Browsing by Author "Sinha, Palash"

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    A long-term regional variability analysis of wintertime temperature and its deep learning aspects
    (Springer Science and Business Media Deutschland GmbH, 2023) Singh, Saurabh; Bhatla, R.; Sinha, Palash; Pant, Manas
    In present study, the variability in wintertime maximum (Tmax) and minimum (Tmin) temperature patterns over India using observed and deep learning techniques have been assessed. The analysis has been caried out for the period 1979�2018 during the months from November to February. The month of February depicted strongest variability in Tmax and Tmin over Northwest India (NWI) with significant + ve trend for upper half of the country. Wintertime temperature variability was seen to be dominant in the Indo-Gangetic plain area covering some parts of NWI and Northeast India (NEI) for Tmax and Tmin. Also, a gradual increase in the spatial coverage, engulfing majority of South Peninsular India (SPI) and Central India (CI) of the rising Diurnal Temperature Range (DTR) was found from November to January. Decreasing DTR was observed only for January extending along Indo-Gangetic plains. The model Random Forest (RF) performed quite well relative to Long Short-Term Memory model (LSTM) in predicting the winter temperatures (especially for Tmax) during all the considered months. The RF made a robust Tmax forecast during NDJF over all India (RMSE � 0.51, MAPE � 1.4). However, its performance is not up to the mark during the month of February over NEI (RMSE � 1.63, MAPE � 4.5). The maximum fluctuating patterns of temperature have been found during the month of February. The study emphasizes on algorithm-based approaches to study the temperature, so that better understanding could be developed for the meteorological sub-divisions over India. � 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
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    Assessment of climate change of different meteorological state variables during Indian summer monsoon season
    (Springer, 2022) Bhatla, R.; Maurya, Archana; Sinha, Palash; Verma, Shruti; Pant, Manas
    Long-term assessment of basic meteorological field variability is an important factor that influences the Indian summer monsoon and consequently affects the socio-economic aspects of India. In this study, the spatial and temporal variation of meteorological parameters during summer monsoon season using NCEP/NCAR reanalysis datasets for the period of 70�years (1948�2017) has been analyzed in climatology, early-late phase and multidecadal epochs over India and its regions. Statistical techniques such as the standardized anomaly index of surface temperature, rainfall and zonal and meridional wind (at 850 and 200�hPa) and temporal analysis of Mann�Kendall trend test over six selected regions, viz., North India (NI), Central India (CI), Southern India (SI), Arabian Sea (AS), Bay of Bengal (BoB) and Equatorial Indian Ocean (EIO) reveal higher variability during summer monsoon season from 1948 to 2017. The significant spatial changes in the value of standard deviation and coefficient of variation confirm the early-late phase and multidecadal modulation of the seasonal variability of selected climatic parameters. The results indicate that the escalation in the surface temperature multidecadal variability and trend has dominating characteristics over NI, CI and SI regions at an alarming range (0.5�1.0�C). The major hotspots of increasing early-late phase and multidecadal variability and average precipitation have been found over BoB, EIO and SI (~1�3.5 mm/day). The decreasing changes in the mean rainfall pattern and associated variability is strongly linked with increasing surface warming and significant reduction in the strength of surface zonal wind over BoB, IO, SI and CI region which cause the weakening of important atmospheric circulations such as the role of Somali jet and strong low-level jet (LLJ) during Indian summer monsoon season. Also, the meridional wind at the surface and upper level has shown significant enhancement over AS and EIO. The recent decadal anomaly (2008�2017) is really a matter of concern as precipitation and wind circulation anomaly at 850 and 200�hPa have shown decreasing trends over all the regions. In recent years, the variation in meteorological parameters and distribution are asymmetrical during summer monsoon season in changing climate. � 2022, Indian Academy of Sciences.
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    Simulation of an extreme rainfall event over Mumbai using a regional climate model: a case study
    (Springer, 2022) Pant, Manas; Ghosh, Soumik; Verma, Shruti; Sinha, Palash; Mall, R.K.; Bhatla, R.
