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Little Ice Age (LIA; 1500–1900 CE) was the most recent cold period. The majority of the summer monsoon precipitation records show weakening of it during LIA. However, few studies have shown wet and dry phases, and southern Indian records show wet conditions. To assess the monsoon variability during the LIA from the western Bay of Bengal we studied dinoflagellate cysts, palynological and palynofacies records from the Bay of Bengal. The present high-resolution record reveals the presence of four phases: Phase I (1500–1700 CE) with high runoff discharge, followed by phase II (1700–1785 CE), which is a dry phase. Phase III (1785–1840 CE) shows a slightly strengthened monsoon, and phase IV (1840–2010 CE) is again a dry phase. In contrast to previously documented uniform cold and dry conditions from the Bay of Bengal, multidecadal wet and dry phases during the LIA are indicated. Primary productivity in the studied region is governed by both runoff-mediated nutrients and wind-driven mixing. High primary productivity since 1900 CE under dry conditions is governed by the enhanced mixing due to the weakening of summer and/or strengthening of winter winds over the western Bay of Bengal. The regional scale records show that the LIA, unlike a period of cold and dry conditions, is characterized by multidecadal scale wet and dry conditions governed by southwest and northeast monsoon intensity in southern India. The southward migration of ITCZ played a major role in the precipitation changes during the LIA. [ABSTRACT FROM AUTHOR]

We identified a set of bias-corrected and downscaled Coupled Model Intercomparison Project 6 (CMIP6) models capable of accurately simulating the observed mean Indian summer monsoon rainfall, extreme rain events (EREs) and their respective interannual variability. The future changes in EREs projected by these models for four climate change scenarios—Shared Socioeconomic Pathways (SSPs), 1–2.6, 2–4.5, 3–7.0 and 5–8.5 were estimated using percentile thresholds. Under the highest emission scenario, SSP5-8.5, at the end of the century, summer monsoon season total rainfall exhibits a 1.1-fold increase, while extreme rainfall intensity demonstrates a more substantial rise of 1.3-fold. The spatial variability of seasonal total rainfall increases by 1.2-fold compared to the baseline period, with an even more pronounced 2.1-fold increase in the spatial variability of extreme rainfall (R99p). These findings underscore the significant amplification of rainfall variability and intensity under the most extreme climate scenario. The intensity and frequency of very extreme rainfall events (vEREs) were also found to increase, though with a substantial inter-model spread. Under SSP5-8.5, extreme rainfall intensity scales with temperature at 1.5 to 2 times the Clausius-Clapeyron (CC) rate. While mid-century scenarios show minimal variations in extreme rainfall intensity from the historical period, end-century projections reveal significant shifts; an increase in north India and a decrease in south India due to cloud-induced cooling effects. [ABSTRACT FROM AUTHOR]

The Central Ganga Plain boasts a rich cultural history and a complex climatic past, shaped mainly by the Indian summer monsoon (ISM). The present study critically assesses current archaeological methodologies for palaeovegetational reconstruction and offers an updated overview of major multi-proxy studies conducted in response to ISM between ~100-2 ka BP. These studies reveal a correlation between high ISM periods and the prevalence of C3 vegetation, while low ISM periods are associated with C4 plants. The archaeological record also indicates corresponding adaptations in dietary habits and subsistence strategies. The study emphasizes the need for more localized multi-proxy research to enable inter-site comparisons, aiming for a holistic under-standing of the evolution of the Ganga Plain. [ABSTRACT FROM AUTHOR]

The Indo‐Pacific warm pool (IPWP), enclosed by a 28°C isotherm, is vital in controlling atmospheric circulations affecting monsoonal flow. The warming trend of sea surface temperatures (SSTs) over the IPWP has expanded the IPWP region. This study examines the impact of the IPWP warming on the Indian summer monsoon rainfall (ISMR) patterns using ERA5 reanalysis and India Meteorological Department rainfall records based on station data from 1959 to 2021. Analyses based on correlation, regression and composite anomalies show the complex relationship between recent decades of IPWP expansion/warming and monsoon circulation. However, the effects of regional IPWP SST warming changes on the ISMR pattern remain unexplored. Here, we explore the changes in the monsoonal circulation owing to the warming and expansion of IPWP, by comparing two equal periods (1959–1989 and 1990–2021). The responses of monsoons to IPWP warming in these two periods revealed some interesting facts, but the complexity remained. Further, we examined the composite impacts of IPWP SST warming in three categories, that is, very cool, usual and extremely warm, on the dynamics of monsoon circulations. The very cool IPWP is associated with the dry monsoon, while the extremely warm IPWP produces copious rainfall over southern India and dryness over eastern north India. The study confirms the non‐linear relationship between IPWP warming and ISMR, which has been investigated in detail. [ABSTRACT FROM AUTHOR]

Abstract Global warming has significantly increased the risk of heat waves (HWs) globally, with India being particularly vulnerable during the summer months (March-June; MAMJ). This study investigated the critical relationship between Indian summer monsoon rainfall (ISMR) and the occurrence of premonsoon HWs in subsequent years across the Indian subcontinent. It has been hypothesized that droughts during the ISMR could lead to more frequent HWs in the following MAMJ period. Using the Indian Meteorological Department's (IMD) gridded observed surface air daily maximum temperature (Tmax) dataset for the period 1951–2023, we analyzed the climatic patterns, interannual variability (IAV), and coefficient of variation (CV) of Tmax across India. The analysis compares two distinct periods: 1951–1999 (P1) and 2000–2023 (P2), with focus on Tmax trends and HW duration, distinguishing between short-duration HWs (SHWs, 2 days) and long-duration HWs (LHWs, 5 days or more). A key purpose of this study is to examine the relationship between the preceding all India summer monsoon rainfall (AISMR) and the occurance of various types of HW in the subsequent premonsoon season. In particular extreme AISMR events, such as droughts or excess rainfall, influence HW occurrence. The findings reveal a significant rise in Tmax across many regions of India during the MAMJ period, with the highest temperatures (> 37 °C) observed in northwestern, central, and eastern coastal areas. Northern India, particularly the Himalayan region, exhibits a greater interannual variability in Tmax, with June showing the most pronounced fluctuations. The study also highlights an increase in the frequency and intensity of HWs, especially in central and southern India, with the Chandigarh-Haryana-Delhi region recording the highest occurrences. A critical finding is the strong inverse relationship between the AISMR and conditions in the subsequent premonsoon season. Specifically, drought in the antecedent AISMR results in reduced soil moisture, which is strongly associated with higher premonsoon Tmax and an increased frequency of extreme heat events across India, particularly in regions prone to severe heat during this season. Drought conditions during AISMR are closely linked to higher HW frequencies in the following summer, especially in the central, northeast-central, and east-coastal regions. The frequencies of HW days, SHWs, and LHWs are significantly greater in years following AISMR droughts than in those following excess rainfall, indicating that drought years are more likely to lead to widespread HW activity. Despite the overall warming trends, some regions, such as the Indo-Gangetic Plain and parts of the Himalayan region, show cooling trends, although these trends are less widespread. The onset of the monsoon in June tends to reduce the intensity and spatial extent of warming, particularly in the central and eastern coastal regions, although significant HW trends persist in northwestern India and along the east coast. This study underscores the crucial role of AISMR in influencing HW events across India and highlights the need for adaptive strategies that account for the interactions between monsoon rainfall and HW risk, providing valuable insights for mitigating the impacts of HWs in the context of global warming.

