Region Of Peninsular India Research Articles

Comparative Analysis of Flood Estimation using Log-Pearson Type III and Gumbel Max Models in the Cauvery River, India

Flooding is one of the most destructive global disasters in scale, geographical extent, property and life loss, and population displacement. The Cauvery River is one of the flood vulnerable rivers in the Peninsular region of India. At-site flood frequency analysis is performed using flow data obtained at the Kodumudi gauged site in the Cauvery River. Log Pearson Type III and Gumbel Max distribution models are used in the present study to estimate peak floods for different return periods. The Central Water Commission provides the annual maximum discharge for the Kodumudi gauged site over 39 years (1980-2018). The goodness of fit test employing the Kolmogorov-Smirnov and Anderson- Darling tests, reveals that Log-Pearson Type III best estimates peak floods in the study area. The peak floods predicted by Log-Pearson Type III for return periods 2, 5, 10, 25, 50, 100, 200, and 500 years are approximately 929, 1886, 2998, 5303, 8002, 11929, 17633, and 29228 cumecs. Hydraulic structures can be designed in the region based on 100-year flood. The present research could help with flooding management approaches, vulnerability analyses, and hydraulic structure design in the study region.

Correction to: Evaluating the Influence of El Nino–Southern Oscillation (ENSO) Patterns on the Spatio-Temporal Variations of Drought over Southern Peninsular Indian Region

Correction to: Evaluating the Influence of El Nino–Southern Oscillation (ENSO) Patterns on the Spatio-Temporal Variations of Drought over Southern Peninsular Indian Region

Sub-basalt hydrocarbon prospect assessment in Peninsular India using seaward dipping reflectors

Conventionally, volcanic margins have been considered devoid of hydrocarbon, but many discoveries and research in recent past have proved the presence of hydrocarbon prospects within them. However, hydrocarbon exploration within volcanic margin is constrained by seismic imaging. Further, identification of continent to oceanic boundary (COB) is critical to hydrocarbon search as hydrocarbon is found mostly over continental crust. Seaward dipping reflectors, associated with volcano-sedimentary sequences, located along rifted continental margins and represented by highly dipping strong amplitude seismic reflectors, play an important role to study volcanic margins. Keeping in view the problems of hydrocarbon exploration within volcanics, seaward dipping reflectors (SDRs) in Indian context have been studied in detail in this paper. It facilitates mapping of continent-oceanic boundary (COB). It has impact on hydrocarbon prospectivity in volcanic margins as it can provide formidable seal and secondary induced maturity. In India, several discoveries have been made in volcanic margins along west coast, from weathered, fractured basalt and sub-basalt sediments. In the present work, long offset regional seismic data (18 dip lines and 1 cross line), along east coast, have been interpreted. SDRs help in hydrocarbon prospectivity assessment for both discrimination of interbedded sediments and preferential accumulation of hydrocarbon. Mapping of linear features not only helped to demarcate COB but also their presence at 6–10 km depth. For the first time, such comprehensive study on SDRs has been done along Indian peninsular region with indications for hydrocarbon prospectivity at deeper levels along Indian peninsular region.

From the Arabian Peninsula to Indian shores: Crab Plover Dromas ardeola Paykull, 1805 (Aves: Charadriiformes: Dromadidae) breeding at Point Calimere, India

Crab Plover Dromas ardeola is endemic to the subtropical and tropical coastlines of the Indian Ocean. It breeds along the easterncoasts of Africa, the Persian Gulf, and southern coasts of the Arabian Peninsula; occurs also in the western Madagascar and most islands northwards to Seychelles. It is a winter visitor to Pakistan, Gujarat, and peninsular India, Andaman & Nicobar Islands, Lakshadweep, northern Sri Lanka, Maldives, and a vagrant to Bangladesh. The objective of this study was to assess the breeding records of the Crab Plover in Point Calimere. After some preliminary surveys and interactions with local birders, between June and August 2023, boat surveys and foot surveys were carried out in the Great Vedaryanam Swamp (GVS) and nearby islets to document the presence of Crab Plover and locate its nests. The presence of five nests of D. ardeola was recorded in Manaaran Theevu islet near Siruthalaikkadu of GVS. This observation marks the first documentation of breeding of Crab Plover in the Indian subcontinent. In the context of species conservation within the peninsular Indian region, there is a need for comprehensive and continuous monitoring of breeding sites.

