Central Part Of India Research Articles

Spatial prevalence and its contextual determinants of early initiation of breastfeeding in cases of C-section deliveries in India: a study based on National Family Health Survey-4, 2015-2016

Background: Delayed early initiation of breastfeeding (EIBF) between 2 to 23 hours has increased 1.3 times risk of neonatal and it goes up double when it crosses more than 24 hours. Babies who were born through caesarean section (C-section) were less likely to initiate early breastfeeding as compared to normal vaginal delivery.Methods: The present study has utilized 14774 weighted samples of C-section delivered women from National Family Health Survey-4 (NFHS-4) (2015-2016). Spatial analysis software i.e. ArcGIS 10.8 and STATA 14 including logistics regression has been utilized to show the spatial prevalence and contextual determinants of EIBF on C-section birth babies in India.Results: In India, around 31.8% of C-section mothers breastfeed their children within one hour of delivery. The prevalence of EIBF is highest in Goa and lowest in Rajasthan. The central part of India mostly from the empowered action group (EAG) states practices a very low level of EIBF practices whereas, the north-east region represents the highest prevalence for the same. The odds of logistic regression shows that mother’s higher education (OR: 1.38), everyday mass media exposure (OR: 1.66), and initiation of postnatal care (PNC) within one hour (OR: 1.79) help to increase the practices of EIBF. On the other hand, delivery in the private hospital (OR: 0.61).Conclusions: The study shows remarkable geographical variations in EIBF and its correlates in the country. It recommends that the public health programmes need to target the states with less practice of EIBF (i.e. EAG state or central part of India) F among C-section delivery mothers. By increasing the level of mothers’ education status, mass media exposure and early PNC care can improve the EIBF practices among C-section mothers in India.

Impact of planting dates on Thrips tabaci Lindeman infestation and yield in onion (Allium cepa L.) in central India

The aim of the present research work was to investigate the impact of planting dates on thrips populations in onions was monitored throughout two growing seasons and field experiments were carried out for two years (2013-14 to 2014-15) to determine the Impact of planting dates on Thrips tabaci Lindeman infestation and yield in onion (Allium cepa L.) in central part of India. Plant samples were collected to assess Impact of planting dates on thrips and their abundance. Results showed that the significantly lowest population of onion thrips was recorded on 1st November transplanted onion crop (12.97 thrips/plant), while significantly highest population of onion thrips was recorded on 15th January transplanted onion crop (34.25 thrips/plant). Significantly higher yield was recorded in 1st January transplanted crop (275.83 q/ha), while significantly lowest yield was recorded in 1st November transplanted crop (236.30 q/ha).

Prevalence of malocclusion and orthodontic treatment need among 15 year old school children of rural Central India

Objective: To assess the prevalence of malocclusion and orthodontic treatment need among the rural school going 15‑years-old children Materials and Methods: A descriptive cross sectional study was carried out among 400 school going children in the central part of India. Occlusal features such as overjet, overbite, crossbite, crowding, and spacing were documented using a structured proforma and the need for orthodontic treatment was evaluated using the index of orthodontic treatment need dental health component. Results: It was found that the prevalence of malocclusion among the study participants was 70%, and the overall treatment need was 29.5%.Conclusion: This study offers baseline data on the need and demands for orthodontic treatment within the sample, which is critical for public orthodontic and dental service planning.

Impact of COVID-19 lockdown on the atmospheric boundary layer and instability process over Indian region

The abrupt reduction in the human activities during the first lockdown of the COVID-19 pandemic created unprecedented changes in the background atmospheric conditions. Several studies reported the anthropogenic and air quality changes observed during the lockdown. However, no attempts are made to investigate the lockdown effects on the Atmospheric Boundary Layer (ABL) and background instability processes. In this study, we assess the lockdown impacts on the ABL altitude and instability parameters (Convective Available Potential Energy (CAPE) and Convective Inhibition Energy (CINE)) using WRF model simulations. Results showed a unique footprint of COVID-19 lockdown in all these parameters. Increase in the visibility, surface temperature and wind speed and decrease in relative humidity during the lockdown is noticed. However, these responses are not uniform throughout India and are significant in the inland compared to the coastal regions. The spatial variation of temperature (wind speed) and relative humidity shows an increase and decrease over the Indo Gangetic Plain (IGP) and central parts of India by 20% (100%) and 40%, respectively. Increase (80%) in the ABL altitude is larger over the IGP and central parts of India during lockdown of 2020 compared to similar time period in 2015–2019. This increase is attributed to the stronger insolation due to absence of anthropogenic activity and other background conditions. At the same time, CAPE decreased by 98% in the IGP and central parts of India, where it shows an increase in other parts of India. A prominent strengthening of CINE in the IGP and a weakening elsewhere is also noticed. These changes in CAPE and CINE are mainly attributed to the dearth of saturation in lower troposphere levels, which prevented the development of strong adiabatic ascent during the lockdown. These results provide a comprehensive observation and model-based insight for lockdown induced changes in the meteorological and thermo-dynamical parameters.