ABSTRACT Indian summer monsoon (ISM) is the prominent global monsoon system, which occur annually from June to September and impacts the lives of over a quarter of the world's population. Studies show that global warming is one of the key reasons for the extreme events such as droughts and floods, and that also alter regional dynamics of ISM. Consequently, a comprehensive investigation of flood and drought events in India is imperative, because of their important role in the economy of the country. Here, we employ simulations from the Coupled Model Intercomparison Project phase 6 (CMIP6) models to evaluate the intensity and frequency of droughts and floods across historical (1950–2014) and future (2015–2100) periods. We explore the best‐performing model for the ISM rainfall (ISMR) to unravel the characteristics of floods and droughts by analysing rainfall data from 53 models. Although majority of the models successfully replicate the annual cycle of ISMR, there exists a significant difference in rainfall amounts. Following an initial screening to identify the most efficient models, eight are selected for an in‐depth assessment. The chosen models slightly overestimate drought conditions, although they demonstrate a commendable concurrence in simulating the flood occurrences in India. Regarding the future projections, we analyse the Shared Socioeconomic Pathways (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 and SSP5‐8.5) for near (2015–2035)‐, mid (2047–2067)‐ and far (2079–2099)‐future periods, in addition to the total projection period (2015–2100). Our analysis reveals an increasing trend of droughts in the near‐future, compared to an increase in floods during the far‐future. It is also highlighted that the intensity of droughts is projected to amplify in the far‐future, while the intensity of floods is likely to diminish. Therefore, this study serves as a valuable resource for decision‐making processes, particularly in the flood, drought and agricultural disaster preparedness. [ABSTRACT FROM AUTHOR]

Monsoonal precipitation is dominated by intraseasonal variabilities, whose skillful prediction lead time is currently less than 5 days and remains a grand challenge. Here we show that an intrinsic variability in the Indian Ocean, the Central Indian Ocean (CIO) mode, when combined with a machine learning (ML) algorithm, can produce skillful predictions of intraseasonal precipitation over the monsoon region with a lead time of over 15 days, which is close to the theoretical predictability limit. This remarkable skill improvement stems from the fact that the CIO mode is dynamically related to the intraseasonal monsoon rainfall, while the data‐driven ML algorithm suppresses unwanted high‐frequency noise. Using the CIO mode and the ML algorithm, the forecast system hybridizes physical fundamentals and versatility of data‐driven algorithms. The identification of CIO mode and the verification of its significant contribution to intraseasonal predictions advance our understanding of the coupled monsoon system and also underscores the great potential of ML techniques in weather forecasts and climate predictions. Plain Language Summary: Rainfall during the Indian summer monsoon is dominated by variations with a period of tens of days, which are referred to as intraseasonal variabilities. Current prediction skill of intraseasonal monsoonal rainfall is less than 5 days and it remains a grand challenge in terms of increasing the current prediction skill. Here we show that an intrinsic mode of variability in the Indian Ocean, called the Central Indian Ocean (CIO) mode, when combined with a machine learning (ML) algorithm, can produce skillful predictions of intraseasonal precipitation over the monsoon region with a lead time of over 15 days. This remarkable skill improvement stems from the fact that the CIO mode is dynamically related to intraseasonal monsoon rainfall, while data‐driven ML algorithm suppresses disruptive noise with a period shorter than 10 days. Using the CIO mode and an ML algorithm, the forecast system synergizes physical fundamentals and versatility of data‐driven algorithm. The identification of CIO mode and the verification of its significant contribution to intraseasonal prediction advance our understanding of the coupled monsoon system and also demonstrate the great potential of ML techniques in weather forecasts and climate predictions. Key Points: The Central Indian Ocean (CIO) mode provides a dynamical basis for the prediction of monsoon intraseasonal rainfallThe machine learning (ML) algorithm suppresses high‐frequency noise while capturing the real‐time CIO mode indexThe dynamics and ML hybrid forecast system can skillfully predict monsoon intraseasonal rainfall with a lead time of ∼15 days [ABSTRACT FROM AUTHOR]