Standardized Precipitation Index Based Drought Assessment over the North Western Zone of Tamil Nadu, India

Drought is a natural disaster that tremendously affect the agriculture production and livelihood. Though the Tamil Nadu state is located at peninsular region of India and contributed from both the monsoons, the frequency of drought is high due to vagaries of monsoonal pattern. A study was conducted at Tamil Nadu Agricultural University to assess the drought characteristics across the north western Agro Climatic Zone (ACZ) of Tamil Nadu using Standardized Precipitation Index (SPI) during the past 30 years (1991-2020). The study clearly indicated that the Salem district had high vulnerability to drought followed by Dharmapuri and Namakkal districts during the South West Monsoon (SWM), whereas the Namakkal had high vulnerability followed by Salem and Dharmapuri during North East Monsoon (NEM).

Retrieval of atmospheric temperature and humidity profiles over a tropical coastal station from ground-based Microwave Radiometer using deep learning technique

Ground-based multi-frequency microwave radiometer Profiler (Microwave Radiometer Profiler-MRP) provides valuable information on the altitude distribution of atmospheric humidity and temperature in the troposphere (upto ∼10 km) with high temporal resolution (of ∼1 min) under all-weather condition. These information are vital inputs for characterization of the atmospheric boundary layer, convective cloud systems, local weather modification and for studying the atmospheric dynamics. Potential of such radiometers are well established over the mid-latitude region. Thiruvananthapuram, located in the Indian peninsular region, is one of the first stations in the equatorial region where such an instrument made continuously operational for seven years since 2010 at the tropical coastal station. The instrument measures the brightness temperatures (Tb in Kelvin) at Ka- and V-band frequencies with a temporal resolution of ∼1 min. A trained back-propagation neural network technique based on the radiosonde ascends data for more than one decade obtained by India Meteorological station at Thiruvananthapuram, was used to derive the atmospheric humidity and temperature profiles. This paper presents the implementation of another retrieval technique based on deep learning approach - batch normalization and neural network (BNN) to retrieve temperature and water vapour density (WVD) profiles from Tb values during clear sky conditions and validation of the retrieval accuracies. This inversion model, much faster in computation, consists of two hidden layers and the rectified linear unit (ReLU) is used as the activation function as it can overcome the problems of saturation and vanishing gradients. The Tbs observed by radiometer are corrected by reducing the bias between the simulated Tb, using forward radiative transfer model, and the observed Tb. The validation of retrieved profiles with the radiosonde demonstrates a good retrieval capability, showing a root-mean-square error of 1.8K for temperature, <2 g/m3 for WVD and ∼14% for RH.

Spatial Patterns in the Distribution of Hypertension among Men and Women in India and Its Relationship with Health Insurance Coverage.

The present study explores district-level data associated with health insurance coverage (%) and the prevalence of hypertension (mildly, moderately, and severely elevated) observed across men and women as per NFHS 5. Coastal districts in the peninsular region of India and districts in parts of northeastern India have the highest prevalence of elevated blood pressure. Jammu and Kashmir, parts of Gujarat and parts of Rajasthan have a lower prevalence of elevated blood pressure. Intrastate heterogeneity in spatial patterns of elevated blood pressure is mainly seen in central India. The highest burden of elevated blood pressure is in the state of Kerala. Rajasthan is among the states with higher health insurance coverage and a lower prevalence of elevated blood pressure. There is a relatively low positive relationship between health insurance coverage and the prevalence of elevated blood pressure. Health insurance in India generally covers the cost of inpatient care to the exclusion of outpatient care. This might mean that health insurance has limited impact in improving the diagnosis of hypertension. Access to public health centers raises the probability of adults with hypertension receiving treatment with antihypertensives. Access to public health centers has been seen to be especially significant at the poorer end of the economic spectrum. The health and wellness center initiative under Ayushman Bharat will play a crucial role in hypertension control in India.

