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Article: Projection of annual maximum temperature over Northwest Himalayas using probability distribution models

Poonia, Neeraj / Azad, Sarita

Theoretical and applied climatology. 2022 Aug., v. 149, no. 3-4

2022

Abstract: 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- ... ...

Abstract	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-fit of the two-parameter bell-shaped, light-tailed, and heavy-tailed distribution functions for modeling the annual maximum temperature in the Northwest Himalayan region of India. The distributions under consideration are Gamma, Gumbel, Lognormal, Normal, and Weibull. Method of maximum likelihood estimation is used for parameter estimation along with Akaike information criteria for model selection. Gridded data from Climate Research Unit, UK, was obtained at the 525 grids of the region. This study shows that Normal distribution gives the best fit followed by Lognormal and Gamma distributions, and these three models jointly fit all the grids in the region. Furthermore, we estimate the 5, 10, 20, 50, 100, and 500 years return level of annual maximum temperature starting from 2017. The future projections reveal that, on average, the region will face [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text] temperature rise by the years 2022, 2027, 2037, 2067, 2117, and 2517, respectively. In comparison to the middle of the region, the higher and lower belts of the region will be severely impacted.
Keywords	Weibull statistics ; climate ; climatology ; normal distribution ; temperature ; Himalayan region ; India
Language	English
Dates of publication	2022-08
Size	p. 1599-1627.
Publishing place	Springer Vienna
Document type	Article
ZDB-ID	1463177-5
ISSN	1434-4483 ; 0177-798X
ISSN (online)	1434-4483
ISSN	0177-798X
DOI	10.1007/s00704-022-04121-5
Database	NAL-Catalogue (AGRICOLA)

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Article: Alpha power exponentiated Teissier distribution with application to climate datasets

Poonia, Neeraj / Azad, Sarita

Theoretical and applied climatology. 2022 July, v. 149, no. 1-2

2022

Abstract: 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, ... ...

Abstract	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 modelling annual maximum rainfall and temperature of four locations in India. We derived statistical properties of the proposed model like survival function, hazard rate function, median, mode, skewness, kurtosis, etc. The proposed model exhibits decreasing, increasing, and uni-modal density functions including bathtub-shaped, increasing, and decreasing hazard rates. Parameters of the proposed model were estimated using the method of maximum likelihood estimation. At last, four real-life datasets, two of annual maximum rainfall and another two of temperature, were used to show the efficiency of the proposed model. Four distributions, namely Gumbel (type 1 generalized extreme value distribution), Fréchet (type 2 generalized extreme value distribution), Teissier, and exponentiated Teissier distributions, were used for comparison with the proposed model. Later, we calculated the return level of both datasets for different return periods. And the 95% bootstrap confidence intervals are constructed for the parameters of the proposed model.
Keywords	climate ; climatology ; data collection ; models ; probability distribution ; rain ; temperature ; India
Language	English
Dates of publication	2022-07
Size	p. 339-353.
Publishing place	Springer Vienna
Document type	Article
ZDB-ID	1463177-5
ISSN	1434-4483 ; 0177-798X
ISSN (online)	1434-4483
ISSN	0177-798X
DOI	10.1007/s00704-022-04039-y
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Regional selection of satellite estimates over the Northwest Himalayan region using the merged ranking methods

Garg, Sourabh / Jena, Pravat / Azad, Sarita

Theor Appl Climatol. 2023 Jan., v. 151, no. 1-2 p.515-533

2023

Abstract: 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. ...

