Sarita AzadIndian Institute of Technology Mandi | भारतीय प्रौद्योगिकी संस्थान मंडी · School of basic science
Sarita Azad
Doctor of Philosophy
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52
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529
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Citations since 2017
Publications
Publications (52)
The main goal of this research is to assess the Indian Monsoon Data Assimilation and Analysis (IMDAA), a recently established high‐resolution (0.12°×0.12°) reanalysis dataset, for observing cloudburst events over the Northwest Himalaya (NWH). In addition, a high‐resolution (0.1°×0.1°) satellite estimate, the Integrated Multi‐satellitE Retrievals fo...
The economic impact of the COVID-19 pandemic has been devastating for countries across the world. We propose a novel method for estimating reproduction number (R 0) using community mobility to obtain optimal vaccination coverage (OVC). Different scenarios for achieving the desired immunization rates are evaluated using nonlinear regression models....
Temperatures have risen at a faster rate across various mountainous regions around the world. A study of the changing rainfall patterns and their spatiotemporal variability is critical for agricultural, water resource, and hydrological planning and management. The goal of this research is twofold: first, using functional data analysis climate chang...
Mountainous regions are often faced with various challenges of monitoring and predicting accurate rainfall due to complex topography. Satellite precipitation estimates serve as rich repositories of data, which are highly valuable for varied applications. However, it is essential to prioritize satellite estimates based on their performance in captur...
Recent studies have shown that the univariate exponentiated Teissier distribution is an effective model for analysing rainfall data. A bivariate probability distribution offers greater insight into a process like a flood, or drought than a univariate method for analysing the characteristics of environmental occurrences. As a result, in this study w...
The temperature in the mountains has been increasing at an unprecedented rate in the global warming era. As a result, it is necessary to evaluate suitable models that could provide precise maximum temperature estimates. This paper explores the goodness-of-ft of the two-parameter bell-shaped, light-tailed, and heavy-tailed distribution functions for...
In the global warming era, discovering new probability distribution for modelling the meteorological parameters is highly desirable. Particularly, in some instances, experts' interest lies mainly in the extreme values like maximum rainfall, temperature, level of flood water, etc. In this article, we introduced a probability distribution for modelli...
The present study aims to evaluate four satellite estimates, namely CMORPH v0.x, PER-SIANN-CDR, TMPA-V7 and TMPA-V7-RT, over four seasons (during 2003-2017) against ground observations (0.25° × 0.25° lat./long). For this purpose, precipitation statistics such as MEAN (mean overall days), AWET (mean over wet days), NDRY (no. of dry days), NWET (no....
Pandemics have a high socio-economic impact on countries. Singapore and Taiwan, which had pandemic strategies in place, fared much better than almost all other countries in the world during the recent COVID-19 pandemic. In a massive country like India, the coronavirus (COVID-19) has infected millions of people. While studies have estimated the rate...
Past versions of the vulnerability indices have shown the ability to detect susceptible regions by assessing climatic and socioeconomic parameters at local scales. These parameters significantly vary over geographic regions, therefore such an index may not be suitable to identify and predict susceptibility over a large domain. The present endeavour...
A new exponentiated generalized linear exponential distribution (NEGLED) is introduced, which poses increasing, decreasing, bathtub-shaped, and constant hazard rate. Its various mathematical properties such as moments, quantiles, order statistics, hazard rate function (HRF), stress–strength parameter, etc. are derived. Five distributions, exponenti...
The proposition of a new algorithm facilitates the predictability of weak/strong monsoons that lead to drought/flood events, respectively, in the Indian summer monsoon rainfall (ISMR). The proposed method estimates skewed Gaussian kernel distribution in the extreme values extracted from the rainfall series, and confidence levels of drought and floo...
Past versions of vulnerability index have shown ability to detect susceptible region by assessing socio-economic parameters at local scales. However, due to variability of these vulnerability index respect to socio-economic parameters, cann’t be utilized to predict the susceptibility region. The present endeavor aims to develops a new vulnerable in...
Drought is a function of time as well as climate variables such as temperature and precipitation. The process of drought forming is slow, and it manifests at different time scales, which adversely affects the economy of a country. The identification and characterization of droughts at various spatiotemporal scales are of great importance. It helps...
Background:
The coronavirus pandemic (COVID-19) has spread worldwide via international travel. This study traced its diffusion from the global to national level and identified a few superspreaders that played a central role in the transmission of this disease in India.
Data and methods:
We used the travel history of infected patients from Januar...