Current scenario of ocular morbidity in severe acute childhood malnutrition in central part of India

The study aimed to assess the prevalence of ocular involvement in children 6 months to 5 years attending tertiary care centre with Severe Acute Malnutrition and to detect the associated risk factors for ocular morbidity in severe acute malnutrition.: This hospital based observational study was carried out at Gandhi Medical College, during the study period of 2 years on children diagnosed with SAM belonging to 6 months to 5 years of age. Detailed history was obtained and physical, systemic and ocular examination was done. : A total of 100 severe acute malnourished children were included. Prevalence of ocular involvement in severe acute malnourished children was 72%. Conjunctival pallor was observed in 71.5% eyes and retinal hemorrhages were most common posterior segment finding. Vitamin A deficiency signs were observed in 17 eyes (8.5%). Higher birth order and number of sibling was significantly associated with higher incidence of ocular manifestations (p<0.05). However, other variables showed no significant association between other variables and ocular manifestations (p>0.05). Training should be given to health workers at the primary health care level and health centers on counseling mothers on feeding, growth monitoring, the preventable eye blinding diseases and hygiene during the vaccination sessions and early referral of children with eye signs to hospitals. Also education of couple regarding proper nutrition of mother and child should be encouraged and couples should be insisted to have not more than two children.

Geospatial variability mapping of soil nutrients for site specific input optimization in a part of central India

AbstractThe ability to define site‐specific variability affects the acceptability of precision farming. A study was conducted to determine the soil nutrient spatial variability in the Nagpur Rural block of Nagpur district, Maharashtra, India. A total of 1707 surface soil samples (0‐to‐15‐cm soil depth) were collected from a 65,386‐ha region. Soil samples were analyzed for pH, electrical conductivity (EC), soil organic carbon (SOC), and available macronutrients (N, P, K, and S) and micronutrients (Fe, Mn, Cu, and Zn). Geostatistical modeling (kriging) was run on soil geodatabase to obtain the best‐fit experimental semivariogram having the lowest RMSE. Exponential (for pH, SOC, and N) and spherical (for P, K, and S) variogram model of ordinary kriging type as well as exponential variogram of simple kriging (for EC) were found to be best fitted to the soil parameters studied. The spatial distribution of maps showed deficiency of available N, P, and Zn, whereas soil test K, Mn, and Cu was high in most of the study area. Spatial dependence was moderate for all soil fertility parameters (N/S ratio 0.25–0.75), whereas soil test P exhibited strong spatial dependency (N/S ratio 0.19). The soil fertility maps developed through geostatistical techniques can be successfully used for managing site‐specific nutrients, enhancing fertilizer use efficiency, minimizing cost of cultivation, improving socioeconomic status of farmers, and increasing farm income without adverse effects on soil environment.

Renal biopsy profile in elderly population and its comparison with young patients: A study from the central part of India

Renal biopsy profile in elderly population and its comparison with young patients: A study from the central part of India

Clinical and Histopathological Profile of Immunoglobulin A Nephropathy Patients in Central Part of India: A Single-Center Study.