High-Resolution Bayesian Inversion of Carbon Dioxide Flux Over Peninsular India

Accurate estimation of the flux of the most important greenhouse gas, carbon dioxide (CO2), plays a decisive role in designing the policies to reduce the atmospheric CO2 burden to combat climate change. Here we integrate recent (2017–2020) in-situ measurements with a high-resolution particle dispersion model for optimising CO2 flux over peninsular India based on a top-down approach. Using weekly observations of atmospheric boundary layer CO2 from three distinct locations representing peninsular India, the total surface fluxes of CO2 are optimised based on the fluxes from fossil fuel, wildfire, terrestrial biosphere and ocean. Our Bayesian mode inversion using the Lagrangian Particle Dispersion Model FLEXPART suggests that the peninsular Indian region is a slightly stronger source of CO2 (3.34 TgC yr−1) than what is synthesised in the fossil fuel and ecosystem exchanges based on independent estimations. On seasonal scale, the flux corrections to the prior fluxes over peninsular India are 4.68, 6.53, −2.28 and 4.41 TgC yr−1during winter, pre-monsoon, monsoon and post-monsoon seasons, respectively. The CO2 measurements from the stations attempted in the present inversion experiments could capture the footprints of peninsular India, giving better constraints to fluxes in the inversion. However, the data gap, pristineness of the samples, and large variabilities in the observations call for sustained monitoring for a longer term to further reduce the uncertainty of the estimated flux.

Development of a New Ground Motion Model for a Peninsular Indian Rock Site

The ground motion model (GMM) plays a vital role in the generation of seismic design basis ground motion parameters. Even though many intra-plate GMMs are available, very few of them are based on Peninsular India (PI) region-specific seismological parameters. Hence, it is imperative to develop a GMM using seismological parameters derived from earthquakes in the Peninsular Indian region. In this study, a new GMM is developed for a PI rock site. Due to the scarcity of real earthquakes, artificial earthquake records are simulated to generate a new GMM for PI. The accelerograms of these artificial earthquakes are obtained from the stochastic finite fault simulation technique. Region-specific seismological parameters are obtained from the available PI earthquakes. The generated GMM is compared with other intra-plate GMMs for different earthquake magnitudes. Also, the generated GMM is validated with the Koyna earthquake record and it is observed that the GMM’s predictions are closer to the record.

Impact of CCN on mixing line structure over the peninsular Indian region

Impact of CCN on mixing line structure over the peninsular Indian region

Land‐Atmosphere Interactions at a Semi‐Arid Region in the Deccan Plateau

AbstractComprehensive characterization of turbulent fluxes and land‐atmosphere interactions at a semi‐arid region in the Deccan Plateau of peninsular India is presented using 2‐year eddy covariance measurements. Contrary to previously reported results over the Indian region, surface energy partitioning is more into sensible heat flux than latent heat flux, even during the monsoon season. Irrespective of the seasons, the soil moisture and its response to rainfall drive the land‐atmosphere interactions and along with the net radiation, play crucial roles in deciding the surface fluxes and its partitioning. Time series comparison with ERA5 reanalysis data reveals the inadequate representation of land‐atmosphere interactions in ERA5 reanalysis over the peninsular Indian region, particularly the intensity and duration of rainfall and the feedbacks of soil moisture to the atmosphere. The surface energy balance closure improves by ∼3% when the soil heat storage term is considered and is the highest when the height and scatter of the roughness elements around the measurement site are the lowest. The influence of rainfall on energy balance closure is lower as compared to land surface heterogeneity. The present study also fills an existing gap of validating the surface fluxes and its partitioning in ERA5 reanalysis in the tropics and will provide deeper insights on the land‐atmosphere interactions in tropical semi‐arid regions.

