Monsoon Research Articles

Empowering Identities: Cross Cultural Navigation in Mitali Perkins’ Monsoon Summer

The paper titled “Empowering Identities: Cross-Cultural Navigation in Mitali Perkins’ Monsoon Summer” explores the intricate ways in which cultural identity is shaped, negotiated, and empowered through cross-cultural experiences. Set against the backdrop of India and the United States, Monsoon Summer delves into the protagonist Jazz Gardner’s journey of self-discovery as she grapples with her dual heritage, familial expectations, and personal ambitions. This paper critically analyses the interplay of native and acquired cultures, examining how Jazz’s experiences in both countries reflect the broader struggles and challenges of bicultural individuals in navigating multiple cultural identities. Through a close reading of the text, the study highlights the tension between native culture and the pressure to assimilate into an acquired culture, emphasizing how this conflict is common in diasporic communities. Jazz’s inner turmoil as she balances her American upbringing with her Indian roots is explored through various lenses, including family dynamics, social expectations, and personal growth. Moreover, the research focuses on how Perkins presents cultural navigation as a pathway to empowerment, where characters like Jazz learn to embrace their multifaceted identities instead of choosing between them. By illustrating the complexities of biculturalism, the paper reveals how cross-cultural navigation can lead to self-empowerment, offering insights into the broader discourse on cultural identity formation in a globalized world. The study concludes that Monsoon Summer serves as a valuable literary piece for understanding the nuanced ways in which young individuals, especially those from diasporic backgrounds, reconcile their intersecting cultural identities while striving for a sense of belonging.

Possible Mechanisms behind Dominant Modes of Seasonal Cycle of Rainfall over India

Abstract The South Asian summer monsoon that occurs over four months from near summer solstice (June) to near Autumnal equinox (September) evolves within the season due to interaction with other climate components. Since most climate patterns are seasonally phase-locked, their interaction and feedback with monsoon should also be season-dependent. Here, using rain-gauge-based precipitation over India for seventy-four years, we show that the onset phase of the monsoon (June) is uncorrelated with rest of the season (July to September). Propagation of Madden Julian Oscillation (MJO) over the Indian Ocean triggers northward-propagation of precipitable water that plays a key role during the onset phase. MJO appears over the Western equatorial Indian Ocean both during the early and late Central Indian onset years. Normal and slow MJO phase propagation during early and late onset years respectively give rise to interannual variations in June rainfall. After onset, till the end of the monsoon season, interannual variability of the dominant seasonal mode of precipitation is regulated by the phase of the El Nino Southern Oscillation (ENSO) through anomalous moisture convergence. We show that, in June, ENSO doesn’t play key role because of the opposing impact on wind and moisture. However, from July to September, ENSO perturbs wind and moisture in a way that gives rise to positive feedback between monsoon, ENSO, and large-scale circulation. Such feedback of monsoon with ENSO results in a coherent impact of ENSO on monsoon precipitation in July-September. Our results suggest that dominant mechanisms for interannual variations of Indian monsoon rainfall in June and the rest of the season are different.

Deciphering the Relationship Between Moisture Flux and Monsoon Extreme Rainfall Over the West Coast of India

ABSTRACTThe west coast of India has recently been experiencing torrential monsoon rains, a trend that studies indicate is likely to continue under future warming scenarios. This study investigates the link between moisture flux and extreme rainfall over the west coast, using observational and reanalysis datasets for the monsoon seasons (June to September) from 1990 to 2023. The analysis shows that, over the Indian subcontinent, rainfall along the west coast is primarily influenced by large‐scale moisture flux from the Arabian Sea. By decomposing the vertically integrated moisture flux into dynamic and thermodynamic components, this study observes that the thermodynamic component of moisture flux exhibits an increasing trend over the southwest coast, while this increasing trend is more prominent for the dynamic component over the northwest coast. Extreme rainfall over the southwest coast is increasing at a rate of 0.23 mm per season, attributed primarily to the increase in the thermodynamic component of moisture flux. It is observed that the rate of sea surface temperature (SST) increase over the Arabian Sea is faster than over the Bay of Bengal, with the average SST over the southeast Arabian Sea exceeding 28°C in recent years. Observations indicate that warming over the southeast Arabian Sea is strongly coupled with moisture accumulation observed over the southwest coast. This study provides strong evidence of a link between moisture transport, extreme rainfall and SST, identifying the southwest coast as a region vulnerable to climate change. Over the northwest coast, the incidence of extreme rainfall is associated with the strengthening of dynamic processes, and the mean monsoon rainfall in this region is increasing in alignment with the rising dynamic component of moisture flux.