    An endeavor has been made to utilize the ICTP�s regional climate model RegCM for simulating one of the most catastrophic rainfall events recorded in the history of Mumbai, India on 26th July 2005. The recent version of the model, i.e., RegCM4.6 has been used to dynamically downscale this extreme event at 25�km horizontal resolution over the South-Asia Coordinated Regional Climate Downscaling Experiment (SA-CORDEX) domain with initial and lateral boundary conditions from ERA-Interim reanalysis (EIN15). Due to the coarse resolution of the EIN15, the rainfall pattern during the extreme rainfall event that occurred over Mumbai is fairly unviable. However, the implementation of the dynamical downscaling using RegCM4.6 successfully able to capture the extreme events. The results indicate the RegCM4.6 using mixed cumulus parameterization scheme (CPS; where the Emanuel scheme is considered over land and the Grell scheme is forced over ocean (EL_GO) capable of downscaling the heavy rainfall event with higher accuracy compared to forcing data. This highly confined event over Mumbai might be a manifestation of the low-pressure area formed over Orissa and the adjoining regions associated with mid-tropospheric cyclonic (MTC) circulation over the western coastal region. A detailed analysis suggests that the RegCM4.6 is able to reproduce the localized event satisfactorily as far as the spatial and temporal aspects are concerned. There is a significant improvement in the model simulated output closer to the observations in terms of qualitative and quantitative analysis of rainfall and large-scale fields. Furthermore, the RegCM satisfactorily simulates the features such as the convergence at the lower level accompanied with the divergence at the upper level, higher cyclonic vorticity near lower level, and presence of an enormous amount of moisture content at different pressure levels. � 2021, The Author(s), under exclusive licence to Springer-Verlag GmbH Austria, part of Springer Nature.
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    Spatio-temporal variability of summer monsoon surface air temperature over India and its regions using Regional Climate Model
    (John Wiley and Sons Ltd, 2021) Verma, Shruti; Bhatla, Rajeev; Ghosh, Soumik; Sinha, Palash; Kumar Mall, Rajesh; Pant, Manas
    In this study, a dynamically downscaled regional climate model (RegCM4.3) is used to study the Indian summer monsoon (ISM) surface air temperature over the South-Asia CORDEX domain using six convection schemes during 1986�2010. The spatial and temporal variability of mean surface air temperature has been analysed with reference to the India Meteorological Department (IMD) analysis data using various statistical scores. The sensitivity experiments in selecting the best convective parameterized schemes have been performed in simulating the surface air temperature during the summer monsoon season (June�September) over India and its five sub-regions such as Northwest India, Northcentral India, West Peninsular India, Eastern Peninsular India, and Southern Peninsular India. The model results show the tendency of overestimation of surface air temperature mainly in four cumulus parameterization schemes (CPSs) that is, Tiedtke, Emanuel, Mix98, and Mix99 of RegCM4.3 during the JJAS, where Grell and Kuo CPSs show better agreement with the IMD data. Overall, Grell CPS has a close resemblance to the observation data with a minimum root mean square error, mean absolute error, lowest mean absolute percentage error (MAPE), and higher correlation coefficient. The model simulated results have also been investigated further using modified Nash Sutcliffe efficiency and modified Willmott's degree of index. These analyses confirm the potentiality of the Grell CPS followed by the Kuo CPS in simulating interannual variability of the surface air temperature over Indian and its five sub-regions. The MAPE in Grell and Kuo CPSs are 0.004 and 0.013�C during monsoon season over India, respectively. The inter-scheme difference in simulating surface air temperature is linked with the generation of low cloud convection and warming-induced atmospheric moisture advection in the schemes. Therefore, Emanuel, Tiedtke, and Mix98 CPSs have shown a persistent nature of overestimation in surface air temperature variability during JJAS. It is also inferred that after removing the systematic mean bias from the RegCM4.3 model simulated outputs; the skill of Emanuel, Mix98, and Mix99 could be useful over the Indian subcontinent except for the southern peninsular region. � 2021 Royal Meteorological Society