Abstract	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 capturing the weather patterns over mountainous terrains like Northwest Himalayas (NWH). The present study has spatially ranked five satellite estimates, namely, APHRODITE-V1901, CHIRPS-V2.0, CMORPH-V1.0, PERSIANN-CDR-V1, and TMPA-3B42-V7 against the Indian Meteorological Department observed data at 0.25° × 0.25° resolution over the period 1998–2018. An ensemble methodology that incorporates the ranking methods like GRA, MAUT, TOPSIS, and WASPAS and the statistical metrics is proposed. The analysis is based on precipitation indices such as consecutive wet days, R20mm, Rx1day, Rx5day, total precipitation, R95p, R99p, and SDII. The results show that, in order to monitor rainfall across the NWH region, APHRODITE-V1901 secured the first ranking, followed by PERSIANN-CDR-V1, while CHIRPS-V2.0 received the last rank. Further, NWH is divided into five regions, i.e., region I, region II, region III, region IV, and region V concerning elevation. The ensemble merged ranking method is applied in each of the classified regions. The results reveal that APHRODITE-V1901 secured the first rank in region II, CHIRPS-V2.0 in region IV, CMORPH-V1.0 in region I, PERSIANN-CDR-V1 in region V, and TMPA-3B42-V7 in region III. The analysis of the extreme rainfall events is performed towards the end using the best satellite estimates for the designated locations.
Keywords	mountains ; rain ; satellites ; topography ; Himalayan region
Language	English
Dates of publication	2023-01
Size	p. 515-533.
Publishing place	Springer Vienna
Document type	Article ; Online
ZDB-ID	1463177-5
ISSN	1434-4483 ; 0177-798X
ISSN (online)	1434-4483
ISSN	0177-798X
DOI	10.1007/s00704-022-04277-0
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic.

Azad, Sarita / Devi, Sushma

Journal of travel medicine

2020 Volume 27, Issue 8

Abstract: 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 ... ...

Abstract	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 30 January to 6 April 6 2020 as the primary data source. A total of 1386 cases were assessed, of which 373 were international and 1013 were national contacts. The networks were generated in Gephi software (version 0.9.2). Results: The maximum numbers of connections were established from Dubai (degree 144) and the UK (degree 64). Dubai's eigenvector centrality was the highest that made it the most influential node. The statistical metrics calculated from the data revealed that Dubai and the UK played a crucial role in spreading the disease in Indian states and were the primary sources of COVID-19 importations into India. Based on the modularity class, different clusters were shown to form across Indian states, which demonstrated the formation of a multi-layered social network structure. A significant increase in confirmed cases was reported in states like Tamil Nadu, Delhi and Andhra Pradesh during the first phase of the nationwide lockdown, which spanned from 25 March to 14 April 2020. This was primarily attributed to a gathering at the Delhi Religious Conference known as Tabliqui Jamaat. Conclusions: COVID-19 got induced into Indian states mainly due to International travels with the very first patient travelling from Wuhan, China. Subsequently, the contacts of positive cases were located, and a significant spread was identified in states like Gujarat, Rajasthan, Maharashtra, Kerala and Karnataka. The COVID-19's spread in phase one was traced using the travelling history of the patients, and it was found that most of the transmissions were local.
MeSH term(s)	Air Travel/statistics & numerical data ; COVID-19/epidemiology ; COVID-19/prevention & control ; Communicable Disease Control/methods ; Contact Tracing/methods ; Contact Tracing/statistics & numerical data ; Disease Transmission, Infectious/prevention & control ; Disease Transmission, Infectious/statistics & numerical data ; Global Health/statistics & numerical data ; Humans ; India/epidemiology ; SARS-CoV-2 ; Social Networking ; Travel Medicine/methods ; Travel Medicine/trends ; Travel-Related Illness
Keywords	covid19
Language	English
Publishing date	2020-08-05
Publishing country	England
Document type	Journal Article
ZDB-ID	1212504-0
ISSN	1708-8305 ; 1195-1982
ISSN (online)	1708-8305
ISSN	1195-1982
DOI	10.1093/jtm/taaa130
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Analysis of genetic diversity in indian natural populations of

Singh, Pranveer / Narula, Pankaj / Azad, Sarita

Frontiers in bioscience (Elite edition)

2020 Volume 12, Issue 2, Page(s) 237–253

Abstract: Forty five natural populations ... ...

