDI_M), situated in the central part of Maharashtra, India. In this study, satellite and model-based input parameters (i.e., standardized precipitation index (SPI-3), land surface temperature (LST), soil moisture (SM), and normalized difference vegetation index (NDVI)) were analyzed at a monthly scale from 2001 to 2018. Two quantitative methods were tested to combine the input parameters for developing the CDI_M. These methods included an expert judgment-based weight of each parameter (Method-I) and principle component analysis (PCA)-based weighting approach (Method-II). Secondary data for major types of crop yields in Marathwada were utilized to assess the CDI_M results for the study period. CDI_M maps depict moderate to extreme drought cases in the historic drought years of 2002, 2009, and 2015–2016. This study found a significant increase in drought intensities (p ≤ 0.05) and drought frequency over the years 2001–2018, especially in the Latur, Jalna, and Parbhani districts. In comparison to Method-I (r ≥ 0.4), PCA-based (Method-II) CDI_M showed a higher correlation (r ≥ 0.60) with crop yields in both harvesting seasons (Kharif and Rabi). In particular, crop yields during the drier years showed a greater association (r > 6.5) with CDI_M over Marathwada. Hence, the present study illustrated the effectiveness of CDI_M to monitor agricultural drought in India and provide improved information to support agricultural drought management practices.

Lag effect of climatic variables on dengue burden in India

Dengue is a widespread vector-borne disease believed to affect between 100 and 390 million people every year. The interaction between vector, host and pathogen is influenced by various climatic factors and the relationship between dengue and climatic conditions has been poorly explored in India. This study explores the relationship between El Niño Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD) and dengue cases in India. Additionally, distributed lag non-linear model was used to assess the delayed effects of climatic factors on dengue cases. The weekly dengue cases reported by the Integrated Disease Surveillance Program (IDSP) over India during the period 2010-2017 were analysed. The study shows that dengue cases usually follow a seasonal pattern, with most cases reported in August and September. Both temperature and rainfall were positively associated with the number of dengue cases. The precipitation shows the higher transmission risk of dengue was observed between 8 and 15 weeks of lag. The highest relative risk (RR) of dengue was observed at 60 mm rainfall with a 12-week lag period when compared with 40 and 80 mm rainfall. The RR of dengue tends to increase with increasing mean temperature above 24 °C. The largest transmission risk of dengue was observed at 30 °C with a 0-3 weeks of lag. Similarly, the transmission risk increases more than twofold when the minimum temperature reaches 26 °C with a 2-week lag period. The dengue cases and El Niño were positively correlated with a 3-6 months lag period. The significant correlation observed between the IOD and dengue cases was shown for a 0-2 months lag period.

Surface chlorophyll anomalies associated with Indian Ocean Dipole and El Niño Southern Oscillation in North Indian Ocean: a case study of 2006-2007 event

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.

Complexity-based approach for El Niño magnitude forecasting before the spring predictability barrier

The El Niño Southern Oscillation (ENSO) is one of the most prominent interannual climate phenomena. Early and reliable ENSO forecasting remains a crucial goal, due to its serious implications for economy, society, and ecosystem. Despite the development of various dynamical and statistical prediction models in the recent decades, the "spring predictability barrier" remains a great challenge for long-lead-time (over 6 mo) forecasting. To overcome this barrier, here we develop an analysis tool, System Sample Entropy (SysSampEn), to measure the complexity (disorder) of the system composed of temperature anomaly time series in the Niño 3.4 region. When applying this tool to several near-surface air temperature and sea surface temperature datasets, we find that in all datasets a strong positive correlation exists between the magnitude of El Niño and the previous calendar year's SysSampEn (complexity). We show that this correlation allows us to forecast the magnitude of an El Niño with a prediction horizon of 1 y and high accuracy (i.e., root-mean-square error = 0.23° C for the average of the individual datasets forecasts). For the 2018 El Niño event, our method forecasted a weak El Niño with a magnitude of 1.11±0.23° C. Our framework presented here not only facilitates long-term forecasting of the El Niño magnitude but can potentially also be used as a measure for the complexity of other natural or engineering complex systems.

