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Study of a western disturbance

M.S SINGH, S. KUMAR
1977 Mausam  
R ecentlv again Singh (see R ef.) st udied the int ensification of a western disturbanc e oyer northwest India an d found th at it wa s preceded by the dew lopm ent of an upper air trough in the west erlies  ... 
doi:10.54302/mausam.v28i2.2693 fatcat:klcqregvgvbgna33u4fif7qjyy

UNUSUAL SNOWFALL AND THUNDERSQUALLS OVER WESTERN HIMALAYAN REGION DURING 2012

CHARAN SINGH, B. P. YADAV, VIRENDRA SINGH, NARESH KUMAR
2021 Mausam  
Singh and Kumar (1977) carried out the detailed study of western disturbances and a book was published by Upadhyay (1995) about cold climate hydrometeorology associated with western disturbances.  ...  Agnihotri and Singh (1982) studied the WDs approaching northwest India & adjoining areas during winter period (November-March) with the help of satellite cloud imageries.  ... 
doi:10.54302/mausam.v67i4.1425 fatcat:t3a22a7pxbaqhdjycl5zqp6xp4

Estimation of biophysical parameters of rice using Sentinel-1A SAR data in Udham Singh Nagar (Uttarakhand)

CHETAN KUMAR BHATT, AJEET SINGH NAIN
2021 Mausam  
Udham Singh Nagar is the major rice producing area of Uttarakhand state, and falls in Tarai region.  ...  relationship between Sentinel-1A backscattering coefficients 𝜎0VV, 𝜎0VH and (𝜎0VV/𝜎0VH) were analyzed, for this multitemporal data of Sentinel-1A were taken from June 2017 to September 2017 over Udham Singh  ...  The map depicting water content in rice plants in Udham Singh Nagar district has been figured in (Fig. 13 ).  ... 
doi:10.54302/mausam.v72i4.3544 fatcat:dkhurssp2zew5cdybqvkboqeji

Rainfall variability analysis of Uttar Pradesh for crop planning and management

ARVIND KUMAR, P. TRIPATHI, AKHILESH GUPTA, K. K. SINGH, P. K. SINGH, RANJIT SINGH, R. S. SINGH, AMITABH TRIPATHI
2021 Mausam  
Time series analysis and statistical significance of trends in rainfall data was carried out using standard Mann-Kendall test statistics. The non-parametric Mann-Kendall (M-K) statistical rank test, which is widely used in climate research, was employed in this study to find out fluctuations and presence of trend in time series data of rainfall at a single station, as well as regional averages. Analysis of rainfall data of Uttar Pradesh reveals significant decreasing trend in total quantum of
more » ... nual rainfall. It was also noticed that the frequency of occurrence of annual rainfall below normal was less before 1990s while increased after 1990s. The amount of annual rainfall decreased significantly after 1996 from 1040.5 mm to 988 mm, i.e., a decrease of 5 percent. A very interesting trend has been noticed for the quantum of monthly rainfall, i.e., it was found significantly decreased after 1996 for the months of winter season (October-February) while at par for the months of summer season except May only which was found increased as compared to before 1996. The quantum of monthly rainfall was found significantly decreased after 1996 for initial and last months of monsoon season, i.e., June and September while increased for the middle months, i.e., July and August as compared to before 1996. The study of decadal variability in annual rainfall showed that an alternate decreasing and increasing trend in all the three decades viz.
doi:10.54302/mausam.v69i1.244 fatcat:rkskspfpfzde3dxwk4iv7axb7u

Comparison of recent rainfall trend in complex hilly terrain of sub-temperate region of Uttarakhand

UTKARSH KUMAR, SURESH CHANDRA PANDAY, JITENDRA KUMAR, VIJAY SINGH MEENA, MANOJ PARIHAR, SHER SINGH, JAIDEEP KUMAR BISHT, LAKSHMI KANT
2021 Mausam  
The negative rainfall trends are reported by others, such as Singh and Sen Roy (2002) for Beas basin and Kumar and Jain (2010) for Qazigund and Kukarnag of Kashmir.  ...  The results found in this research agree with previous studies conducted in the Himalaya region (Basistha et al., 2009; Singh et al., 2014; Kumar et al., 2015) .  ... 
doi:10.54302/mausam.v72i2.622 fatcat:r2xjurn2qbdbppa67xcbc73654

Delineation of subsurface features by gravity technique in parts of Shivpuri District, M.P

RAJAN KUMAR, ANIL KUMAR SINGH
2021 Mausam  
Aprana Singh for the supporting in work. We are thankful to the Dr. R. K. Gedam, Sr. Geophysicist, Geophysics Division, GSI, CR, Nagpur who have given critical and thoughtful suggestions.  ...  ., 2016; Subasinghe, 1998; Kumar and Punekar, 2018) .  ...  For latitude correction, international gravity formula 1980 was used (Bharati et al., 2016; Gorle et al., 2016; Kumar and Punekar, 2018) .  ... 
doi:10.54302/mausam.v72i3.1316 fatcat:jmabdbj7kzdctnqdzyop3vymoy

Frequencies of drought at Ranchi regions, Jharkhand

P. K. SINGH, L. S. RATHORE, B. ATHIYAMAN, K. K. SINGH, A. K. BAXLA, ASHOK KUMAR, A. K. BHARGAVA
2021 Mausam  
Utilizing this method, the years of drought were identified and their intensities were assessed through a study of the departure of the Ia from the median value, following (Subrahmanyam, 1982 and Singh  ... 
doi:10.54302/mausam.v60i4.1114 fatcat:siuh5b2crvdy3mgh6pz7vkt4am