The objective of the study was to assess clinical and histopathological profile of patients who were diagnosed as immunoglobulin A nephropathy (IgAN) on renal biopsy. Medical data were collected for this retrospective study at a single center from patients with biopsy-proven IgAN, from those biopsied between January 2017 and September 2020. A total of 347 renal biopsies were performed during the study. There were 52 patients with primary IgAN who met our inclusion criteria. Males were more commonly affected (61.5%). The mean age at the time of kidney biopsy was 35.26 ± 10.39 years. Hypertension was present in 84.5% of patients. Median serum creatinine and estimated glomerular filtration rate (eGFR) at presentation were 3.58 mg/dL and 15.8 mL/min/1.73 m2, respectively. Mesangial hypercellularity (M1), endocapillary hypercellularity (E1), segmental glomerulosclerosis (S1), tubular atrophy/ interstitial fibrosis (T1/T2), and crescents (C1/C2) were present in 46.2%, 38.5%, 88.5%, 75% and 36.6% of patients respectively. Thrombotic microangiopathy (TMA) and hypertensive vasculopathy were seen in 38.5% and 86.5% of patients respectively. The presence of tubular atrophy (T1/T2), hypertensive vasculopathy, and TMA on renal biopsy was significantly associated with low eGFR at presentation whereas no such correlation could be established with segmental glomerulosclerosis (S1), crescents (C1/C2), mesangial (M1) and endocapillary hypercellularity (E1). The presence of hypertensive vasculopathy and TMA on renal biopsy was associated with poor renal function at presentation. The most common clinical presentation of IgAN was hypertension and so we suggest patients with hypertension should be screened for microscopic dysmorphic hematuria and proteinuria, if present, should undergo a renal biopsy to diagnose this disease in early stages.

Crop Health Assessment Using Sentinel-1 SAR Time Series Data in a Part of Central India

Crop Health Assessment Using Sentinel-1 SAR Time Series Data in a Part of Central India

\u201cChildhood Anemia in India: an application of a Bayesian geo-additive model\u201d

BackgroundThe geographical differences that cause anaemia can be partially explained by the variability in environmental factors, particularly nutrition and infections. The studies failed to explain the non-linear effect of the continuous covariates on childhood anaemia. The present paper aims to investigate the risk factors of childhood anaemia in India with focus on geographical spatial effect.MethodsGeo-additive logistic regression models were fitted to the data to understand fixed as well as spatial effects of childhood anaemia. Logistic regression was fitted for the categorical variable with outcomes (anaemia (Hb < 11) and no anaemia (Hb ≥ 11)). Continuous covariates were modelled by the penalized spline and spatial effects were smoothed by the two-dimensional spline.ResultsAt 95% posterior credible interval, the influence of unobserved factors on childhood anaemia is very strong in the Northern and Central part of India. However, most of the states in North Eastern part of India showed negative spatial effects. A U-shape non-linear relationship was observed between childhood anaemia and mother’s age. This indicates that mothers of young and old ages are more likely to have anaemic children; in particular mothers aged 15 years to about 25 years. Then the risk of childhood anaemia starts declining after the age of 25 years and it continues till the age of around 37 years, thereafter again starts increasing. Further, the non-linear effects of duration of breastfeeding on childhood anaemia show that the risk of childhood anaemia decreases till 29 months thereafter increases.ConclusionStrong evidence of residual spatial effect to childhood anaemia in India is observed. Government child health programme should gear up in treating childhood anaemia by focusing on known measurable factors such as mother’s education, mother’s anaemia status, family wealth status, child health (fever), stunting, underweight, and wasting which have been found to be significant in this study. Attention should also be given to effects of unknown or unmeasured factors to childhood anaemia at the community level. Special attention to unmeasurable factors should be focused in the states of central and northern India which have shown significant positive spatial effects.

Appraisal of natural groundwater reserve using entropy-based model at the proximity of Deccan Trap Basalt and Gondwana Sandstone in a part of Central India

Appraisal of natural groundwater reserve using entropy-based model at the proximity of Deccan Trap Basalt and Gondwana Sandstone in a part of Central India

Characterizing rainfall occurrence in India: Natural variability and recent trends