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&2 (NE1 & 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

Environmental features related to the decadal variation of South China Sea tropical cyclogenesis in the context of summer monsoon

Environmental features related to the decadal variation of South China Sea tropical cyclogenesis in the context of summer monsoon

Improved Simulation of East Asian Summer Monsoon in the High-resolution CESM1 and Its Causes

Improved Simulation of East Asian Summer Monsoon in the High-resolution CESM1 and Its Causes

Dengue dynamics, predictions, and future increase under changing monsoon climate in India

The global burden of dengue disease is escalating under the influence of climate change, with India contributing a third of the total. The non-linearity and regional heterogeneity inherent in the climate-dengue relationship and the lack of consistent data makes it difficult to make useful predictions for effective disease prevention. The current study investigates these non-linear climate-dengue links in Pune, a dengue hotspot region in India with a monsoonal climate and presents a model framework for predicting both the near-term and future dengue mortalities. Dengue mortality and meteorological conditions over a twelve-year period (2004–2015) are analyzed using statistical tools and machine learning methods. Our findings point to a significant influence of temperature, rainfall, and relative humidity on dengue mortality in Pune, at a time-lag of 2–5 months, providing sufficient lead time for an early warning targeted at curbing dengue outbreaks. We find that moderate rains spread over the summer monsoon season lead to an increase in dengue mortality, whereas heavy rains reduce it through the flushing effect, indicating the links between dengue and monsoon intraseasonal variability. Additionally, warm temperatures above 27°C and humidity levels between 60% and 78% elevate the risk of dengue. Based on these weather-dengue associations, we developed a machine-learning model utilizing the random forest regression algorithm. The dengue model yields a skillful forecast, achieving a statistically significant correlation coefficient of r = 0.77 and a relatively low Normalized Root Mean Squared Error score of 0.52 between actual and predicted dengue mortalities, at a lead time of two months. The model finds that the relative contributions of temperature, rainfall, and relative humidity to dengue mortality in Pune are 41%, 39%, and 20%, respectively. We use the dengue model in conjunction with the climate change simulations from the Coupled Model Intercomparison Project phase 6 for the future dengue mortality projections under a global warming scenario. In a changing climate, dengue-related mortality in Pune is projected to rise by 13% in the near future (2021–2040), 23–40% in the mid-century (2041–2060), and 30–112% in the late century (2081–2100) under low-to-high emission pathways in response to the associated increase in temperature and changes in monsoon rainfall patterns.

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.

Predictability of tropical cyclone track density in S2S reforecast

In this study, we examine the predictability of tropical cyclone (TC) track density in the subseasonal-to-seasonal (S2S) reforecast ensembles of the European Centre for Medium-range Weather Forecasts (ECMWF) using the method of average predictability time (APT). Eleven of the retrieved APT modes (APTMs) of TC track density possess an APT longer than 1 week. The most predictable of them, APTM-1, has an APT of almost three weeks and is found to be closely linked to the Boreal Summer Intraseasonal Oscillation (BSISO) and monsoon variability. Another discovery is the strong relationship between APTM-7 and the activity of mixed Rossby-gravity (MRG) waves and tropical depression (TD) type disturbances despite its short APT of ~12 days. We further carry out a simple case analysis to see how the relatively high predictability of APTM-1 manifests in the S2S model. Our work provides a new possibility for improving medium-range TC forecast skill, and has revealed how underlying tropical variability can play a role in determining TC predictability.