This paper provides a comprehensive and comparative analysis of extreme precipitation patterns from 1971 to 2015 in Nepal, a data scarce, but "hot spot" region in global climate change. We compare in‐situ observations and gridded precipitation data from the Asian Precipitation Highly Resolved Observational Data Integration Toward Evaluation of Water Resources (APHRODITE). Using 11 precipitation indices, we show that high‐intensity (RX1day, R95pTOT, R99pTOT) and frequency‐related indices (R10 mm, R20 mm) have decreased but annual maximum consecutive dry and wet days have increased. Observations affirm these trends found by the APHRODITE, but show smaller magnitudes likely due to differences in measurements at locations made below the 3,000 m elevation line. Spatially, the relatively dry western region has become wetter, and the relatively wet eastern region has become drier post‐2003. The weakening of the South Asia Monsoon circulation, particularly assessed by the Webster and Yang Monsoon Index, correlates strongly with extreme precipitation indices. Changes in upper‐level jet and associated lower‐level monsoon trough are identified as critical factors influencing the extreme precipitation trend post‐2003. This study is the first to confirm the efficacy of APHRODITE in providing spatial and temporal precipitation patterns in a data‐limited region. We conclude that monsoon weakened circulations and changes in regional wind fields play dominant roles in the long‐term temporal and spatial trends of extreme precipitation in Nepal. The reduced precipitation extremes in the wet eastern region may somewhat lessen severe flooding and erosion, but the drier western region may face heightened risks in precipitation‐related hazards in Nepal. Plain Language Summary: Precipitation is one of the most important components of the Earth's water cycles but is least predictable locally amid global climate change. Understanding the historical dynamics of extreme precipitation provides critical information for developing climate mitigation and adaptation strategies. This paper examines extreme precipitation patterns in Nepal from 1971 to 2015. Comparing observations on site and Asian Precipitation Highly Resolved Observational Data Integration data, the study identifies decreasing intense and frequent rainfall and increasing prolonged precipitation. On‐site data show similar trends to the integration data, but have smaller magnitudes. Post‐2003, the west and the east tend to get wetter and drier, respectively. The study links these changes to a weakened South Asia Monsoon circulation, particularly indicated by the Webster and Yang Monsoon Index. The shift in upper‐level jet and lower‐level monsoon trough are identified as key factors influencing extreme precipitation trends post‐2003. This study validates APHRODITE in data‐limited regions. The findings suggest that weakened monsoon circulations and changes in wind patterns significantly contribute to long‐term trends in extreme precipitation in Nepal. While reduced extremes in the wet eastern region may imply decreased flooding risks, but the drier western region may face increased hazards and ecosystem changes related to precipitation. Key Points: From 1971 to 2015, extreme precipitation events decreased in Nepal overall, with the west getting wetter and the east drier post‐2003The APHRODITE gridded reliably reproduces Nepal's extreme precipitationChanges in precipitation are the results of variations in monsoon intensity and shifts in wind patterns [ABSTRACT FROM AUTHOR]

Climate change is expected to have a considerable impact on precipitation leading to more intense and frequent extreme events. Considering the different driving mechanisms of precipitation extreme is essential to understand the changes in response to climate change. In this study, we decompose the intensity of extreme wet month precipitation (EWMP) during the Indian summer monsoon (ISM) into atmospheric dynamic, thermodynamic and non‐linear components by using moisture budget estimation. The data from 19 Coupled Model Intercomparison Project phase‐6 (CMIP6) models are used for historical, intermediate (SSP2‐4.5), and high‐emission (SSP5‐8.5) scenarios and the changes are estimated for near (2021–2040), mid (2041–2060), and far‐future (2081–2100) relative to the historical (1995–2014) period for different monsoon sub‐domains. The findings reveal a significant increase in the intensity of EWMP in the ISM, projecting 2%–12% in SSP2‐4.5 and 8%–25% in SSP5‐8.5 for the far‐future. The enhanced vertical ascent of moisture (V‐Dyn) is found to be a dominant factor contributing more than 70% to EWMP in most sub‐domains. However, regardless of enhancement in intensity of precipitation, the models simulate a reduction in impact of the V‐Dyn by 10%–35% from the near to far‐future period, particularly in high emission scenarios. Vertical thermodynamic and non‐linear moisture advection components also play minor roles (<5% in historical), with their influence gradually increasing with future warming (>15% in SSP5‐8.5). The responses also vary regionally for components such as horizontal dynamic term, where it leads to precipitation offset in the northern regions, but causes enhanced precipitation in southern regions. The study highlights the spatial and temporal variability of moisture budgets of extreme wet Indian summer monsoon precipitation in a warming environment. [ABSTRACT FROM AUTHOR]

Global warming has significantly increased the risk of heat waves (HWs) globally, with India being particularly vulnerable during the summer months (March-June; MAMJ). This study investigated the critical relationship between Indian summer monsoon rainfall (ISMR) and the occurrence of premonsoon HWs in subsequent years across the Indian subcontinent. It has been hypothesized that droughts during the ISMR could lead to more frequent HWs in the following MAMJ period. Using the Indian Meteorological Department's (IMD) gridded observed surface air daily maximum temperature (Tmax) dataset for the period 1951–2023, we analyzed the climatic patterns, interannual variability (IAV), and coefficient of variation (CV) of Tmax across India. The analysis compares two distinct periods: 1951–1999 (P1) and 2000–2023 (P2), with focus on Tmax trends and HW duration, distinguishing between short-duration HWs (SHWs, 2 days) and long-duration HWs (LHWs, 5 days or more). A key purpose of this study is to examine the relationship between the preceding all India summer monsoon rainfall (AISMR) and the occurance of various types of HW in the subsequent premonsoon season. In particular extreme AISMR events, such as droughts or excess rainfall, influence HW occurrence. The findings reveal a significant rise in Tmax across many regions of India during the MAMJ period, with the highest temperatures (> 37 °C) observed in northwestern, central, and eastern coastal areas. Northern India, particularly the Himalayan region, exhibits a greater interannual variability in Tmax, with June showing the most pronounced fluctuations. The study also highlights an increase in the frequency and intensity of HWs, especially in central and southern India, with the Chandigarh-Haryana-Delhi region recording the highest occurrences. A critical finding is the strong inverse relationship between the AISMR and conditions in the subsequent premonsoon season. Specifically, drought in the antecedent AISMR results in reduced soil moisture, which is strongly associated with higher premonsoon Tmax and an increased frequency of extreme heat events across India, particularly in regions prone to severe heat during this season. Drought conditions during AISMR are closely linked to higher HW frequencies in the following summer, especially in the central, northeast-central, and east-coastal regions. The frequencies of HW days, SHWs, and LHWs are significantly greater in years following AISMR droughts than in those following excess rainfall, indicating that drought years are more likely to lead to widespread HW activity. Despite the overall warming trends, some regions, such as the Indo-Gangetic Plain and parts of the Himalayan region, show cooling trends, although these trends are less widespread. The onset of the monsoon in June tends to reduce the intensity and spatial extent of warming, particularly in the central and eastern coastal regions, although significant HW trends persist in northwestern India and along the east coast. This study underscores the crucial role of AISMR in influencing HW events across India and highlights the need for adaptive strategies that account for the interactions between monsoon rainfall and HW risk, providing valuable insights for mitigating the impacts of HWs in the context of global warming. [ABSTRACT FROM AUTHOR]