A deficit in rainy days can affect crop production and escalate groundwater abstraction leading to groundwater depletion, thus may threaten food and water security in the Indian subcontinent. The available researches on rainfall occurrence in India represent inconsistency in several fundamental considerations (spatial scale of analysis, the definition of rainfall classes, methods, dataset, study period, etc.) and lack of studies for non-monsoon seasons over large parts of the subcontinent. Here we attempt to deal with these inconsistencies by examining space–time patterns in seasonal count of rainfall events and their count in different rainfall classes during 1951–2015 for all meteorological seasons of India using high resolution (0.25°) gridded daily rainfall dataset. The results show a widespread decline in monsoon rainy days over major crop-growing regions including north-central, central, and northeast India. A reduction in rainy days is also observed over parts of central India in premonsoon; over north-central and northeast India in postmonsoon; and over peninsular India in winter. These trends are mainly observed in events with rainfall <95th percentile (light to heavy rainfall events) in all the seasons. Occurrence of extreme events (above 95th and 99th percentile) exhibits contrasting trends over different zones with mainly an increase over central and south-central India and decline over central-north India. However, trends in extremes are highly dispersed in space and are conclusive only over a few regions. The observed trends substantially deviate from the patterns reported in past studies for different regions. Rainfall occurrence in different meteorological zones also represents strong interannual and decadal variability, however, the observed trends have emerged beyond the inherent natural variability. The present findings provide an essential foundation for several future explorations with improved understanding of change in rainfall frequency and its possible impacts. It would also assist in developing a comprehensive framework for year-wide management of water resources and agriculture, considering all crop seasons.

Drought vulnerability and risk assessment in India: Sensitivity analysis and comparison of aggregation techniques

Long term drought management requires proper assessment and characterization of drought hazard, vulnerability and risk. This is particularly important for an agriculture-dependent, highly-populated, developing country such as India. However, the regulation of drought vulnerability and drought risk assessment in the country is mostly region-specific and ad-hoc, considering only a limited number of vulnerability indicators. In this study, a comprehensive, fine-resolution, country-wide drought risk assessment is carried out considering drought hazard in a multivariate framework, and using reliable drought vulnerability indicators that account for exposure, sensitivity and adaptive capacity. Further, multiple aggregation techniques including subjective, objective and comprehensive methods are employed for vulnerability assessment, and their performance assessed and compared. The Analytic Hierarchy Process (AHP)+Entropy and TOPSIS methods, which are comprehensive aggregation techniques are found to be better performing, TOPSIS being the most robust method. A bivariate choropleth map based on the TOPSIS-derived drought vulnerability shows regions of Punjab, Haryana, Uttar Pradesh and Tamil Nadu subjected to drought hazard-driven risk, while risk in other regions such as Rajasthan, parts of Central India, Orissa and parts of Maharashtra are driven more by drought vulnerability. Parts of Western Rajasthan, Vidharbha, North-East India, Chattisgarh, Tamil Nadu and Karnataka are under severe drought risk resulting from an interplay of hazard and vulnerability. Irrigation index, water body fraction, and groundwater availability are found to be the most significant indicators for assessing drought vulnerability in India. The above findings can aid decision makers and government bodies to plan region-specific line of action for building drought resilience.

Habitat vulnerability in slum areas of India – What we learnt from COVID-19?

UN-Habitat identified the present COVID-19 pandemic as ‘city-centric’. In India, more than 50% of the total cases were documented in megacities and million-plus cities. The slums of cities are the most vulnerable due to its unhygienic environment and high population density that requires an urgent implementation of public healthcare measures. This study aims to examine habitat vulnerability in slum areas to COVID-19 in India using principal component analysis and Fuzzy AHP based technique to develop slum vulnerability index to COVID-19 (SVIcovid-19). Four slum vulnerability groups (i.e. principal components) were retained with eigen-values greater than 1 based on Kaiser criterion - poor slum household status; lack of social distance maintenance; high concentrations of slum population and towns and mobility of the households. This study also mapped composite SVIcovid-19 on the basis of PCA and Fuzzy AHP method at the state level for a better understanding of spatial variations. The result shows that slums located in the eastern and central parts of India (particularly Uttar Pradesh, Bihar, Jharkhand, Odisha, West Bengal) were more vulnerable to COVID-19 transmission due to lack of availability as well as accessibility to the basic services and amenities to slum dwellers. Thus, the findings of the study may not only help to understand the habitat vulnerability in slum areas to COVID-19 but it will also teach a lesson to implement effective policies for enhancing the quality of slum households (HHs) and to reduce the health risk from any infectious disease in future.

