Rethinking Indian monsoon rainfall prediction in the context of recent global warming

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.

Population exposure to drought severities under shared socioeconomic pathways scenarios in India

As a widespread natural hazard, droughts impact several aspects of human society adversely. Thus, the present study aims to answer the following research questions; (i) What are the expected variabilities in different drought conditions over India in the future? (ii) How the population exposure to drought varies under different climate change and population scenarios? (iii) How is the total exposure attributed to the individual exposure (climate, population, and interaction) in future climate change scenarios? In this sense, the study is performed under four Shared Socioeconomic Pathways scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) using thirteen Global Climate Models from Coupled Model Intercomparison Project Phase 6 and Standardized Precipitation Evapotranspiration Index as a drought indicator. The future period is divided into two parts i.e., 2023-2061 (T1) and 2062-2100 (T2), and compared with the historical period during 1967-2005. The results show that the severe (56 % to 72 % of the area) and extreme (99 % of the area) droughts are likely to increase under all the scenarios for 3-month scale conditions, respectively. The drought intensity is projected to increase under 3-and 12-month scale drought conditions. The population exposure to the extreme drought severity is anticipated to increase for both the drought conditions and the highest exposure is noticed under the SSP3-7.0 scenario. The significant contribution from climate or interaction effects is observed in the case of 3- and 9-month scale extreme drought conditions. The present study necessitates a call for effective measures to alleviate the risk, especially in the high-risk areas of India.

Oceanic and atmospheric anomalies associated with extreme precipitation events in China 1983-2020

Observed synoptic anomalies in connection with China's extreme precipitation events/floods in the summers of 1982/83, 1997/98, 2010, 2014, 2015/16, and 2020 are studied. These events mainly occur within the middle and lower Yangtze basins. The dominant moisture source is the Northern Indian Ocean and the Southwestern Pacific Ocean of the Indo-Pacific warm pool (IPWP). Both of these bodies of water have warmed since 1979. In East Asia, the strong land-sea thermal contrast driven by global warming drives the increased East Asian summer monsoon (EASM) circulation, which develops deep convective precipitation. The total precipitable water in the Indo-Pacific region has also been increasing since 1979. The intense southwest Indian monsoon transports moist air to the Yangtze basin in mid-June and forms the Meiyu (plum rain) front. Strengthened Okhotsk/Ural blocking highs in East and West Asia, as well as the Western Pacific subtropical high (WPSH) and the South Asian high (SAH) over south Eurasia, remain stationary for long periods and interact to exacerbate the precipitation. The western edge of the WPSH expands westward towards East Asia to transport moisture. To the north, the WPSH combines with the two blocking highs to trigger more rain. The intensified SAH expands eastward and merges with the extended WPSH to add rain. On the other hand, rainfall is modulated by the El Niño-Southern Oscillation (ENSO), notably in relation to the super El Niño events in 1982-1983, 1997-1998, 2015-2016, and 2020. The research described in this paper highlights changes in the weather systems with warming and, in particular, the enormous and dominating impact of the warming and expanding IPWP on rainfall extremes. Improved seasonal forecasts and planning ahead will protect lives and livelihoods.

Global decline in ocean memory over the 21st century

Ocean memory, the persistence of ocean conditions, is a major source of predictability in the climate system beyond weather time scales. We show that ocean memory, as measured by the year-to-year persistence of sea surface temperature anomalies, is projected to steadily decline in the coming decades over much of the globe. This global decline in ocean memory is predominantly driven by shoaling of the upper-ocean mixed layer depth in response to global surface warming, while thermodynamic and dynamic feedbacks can contribute substantially regionally. As the mixed layer depth shoals, stochastic forcing becomes more effective in driving sea surface temperature anomalies, increasing high-frequency noise at the expense of persistent signals. Reduced ocean memory results in shorter lead times of skillful persistence-based predictions of sea surface thermal conditions, which may present previously unknown challenges for predicting climate extremes and managing marine biological resources under climate change.

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.