The magnetic parameters within lacustrine sediments serve as invaluable proxies for deciphering the paleoenvironmental and paleoclimatic conditions. However, the dissolution of magnetic minerals can significantly alter detrital magnetic mineral assemblages, thereby complicating their interpretation in paleoenvironmental reconstructions. In an effort to clarify the impact of this dissolution on the grain size of magnetic minerals in lacustrine sediments, we undertook a thorough analysis of the rock magnetic properties on samples from the interval characterized by low ARM (anhysteretic remanent magnetization)/SIRM (saturation isothermal remanent magnetization) values between 140 and 320 ka in the Heqing (HQ) lacustrine drill core, located in Southwest China. Temperature-dependent magnetic susceptibility and FORC diagrams revealed a predominance of single-vortex and pseudo-single domain (PSD) magnetite and maghemite within the sample. When compared to samples from both the glacial and interglacial periods, the high SIRM, elevated magnetic susceptibility, and low ARM/SIRM ratio intervals from 140 to 320 ka suggested a high concentration of magnetic minerals coupled with a relatively low concentration of fine-grained particles in the sediments. The reductive dissolution of the fine-grained magnetic oxides is responsible for the reduction in the fine-grained magnetic particles in this interval. Our findings indicate that pedogenic fine-grained magnetite and maghemite are the first to dissolve, followed by the dissolution of coarser-grained iron oxides into finer particles. This process underscores the complex interplay between magnetic mineral dissolution and grain size distribution in lacustrine sediments, with significant implications for the reliability of paleoenvironmental interpretations derived from magnetic parameters. [ABSTRACT FROM AUTHOR]

We present monsoon variability records for the Holocene using multi-proxy approach (environmental magnetism, carbon isotope, and total organic carbon) from a 146 cm thick sedimentary profile in the Kotikanasar meadow (Chakrata), Northwest Himalaya. The chronology of the record was constrained by five AMS 14C ages. The carbon isotope (δ13C) and Total Organic Carbon (TOC) data highly variable which vary between −26.62‰ and −22.46‰ (C 3 -plants) and 0.1–∼4%, respectively, indicating paleo-vegetation history and productivity of the studied area. The environmental magnetism is highly fluctuating in the Early Holocene with high concentrations of magnetic minerals during the high monsoon conditions and vice-versa. Intense Indian Summer Monsoon (ISM) phases were identified during the Early and Late Holocene i.e., ∼9.2 to 7.4 ka, and ∼4.8 ka to Modern which shows warm and wet climate. While decline in the ISM intensity during ∼7.4 to 4.8 ka which indicates cold and dry climatic condition in the Northwest Himalayan regions. From ∼9.2 to 7.4 ka, highly fluctuating climate linked with the Early Holocene warming. Sediment profile exhibits aridity in climate accompanying with the high influence of mid-latitude westerlies during ∼7.4 to 4.8 ka from Northwest Indian regions. Hence the long-term fluctuation in the climate governed by the changes in the North Atlantic Ocean circulation as well as variations in the incoming solar radiations. [ABSTRACT FROM AUTHOR]

Speleothems from the Gupteswar and Kadapa caves were investigated using trace element (TE) ratios (Mg, Ba, Sr, Rb, Mn, Ti, U) over the last 7000 years, supported by 230Th/234U dating, to understand the regional and local climate variability induced by the Indian Summer Monsoon. The behavior of TE in calcite is influenced by temperature, seepage pathways, bedrock chemistry, and vegetation cover above the cave. A continuous decrease in the Ba/Sr ratio since 7 ka BP indicates changes in regional precipitation or local moisture availability during this period. However, determining changes in drip water rate and chemical composition is challenging due to the lack of supporting data. Variations in the TE ratios suggest significant climate and depositional changes at ∼4.2 ka BP and ∼2.8 ka BP. A decline in precipitation was observed between 4.2 and 3.8 ka BP and at ∼2.8 ka BP, with an increase in aeolian deposition at the study site since 3.8 ka BP because of preceding dry conditions. The moist and dry climate phases deduced from stable isotope values corroborate the variations in trace element ratios, affirming the paleoclimatic significance of the studied trace elements in tropical cave deposits. A probable explanation for the decline in precipitation at the study location around 4.2 ka BP is the southward migration of the Intertropical Convergence Zone (ITCZ) along with a negative phase of the Indian Ocean Dipole. The prevailing dry conditions in this region could have impacted the northward monsoonal winds, contributing to the decline of the Indus Valley Civilization. Another abrupt change observed at ∼2.8 ka BP can be linked to low solar activity and the southward movement of the ITCZ, coupled with enhanced El Niño-Southern Oscillation activity. [ABSTRACT FROM AUTHOR]

The drainage basins of Peninsular India are characterized by silicate-dominated lithologies, and influenced by Indian Summer Monsoon (ISM) precipitation. The Godavari River Basin (GRB), the largest river basin in Peninsular India situated within the ISM region, represents an ideal case for assessing weathering and climate interaction at different timescales. In this contribution, major and trace elemental geochemistry of a radiocarbon-dated sediment core (CY; 54.2 m long) from the Godavari delta region was investigated to reconstruct erosional changes in the Godavari basin in response to ISM variations during the Late Holocene. Comparison of geochemical data for the CY sediments and their possible sources confirm dominant sediment supply from the Deccan basalts and Archean Gneisses to the site. A distinct increase in Ti/Al, Ca/Al, and Cr/Al, along with a decrease in CIA* and LREE/HREE at 3.2 ka BP, point to relative increase in sediment supply from the Deccan Traps. Inverse model calculations of Al-normalized ratios of selected elements (Ti, Fe, V, Cr, Cu, Co) estimate that the core site on average receives ∼41 % sediments from the Deccan regions, which increased by ∼20% since last 3.2 ka BP. This accelerated erosion is attributed to the coupled effect of aridity-induced Deccan upland erosion with a relative decrease from the Archean rock source. This period of accelerated erosion coincides with the abandonment of Chalcolithic settlements. [ABSTRACT FROM AUTHOR]