Assimilation of remote sensing based surface soil moisture to develop a spatially varying vertical soil moisture profile database for entire Indian mainland

The Climate Change Initiative (CCI) program of the European Space Agency (ESA) (ESA-CCI) provides a global surface Soil Moisture (SM) product by merging the information from various Active and Passive sensors on board for the period of 1971–2014. This study aims to assimilate this surface SM product into a recently developed model, namely Statistical Soil Moisture Profile (SSMP) model, to investigate the efficacy of this combination in developing a vertical soil moisture profile database over a climatologically vast area, such as Indian mainland. The SSMP model is a spatially varying statistical framework that couples the memory and forcing of SM from the overlying layers and utilizes the information of Hydrologic Soil Groups (HSGs) that makes it spatially transferable. The model estimates SM at four depths i.e. 10, 20, 51 and 102 cm using the surface SM information (~0–5 cm). The developed database is named as ‘ESA-CCI Driven Vertical Soil Moisture Profile (root zone) Database (EDVSMPD)’ and the simulated values are validated with observed SM data at many monitoring stations across India, maintained by India Meteorological Department (IMD). As an exemplary demonstration of the utility of the data, basin scale reconstruction of the historical agricultural droughts and its spatial distribution, using the developed EDVSMPD product, is illustrated for a medium sized drought-stricken river basin, namely Wardha, in the central part of India. The resulting SM product for a considerable length of period (more than 30 years) will be immensely useful for many hydro-climatological studies.

Evaluation of Weather Research and Forecasting model downscaled rainfall and its variability over India

AbstractLong‐term variations in the frequencies of different rainfall events during summer monsoon season (June through September) are analysed over a period of 38‐years (1980–2017) using the simulations of weather research and forecasting (WRF) model evaluated against the India Meteorological Department (IMD). Further, we have divided the study period into two sub‐periods such as before (1980–1998), and after the mega ENSO event (1999–2017). Our analysis suggests the WRF exhibits good skill in capturing the increased trends in the frequency of heavy and very heavy (extreme) rainfall events during the recent epoch (1999–2017).We have assessed the skill of WRF in capturing the observed probability distributions of daily rain rates over different sub‐regions of India. Our results depict that the downscaled products of WRF captured well the extreme rainfall as observed in IMD, signifying that this dynamically downscaled model with continuous 36‐hr re‐initialization makes it suitable to simulate extreme rainfall events compared to light rainfall event. However, our analysis reports that there is a slight overestimation in WRF rainfall and fails in capturing the light rainfall events compared to IMD. The overestimation of rainfall by WRF possibly be due to increased pressure gradients and enhances the convection in the upper streams and associated rainfall. Our study emphasizes that the variability in summer monsoon rainfall during the recent period is due to the changes in the monsoon circulations, particularly monsoon low‐level jet that leads to alter the moisture budget in terms of moisture convergence and transport. Moreover, the variability in frequencies of rainfall events are analysed for strong La Niña/El Niño years and observed an increase in extremes over major part of India during strong La Niña except over parts of Central India and NEI where strong El Niño dominates; which is well captured by the WRF model.

Molecular analysis, infectivity and host range of Tomato leaf curl Karnataka virus associated with Corchorus yellow vein mosaic betasatellite

Severe leaf curl disease of tomato (ToLCD) was noticed recently in the central parts of India and is an emerging threat to the cultivation of tomato. The genomic components of the begomovirus isolate, DNA A and betasatellite associated with ToLCD were cloned by rolling circle amplification method and sequenced. The sequence analysis revealed that the DNA A (2766 nt) of this isolate had the nucleotide identity of >91% with other strains of Tomato leaf curl Karnataka virus (ToLCKV), hence this isolate is proposed as a strain of ToLCKV, named as ToLCKV-Raipur. Similarly, the betasatellite molecule (1355 nt) had the highest identity of 91.1% with Corchorus yellow vein mosaic betasatellite (CoYVMB) and named as CoYVMB-Raipur. The full-length dimerized clones of these two genomic components were agroinoculated on natural (tomato), experimental (Nicotiana benthamiana) hosts and other 20 plant species belong to six different families. The severe leaf curl symptoms appeared only in the hosts, N. benthamiana, and in tomato inoculated with ToLCKV-Raipur alone and ToLCKV-Raipur with CoYVMB-Raipur after 8 and 16-18 days inoculation, respectively. This isolate was also transmissible to healthy tomato plants by whitefly from the tomato plant agroinoculated with ToLCKV-Raipur alone and with CoYVMB-Raipur and produced symptoms within 14-16 days after inoculation. Interestingly, this isolate infects horse gram and chilli by whitefly transmission and both the hosts showed positive for DNA A alone but not for betasatellite. Quantification of the genomic components of this isolate with the agroinoculated N. benthamiana samples by qRT-PCR results showed that the quantity of ToLCKV-Raipur was enhanced by three-fold while inoculated with CoYVMB-Raipur compared to ToLCKV-Raipur alone inoculated plants. However, CoYVMB-Raipur did not enhance the levels of ToLCKV-Raipur in the agroinoculated tomato plants. This is the first evidence of the natural co-occurrence of ToLCKV with betasatellite, CoYVMB causing ToLCD.