A record of monsoon rainforest variability from the Kimberley region in northwestern Australia

ABSTRACTNorthern Australia experiences extreme seasonality via the Indo‐Australian summer monsoon, with high inter‐annual variability in hydroclimate. Understanding the influence of hydrological variability on the landscape through the period of human occupation provides important environmental context to support the interpretation of the rich archaeological and rock art records of the region. The development of terrestrial records of environmental change has remained challenging due to the limited traditional palaeoenvironmental archives in the region. This study reports on the potential of sediments from ecologically significant monsoon rainforest patches to further elucidate the palaeoenvironmental history of the Kimberley. An ~19 000‐year record of monsoon rainforest variability is presented, inferred from pollen, charcoal and major element geochemical analysis. Monsoon rainforest‐associated taxa vary in abundance through the deglacial and the Holocene, which is compared to broad‐scale hydroclimate variability inferred from previous studies in the region. The persistence of arboreal, riparian and monsoon rainforest‐associated taxa suggest a positive moisture balance at the site throughout the period archived. Fire activity inferred from micro‐ and macrocharcoal is greatest over the last ~6000 years, and broadly corresponds to periods when monsoon rainforest‐associated taxa are less abundant. Challenges remain in using this type of site as an archive of environmental change, but they also present an opportunity to extend previous records both spatially and temporally with thousands of monsoon rainforest patches present across the Kimberley, and similar ecosystems found across northern Australia.

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.

Mechanisms and quantification: How anthropogenic aerosols weaken the East Asian summer monsoon

Anthropogenic aerosols could weaken the East Asian summer monsoon (EASM). This study investigated the regional effects of varying aerosol optical depth (AOD) on the EASM through qualitative and quantitative analyses for three subregions in eastern China. After assessing 38 CMIP6 models, four models (ACCESS-CM2, CanESM5, MIROC6, and MRI-ESM2-0) were selected for detailed analysis. Results showed that the weakening of EASM was predominantly attributed to anthropogenic aerosols. Increased AOD reduced land-sea temperature and pressure differences, weakening the EASM as indicated by the EASMI. Higher aerosol levels decreased surface shortwave radiation, land surface temperature, and evaporation, weakening the land-sea thermal contrast. Enhanced aerosol-induced cooling increased atmospheric stability and downward flow, suppressing upper air water vapor flux and precipitation. These findings underscore the critical role of anthropogenic aerosols in altering regional climate patterns and the importance of emission control to mitigate their effects on the EASM.

Paleolimnology and Natural Versus Anthropogenic Influx During the Late Holocene from Vembanad Wetland, Ramsar Site, Kerala, India

A multi-proxy study of diatoms, palynofacies, and grain size was conducted on a 100 cm core from Arookutty, Vembanad wetland, Kerala, India, to reconstruct paleolimnological changes during the late Holocene, with a focus on natural versus anthropogenic influences. Four distinct depositional phases, from ca. 500 BCE to ca. 400 CE, were identified, aligning with the Roman Warm Period (RWP). The period from ca. 500 BCE to ca. 450 BCE shows high freshwater and marine planktic diatoms, augmented by silicoflagellates and terrestrial organic matter, with a low dinocyst presence, suggesting a dynamic aquatic environment. The period from ca. 450 BCE to ca. 350 BCE is marked by a high sand content, indicating significant runoff and terrestrial influx, along with increased freshwater and marine planktic diatoms and evidence of human activity in the area. Similarly, the period from ca. 350 BCE to ca. 50 CE is characterized by high sand content and strong anthropogenic influences, with a rise in silicoflagellates, pointing to rising sea levels and high monsoonal precipitation. The period from ca. 50 CE to ca. 400 CE initially shows a decrease in sand and an increase in mud, reflecting a weakening southwest monsoon, likely due to solar variations. However, from ca. 300 CE to ca. 400 CE, sand content rises again, accompanied by high terrestrial influx and dinocysts, while silicoflagellates diminish completely. Thus, despite the dominance of the RWP, the coastal region experienced an extended period of reduced monsoonal activity for a particular span.

Suboxic waters of the eastern Arabian Sea shelter secondary chlorophyll maximum dominated by heterotrophic dinoflagellate Pronoctiluca spp. (order Noctilucales).