In this study, we aim to reconstruct southern India's intrinsic environmental changes over the past 1500 years from 3330 to 1830 cal BP by investigating the sedimentation and weathering dynamics in Lake Shantisagara, one of Karnataka's largest lakes. Four distinct climatic phases were delineated based on sedimentological, geochemical, and End Member Modelling Analysis (EMMA) results. Phase 1 (3330-3100 cal BP) is a short-term low rainfall zone characterized by a calm hydrodynamic environment and weak chemical weathering. Phase 2 (3100-2800 cal BP) is a climatically unstable phase, fluctuating between low and high rainfall conditions. Phase 3 (2800-2200 cal BP) is characterized by a stable, low rainfall climate with weak fluvial activity and chemical weathering. It is followed by a highly unstable phase marked by frequent extreme climatic events (Phase 4; 2200-1830 cal BP). Our study reveals a highly unstable hydrodynamic condition that culminated in potentially catastrophic high rainfall events that triggered intense and frequent floods in southern India around ∼2208, 2054, 1958, and 1891 cal BP. Comparative studies of regional records show that the regional climate pattern is similar. There is a strong effect of Total Solar Irradiance (TSI), Sea Surface Temperature (SST) off the Malabar coast, location of the Intertropical Convergence Zone (ITCZ), and the El Niño Southern Oscillation (ENSO) on the monsoon system in southern India. This suggests that there is a global teleconnection. [ABSTRACT FROM AUTHOR]

This study focuses on the impact of the stratospheric quasi-biennial oscillation (QBO) on the early stage of the Indian summer monsoon (ISM) in May and June, which has thus far been an ambiguous topic of research. It is found that the 50-hPa QBO in the preceding winter and spring is significantly and negatively correlated with precipitation in the southern Arabian Sea and central India in May, which shifts northward to northern India in June. This correlation is nearly the opposite for the 10-hPa and 20-hPa QBO. An easterly phase of the 50-hPa QBO corresponds to a colder and higher tropopause over the subtropical ISM region which is related to vigorous convection over India. Meanwhile, the QBO-related meridional dipole pattern of zonal wind from the stratosphere to troposphere in the subtropics and mid-latitudes connects to an anomalous high in the upper troposphere across the subtropical land and the northern Arabian Sea, which causes an anomalous descent and in situ adiabatic heating. This heating supports an enhanced meridional land-sea thermal contrast and thus an early and strong ISM. The situation for westerly 50-hPa QBO is generally the opposite. The climate models from the Coupled Model Intercomparison Project Phases 6 (CMIP6) can generally reproduce the QBO–ISM relationship in June (but not in May), though with some discrepancies from the observation. Inter-model comparison demonstrates that better representation of the QBO–ISM correlation depends well on a better simulation of the QBO-related meridional dipole of zonal wind in the subtropical ISM region. [ABSTRACT FROM AUTHOR]

Abstract The Bengal Fan is the largest submarine fan on Earth with a complex submarine channel system. Therefore, it is challenging to understand the evolution of Bengal Fan sediment source‐to‐sink processes. Here we present a synthesis of high‐resolution environmental magnetic records of five sediment cores from the central and lower Bengal Fan to reconstruct sedimentation history for the past 45 ka. Rock magnetic measurements and electron microscopic analyses reveal that detrital (titano)magnetites are the dominant magnetic minerals in the central fan sediments, while lower fan deposits exhibit enhanced magnetofossil contribution. During the last three marine isotope stages, glacial periods have increased detrital magnetic mineral concentration and grain size compared with interglacial periods. This increase is primarily attributed to the weakening of the Indian summer monsoon. Spatially, magnetic mineral concentration and grain size show decreasing trends from north to south and from east to west in the Bengal Fan, which may be modulated by submarine channel shifts. Deposition center migration driven by sea level fluctuations and sediment provenance variations were key factors controlling magnetic mineral concentration and grain size. Therefore, magnetic proxies serve as sensitive indicators of sedimentation patterns within the Bengal Fan. The spatiotemporal distribution of magnetic particles provides valuable insights into the source‐to‐sink dynamics and the dominant factors affecting sediment transportation in global submarine fans.

Identifying the late Holocene Indian summer monsoon (ISM) changes and their possible forcing mechanisms provides an important perspective for understanding the current monsoon shifts driven by anthropogenic climate change within a natural baseline. In this study, we present a well-dated, ca. 4.0 ka grain-size sensitive component record from Lake MangCo, located in the southeastern Tibetan Plateau. The record depicts late Holocene ISM evolution and centennial-scale precipitation events superimposed on millennial-scale climate changes. The results indicate that precipitation was relatively high during the first half of the late Holocene, likely before 2.0 cal ka BP, followed by a period of relatively reduced precipitation thereafter, which indicates that the Northern Hemisphere summer insolation (NHSI) has primarily controlled ISM intensity. A slight increasing trend in ISM strength since 1.1 cal ka BP was observed, which may correspond to the reported “2.0-kyr-shift” and could be related to warming tropical temperatures. Three low precipitation intervals, occurring at ∼1.1, 2.0, and 3.2 cal ka BP, align well with known centennial-scale ISM weakening events during the late Holocene, such as the Medieval Warm Period (MWP) and the “2.0-ka-dry-event.” Our findings further validate the climatic effects of tropical ocean–atmospheric interactions in the Pacific and Indian Ocean basins on ISM variabilities at centennial timescales.

This study enhances existing understanding of extreme precipitation spells induced by cloudburst-like (EPS-CBL) events in India, emphasizing climatology and geographical distribution often overlooked by traditional observations. EPS-CBL is defined as continuous rainfall exceeding 200 mm/day and intermittent extreme rates above 30 mm/hour or the 99.9th percentile threshold, differing from definitions proposed by the IMD and other studies. Our findings reveal significant biases in various precipitation products compared to IMD data. CMORPH consistently outperforms other datasets by capturing more extreme events and showing significant rising trends in regions influenced by orographic effects, such as the Himalayan foothills and the Western Ghats. Although IMERG aligns well with IMD overall, it exhibits variability in extreme events, while IMDAA tends to underestimate these extremes, especially in complex terrains. Analysis of EPS-CBL trends from 2000 to 2022 highlights regional differences across datasets. Both CMORPH and IMERG show an increase in EPS-CBL events in the hilly region, while IMDAA indicates a decline. Understanding EPS-CBL climatology provides valuable insights for modeling studies exploring the underlying mechanisms of these events.