Morphological and microphysical characteristics associated with the lifecycle of a stationary cloud cluster during the Indian Summer Monsoon: A comparative study with numerical simulations and radar observation

The simulated morphological, dynamical, and microphysical characteristics, by the three microphysics schemes with increasing complexities, during the lifecycle of a tropical continental mesoscale cloud cluster observed during the monsoon over the peninsular Indian region are illustrated in this study. Observations from a polarimetric C-Band radar have set the benchmark for the evaluation of the performances of the three microphysics schemes. Results show that all the simulations have a tendency to produce intense convection in comparison to observations, where the least complex scheme projected the maximum value. The contrasting dynamical characteristics by each microphysics scheme resulted in different cloud structure. The simulated aggregation/clustering properties of convection by the microphysics schemes were different, where the most sophisticated scheme produced the convective aggregation/clustering closer to radar-derived products. Significant differences in upper-level cloud fractions are noted among the simulations, which are manifested by the variations in the upper-level relative humidity and distribution of ice-phase hydrometeors. Intercomparison of radar-derived and simulated hydrometeor fractions suggests that all the simulations have a tendency to produce lesser snow fraction, higher graupel fraction, and higher ice fraction. Overall analyses suggest that the most sophisticated microphysics scheme produced a more realistic simulation of the cloud system.

Evaluating the Influence of El Nino–Southern Oscillation (ENSO) Patterns on the Spatio-Temporal Variations of Drought over Southern Peninsular Indian Region

Evaluating the Influence of El Nino–Southern Oscillation (ENSO) Patterns on the Spatio-Temporal Variations of Drought over Southern Peninsular Indian Region

Detection of the impact of a tropical cyclonic system on the dynamics and energetics of the atmosphere using wind profiler radar

Rapid changes in the tropospheric circulation features associated with the overhead passage of the Gaja cyclonic system over the 205 MHz Stratosphere Troposphere wind profiler radar observations at Kochi (10.03° N, 76.33° E), India, have been studied. The severe cyclonic system formed in the southeast Indian Peninsular region weakened into a depression after landfall near the Tamil Nadu coast. On 16th November 2018, the cyclonic system crossed the Western Ghats and travelled westward at 33 knots over the ST radar site at Kochi in the evening. Later it reached the Arabian Sea and intensified again into a severe cyclone. Continuous observations of the vertical structure of the wind pattern at 4-min intervals from the wind profiler radar have been examined. The impact of the transit of the cyclonic system extends up to a height of 13 km in the atmosphere. The vertical distribution of turbulent kinetic energy in the atmosphere indicates a sudden disruption in the tropospheric levels at the time of storm passage. The cyclonic system traversed over the Western Ghats positioned at an altitude of 2500 m. It crossed the radar site at the mean sea level after passing a horizontal distance of 100 km. The abrupt changes in the topographical conditions generate atmospheric gravity waves in the leeward side of the Western Ghats, as observed from the ST radar, are presented. During the period, changes in surface parameters were evaluated using co-located automatic weather station (AWS) data. Satellite information and Doppler weather radar observations from Kochi have also supplemented the investigation.

The Life Cycle of a Stationary Cloud Cluster during the Indian Summer Monsoon: A Microphysical Investigation Using Polarimetric C-Band Radar

Abstract Multiplatform observations of the life cycle of a tropical continental mesoscale cloud cluster (CC) during the Indian summer monsoon, which contributed more than ~70 mm of rainfall over the arid peninsular Indian region, are presented in this study. The CC was characterized by a deep warm cloud layer with isolated convective cells in the initiation phase, merging of several deep cumulus clouds (~6 km) during the mature phase, growing up to ~15 km with mixed-phase and ice-phase cloud microphysical processes. Throughout the life cycle of the CC, polarimetric radar analyses revealed size sorting of falling raindrops, growth of dendritic particles, riming, aggregation, the occurrence of a saggy bright band, etc. The formation of big raindrops is observed during the initial convective rain, associated with the melting of hail. The stratiform counterpart is primarily associated with aggregates, ice crystals, and melting snow, resulting in surface rainfall. Aggregates are found to be the spatially dominant hydrometeor followed by ice crystals. The presence of vertically oriented ice crystals indicates active cloud electrification processes during the spatial aggregation of convective clouds. The dominant microphysical processes and precipitation pathways are illustrated. The study forms a benchmark case for model intercomparisons and evaluations.