Increased drought events in southwest China revealed by tree ring oxygen isotopes and potential role of Indian Ocean Dipole

The highlands in southwestern China experience pronounced fluctuations in the hydroclimate with profound impacts on agriculture and economics. To investigate the drought history of this region beyond instrumental records, a tree ring cellulose oxygen isotope (δ¹⁸O_c) chronology was developed for the period 1733-2013 using samples collected from six Larix trees in the low-latitude highlands (LLH) of southwestern China. The analysis revealed that δ¹⁸O_c is significantly correlated with the rainy season (May-October) precipitation and relative humidity, as well as drought severity. The δ¹⁸O_c chronology accounts for 46% of the observed variance in the rainy season precipitation and it was subsequently used to reconstruct precipitation. The reconstructed precipitation reveals an apparent drying trend since 1840, accompanied by increasingly frequent drought events since 1970. Interdecadal variability is also present, characterized with two distinct wet periods in 1740-1760 and 1800-1900 and two drier periods in 1760-1800 and 1900-2013. On the interannual timescale, the LLH precipitation was modulated collectively by the El Niño-Southern Oscillation (ENSO) and the Indian Ocean dipole (IOD). There appears to be an enhanced precipitation-IOD relationship since 1970 in response to the increase in positive-IOD events, implying an increasing likelihood of drought for the southwest China LLH.

Sensitivity of speleothem records in the Indian Summer Monsoon region to dry season infiltration

In climates with strongly seasonal rainfall, speleothem-based paleoclimate reconstructions are often thought to reflect wet season conditions, assuming a bias toward the season with greater water supply. This is particularly true in monsoon regions, where speleothem records are interpreted to document monsoon strength changes on multiple timescales. Dry season infiltration variability and rainfall seasonality are not typically considered in these reconstructions, even though cave ventilation could bias speleothem growth toward the cooler season. To investigate the influence of dry season infiltration on speleothem geochemistry, we combine a modern, sub-seasonally resolved trace element record from Mawmluh Cave in Northeast India with forward modeling experiments. We find that variations in the amplitude of seasonal signals in speleothem Mg/Ca, which reflects prior carbonate precipitation, are more sensitive to dry season rather than monsoon season infiltration. This sensitivity may be enhanced by dry season cave ventilation. The Mawmluh speleothem Mg/Ca record is consistent with increased dry season rainfall during the 1976–1998 warm phase of the Pacific Decadal Oscillation relative to 1964–2013. Our work demonstrates the importance of considering non-monsoon season rainfall when interpreting speleothem paleoclimate records and suggests that trace elements could provide insight into periods of enhanced dry season infiltration in monsoonal climates.

The weakening relationship between Eurasian spring snow cover and Indian summer monsoon rainfall

Substantial progress has been made in understanding how Eurasian snow cover variabilities affect the Indian summer monsoon, but the snow-monsoon relationship in a warming atmosphere remains controversial. Using long-term observational snow and rainfall data (1967-2015), we identified that the widely recognized inverse relationship of central Eurasian spring snow cover with the Indian summer monsoon rainfall has disappeared since 1990. The apparent loss of this negative correlation is mainly due to the central Eurasian spring snow cover no longer regulating the summer mid-tropospheric temperature over the Iranian Plateau and surroundings, and hence the land-ocean thermal contrast after 1990. A reduced lagged snow-hydrological effect, resulting from a warming-induced decline in spring snow cover, constitutes the possible mechanism for the breakdown of the snow-air temperature connection after 1990. Our results suggest that, in a changing climate, Eurasian spring snow cover may not be a faithful predictor of the Indian summer monsoon rainfall.