This study examines the inter-annual variation of the difference in summer precipitation over the east and west side of the Ailao Mountain， as well as its relationship between the East Asia summer monsoon and the South Asia summer monsoon based on in situ observations， reanalysis products and model sensitivity experiments.As the result， climatological statistics show that there is more precipitation on the west side than on the east side of the Ailao Mountain.Compared to the total summer precipitation amount observed over five pairs of state-level weather stations， the difference is higher on the north part than on the south part， with negative correlations to some extent.The observed differences in precipitation are generally with a negative correlation between the East Asia summer monsoon index， and with a positive correlation between the South Asia summer monsoon index.The linear correlation coefficients with the index of monsoon interface， which stands for the relative strengths of the East Asia and South Asia monsoons， are higher than those with one single monsoon.With one positive and one negative year selected based on the index of monsoon interface， we design and conduct a set of model sensitivity experiments through changing the boundary condition of wind and water vapor fields respectively to quantify the impact on precipitation difference of monsoons.The result shows that the anomaly in the wind field is the major contributing factor of the difference in precipitation on the two sides of the Ailao Mountain.On the other hand， the anomaly in the water vapor field makes synchronized changes in precipitation on both sides of the mountain， while it contributes little to the precipitation difference.

The Indian Central Himalaya Region (ICHR), the northern topographic front of the Indian summer monsoon (ISM), is an ideal location to study topography-climate interactions because two weather systems—the ISM and mid-latitude westerlies (MLW)—create distinct eco-climatic regimes from tundra (north) to tropical (south). The region's paleoclimatic studies show considerable climatic variations since the late Pleistocene. We evaluated 29 paleoclimatic records from the region and synthesized the results semi-quantitatively using the weighted palaeoclimate index (WApCI) to better understand the important climatic events and their driving mechanisms. According to the WApCI, the region has at least six enhanced monsoonal periods and eight drier spells during the past 34 ka. The cold-dry climatic events, such as the last glacial maxima (LGM), Younger Dryas (YD), 8.2 ka, and 4.2 ka, are associated with northern-hemisphere (NH) climate dynamics and propagated via MLWs. While, the warmer phases are dictated by the insolation-driven ISM dynamics. The WApCI's reconstructed rainfall anomaly aligns with paleoclimatic-model experiments for dynamically generated Paleoclimate Modeling Intercomparison Projects (PMIP3/PMIP4) rainfall for chosen time-slices (last-millenium, historical, mid-Holocene, and LGM). Finally, the Granger causality test determines the temporal relationship between the climatic drivers/forcing indices and primary meteorological parameters. The results showed that summer and post-monsoon precipitation is primarily influenced by total solar irradiation, winter precipitation is driven by a complex mix of variables, and pre-monsoon precipitation is driven by the Arctic oscillation. Based on the facts, we hypothesize that past climate variability demonstrates a complex interplay of local and hemisphere teleconnections in ICHR's climate dynamics. [ABSTRACT FROM AUTHOR]

It is found that the winter (December–February) barrier layer (BL) in the Bay of Bengal (BoB) acts as a dynamical thermostat, modulating the subsequent summer BoB sea surface temperature (SST) variability and potentially affecting the Indian summer monsoon (ISM) onset and associated rainfall variability. In the years when the prior winter BL is anomalously thick, anomalous sea surface cooling caused by intensified latent heat flux loss appears in the BoB starting in October and persists into the following year by positive cloud-SST feedback. During January–March, the vertical entrainment of warmer subsurface water induced by the anomalously thick BL acts to damp excessive cooling of the sea surface caused by atmospheric forcing and favors the development of deep atmospheric convection over the BoB. During March-May, the thinner mixed layer linked to the anomalously thick BL allows more shortwave radiation to penetrate below the mixed layer. This tends to maintain existing cold SST anomalies, advancing the onset of ISM and enhancing June ISM precipitation through an increase in the land-sea tropospheric thermal contrast. We also find that most of the coupled model intercomparison project phase 5 (CMIP5) models fail to reproduce the observed relationship between June ISM rainfall and the prior winter BL thickness. This may be attributable to their difficulties in realistically simulating the winter BL in the BoB and ISM precipitation. The present results indicate that it is important to realistically capture the winter BL of the BoB in climate models for improving the simulation and prediction of ISM. [ABSTRACT FROM AUTHOR]

The Central Ganga Basin is one of the most densely populated regions of India. It is agriculturally diverse and contributes much to the Indian economy. The region has housed numerous ancient and mediaeval empires. This study presents a continuous record of the paleomonsoon from the Chandrika Devi lake, Lucknow district of Uttar Pradesh, India which is linked with paleo vegetational shifts over the last ~6000 years (5871–75 cal yr BP). The chronology of the lake core is based on three accelerated mass spectrometry (AMS) radiocarbon and two Optically Stimulated Luminescence (OSL) dates. The multiproxy data (grain size, major and trace element ratio, total organic carbon (TOC wt%), carbon isotopes (δ13Corg‰) and pollen), suggest that the lake was initially a part of the Gomti river that began to transform into a lake at ~5000 cal yr BP with weakening of the Indian summer monsoon (ISM) in the Central Ganga Basin. The lake formation was completed at ~4100 cal yr BP under the influence of the 4.2 ka arid event. This phase marks the beginning of human presence as well as agricultural activities in the lake region with the appearance of Cerealia pollen and other agricultural taxa. The agricultural activity surrounding the lake catchment peaked at ~3000 cal yr BP. The lake gradually shrank and became a marshy lowland at ~75 cal yr BP. Our study is significant because it is the first comprehensive multiproxy study from the Lucknow region in the Central Ganga Basin on paleomonsoonal variability and its relationship to human activity, agricultural practices during the Late-Holocene with a focus on the 4.2 Ka arid event. Also, pollen record suggests that the changes in agriculture and human activity began just after 4.2 ka arid event in the study area. [ABSTRACT FROM AUTHOR]