1. ABSTRACT Forty five natural populations of Drosophila ananassae, collected from entire geo-climatic regions of the India were analyzed to determine the distribution of genetic diversity relative to different eco-geographic factors. Quantitative data on the frequencies of three cosmopolitan inversions in the sampled populations were utilized to d...
Social network analysis is an essential means to uncover and examine infectious contact relations between individuals. This paper aims to investigate the spread of coronavirus disease (COVID-19) from international to the national level and find a few super spreaders which played a central role in the transmission of disease in India. Our network me...
The presence of a sparse rain gauge network in complex terrain like Himalaya has encouraged the present study for the concerned evaluation of Indian Meteorological Department (IMD) ground-based gridded rainfall data for highly prevalent events like cloudbursts over Northwest Himalaya (NWH). To facilitate the above-mentioned task, we intend to evalu...
The very first case of corona-virus illness was recorded on 30 January 2020, in India and the number of infected cases, including the death toll, continues to rise. In this paper, we present short-term forecasts of COVID-19 for 28 Indian states and five union territories using real-time data from 30 January to 21 April 2020. Applying Holt’s second-...
India’s agricultural production, which is a significant component of the Gross National Product, is largely dependent on the Indian summer monsoon. This makes an accurate prediction of Indian summer monsoon rainfall a key factor in improving agricultural
production. A statistical cycle widely known to have a strong 2.8 y period and will therefore b...
The diligence of global warming over the course of 20th century has been an impelling driver of climate change and consequently of socioeconomic developments across the world. The warming is clearly evident in the linear trend of time series (in particular, climate). A linear trend estimation expresses data as a linear function of time, in particul...
The Tropical Rainfall Measuring Mission (TRMM) 3B42 version 7 precipitation data has been extensively used for inter-comparison with observations and model validation. The rain distribution over the Northwest Himalaya (NWH) were found to be accurate with a strong positive correlation of 0.88 between TRMM and India Meteorological Department (IMD) st...
The severity of rainfall exposure endured by vertical building facades is often quantified using the “annual driving rain index (aDRI)” subjected to the availability of adequate wind and rainfall data. The present endeavor adopts the instance of Indian subcontinent to demonstrate the suitability of gridded data, which represent the average climatic...
The present endeavour aims to identify the spatiotemporal footprints of temperature change in India by
analysing monthly temperature data pertaining to the period of 1901–2005. Functional data analysis (FDA) has been implemented for detecting the temporal manifestation of mean change years. The estimated change years have been observed to largely p...
Estimates of driving rain index at finer spatial resolutions facilitate a reliable consideration of potential moisture loads in the design of efficient building envelopes for any given location. In this study, a driving rain index map for India has been developed at 1°×1°(lat./long.) resolution using 60-years’ 1951–2010) monthly data for rainfall a...
Background Tuberculosis (TB) is one of the main causes of mortality on the globe. Besides the full implementation of Revised National Tuberculosis Control Programme (RNTCP), TB continues to be a major public health problem in India. Methods In the present study, parameters of a TB model are estimated using Ensemble Kalman filter (EnKf) approach. In...
The annual cycle of Indian monsoon rainfall plays a critical role in the agricultural as well as the industrial sector. Thus, it is necessary to evaluate the behaviour of the monsoon annual cycle in a warming climate. There are several studies on the variability and uncertainty of the Indian monsoon. This study, examines the impact of climate chang...
EI Nino-Southern Oscillation (ENSO) and Indian monsoon rainfall are known to have an inverse relationship, which we have observed in the rainfall spectrum exhibiting a spectral dip in 3–5 y period band. It is well documented that El Nino events are known to be associated with deficit rainfall. Our analysis reveals that this spectral dip (3–5 y) is...
Monsoons are the life and soul of India’s financial aspects, especially that of agribusiness in deciding cropping patterns. Around 80% of the yearly precipitation occurs from June to September amid monsoon season across India. Thus, its seasonal mean precipitation is crucial for agriculture and the national water supply. From the start of the 19th...
This paper examines monthly and annual data to analyse predictability in the Indian monsoon rainfall. The periodic structure in the time series data is extracted using wavelets and the residual random part is separately modeled using artificial neural networks (ANN). Although wavelet and neural network based hybrid techniques have been widely appli...
Tuberculosis (TB) is one of the most common infectious diseases and a leading cause of death in the world. Despite the full implementation of Revised National Tuberculosis Control Programme, the disease continues to be a leading cause of morality and economic burden in India. The basic reproduction is a fundamental key parameter that quantifies the...