Rainfall types in the lifecycle of a stationary cloud cluster during the Indian Summer Monsoon: An investigation with numerical simulations and radar observation

The performance of three microphysics schemes (WRF Double Moment 6-class (WDM6), Morrison double moment (MORR), and spectral bin microphysics (Fast version) (SBMF)), with increasing complexities, in simulating various rainfall-types during the lifecycle of a tropical continental mesoscale cloud cluster (CC) are presented in this study. The CC spent its entire lifetime over the surveillance area of a polarimetric C-band radar, over the peninsular Indian region in a monsoon environment. Observed and simulated rainfall properties throughout the lifecycle of the CC are intercompared. A rainfall-type categorization algorithm has been applied to the observed and model simulated reflectivity fields. Microphysics scheme with the least complexities produced the highest convective rainfall-type, lowest stratiform rainfall-type, and a remarkable early cessation of the CC. With increasing complexities, the microphysics schemes are found to represent the rainfall-types more close to radar observations. Major differences are noted during the mature and dissipation phases, especially in the stratiform rainfall-type. The rainfall-types derived from radar, as well as three simulations with WDM6, MORR, and SBMF schemes, showed ~18%, ~54%, ~41%, and ~29% of convective rainfall fraction (including isolated convective categories), ~14%, ~33%, ~18%, and ~20% of mixed rainfall fraction and ~68%, ~13%, ~42%, and ~50% of stratiform rainfall fraction respectively during the lifecycle of the CC. The accumulated rainfall derived from radar observations, using a blended rainfall estimation algorithm, indicated substantial differences in the observed and simulated rainfall pattern. The lower moment scheme has a tendency to produce more lighter as well as heavy rainfall compared to the higher moment schemes.

Vertical profile of aerosol characteristics including activation over a rain shadow region in India

Unique airborne observations of aerosol size spectral and chemical characteristics over the peninsular Indian region are illustrated in this case study. Multimodal lognormal distributions were required to fit the observed in situ aerosol size distribution. The aerosol composition and mixing state was deduced from the single-particle analyses of aerosols using the transmission electron microscope and soot photometer coupled with satellite retrieved aerosol classification, and back trajectory analyses. Organic carbon was the most prominent aerosol type found at all altitudes. Refractory black carbon aerosols which constituted about 10–12% of the aerosols in the boundary layer were primarily internally mixed with both inorganic and organic coating. Other major aerosol types were dust and sea salt, with the latter primarily found below 2 km. Further, the cloud forming ability of in-situ aerosols is tested through a cloud condensation nuclei closure analysis. The effective hygroscopicity decreased above cloud base due to the absence of sea salt aerosols. The change in large-scale winds with altitude affected the aerosol composition and hygroscopicity. The multimodal aerosol size distribution and hygroscopicity parameter (κ = 0.18) obtained for the cloud base aerosols over the rain shadow region are useful for studying aerosol-cloud interactions using regional cloud-resolving models.

Characterization and evaluation of mountain sweet thorn (Flacourtia montana J. Grah) collections

Mountain sweet thorn (Flacourtia montana J. Grah) is an indigenous underutilized fruit of the Western Ghats and other regions of peninsular India. It is a close relative of Governor’s plum. It is a bushy shrub or small tree with spiny trunks and branches which may grow up to 2.5 m in height. The fruits are bright dark red 1-2 cm in diameter, sweet edible, and have the potential for processing into jams and jellies. The presence of thorn is one of the major hurdles for the commercialization of this crop. Thus, seeds of the thorny plants of the Mountain sweet thorn were collected from different locations, and seedlings were planted to identify the suitable line. The plant height ranged from 425 cm (accession 0208) to 710 cm (accession​ ​0202). The plant girth ranged from 34.5 cm to 82 cm. The growth data revealed that all​ ​the accessions are vigorous, fast-growing, and have various levels of thorniness. All the​ ​accessions were found to be spreading type. Significant variability was recorded for leaf​ ​characteristics among the accessions studied. Three major clusters were observed in​ ​cluster analysis for morphological and fruiting characters consisting of 1, 8, and 9 accessions,​ ​respectively. The number of fruits ranged from 0 to 4008. The highest yield (9.46 kg/plant)​ ​was obtained in accession - 0106 followed by accession- 0201 (7.83 kg). The average​ ​fruit weight ranged from 1.51 g to 3.94 g. The highest fruit weight (3.94g) was also recorded​ ​in 0106 followed by 2.84 (0102). The total soluble solids ranged from 10 0 Brix to 15.1 0​ ​Brix. Overall, accession 0201 was found better than others with respect to yield, regular​ ​bearing, and less thorniness.