•

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

•

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

•

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

Storm types in India: linking rainfall duration, spatial extent and intensity

We examine wet events (WEs) defined from an hourly rainfall dataset based on 64 gauged observations across India (1969-2016). More than 90% of the WEs (accounting for nearly 60% of total rainfall) are found to last less than or equal to 5 h. WEs are then clustered into six canonical local-scale storm profiles (CanWE). The most frequent canonical type (CanWE#1 and #2) are associated with very short and nominal rainfall. The remaining canonical WEs can be grouped into two broad families: (i) CanWE#3 and #5 with short (usually less than or equal to 3-4 h), but very intense rainfall strongly phase-locked onto the diurnal cycle (initiation peaks in mid-afternoon) and probably related to isolated thunderstorms or small mesoscale convective clusters (MCS), and (ii) CanWE#4 and #6 with longer and lighter rainfall in mean (but not necessarily for their maximum) and more independent of the diurnal cycle, thus probably related to larger MCSs or tropical lows. The spatial extent of the total rainfall received during each CanWE, as shown by IMERG gridded rainfall, is indeed smaller for CanWE#3 and #5 than for CanWE#4 and especially #6. Most of the annual maximum 1 hour rainfalls occur during CanWE#5. Long-term trend analysis of the June-September canonical WEs across boreal monsoonal India reveals an increase in the relative frequency of the convective storm types CanWE#3 and #5 in recent years, as expected from global warming and thermodynamic considerations. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'.

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.

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.

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.

Coherent response of the Indian Monsoon Rainfall to Atlantic Multi-decadal Variability over the last 2000 years

Indian Summer Monsoon (ISM) rainfall has a direct effect on the livelihoods of two billion people in the Indian-subcontinent. Yet, our understanding of the drivers of multi-decadal variability of the ISM is far from being complete. In this context, large-scale forcing of ISM rainfall variability with multi-decadal resolution over the last two millennia is investigated using new records of sea surface salinity (δ18Ow) and sea surface temperatures (SSTs) from the Bay of Bengal (BoB). Higher δ18Ow values during the Dark Age Cold Period (1550 to 1250 years BP) and the Little Ice Age (700 to 200 years BP) are suggestive of reduced ISM rainfall, whereas lower δ18Ow values during the Medieval Warm Period (1200 to 800 years BP) and the major portion of the Roman Warm Period (1950 to 1550 years BP) indicate a wetter ISM. This variability in ISM rainfall appears to be modulated by the Atlantic Multi-decadal Oscillation (AMO) via changes in large-scale thermal contrast between the Asian land mass and the Indian Ocean, a relationship that is also identifiable in the observational data of the last century. Therefore, we suggest that inter-hemispheric scale interactions between such extra tropical forcing mechanisms and global warming are likely to be influential in determining future trends in ISM rainfall.

Southern Hemisphere forcing of South Asian monsoon precipitation over the past ~1 million years

The orbital-scale timing of South Asian monsoon (SAM) precipitation is poorly understood. Here we present new SST and seawater δ¹⁸O (δ¹⁸Osw) records from the Bay of Bengal, the core convective region of the South Asian monsoon, over the past 1 million years. Our records reveal that SAM precipitation peaked in the precession band ~9 kyrs after Northern Hemisphere summer insolation maxima, in phase with records of SAM winds in the Arabian Sea and eastern Indian Ocean. Precession-band variance, however, accounts for ~30% of the total variance of SAM precipitation while it was either absent or dominant in records of the East Asian monsoon (EAM). This and the observation that SAM precipitation was phase locked with obliquity minima and was sensitive to Southern Hemisphere warming provides clear evidence that SAM and EAM precipitation responded differently to orbital forcing and highlights the importance of internal processes forcing monsoon variability.

The orbital-scale timing of South Asian monsoon precipitation is poorly understood. Here the authors show that the long held view that precession drove changes in monsoon strength is wrong, and that obliquity and eccentricity played a stronger role.

Palaeoclimatic insights into forcing and response of monsoon rainfall

Monsoons are the dominant seasonal mode of climate variability in the tropics and are critically important conveyors of atmospheric moisture and energy at a global scale. Predicting monsoons, which have profound impacts on regions that are collectively home to more than 70 per cent of Earth's population, is a challenge that is difficult to overcome by relying on instrumental data from only the past few decades. Palaeoclimatic evidence of monsoon rainfall dynamics across different regions and timescales could help us to understand and predict the sensitivity and response of monsoons to various forcing mechanisms. This evidence suggests that monsoon systems exhibit substantial regional character.