Indian Summer Monsoon Research Articles

Antarctica warming induces alarming negative impact on Indian summer monsoon rainfall

Antarctica warming induces alarming negative impact on Indian summer monsoon rainfall

Mangrove flourishing/deterioration under the control of the Indian Summer Monsoon over the past ∼3,195 years in Phang Nga Province, Thailand.

Mangrove wetlands are strategic locations for mitigating climate changes. In order to address the harm of rapid climate change to mangrove ecosystems, it is necessary to scientifically predict the fate of mangrove ecosystems, which can be achieved by reconstructing the development history of mangrove forests. This study analyzes the contribution of mangrove-derived organic matter (CMOM) from sediment core F in Phang Nga Province, Thailand by using the endmember mixing model based on stable organic carbon isotopes (δ13Corg) and C/N (molar) ratio. The variations of CMOM over the past ∼3195calyr BP indicate that mangrove forests underwent three periods of flourishing: ∼3195-2620calyr BP, ∼2030-1130calyr BP, and ∼410-0calyr BP, and two periods of deterioration: ∼2620-2030calyr BP and ∼1130-410calyr BP. Among the potential factors that might affect the development of mangrove forests, relative sea level (RSL), regional hydrodynamics, and human activities do not have notable effects on mangrove flourishment/deteriorating. However, climate factors, particularly air temperature, rainfall, and sea surface salinity are the main factors influencing the flourishing/deterioration of mangrove forests. In the Andaman Sea, these climatic factors are mainly driven by the Indian summer monsoon (ISM).

Changing spatiotemporal dependence of the precipitation-temperature during Indian Summer Monsoon using observational and CMIP6 model simulations

Changing spatiotemporal dependence of the precipitation-temperature during Indian Summer Monsoon using observational and CMIP6 model simulations

Precipitation Structure and Convective Intensity Over South‐East South Asia During Active and Break Spells of the Indian Summer Monsoon Using TRMM, GPM, Megha‐Tropiques Satellites and Reanalysis Data

Precipitation Structure and Convective Intensity Over South‐East South Asia During Active and Break Spells of the Indian Summer Monsoon Using <scp>TRMM</scp>, <scp>GPM</scp>, Megha‐Tropiques Satellites and Reanalysis Data

Changes in physical characteristics of extreme rainfall events during the Indian summer monsoon based on downscaled and bias-corrected CMIP6 models

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.

Palaeoclimatic Signatures Based on Pollen Fingerprints: Reconstructing Mid–Late Holocene Climate Dynamics in Northwestern Himalaya, India

This study presents a high-resolution palaeoclimate reconstruction based on a radiocarbon-dated 240 cm deep trench profile from Renuka Lake, Northwestern Himalaya, India. The palynological analysis provides insight into the palaeovegetation and palaeoclimatic dynamics of a subtropical, dense, mixed deciduous forest, predominantly characterized by Sal (Shorea robusta). The fossil pollen reveals the presence of tropical Sal mixed deciduous taxa, including Shorea robusta, Emblica officinalis, Murraya koenigii, Toona ciliata, Syzygium cumini, and Terminalia spp., which indicate that the region experiences a warm and humid climate with the strong Indian Summer Monsoon (ISM) during ~7500–4460 cal yr BP. Subsequently, Sal-mixed deciduous forests were replaced by highland taxa, viz., Pinus roxburghii and Abies pindrow, suggesting dry and cold conditions during ~4460–3480 cal yr BP. Additionally, warm and humid (~3480–3240, ~3060–2680, ~2480–2270 cal yr BP) and cold and dry conditions (~3240–3060, ~2680–2480, ~2270–1965 cal yr BP) recorded alternatively in this region. Improved ISM prevailed ~1965–940 cal yr BP, followed by cold and dry conditions ~940–540 cal yr BP. From ~540 cal yr BP to present, the appearance of moist deciduous taxa alongside dry deciduous and highland taxa in similar proportions suggests moderate climate conditions in the region.