Abstract	Forty five natural populations of
MeSH term(s)	Animals ; Chromosome Inversion ; Drosophila/genetics ; Female ; Genetic Variation ; India ; Phylogeography ; Seasons
Language	English
Publishing date	2020-06-01
Publishing country	Singapore
Document type	Comparative Study ; Journal Article
ZDB-ID	2565080-4
ISSN	1945-0508 ; 1945-0494
ISSN (online)	1945-0508
ISSN	1945-0494
DOI	10.2741/E869
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Article: A novel method to detect drought and flood years in Indian rainfall associated with weak and strong monsoon

Jena, Pravat / Azad, Sarita

Theoretical and applied climatology. 2021 July, v. 145, no. 1-2

2021

Abstract: 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 ... ...

Abstract	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 flood years are obtained using bootstrap. Using the selected Coupled Model Intercomparison Phase 5 (CMIP5) simulations under representative concentration pathways (RCP) 8.5 scenario, the proposed method detects that extreme droughts (at 99% confidence level) in India are likely to occur in 2024 and 2027 in the early 21st century. Similarly, models project that 2031, 2032, and 2033 will be the most prominent flood years. It is projected that the probability of drought occurrence is likely to increase by 16%. In contrast, it is expected to diminish flood events by 11% in the future under projected global warming. Notably, our analysis reveals that 23.4% of grids covering ~30% of the Indian region are likely to experience increased frequency and intensity of droughts during 2020–2029, mainly covering the Northeast, Central, and Southern India. Furthermore, during this period, the Northeast and some parts in the North would experience floods over 29.6% (which covers ~ 39%) of the total grids. The proposed algorithm may be used for drought and flood monitoring over any geographical terrain.
Keywords	algorithms ; climatology ; drought ; landscapes ; models ; monsoon season ; probability ; rain ; India
Language	English
Dates of publication	2021-07
Size	p. 747-761.
Publishing place	Springer Vienna
Document type	Article
ZDB-ID	1463177-5
ISSN	1434-4483 ; 0177-798X
ISSN (online)	1434-4483
ISSN	0177-798X
DOI	10.1007/s00704-021-03652-7
Database	NAL-Catalogue (AGRICOLA)

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Article: Observed and projected changes in extreme drought and flood-prone regions over India under CMIP5 RCP8.5 using a new vulnerability index

Jena, Pravat / Azad, Sarita

Climate dynamics. 2021 Nov., v. 57, no. 9-10

2021

Abstract: 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 ... ...

Abstract	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 aims to develop a new vulnerablity index that identifies and predicts the spatiotemporal imprint of extreme drought and flood cases at various scales in India by analyzing monthly observed and Coupled Model Intercomparison Phase 5 (CMIP5) rainfall data at a spatial scale of 1° × 1° from 1901 to 2100. It is proposed by consolidating the outcomes of the Standard Precipitation Index (SPI) at different time scales, such as 3 and 12 months, along with the weights of individual grids. The weights of individual grids are calculated through the occurrence of extreme drought and flood years in the recent past to include a climate change factor in the proposed index. Based on the spatial distribution of high index values, the vulnerable regions concerning extreme droughts are expected to be in the Northeast, Northeast-central, East-coast, West, Northwest, North-central, and some grids in South India. Similarly, vulnerable regions concerning extreme flood cases are likely to be in the Northeast, West-coast, East-coast, and some grids in the Peninsular region.Furthermore, a conceptual model is presented to quantify the severity of extreme cases. The analyses reveal that on the CMIP5 model data, 2024, 2026–2027, 2035, 2036–2037, 2043–2044, 2059–2060, and 2094 are likely to be the most prominent extreme drought years in all India monsoon rainfall, and their impacts will persist for a longer time than others. Similarly, the most prominent extreme flood cases are likely to occur in the year 2076, 2079–2080, 2085, 2090, 2092, and 2099.
Keywords	climate ; climate change ; drought ; dynamics ; meteorological data ; models ; monsoon season ; rain ; India
Language	English
Dates of publication	2021-11
Size	p. 2595-2613.
Publishing place	Springer Berlin Heidelberg
Document type	Article
ZDB-ID	1471747-5
ISSN	1432-0894 ; 0930-7575
ISSN (online)	1432-0894
ISSN	0930-7575
DOI	10.1007/s00382-021-05824-7
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Article: Synovial Sarcoma of Ethmoidal Sinus.