The sensitivity of increased vertical resolution in the present operational global forecast system (GFS) at T1534 (~ 12.5 km) model on the short to medium range forecast of Indian summer monsoon (ISM) is investigated during June to September for year of 2020. The present operational GFS model has 64 hybrid vertical layers with model top at 0.27 hPa (~ 54 km) which is enhanced to 128 hybrid levels with model top at 0.01 hPa (~ 80 km). The results reveal that GFS L128 (EXPT) shows improved mean precipitation distribution over the central India, Indo-Gangetic Plain, and southern Peninsula region compared to GFS L64 (CTRL) forecast. It is found that CTRL forecast predicts around 20% excess rainfall over the central India region which is reduced to 3% excess in EXPT forecast. However, EXPT shows excess rainfall (23%) over the northeast India, Himalayan foothills, Western Ghats (WGs) and Bay of Bengal (BoB) region compared to both observation and CTRL forecast (19.5%). The precipitation probability distribution function (PDF) shows notable improvement in the heavy to extreme category rainfall in EXPT for all the lead times over the central India region. The improvement in the total rainfall over the central Indian landmass region is likely contributed by the realistic convective and large-scale rainfall in EXPT forecast. The enhanced vertical resolution in EXPT likely helped in resolving the vertical moisture distribution resulting better moist-convective feedback in the atmospheric column. Moreover, skill score analysis based on precipitation clearly brings out the better model fidelity with enhanced vertical levels in EXPT forecast over the central Indian landmass region. In addition to daily scale, diurnal cycle of precipitation shows realistic phase and amplitude over the above region in EXPT forecast compared to CTRL. Finally, the fidelity of increased vertical velocity is tested for few extreme rainfall cases and it is found that EXPT is able to retain the intensity of the extreme rainfall with longer lead times over that of CTRL forecast. With the increasing trend in extreme rainfall events over India, the EXPT forecast shows its potential in improving heavy rainfall forecasting during summer monsoon. Additionally, the enhance skill of predicting extreme rainfall events is crucial for several societal applications, such as businesses and energy trading sectors increasingly rely on weather forecasts. Therefore, the present study is not only beneficial for the current operational prediction system but also paves the way for further enhancements. [ABSTRACT FROM AUTHOR]

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Precipitation can induce a surface sensible heat flux since the raindrops are generally cooler than the surface. This precipitation‐induced sensible heat flux (QP) is typically ignored in models. However, during heavy rainfall, QP can be large and may not be negligible such as over India during the summer monsoon season. We provide the first results of incorporating QP in a simulation that shows ∼2% (∼5%) reduction in precipitation over India compared to the simulation without QP during a monsoonal active phase in 2017 (2018). This reduction was primarily due to a reduction in vertical advection of moisture. Additionally, QP modified the spatial distribution of precipitation with 40% of the geographical area encountering alterations of at least 20% in precipitation. This change in precipitation distribution across the region can have important implications for regional agriculture and irrigation practices. Changes in the partitioning of surface heat flux components due to QP is also discussed. Plain Language Summary: Rainfall during the monsoon season in India has widespread influences on agriculture and water supply. Therefore, understanding and predicting monsoon rainfall is of utmost importance. Among many parameters, surface energy budget influences precipitation. One of the components of the surface energy budget is the sensible heat flux due to precipitation (QP), which arises because the temperature of raindrops is typically different (cooler) than the temperature of the surface. The QP is thought to be small and is neglected in climate models. By incorporating QP in a regional climate model, we show its influence on monsoon precipitation and surface energy budget. We found that QP reduces precipitation by ∼2% and affects the spatial distribution of precipitation, which may have implications for regional agriculture and irrigation strategies. We also show that QP leads to significant changes in the magnitude and spatial distribution of surface energy budget terms. Key Points: Precipitation‐induced surface sensible heat flux is typically neglected in numerical weather and climate modelsModel simulations show that rain‐induced sensible heat flux reduces monsoonal precipitation and changes its spatial distributionChanges in the spatial distribution of monsoonal rain can have important implications for regional agriculture and irrigation practices [ABSTRACT FROM AUTHOR]

The advent of weather and climate models has equipped us to forecast or project monsoon rainfall patterns over various spatiotemporal scales; however, utilizing a single model is not usually sufficient to yield accurate projection due to the inherent uncertainties associated with the individual models. An ensemble of models or model runs is often used for better projections as a multimodel ensemble (MME). This study analyzes the accuracy of MME in simulating the Indian summer monsoon rainfall (ISMR) variability using Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations. The results highlighted that although the MME primarily reproduces the observed pattern and annual cycle of rainfall, significant biases are noted over homogeneous meteorological regions of India, except northeast India. To overcome this issue, an analysis of variance (ANOVA) and post hoc statistical tests are employed to identify a group of models for which the modified MME gives a better estimate of rainfall and reduces the bias significantly. Our findings underscore the potential of ANOVA and post hoc tests as a practical approach to enhancing the accuracy of multimodel ensemble rainfall for the assessment of model projections. [ABSTRACT FROM AUTHOR]

Episodes of dry‐air intrusion over northern India have been observed during break phases of the Indian summer monsoon (ISM). Previous investigations have provided observational evidence of a significant reservoir of unsaturated air over the northern Arabian Sea, serving as the source of this dry‐air intrusion. It was also suggested that the monsoon low‐level jet, which typically transports moisture to continental India during the active phase, instead transports dry air during the break phase of the ISM. While the existence of dry‐air intrusion is well‐documented through observations, its representation in climate models remains uncertain. It is important to enhance our understanding of the process of dry‐air advection in climate models to assess their fidelity in simulating the climate over the region. In this study, we quantify the extent of dry‐air intrusion and examine its mechanisms in simulations from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Most CMIP6 models analysed in this study simulate the observed pattern of dry‐air advection over continental India realistically during the summer monsoon‐break phase. Some models also simulate dry‐air transport from West Asia, possibly due to an overly smoothed representation of orography. Furthermore, the majority of CMIP6 models successfully capture the intrinsic modes associated with the dry monsoon phase, as demonstrated by empirical orthogonal function analysis of low‐level zonal winds. Our analyses indicate that global climate models exhibit better skill in simulating dry processes of the monsoon compared with moist processes. These findings uncover previously underexplored aspects of the monsoon, which are essential for assessing future regional climate changes accurately. [ABSTRACT FROM AUTHOR]