Characterization and evaluation of mountain sweet thorn (Flacourtia montana J. Grah) collections

Mountain sweet thorn (Flacourtia montana J. Grah) is an indigenous underutilized fruit of the Western Ghats and other regions of peninsular India. It is a close relative of Governor’s plum. It is a bushy shrub or small tree with spiny trunks and branches which may grow up to 2.5 m in height. The fruits are bright dark red 1-2 cm in diameter, sweet edible, and have the potential for processing into jams and jellies. The presence of thorn is one of the major hurdles for the commercialization of this crop. Thus, seeds of the thorny plants of the Mountain sweet thorn were collected from different locations, and seedlings were planted to identify the suitable line. The plant height ranged from 425 cm (accession 0208) to 710 cm (accession​ ​0202). The plant girth ranged from 34.5 cm to 82 cm. The growth data revealed that all​ ​the accessions are vigorous, fast-growing, and have various levels of thorniness. All the​ ​accessions were found to be spreading type. Significant variability was recorded for leaf​ ​characteristics among the accessions studied. Three major clusters were observed in​ ​cluster analysis for morphological and fruiting characters consisting of 1, 8, and 9 accessions,​ ​respectively. The number of fruits ranged from 0 to 4008. The highest yield (9.46 kg/plant)​ ​was obtained in accession - 0106 followed by accession- 0201 (7.83 kg). The average​ ​fruit weight ranged from 1.51 g to 3.94 g. The highest fruit weight (3.94g) was also recorded​ ​in 0106 followed by 2.84 (0102). The total soluble solids ranged from 10 0 Brix to 15.1 0​ ​Brix. Overall, accession 0201 was found better than others with respect to yield, regular​ ​bearing, and less thorniness.

Assessment of newly-developed high resolution reanalyses (IMDAA, NGFS and ERA5) against rainfall observations for Indian region

In this study, a comprehensive assessment has been provided for the performance of three newly-developed high resolution reanalysis (IMDAA, NGFS, ERA5) datasets w.r.t. IMD rainfall observation over six homogeneous monsoon regions of India during 1999–2018. It is necessary to understand how these reanalyses rainfall datasets are performing spatio-temporally, specifically during monsoon in order to apply them in further research and developmental purposes. Focus has been given to assess their relative performances during monsoonal rainfall extremes against IMD observations. Results reveal that all these three reanalysis datasets captured the spatial patterns of observed rainfall climatology reasonably well in all the seasons, except for hilly regions where there is over-estimation against the observed patterns. Moreover, wet biases over the entire foothills of Himalayas extending up to north-east are more dominant during monsoon for IMDAA reanalysis, whereas bias is mixed type and region-specific in all seasons for NGFS and ERA5 reanalysis. Both IMDAA and NGFS reanalysis captured the probability distribution of observed daily rainfall intensity diligently especially in the range of extremes while ERA5 reanalysis underestimated the same. However, spatial distribution for rainfall extremes (based on intensity and 95th percentile) reveals that all the reanalyses have failed to capture patterns in the hilly topography as well as over peninsular Indian region. In comparison to IMDAA and ERA5 reanalysis, NGFS captured reasonably well for heavy and very heavy rainfall over Western Ghats. ERA5 reanalysis always underestimated all the extreme rainfall categories in comparison to IMDAA and NGFS reanalysis which is also confirmed from probability distribution curve. Moreover, bi-decadal (pre- and post-2008) spatial trend distribution for 95th percentile rainfall extremes indicate a reversal in trend (wetter to drier and vice versa) over India. Both IMDAA and NGFS have captured the moist and desiccated trend region-specifically along with ERA5 reanalysis against observational trends. Thus, the result provides useful insights for the climate modeling to establish appropriate standards for performing climate model evaluation over Indian region.