Etiological factors &amp; microbiological characteristics of infectious keratitis in western Maharashtra

To identify the etiological factors and study the microbiological characteristics of infectious keratitis in Western Maharashtra. This was a prospective observational hospital‐based study conducted at the Department of Ophthalmology, at a tertiary care hospital, in a part of central India. Data related to socioeconomic status and etiological factors was collected. Results were analyzed on the basis of history, slit lamp examination, microbiological scraping and culture results. During the period of September 2018 to August 2020, a total of 60 patients with infectious keratitis were examined in the Ophthalmology OPD. Majority of patients of infectious keratitis were between 61 and 70 (18.33%) age group. Incidence in male was higher (68%) than female. Ocular trauma was the most common etiological factor (52%). Prevalence of Fungal keratitis (52%) was higher than bacterial (46%) in this part of India. 57% subjects showed organism on Gram staining. 53% subjects showed KOH positivity. 68.3% showed growth over microbiological culture with the most common species isolated as Fusarium species (26.6%) followed by Pseudomonas aeruginosa. Incidence of fungal keratitis is higher in this part of Western Maharashtra. Most common etiological factor was determined to be trauma with vegetative matter among farmers which tells us that they are most prone for infectious keratitis. Prompt diagnosis, microbiological scraping, culture growth identification and starting on appropriate treatment can help reduce the morbidity of corneal ulcers.

A Comparative Economic Analysis of Tulsi and Other Competitive Crops in Central Part of India

The study has been conducted in Ratlam, Mandsaur and Neemuch districts in Malwa Plateau location of Madhya Pradesh. The researcher has been selected Tulsi crop on the premise of most regions included by it. From the selected districts, 6 blocks 30 villages (and forty five pattern farmers were decided on randomly for detail investigation. For estimation value and returns, fee ideas Cost Concepts and B.C. Ratio had been considered. The cost of cultivation becomes estimated to be Rs. 40811.31, Rs. 21892.Eleven and Rs. 34445.04 for Tulsi, Soybean and Maize respectively. Regarding fee of manufacturing, it became Rs. 4739, Rs. 1360 and Rs. 956 beneath Tulsi, Soybean and Maize crop respectively. The statistics discovered that the net income turned into expected to be Rs. 40720, Rs. 21325 and Rs. 14963 for Tulsi, soybean and Maize crop respectively. It clear cut indicates that 37 to fifty two percentage greater profits benefit from Tulsi crop than the soybean and maize crop by way of the sample farmers. As a ways as the B.C. Ratio became worried it was envisioned to be 1:1.99, 1:1.97 and 1:1.43 for Tulsi, soybean, and maize crop respectively, which shows that the Tulsi crop changed into greater profitable than their competitive plants.

Multi-Model Multi-Physics Ensemble: A Futuristic Way to Extended Range Prediction System

In an endeavor to design better forecasting tools for real-time prediction, the present work highlights the strength of the multi-model multi-physics ensemble over its operational predecessor version. The exiting operational extended range prediction system (ERPv1) combines the coupled, and its bias-corrected sea-surface temperature forced atmospheric model running at two resolutions with perturbed initial condition ensemble. This system had accomplished important goals on the sub-seasonal scale skillful forecast; however, the skill of the system is limited only up to 2 weeks. The next version of this ERP system is seamless in resolution and based on a multi-physics multi-model ensemble (MPMME). Similar to the earlier version, this system includes coupled climate forecast system version 2 (CFSv2) and atmospheric global forecast system forced with real-time bias-corrected sea-surface temperature from CFSv2. In the newer version, model integrations are performed six times in a month for real-time prediction, selecting the combination of convective and microphysics parameterization schemes. Additionally, more than 15 years hindcast are also generated for these initial conditions. The preliminary results from this system demonstrate appreciable improvements over its predecessor in predicting the large-scale low variability signal and weekly mean rainfall up to 3 weeks lead. The subdivision-wise skill analysis shows that MPMME performs better, especially in the northwest and central parts of India.