Dhiman, Sapna / Negi, Sarita / Moudgil, Sandeep / Thakur, Jagdeep S / Azad, Ramesh K

Surgery journal (New York, N.Y.)

2021 Volume 7, Issue 3, Page(s) e195–e198

Abstract: ... ...

Abstract	Background
Language	English
Publishing date	2021-08-03
Publishing country	United States
Document type	Case Reports
ZDB-ID	2864275-2
ISSN	2378-5136 ; 2378-5128
ISSN (online)	2378-5136
ISSN	2378-5128
DOI	10.1055/s-0041-1731634
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Analysis of genetic diversity in indian natural populations ofdrosophila ananassae

Pranveer Singh / Pankaj Narula / Sarita Azad

Frontiers in Bioscience-Elite, Vol 12, Iss 2, Pp 237-

2020 Volume 253

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 ... ...

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 deduce Nei’s gene diversity estimates. Populations were grouped according to the time of collection (years and month); collection-regions like coastal and mainland regions, and collection-seasons. Further, data was subjected to network analysis to detect community structure in the populations and Modularity analysis to quantify the strength in community structure. Gene-diversity statistics revealed the presence of significant variability in the Indian natural populations of D.ananassae. Off all the parameters used to group the populations, geographical attributes seems to have maximum, while the time of collection and seasons have minimum influence on the genetic variability in Indian natural populations of D.ananassae. The results clearly link the association of genetic variability with environmental heterogeneity, elucidating the role of environment specific natural selection. The homogenizing effects could be due to genetic hitchhiking and canalization.
Keywords	gene diversity ; network analysis ; modularity ; inversions ; chromosome polymorphism ; Environmental sciences ; GE1-350 ; Microbiology ; QR1-502
Subject code	580
Language	English
Publishing date	2020-06-01T00:00:00Z
Publisher	IMR Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article: Tracking the spread of COVID-19 in India via social networks in the early phase of the pandemic

Azad, Sarita / Devi, Sushma

J. travel med

Abstract: 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 ... ...

Abstract	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 January 30 to April 6, 2020, as the primary data source. A total of 1386 cases were assessed, of which 373 were international, and 1013 were national contacts. The networks were generated in Gephi software (version 0.9.2). RESULTS: The maximum numbers of connections were established from Dubai (degree 144) and the UK (degree 64). Dubai's eigenvector centrality was the highest that made it the most influential node. The statistical metrics calculated from the data revealed that Dubai and the UK played a crucial role in spreading the disease in Indian states and were the primary sources of COVID-19 importations into India. Based on the modularity class, different clusters were shown to form across Indian states, which demonstrated the formation of a multi-layered social network structure. A significant increase in confirmed cases was reported in states like Tamil Nadu, Delhi, and Andhra Pradesh during the first phase of the nationwide lockdown, which spanned from March 25 to April 14, 2020. This was primarily attributed to a gathering at the Delhi Religious Conference (DRC) known as Tabliqui Jamaat. CONCLUSIONS: COVID-19 got induced into Indian states mainly due to International travels with the very first patient travelling from Wuhan, China. Subsequently, the contacts of positive cases were located, and a significant spread was identified in states like Gujarat, Rajasthan, Maharashtra, Kerala, and Karnataka. The COVID-19's spread in phase one was traced using the travelling history of the patients, and it was found that most of the transmissions were local.
Keywords	covid19
Publisher	WHO
Document type	Article
Note	WHO #Covidence: #704418
Database	COVID19

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