Identification and Variability Analysis of New Homogeneous Summer Monsoon Rainfall Regions Over India by Using K‐Means Clustering Technique

ABSTRACTThe identification of new homogeneous Indian summer monsoon rainfall regions is important for both research and operational forecasting purposes. The homogeneous rainfall regions used by the India Meteorological Department include areas that are actually dissimilar in terms of both the amount of rainfall and its variability. In the present study, we have identified three primary clusters of homogenous summer monsoon rainfall zones (low, medium and high rainfall) of India by using K‐means clustering technique and Calinski–Harabasz (CH) index. The identified clusters are again subdivided based on the distance between the clusters into six homogenous rainfall zones such as Southeast India (SI), West India (WI), Central India (CI), West Coast of India (WC), Northeast India1&amp;2 (NE1 &amp; NE2). Summer monsoon rainfall exhibit a positive trend over the western and southern region of India (SI, WC, and WI) while the eastern part of India (CI, NE1 and NE2) exhibit a negative trend. The increased sea surface temperature of tropical north Atlantic during May is conducive for the enhanced summer monsoon rainfall activity over low rainfall zone (Southeast India and West India). Tropical North Atlantic SST during May is related with the subsequent warming of Indo Pacific Ocean and cooling of Central Pacific Ocean, which induces southeasterlies towards Indian region and strengthen the rainfall activity over SI and WI. The position and intensity of the upper‐level circulations have profound impact on the interannual variability of rainfall over different homogenous regions. Above‐normal rainfall over SI and WI (CI and WC) is enhanced by the upper‐level anticyclonic (cyclonic) circulation in Bay of Bengal (West Asia), which extends north westward (south eastward) to the Indian landmass. Indian Ocean warming during May is associated with above (below) normal rainfall over NE2 region (the eastern part of CI). Southern Ocean SST during May is significantly correlated with the rainfall over southwest coast of India, which is also indicated by the positive correlation between April southern Annular Mode and south west coast rainfall. Sea surface temperature during May in different ocean basins can be used as the potential predictors for improving the long‐range forecast of seasonal rainfall over newly identified homogenous rainfall zones.

High-resolution Indian summer monsoon (ISM) records during the last 1400 yrs BP from the Mahi river basin, Mainland Gujarat, India

High-resolution Indian summer monsoon (ISM) records during the last 1400 yrs BP from the Mahi river basin, Mainland Gujarat, India

Excessive equatorial light rain causes modeling dry bias of Indian summer monsoon rainfall

Simulating accurately the South Asian summer monsoon is crucial for food security of several South Asian countries yet challenging for global climate models (GCMs). The GCMs suffer from some systematic biases including dry bias in mean monsoon rainfall over the India subcontinent and excessive equatorial light rain between which the relationship was rarely discussed. Numerical experiments are conducted for one month during active monsoon with global quasi-uniform resolution of 60 km (U60 km) and 3 km (U3 km) separately. Evaluation with observations shows that U3 km reduces the dry bias over northern India and excessive light rain over the equatorial Indian Ocean (EIO) that are both prominent in U60 km. Excessive light rain in U60 km contributes critically to stronger rainfall and latent heating over the EIO. A Hadley-type anomalous circulation is thus induced, whose subsidence branch suppresses updrafts and reduces moisture transport into northern India, contributing to the dry bias. The findings highlight the importance of constraining excessive light rain for regional climate projection in GCMs.

Recent changes in ENSO’s impacts on the summertime circumglobal teleconnection and mid-latitude extremes

The boreal summer circumglobal teleconnection (CGT) provides a primary predictability source for mid-latitude Northern Hemisphere climate anomalies and extreme events. Here, we show that the CGT’s circulation structure has been displaced westward by half a wavelength since the late 1970s, more severely impacting heatwaves and droughts over East Europe, East Asia, and southwestern North America. We present empirical and modelling evidence of the essential role of El Niño-Southern Oscillation (ENSO) in shaping this change. Before the late 1970s, ENSO indirectly promoted CGT by modulating the Indian summer monsoon rainfall (ISMR). Since 1980s, the ENSO–ISMR link has weakened, but the westward-displaced ENSO forcing has been able to directly trigger a Rossby wave response at the exit of the East Asian westerly jet, resulting in a shift of the previous CGT’s North Pacific and downstream centers westward along the westerly jet waveguide. State-of-the-art climate models with prescribed anthropogenic forcing cannot simulate these changes, suggesting that they are driven by natural variability. This work highlights the importance of studying the impacts of changing ENSO to improve seasonal prediction of mid-latitude extreme events.