In the present study, we investigated the dinoflagellate assemblages in the upper water column (< 150-m depth), focusing on the suboxic waters of the eastern Arabian Sea (EAS) along 68°E from 8°N to 21°N during the southwest monsoon 2020 (SWM-2020). Dinoflagellate abundance was higher in the upper water column (0-80-m depth, mean ± SD = 411 ± 903 cells L-1) compared to deeper waters (80-150-m depth, mean ± SD = 128 ± 216 cells L-1). Among 11 identified taxonomic dinoflagellate orders, Peridinales were predominant in the upper waters column (71%, mean ± SD = 285 ± 858 cells L-1). Noctilucales, particularly Pronoctiluca spp., dominated the deeper water column (78%, mean ± SD = 99 ± 223 cells L-1), especially at the southern stations (8-14°N, mean ± SD = 158 ± 270 cells L-1). During SWM-2020, a strong vertical gradient in Pronoctiluca with increased abundance in suboxic, colder waters (< 0.05mL L-1, < 20°C) coincided with the secondary chlorophyll maximum layers (12°N, SCMLs ~ 145m, maximum 832 cells L-1). To compare this observation, samples were taken at 13°N during the winter monsoon (WM-2023), when the SCML peak was prominent (0.3µg L-1) in suboxic waters. The results revealed an increased abundance of Pronoctiluca close to the SCML depth (~ 117m) during WM. The canonical correspondence analysis revealed a positive correlation between SCML and Pronoctiluca, suggesting that Pronoctiluca relies on prey, i.e. low-light-adapted smaller phytoplankton. The higher abundance of Pronoctiluca compared to other oceanic regimes highlights the importance of assessing their crucial role in nutrient recycling and remineralisation within the suboxic environments of the EAS.

Climate Extremes Related with Rainfall Trends in Agniyar River Basin

The rainfall extremes variability due to climate change can be detected by the trend analysis. The trend analysis is implemented for the precipitation data period starting from year 1980 to 2021 (42 years) for the Agniyar river basin. The Mann-Kendall (M-K) test is employed to identify trends in precipitation, while The trend's magnitude is calculated using the Sen's slope method. The rainfall trend in Yearly Maximum Daily Rainfall (YMDR), South West Monsoon (SWM), Summer season, North East Monsoon (NEM), winter season and annual rainfall are computed. The results of twelve rain gauge stations in the Agniyar river basin revealed increasing, decreasing, and non-significant trends, with a notable increase in precipitation observed at some locations with acceptable significance. Most of the stations showing declining trend in precipitation based on Sen’s magnitude and negative slope. The outcome of this study needs of hour to the hydrologists, water resources engineers, water resources managers, environmentalist, sustainable development policy makers, inter-disciplinary climate change researchers and consultants involved in solving problems related to change in climate impact. The results of precipitation extremes are necessary for creating adaptation strategies in response to climate change.

Seasonal agricultural activities and monsoon shifts drive fluctuations in nitrogen levels in eutrophic coastal waters: A case study of Xiangshan Bay, China.

Xiangshan Bay, one of China's most eutrophic semi-enclosed bays, was studied to examine the seasonal distributions of salinity, temperature, nutrients, and nitrate isotopes (δ15N and δ18O) to elucidate seasonal variations in nitrate sources and the key factors driving nitrogen level fluctuations. Based on nitrate δ15N (6.1-8.9‰) and δ18O (0-5.7‰) values, the primary nitrogen sources in Xiangshan Bay were identified as domestic sewage and agricultural runoff, influenced by seasonal agricultural activities and monsoon-driven Changjiang Diluted Water (CDW) dynamics. Nitrate levels peaked in autumn (53.1±1.6μmol/L), due to intensive agricultural activity and strong CDW intrusion driven by the northeast monsoon. Conversely, the southwest monsoon in summer, coupled with higher nitrogen uptake due to warmer temperatures and increased light availability, resulted in the lowest nitrate levels (35.2±5.4μmol/L). In winter, reduced nitrate inputs were observed, reflecting minimal agricultural activity and weaker Changjiang discharge. Differences in nitrate levels between the upper and lower bay were attributed to weaker mixing and stronger local inputs in the upper bay.

Determining chlorophyll-a thresholds for characterizing algal bloom conditions: An ocean colour remote sensing approach.