An optimum selection of potential future energy resources is now need of all the nations. This study aim1s to rank viable energy resources for India. We consider six sources of energy namely, hydropower, solar, wind, coal and lignite, gas and liquid, and nuclear energy. The objective is to provide a quantitative analysis for the selection of most f...
A significant seasonal variation in tuberculosis (TB) is observed in north India during 2006-2011, particularly in states like Himachal Pradesh, Haryana and Rajasthan. To quantify the seasonal variation, we measure average amplitude (peak to trough distance) across seasons in smear positive cases of TB and observe that it is maximum for Himachal Pr...
Background & objectives:
Malaria and dengue fever are the most common mosquito-borne diseases in the Southeast Asia region (SEAR). We analysed a temporal record of annual cases of malaria and dengue fever from 1985-2009 in SEAR.
Methods:
Data of dengue and malaria cases were obtained from WHO website for the period from 1985-2009. El-Nino Southe...
This work deals with the ranking of Indian states and territories based on several socio-economic indicators namely education, basic living standards, economic standard, awareness, crime against minors, crime rate, status of women, public safety, health care and energy consumption. It is done using a decision making tool namely Technique for Order...
The analysis of strategic partnerships is an important task for policy makers. Quantitative studies are sparse in this area. The objective of this paper is to provide a systematic method to rank India's strategic relations with other countries. Analytic Hierarchy Process (AHP) technique
is a multi-criteria decision-making technique that has been us...
Forecasting an epidemic is a complex task because of its dependence on multiple parameters. The challenges pose by sparse and error-prone data is addressed by stochastic data assimilation model. A two-step algorithm based on ensemble Kalman filter is applied to forecast malaria incidence. The temporal dependence of the data is modelled using simple...
The objective of the present study is to examine the predictability of extreme Indian rainfall years. The all-India rainfall and recently defined spectrally homogeneous region (SHR7) are studied in relation with negative of second derivative (represented as –S′′m)
of annual sunspot numbers for the period 1871–2005. We argue that SHR7, which include...
This paper analyses, the terror attacks in Mumbai on November 26, 2008, popularly known as 26/11 terror attacks, as per a mathematical technique known as Social Network Analysis (SNA). This analysis of the behaviour of the ten attackers and their telephonic communications with their handlers in Pakistan even as the attacks were in progress is based...
In this paper a statistical method for assessing the significance of common periodicities in two correlated time series is proposed. The algorithm uses the hypothesis of Hotelling T
2 statistic and confidence ellipses. The procedure is illustrated on a test case involving
two cross-correlated synthetic white noise signals on which a weak periodic s...
This work presents results of a sharper search for significant periodicities in Indian monsoon rainfall, based on the recognition of the area's meteorological heterogeneity. Towards this end, a quantitative definition of spectral homogeneity is proposed, and the concept is used to classify India into distinct spectrally homogeneous regions (SHR) by...
In the last few decades there has been increasing interest in applying techniques from wavelet theory to nonlinear dynamics. In this work discrete wavelet transform is used as an exploratory method to analyze logistic map at different values of the control parameter. In particular, capability of multi-resolution analysis is explored in identifying...
This paper is a sequel to a recent study of the authors' that uses a combination of multiresolution analysis (MRA) and classical Fourier spectral methods, to identify 17 peaks in the power spectral density of the Homogeneous Indian Monsoon (HIM) rainfall time series constructed in Ref. 1. Here we propose a new procedure for testing the statistical...
In this paper we make use of the multiresolution properties of discrete wavelets, including their ability to remove interference, to reveal closely spaced spectral peaks. We propose a procedure which we first verify on two test signals, and then apply it to the time series of homogeneous Indian monsoon rainfall annual data. We show that, compared t...
We aim to present a new approach that has recently gained momentum in field of nonlinear dynamics. This method is based on time-frequency decomposition of a time series using wavelets and has ability to detect transitions at a exact parameter value where solution space bifurcates from order to chaos. In particular we are considering the time series...
Projects
Projects (2)
In the midst of a global pandemic, we are focusing on developing forecasting and analysis tools to understand the situation in Indian states.
The goal of the endeavor aims to provide guidance to the choice of global precipitation data sets (GPDs). In particular, this study is conducted to evaluate three recent satellite-based rainfall products, i.e. Global Precipitation Measurements (GPM), Indian National Satellite System (INSAT 3D), and CPC Morphing Technique (CMORPH), against the highly used TRMM-RT 3B42 V7 precipitation data for the estimation of rainfall episodes in the recent years (2014-2016).