ARIMA based daily weather forecasting tool: A case study for Varanasi

NIKITA SHIVHARE, ATUL KUMAR RAHUL, SHYAM BIHARI DWIVEDI, PRABHAT KUMAR SINGH DIKSHIT
2021 Mausam  
Autoregressive integrated moving average (ARIMA) is a data mining technique that is generally used for time series analysis and future forecasting. Climate change forecasting is essential for preventing the world from unexpected natural hazards like floods, frost, forest fires and droughts. It is a challenging task to forecast weather data accurately. In this paper, the ARIMA based weather forecasting tool has been developed by implementing the ARIMA algorithm in R. Sixty-five years of daily
more » ... eorological data was procured from the Indian Meteorological Department. The data were then divided into three datasets-(i)1951 to 1975 was used as the training set for analysis and forecasting, (ii)1975 to 1995 was used as monitoring set and (iii)1995 to 2015 data was used as validating set. As the ARIMA model works only on stationary data, therefore the data should be trend and seasonality free. Hence as the first step of R analysis, the acquired data sets were checked for trend and seasonality. For removing the identified trend and seasonality, the data sets were transformed and the removal of irregularities was done using the Simple Moving Average (SMA) filter and Exponential Moving Average (EMA) filter. ARIMA is based on method ARIMA (p,d,q) where p is a value of partial autocorrelation, d is lagged difference between current and previous values and q is a value from autocorrelation. In the present study, we worked on ARIMA (2,0,2) for rainfall data and ARIMA (2,1,3) for temperature data. As a result, it estimated the future values for the next fifteen years. The root means square error values were 0.0948 and 0.085 for rainfall data and temperature data respectively which show that the algorithm worked accurately. The resulted data can be further utilized for the management of solar cell station, agriculture, natural resources and tourism.
doi:10.54302/mausam.v70i1.179 fatcat:edj4p3etxrhlbpsfx3xj7uu63q

The EV1 distribution for modelling extreme In events at Bombay

NITYANAND SINGH, K. KRISHNAN KUMAR
2022 Mausam  
bay ra infall for I. 2.3,6, 12.24 and 48-hr duration have been ext racted from the hourly (cloc k-ho ur) observat ions ta ken at Colaba obser vat o ry durin g 1921-84, deta ils or wh ich a re given by Singh  ... 
doi:10.54302/mausam.v41i3.2734 fatcat:5xdlneukfja7hnhsf6jkbkonty

An analytical model for mountain wave in stratified atmosphere

P. KUMAR, M. P. SINGH, N. NATARAJAN
2021 Mausam  
Kumar. C-7/ 159. Se npura. Chet gunj -werd. V3ra nasi-22 1 001 .  ... 
doi:10.54302/mausam.v49i4.3651 fatcat:te6qnnxglrh7rdbvdqvrrojuti

A rainfall index for hydrological floods/droughts Over India

NITYANAND SINGH, K. KRISHNA KUMAR, R. H. KRIPALANI
2022 Mausam  
In this paper, considering total seasonal rainfall of June through September as well as its time distribution, an index has been evolved for identifying a year as hydrologically flood/drought in different parts of India. After giving a margin of ± 25% to the mean index value for normal years, frequencies of flood/drought year have been calculated. In general, frequencies of both hydrological flood and drought years are more in low rainfall areas as compared to high rainfall areas. They compared
more » ... quite closely with the frequencies of meteorological excessive and deficient rainfall years respectively. But the categorization of some individual years is found to differ between meteorological and hydrological points of view. The nature of these differences is, however, not uniform at all the stations.
doi:10.54302/mausam.v41i3.2748 fatcat:vygqgvlmfvbunp6qor4ot2bxjm

Analysis of trend and temporal variability in rainfall over Northeast India

PRIYANKA SINGH, NARESH KUMAR
2022 Mausam  
Study carried out by Kumar and Jaswal, 2016 for Western Himalayan Region indicates significant decreasing trend in monsoon rainfall and significant increase in post monsoon rainfall.  ...  /MAUSAM annual and seasonal rainfall (Parthasarathy and Dhar, 1975; Mooley and Parthasarathy, 1984; Soman et al., 1988; Thapliyal and Kulshresthra, 1991; Guhathakurta and Rajeevan, 2008; .  ... 
doi:10.54302/mausam.v73i2.5479 fatcat:r3hayyhssbfn7gw2ujaeqmo3ce

Optical characteristics, growth and yield quality of cotton under Different growing environments

SAGAR KUMAR, RAM NIWAS, M. L. KHICHAR, PREM DEEP, AMIT SINGH, YOGESH KUMAR
2021 Mausam  
Similar results were reported by Singh (1999) .  ... 
doi:10.54302/mausam.v69i3.342 fatcat:6y44vgyg7vco7aqfos22mjchze

Estimation of deterministic component of monthly rainfall time series : A case study for Pantnagar

MANISHA MADHAV NAVALE, P. S. KASHYAP, SACHIN KUMAR SINGH, DANIEL PRAKASH KUSHWAHA, DEEPAK KUMAR, PANKAJ KUMAR
2021 Mausam  
Pant University of Agriculture and Technology, Pantnagar (Fig. 1 ) situated in Udham Singh Nagar district of Uttarakhand state.  ... 
doi:10.54302/mausam.v69i3.338 fatcat:xfeucg6wbffkbgf54hmm4inpkm

STATISTICAL ANALYSIS OF SEASONAL AND ANNUAL RAINFALL TRENDS OVER DHANBAD, JHARKHAND INDIA

PRASOON KUMAR SINGH, SHONAM SHARMA
2021 Mausam  
doi:10.54302/mausam.v68i2.644 fatcat:huc556i5rnhi7h7y4ecdci5gxi
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