The present study is done in the Beas river (Manali to Mandi town) after the July 2023 flood to assess the geomorphic and geological vulnerability of the terrain and understand the role of human intervention in the disaster. The study is based on preliminary field observations and morphometric analysis that indicates that the surfaces proximal to the trunk riverbed and the ephemeral tributary channels suffered maximum damage. Along the upper Beas river, the lateral erosion caused by hyperconcentrated flows saturated with paraglacial sediments partly obstructed the river and also increased the erosivity that also led to remobilization of midchannel bars along with the uprooted trees. In the downstream (southern mountain front), maximum damage was caused by activating seemingly dormant ephemeral tributary channels. The slope-channel coupling locally bulked the sediment supply of the trunk river. The disaster was force amplified when the river was temporarily obstructed by the manmade structures (e.g., suspension bridges), and most importantly, urban settlements (largely hotels) on the flood plain. Also, many public buildings suffered as these were constructed in/along the ephemeral tributary channels, which were temporarily blocked by these structures, as well as by logged tree trunks. The Beas flood is yet another brutal reminder to change our perception towards the developmental approach, given that extreme events are projected to increase in the Himalaya. [ABSTRACT FROM AUTHOR]

As one of important large-scale systems in south Asia, the Indian summer monsoon (ISM) can affect the moisture budget and cloud processes over the Tibetan Plateau (TP). The influneces of ISM on cloud and precipitation of the Eastern TP (ETP) are discussed via a cloud-resolving model. The outbreak of ISM can activate the moisture transport between TP and the southern ocean in May, which reaches its annual most active period in July. The simulation results show that, compared to a normal ISM year, the moisture transport is intensified in pre-summer and is weakened in a strong ISM year, leading to more pre-summer deep clouds and rainfall. However, a weak ISM year exhibits weak pre-summer moisture transport and active summer moisture transport, resulting in few pre-summer deep clouds and rainfall. The summer moderate cloud cells are reduced in the strong ISM year while are promoted in the weak ISM year, taking responsibility for the summer precipitation variations. The ETP daily maximum precipitation appears at around 21:00 LST and increases after mid-April, reaches its maximum in summer. The model also suggests that the ETP warm season precipitation variation in the strong ISM year is closely related to deep convective cloud (DCC) properties (e.g. frequency and cloud water content). However, deep clouds (cloud depth > 4.0 km) rather than DCC contribute more to the precipitation diurnal variations during June and July in the weak ISM year. [ABSTRACT FROM AUTHOR]

Forecasting Indian Summer Monsoon Rainfall (ISMR) is a formidable task due to its intricate variability. This study harnesses the power of machine learning (ML) to decipher the chaotic trajectory within ISMR, drawing inspiration from ML's success in predicting analogous systems. By utilizing ERA-interim data, the method dissects ISMR's chaotic nature through correlation dimension-based techniques. Employing the Lorenz-96 model on daily rainfall data, trained with an Echo State Network (ESN), the technique discerns patterns within a span of 1 model time slightly trailing its performance in other systems. This discrepancy could stem from the intricacies of observational data and the training process involving 500 initial conditions. Notably, this method achieves accuracy in slightly over 50% of cases. Despite its current limitations, this approach exhibits promise in shedding light on the chaotic behaviour enforced in ISMR. As a result, it contributes to the advancement of monsoon forecasting techniques. Plain language summary: Predicting Indian Summer Monsoon Rainfall is a challenging task because it is highly variable. This study uses machine learning to better recognize the complex chaotic patterns in ISMR, using a type of data called ERA-interim. Apply a mathematical model called the Lorenz-96 model to daily rainfall data and train it using a neural network called an Echo State Network. This method can identify patterns in ISMR with up to about 1 model time unit, which is slightly less accurate compared to its performance in predicting other systems. This difference may be due to the complexities of the data used and the training process, which involves 500 initial conditions. Importantly, this approach is successful in predicting ISMR accurately in slightly over 50% of cases. While it has some limitations, this method shows promise in helping us recognize the chaotic behaviour of ISMR and may be used in improving monsoon forecasting techniques in future. [ABSTRACT FROM AUTHOR]

Abstract The mid-Brunhes dissolution interval (MBDI; Marine Isotope Stage (MIS) 13 to 7; ~ 533–191 ka) is characterized by various paleoclimatic/paleoceanographic events in the world. We investigated fossil deep-sea benthic foraminifera and sediment geochemistry at the onset of the MBDI (~ 670–440 ka) using Ocean Drilling Program (ODP) Site 758 and core GPC03 in the northeast tropical Indian Ocean (TIO), primarily focusing on the relationship between the paleoceanographic conditions of the surface and deep oceans. Based on multi-dimensional scaling, MDS axis 1 is related to the specific depth habitats of benthic foraminiferal fauna, possibly at the trophic level. In MDS axis 1, the difference between the two core sites was smaller from ~ 610 to 560 ka, whereas it was larger from ~ 560 to 480 ka. In contrast, MDS axis 2 may be related to the low food supply at episodic food pulses/relatively stable and low food fluxes. MDS axis 2 showed generally similar stratigraphic variations between the two cores during ~ 610–560 ka, but was different during ~ 560–480 ka. The proportion of lithogenic matter to biogenic carbonate was relatively low from ~ 610 to 530 ka under the highstand when sediment transport to the study area was reduced. Thus, both the depth gradient in the distribution of benthic foraminiferal fauna and the lithogenic supply between the two cores changed coincidently across the MIS 15/14 (~ 570–540 ka) transition. Such paleoceanographic conditions across MIS 15/14 transition were attributed to the long-term weakening of the wind-driven mixing of surface waters, which might have been caused by the weakening of the Indian summer monsoon in the northeast TIO, possibly with the northward displacement of the InterTropical Convergence Zone in the Northern Hemisphere. In particular, the depth gradient in the distributions of benthic foraminiferal faunas represents the paleoceanographic linkage between the surface and deep oceans through particulate organic matter ballasting by calcareous plankton skeletons in addition to lithogenic matter, which changed transiently and significantly across MIS 15/14 transition close to the onset of the MBDI.