Quantitative Identification of Moisture Sources over the Tibetan Plateau: Spatial Distributions and Temporal Variabilities

Abstract The imbalanced hydrological cycles and water resource instability over the Tibetan Plateau (TP) are a topic of wide concern. Moisture sources affected by large-scale circulations are the main controls of precipitation and water resource distributions; as such, the quantitative identification of moisture sources is the key to the changes in precipitation or water-related environments, further aids efficient water management over the TP and in downstream regions of Asia. In this study, we primarily identified the spatial distributions and temporal variabilities of TP’s varied moisture sources, using HYSPLIT modeling and spatially dense precipitation isotopes (δ18O). Results showed that 1) moistures from the westerlies (West), the western arm of Indian summer monsoon (ISM) (ISM1), the eastern arm of ISM (ISM2), and the inner TP are the TP’s main moisture sources, with highest proportional contributions being &gt;70%, ∼40%, &gt;80%, and ∼10%–20% at northwest, southwest, and southeast sectors of the study area and the central TP region; 2) each moisture has its own region where it predominates and shows specific trends during 1951–2020 (West-northwest sector-increase, ISM1-southwest sector-increase, ISM2-southeast sector-decrease, and TP-central TP region-increase); 3) each of the moisture proportions and their temporal trends varied with different days of back trajectories (days 02–04–06–08–10), while their spatial patterns are similar; and 4) when verifying the modeled moisture proportions, precipitation δ18O is positively correlated or covaries with dry sources such as the West or TP moisture and inversely for humid ISM (ISM1 or ISM2) moisture. This work will improve our understanding of moisture-related hydrological, meteorological, and ecological studies in the “Asian Water Tower” region. Significance Statement The Tibetan Plateau (TP) is undergoing imbalanced hydrological cycles and water resource instability in response to global climate change. As the TP supplies vast quantities of water to Asia’s huge population, the socioeconomic impact caused by these changes is considerable. This study aims to quantitatively identify the spatial distributions and temporal variabilities of varied moisture sources over the TP in recent decades, using high-resolution modeling and ground-based precipitation isotopes. Results show that each moisture has its own region where it predominates and shows specific trends during 1951–2020. These findings can help to explain precipitation patterns or water resource distributions and provide insights into efficient water management over the TP and in downstream regions of Asia.

Investigating the Underlying Mechanisms of Monsoon Season Heavy Precipitation in Central Asian High Mountain Areas

Abstract In this study, fifth major global reanalysis produced by ECMWF (ERA5) reanalysis data from 1979 to 2022 were utilized to investigate extreme precipitation in the central Asian high mountain (CAHM) region, comprising the Pamir Plateau and western, central, and eastern Tianshan regions. This study found that westerlies and monsoons are the primary drivers of extreme precipitation, with distinct mechanisms in the southwestern and northeastern CAHM (divided at approximately 79°E). In the southwestern CAHM, a weak Indian summer monsoon (ISM) leads to negative potential height anomalies, enhancing meridional water vapor flux from the Bay of Bengal and Arabian Sea, thereby increasing precipitation. Conversely, extreme precipitation is associated with the negative phase of the Silk Road pattern in the northeastern CAHM. While the East Asian summer monsoon (EASM) plays a lesser role, it influences water vapor supplies and atmospheric circulation in the southwestern CAHM and modulate meridional wind position in the northeastern CAHM with the ISM, contributing to extreme precipitation. Seasonal analysis revealed May as the peak for extreme precipitation in the southwestern CAHM region, while extreme precipitation in the northeastern CAHM region peaked in the midmonsoon months (June and July) due to the synergy between monsoons and westerlies of different strengths passing through the CAHM. Significance Statement This study explores the occurrence and mechanisms of extreme precipitation in CAHM and explores their four key regions’ water vapor transport pathways during the monsoon period. CAHM has a sensitive and vulnerable ecosystem highlighting the importance of understanding their processes, including the roles of westerlies and monsoons. This is crucial for detecting abnormal water cycles under climate change, such as flood prevention, and enhancing mountain weather forecasting abilities for the monsoon period.