Effects of ENSO on Temperature, Precipitation, and Potential Evapotranspiration of North India’s Monsoon: An Analysis of Trend and Entropy

The influence of El Niño Southern Oscillation (ENSO) on the north Indian temperature, precipitation, and potential evapotranspiration (PET) change patterns were evaluated during the monsoon season across the last century. Trends and shifts in 146 districts were assessed using nonparametric statistical tests. To quantify their temporal variation, the concept of apportionment entropy was applied to both the annual and seasonal scales. Results suggest that the El Niño years played a greater role in causing hydro-climatological changes compared to the La Niña or neutral years. El Niño was more influential in causing shifts compared to trends. For certain districts, a phase change in ENSO reversed the trend/shift direction. The century-wide analysis suggested that the vast majority of the districts experienced significant decreasing trends/shifts in temperature and PET. However, precipitation experienced both increasing and decreasing trends/shifts based on the location of the districts. Entropy results suggested a lower apportionment of precipitation compared to the other variables, indicating an intermittent deviation of precipitation pattern from the generic trend. The findings may help understand the effects of ENSO on the hydro-climatological variables during the monsoon season. Practitioners may find the results useful as monsoon is the most important season for India causing climate extremes.

Temporal evolution of hydroclimatic teleconnection and a time-varying model for long-lead prediction of Indian summer monsoon rainfall

Several cases of failure in the prediction of Indian Summer Monsoon Rainfall (ISMR) are the major concern for long-lead prediction. We propose that this is due to the temporal evolution of association/linkage (inherent concept of temporal networks) with various factors and climatic indices across the globe, such as El Niño-Southern Oscillation (ENSO), Equatorial Indian Ocean Oscillation (EQUINOO), Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO) etc. Static models establish time-invariant (permanent) connections between such indices (predictors) and predictand (ISMR), whereas we hypothesize that such systems are temporally varying in nature. Considering hydroclimatic teleconnection with two major climate indices, ENSO and EQUINOO, we showed that the temporal persistence of the association is as low as three years. As an application of this concept, a statistical time-varying model is developed and the prediction performance is compared against its static counterpart (time-invariant model). The proposed approach is able to capture the ISMR anomalies and successfully predicts the severe drought years too. Specifically, 64% more accurate performance (in terms of RMSE) is achievable by the recommended time-varying approach as compared to existing time-invariant concepts.

The early 20th century warming: Anomalies, causes, and consequences

The most pronounced warming in the historical global climate record prior to the recent warming occurred over the first half of the 20th century and is known as the Early Twentieth Century Warming (ETCW). Understanding this period and the subsequent slowdown of warming is key to disentangling the relationship between decadal variability and the response to human influences in the present and future climate. This review discusses the observed changes during the ETCW and hypotheses for the underlying causes and mechanisms. Attribution studies estimate that about a half (40-54%; p > .8) of the global warming from 1901 to 1950 was forced by a combination of increasing greenhouse gases and natural forcing, offset to some extent by aerosols. Natural variability also made a large contribution, particularly to regional anomalies like the Arctic warming in the 1920s and 1930s. The ETCW period also encompassed exceptional events, several of which are touched upon: Indian monsoon failures during the turn of the century, the "Dust Bowl" droughts and extreme heat waves in North America in the 1930s, the World War II period drought in Australia between 1937 and 1945; and the European droughts and heat waves of the late 1940s and early 1950s. Understanding the mechanisms involved in these events, and their links to large scale forcing is an important test for our understanding of modern climate change and for predicting impacts of future change. This article is categorized under:Paleoclimates and Current Trends > Modern Climate Change.

El Niño–Southern Oscillation and its impact in the changing climate

Extensive research has improved our understanding and forecast of the occurrence, evolution and global impacts of the El Niño–Southern Oscillation (ENSO). However, ENSO changes as the global climate warms up and it exhibits different characteristics and climate impacts in the twenty-first century from the twentieth century. Climate models project that ENSO will also change in the warming future and have not reached an agreement about the flavor, as to the intensity and the frequency, of future ENSO conditions. This article presents the conventional view of ENSO properties, dynamics and teleconnections, and reviews the emerging understanding of the diversity and associated climate impacts of ENSO. It also reviews the results from investigations into the possible changes in ENSO under the future global-warming scenarios.