The Indian coast has been experiencing an increase in algal bloom events over the decades. Owing to the regional and seasonal dynamics of algal biomass (proxy: chlorophyll-a, hereafter chl-a), a multitude of thresholds of chl-a has been defined for different parts of the global seas to determine algal bloom conditions. However, no such clear definition is given for the Indian coastal waters. The current study defined chl-a thresholds to demarcate algal bloom conditions for the coastal waters of India, accounting for the variability at hotspots (in accordance with reported events: secondary data), causative species, and satellite-retrieved long-term trends. The secondary data analysis identified nine bloom hotspots along the east and west coasts of India. Among the blooms, diatoms prevailed the most, compared to dinoflagellates and cyanobacteria. Quartile analysis was employed on satellite-retrieved daily chl-a anomaly to determine specific bloom thresholds. Consequently, these quartile thresholds were utilized to classify various bloom phases, such as the 25th percentile (Likely to Bloom), 50th percentile (Bloom), 75th percentile (Intense Bloom), and 90th percentile (Extreme Bloom). As per this percentile-based classification, the 'Bloom' category corresponds to a chl-a range of 0.89-0.94mgm-3 and 0.76-2.87mgm-3, for the identified hotspots along the east and west coasts, respectively. Likewise, during the 'Intense Bloom' phase, the chl-a concentration exceeds 0.99-1.47 and 1.12-4.46mgm-3 at the hotspots along the east and west coasts, respectively. The seasonality of blooms revealed an increasing trend during the pre-southwest monsoon period on the central east coast of India. On the west coast, significant upwelling during the southwest monsoon period has been substantiated to be conducive for blooms. This study provides an avenue towards utilization of the threshold criteria in detecting different phases of bloom using satellite data in coastal waters where field observations are limited due to various factors.

Evaluation of sources, spatial and temporal distribution, ecological and health risk associated with CAF (Caffeine) and DEET (N, N-diethyl-meta-toluamide) contamination in the urban groundwater parts of Vellore city, Tamilnadu, India.

Urban environments are heavily influenced by various activities, leading to contamination of water sources by emerging contaminants (ECs). Among these, caffeine (CAF) and N, N-diethyl-meta-toluamide (DEET) are notable ECs frequently found in domestic sewage due to human activities. Despite extensive research on emerging contaminants, limited studies have focused on the seasonal variations, human health and ecological risks of CAF and DEET in urban groundwater, particularly in Indian cities. This study aimed to analyze the occurrence, spatial distribution, ecological and health risks of CAF and DEET in groundwater in Vellore city, Tamil Nadu, India. A total of 96 groundwater samples were collected across four seasons in 2022 and analyzed using Hichrom HPLC in an 844 UV/VIS compact Ion Chromatography system. CAF and DEET were detected in 95% and 96% of samples, with mean concentrations of 34μg/L and 30μg/L, respectively. Contamination levels were higher during the Southwest Monsoon (SWM) and Northeast Monsoon (NEM) seasons. Health risk assessments for children, women, and men showed that CAF posed significant risks, particularly to children during the NEM season, followed by women and men. Although DEET exhibited lower health risks overall, children remained the most vulnerable group. Statistical analysis confirmed significant differences in exposure levels, with children showing the highest variations. Ecological risk assessment revealed that 96.88% of samples containing CAF posed moderate ecological risks, while 6.25% of DEET samples fell into the same category. This study highlights the widespread presence of CAF and DEET in urban groundwater and their associated health and ecological risks. The findings emphasize the need for effective strategies to monitor and mitigate EC contamination in urban water systems.

South Asian Summer Monsoon under stratospheric aerosol intervention

The South Asian summer monsoon (SAM) bears significant importance for agriculture, water resources, economy, and environmental aspects of the region for nearly 2 billion people. To minimize the adverse impacts of global warming, Stratospheric Aerosol Intervention (SAI) has been proposed to lower surface temperatures by reflecting a portion of solar radiation back into space. However, the effects of SAI on SAM are still very uncertain. Our study identifies the main drivers leading to a reduction in the mean and extreme summer monsoon precipitation under SAI. These include SAI-induced lower stratospheric warming and the associated weakening of the northern hemispheric subtropical jet, changes in the upper-tropospheric wave activities, geopotential height anomalies, a reduction in the strength of the Asian Summer Monsoon Anticyclone, and, to some degree, local dust changes. As the interest in SAI research grows, our results demonstrate the urgent need to further understand SAM variability under different SAI scenarios.