Climatology of extreme precipitation spells induced by cloudburst-like events during the Indian Summer Monsoon

Climatology of extreme precipitation spells induced by cloudburst-like events during the Indian Summer Monsoon

Can a 12-km GFS Model Simulate the Observed Relationship between Cloud Optical Properties and Extreme Rainfall of Indian Summer Monsoon?

Abstract The increase in the frequency of extreme precipitation in different parts of the world is well documented and a cause for concern in terms of global climate change. Although clouds are the only source of precipitation, there is a lack of knowledge about the type of clouds involved in extreme precipitation events. Satellite- and ground-based observations show that over the central Indian region (19°–26°N, 75°–85°E), about 60% of the extreme precipitation comes from deep convective clouds (DCCs), which have a cloud-top pressure (CTP) of less than 440 hPa and a cloud optical thickness (COT) of over 23. It was also observed that cloud liquid water (CLW) and COT show the highest correlation with extreme precipitation. Furthermore, CLW and COT show the highest contrast between extreme and nonextreme precipitation events. Simulations by a 12-km Global Forecast System (GFS, spectral) model show that the model underestimates the extreme precipitation threshold with increased forecast lead time. The simulation of associated cloud optical parameters is also poor at all lead times in different parts of India. The model also fails to capture the observed relationship between the frequency of extreme precipitation and deep convective clouds without showing any correlation between them at all lead times. This is possibly because the model simulates the observed vertical structure of the apparent heat source poorly at all lead times which leads to poor simulation of the observed relationship between cloud optical properties and extreme rainfall. Significance Statement The occurrence of extreme rainfall events is on the rise across the globe, and India is no exception. Clouds are the only source of rainfall; however, there is a lack of understanding about what type of clouds is causing them. Therefore, it is necessary to understand the relationship between cloud, convection, and extreme rainfall events during the Indian summer monsoon months. Furthermore, it is also important to investigate the skill of the current-generation global models to simulate them. This study highlights how cloud optical properties, convection, and extreme rainfall events are related to each other and also finds that a 12-km GFS model simulates these observed relationships poorly at all lead times leading to the poor simulation of extreme rainfall events.

Arctic sea ice variability and its multiscale association with Indian summer monsoon rainfall at different time scales

Arctic sea ice variability and its multiscale association with Indian summer monsoon rainfall at different time scales

Alternative mechanism of the Indian summer monsoon formation

Alternative mechanism of the Indian summer monsoon formation

Climate predictors in Indian summer monsoon forecasting: a novel De-correlated RVFL ensemble strategy

Climate predictors in Indian summer monsoon forecasting: a novel De-correlated RVFL ensemble strategy

Indian summer monsoon variations since late MIS3: A perspective from multiproxy evidence from Lake Xingyun in southwestern China

Indian summer monsoon variations since late MIS3: A perspective from multiproxy evidence from Lake Xingyun in southwestern China

Rhythmic Indian Summer Monsoon variability inferred from stalagmite δ18O and δ13C record during Middle to Late Holocene transition

Rhythmic Indian Summer Monsoon variability inferred from stalagmite δ18O and δ13C record during Middle to Late Holocene transition

Assessment of Droughts and Floods During the Indian Summer Monsoon Using the Coupled Model Intercomparison Project Phase 6 Historical and Future Simulations

ABSTRACTIndian 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.