Indian summer monsoon variability forecasts in the North American multimodel ensemble

The representation of the seasonal mean and interannual variability of the Indian summer monsoon rainfall (ISMR) in nine global ocean-atmosphere coupled models that participated in the North American Multimodal Ensemble (NMME) phase 1 (NMME:1), and in nine global ocean-atmosphere coupled models participating in the NMME phase 2 (NMME:2) from 1982-2009, is evaluated over the Indo-Pacific domain with May initial conditions. The multi-model ensemble (MME) represents the Indian monsoon rainfall with modest skill and systematic biases. There is no significant improvement in the seasonal forecast skill or interannual variability of ISMR in NMME:2 as compared to NMME:1. The NMME skillfully predicts seasonal mean sea surface temperature (SST) and some of the teleconnections with seasonal mean rainfall. However, the SST-rainfall teleconnections are stronger in the NMME than observed. The NMME is not able to capture the extremes of seasonal mean rainfall and the simulated Indian Ocean-monsoon teleconnections are opposite to what are observed.

Fast Adjustments of the Asian Summer Monsoon to Anthropogenic Aerosols

Anthropogenic aerosols are a major factor contributing to human-induced climate change, particularly over the densely populated Asian monsoon region. Understanding the physical processes controlling the aerosol-induced changes in monsoon rainfall is essential for reducing the uncertainties in the future projections of the hydrological cycle. Here we use multiple coupled and atmospheric general circulation models to explore the physical mechanisms for the aerosol-driven monsoon changes on different time scales. We show that anthropogenic aerosols induce an overall reduction in monsoon rainfall and circulation, which can be largely explained by the fast adjustments over land north of 20∘N. This fast response occurs before changes in sea surface temperature (SST), largely driven by aerosol-cloud interactions. However, aerosol-induced SST feedbacks (slow response) cause substantial changes in the monsoon meridional circulation over the oceanic regions. Both the land-ocean asymmetry and meridional temperature gradient are key factors in determining the overall monsoon circulation response.

Quasi-asymmetric response of the Indian summer monsoon rainfall to opposite phases of the IOD

The El Niño/Southern Oscillation has been traditionally linked to the extremes in the Indian summer monsoon rainfall (ISMR) affecting more than a billion people in the region. This trans-oceanic influence is seen to be moderated by the Indian Ocean Dipole (IOD) phenomenon in recent decades. In the presence of a positive IOD (pIOD), the otherwise subdued ISMR in an El Niño year remains close to normal even in the face of record breaking El Niños. While this general influence of pIOD on ISMR is understood, the influence of negative IOD (nIOD) on ISMR is not yet recognized. In this study, it is revealed that those opposite phases of IOD are associated with distinct regional asymmetries in rainfall anomalies. The pIOD is associated with a tripolar pattern in rainfall anomalies with above normal rainfall in central parts of India and below normal rainfall to north and south of it. Conversely, the nIOD is associated with a zonal dipole having above (below) normal rainfall on the western (eastern) half of the country. This spatial quasi-asymmetry arises from the differences in the atmospheric responses and the associated differences in moisture transports to the region during contrasting phases of the IOD.

Increasing frequency and spatial extent of concurrent meteorological droughts and heatwaves in India

The impacts of concurrent droughts and heatwaves could be more serious compared to their individual occurrence. Meteorological drought condition is generally characterized by low rainfall, but impact of such an event is amplified with simultaneous occurrence of heatwaves. Positive feedback between these two extremes can worsen the rainfall deficit situation to serious soil moisture depletion due to enhanced evapotranspiration. In this study, the concurrence of meteorological droughts and heatwaves is investigated in India using Indian Meteorological Department (IMD) high resolution gridded data over a period of 60 years. Significant changes are observed in concurrent meteorological droughts and heatwaves defined at different percentile based thresholds and durations during the period 1981-2010 relative to the base period 1951-1980. There is substantial increase in the frequency of concurrent meteorological droughts and heatwaves across whole India. Statistically significant trends in the spatial extent of droughts are observed in Central Northeast India and West Central India; however, the spatial extent affected by concurrent droughts and heatwaves is increasing across whole India. Significant shifts are identified in the distribution of spatial extent of concurrent drought and heatwaves in India compared to the base period.