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1,071 results on '"Mohapatra, M."'

7. Pacific decadal oscillation causes fewer near-equatorial cyclones in the North Indian Ocean.

Author

Roose, Shinto, Ajayamohan, R, Ray, Pallav, Sabeerali, C, Mohapatra, M, Taraphdar, S, Mohanakumar, K, Rajeevan, M, and Xie, Shang-Ping

Abstract

Tropical cyclones do not form easily near the equator but can intensify rapidly, leaving little time for preparation. We investigate the number of near-equatorial (originating between 5°N and 11°N) tropical cyclones over the north Indian Ocean during post-monsoon season (October to December) over the past 60 years. The study reveals a marked 43% decline in the number of such cyclones in recent decades (1981-2010) compared to earlier (1951-1980). Here, we show this decline in tropical cyclone frequency is primarily due to the weakened low-level vorticity modulated by the Pacific Decadal Oscillation (PDO) and increased vertical wind shear. In the presence of low-latitude basin-wide warming and a favorable phase of the PDO, both the intensity and frequency of such cyclones are expected to increase. Such dramatic and unique changes in tropical cyclonic activity due to the interplay between natural variability and climate change call for appropriate planning and mitigation strategies.

Published
2023

11. On the Relative Role of East and West Pacific Sea Surface Temperature (SST) Gradients in the Prediction Skill of Central Pacific NINO3.4 SST

Author

S, Lekshmi, Chattopadhyay, Rajib, Pai, D. S., Rajeevan, M., Valsala, Vinu, Hosalikar, K. S., and Mohapatra, M.

Subjects
Physics - Atmospheric and Oceanic Physics, Physics - Data Analysis, Statistics and Probability
Abstract

Dominant modes of SST in the west and east Pacific show strong but regionally different gradients caused by waves, internal dynamics, and anthropogenic warming, which drives air-sea interaction in the Pacific. The study discusses the relative contribution of SST gradients over the western and eastern Pacific to the prediction skill of SST in the central Pacific, where El-Nino, La-Nina, or El-Nino Modoki events project significantly. For this, the analysis develops a convolutional neural network (CNN) based prediction model to predict the Nino3.4 SST. CNN-based prediction models use a spatial filter at the initial stage, which is highly efficient in capturing the edges or gradients and hence are useful to understand the role of SST spatial gradients in the prediction skill. The study reports three CNN-based model experiments. The first one is a CTRL experiment that uses the whole equatorial Pacific domain SST pattern. The second and third models use the equatorial eastern and western Pacific domain SST only. Another novel feature of this study is that we have generated a large number of ensemble members (5000) through random initialization of CNN filters. It is found that random initialization affects the forecast skill, and the probability density function of the correlation skill of the 5000 models at each lead time shows a gaussian distribution. The model experiments suggest that the west Pacific SST model provides better Nino3.4 skills as compared to the east Pacific skill. The CNN-based model forecast based on the SST pattern, thus, shows the impact of the SST spatial pattern on the ENSO forecast., Comment: 21 pages, 11 figures

Published
2023
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27. Bay of Bengal Intraseasonal Oscillations and the 2018 Monsoon Onset

Author

Shroyer, Emily, Tandon, Amit, Sengupta, Debasis, Fernando, Harindra J. S., Lucas, Andrew J., Farrar, J. Thomas, Chattopadhyay, Rajib, de Szoeke, Simon, Flatau, Maria, Rydbeck, Adam, Wijesekera, Hemantha, McPhaden, Michael, Seo, Hyodae, Subramanian, Aneesh, Venkatesan, R, Joseph, Jossia, Ramsundaram, S., Gordon, Arnold L., Bohman, Shannon M., Pérez, Jaynise, Simoes-Sousa, Iury T., Jayne, Steven R., Todd, Robert E., Bhat, G. S., Lankhorst, Matthias, Schlosser, Tamara, Adams, Katherine, Jinadasa, S. U. P, Mathur, Manikandan, Mohapatra, M., Rao, E. Pattabhi Rama, Sahai, A. K., Sharma, Rashmi, Lee, Craig, Rainville, Luc, Cherian, Deepak, Cullen, Kerstin, Centurioni, Luca R., Hormann, Verena, MacKinnon, Jennifer, Send, Uwe, Anutaliya, Arachaporn, Waterhouse, Amy, Black, Garrett S., Dehart, Jeremy A., Woods, Kaitlyn M., Creegan, Edward, Levy, Gad, Kantha, Lakshmi H., and Subrahmanyam, Bulusu

Published
2021

34. Heat Transfer in Triple-Concentric-Pipe Heat Exchanger: With/Without Corrugations

Author

Beura, S., Mishra, V. P., Das, S. N., Mohanty, U. K., Mohapatra, M., Thatoi, D. N., Cavas-Martínez, Francisco, Series Editor, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Haddar, Mohamed, Series Editor, Ivanov, Vitalii, Series Editor, Kwon, Young W., Series Editor, Trojanowska, Justyna, Series Editor, Ramgopal, Maddali, editor, Rout, Sachindra Kumar, editor, and Sarangi, Sunil Kr, editor

Published
2021
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38. Climatology of thermodynamic indices and background synoptic conditions responsible for severe convection during pre‐ to post‐monsoon seasons over Indian region.

Author

Madhulatha, A., Mohapatra, M., Devi, K. Sathi, Pattanaik, D. R., Rajeevan, M., Das, Anand Kumar, Jenamani, R. K., and Kumar, Naresh

Subjects
*CLIMATOLOGY, *PRECIPITABLE water, *WIND shear, *JET streams, *SEASONS
Abstract

To investigate the mechanisms responsible for severe convection linked with a variety of mesoscale, synoptic systems over the Indian region, a preliminary analysis is conducted. Using IMD RSRW/Reanalysis (ERA5)/Lightning (TRMM LIS) products both local‐scale thermodynamics and large‐scale background conditions responsible for the major lightning hot spots in different seasons are investigated. In the pre‐monsoon season, high lightning activity over NE Indian region is due to moisture intrusion by south‐westerly at lower levels (warm air advection), along with mid‐level north westerlies (cold air advection) which favour the low‐level convergence and upper‐level divergence. SCS over south India are mainly attributed to wind discontinuity over the region. During monsoon season major lightning activity in NW India is due to the presence of heat low and the rest of the country less intense SCS activity is evident due to high wind shear conditions in connection with low‐level (westerly) and upper‐level (easterly jet stream). In the post‐monsoon season, major lightning in south India are due to the prevailing north‐easterlies and in north India, the activity is attributed to the passage of western disturbance (WD). Station plot analysis suggests the varied distribution of thermodynamic indices season/region‐wise due to the diverse background forcing. Correlation analysis between the lightning and thermodynamic indices suggests that more skillful indices are KI (~0.7 to 0.8), precipitable water (PPW) (~0.8) (pre‐monsoon, monsoon) and (PPW) (~0.8), convective available potential energy (CAPE) (~0.6) in post monsoon over respective lightning hot‐spot regions. Independent verification using Wyoming data/reanalysis for different case studies suggests that monitoring the monthly thresholds of highly correlated indices provides a helpful proxy to operationally forecast the severe convective systems (season/region). Mean Equivalent potential temperature, and mixing ratio in mixed layer has shown reasonable association with the lightning occurrence over all lightning hot spot regions which are implemented in the IMD GFS and IMD WRF models. [ABSTRACT FROM AUTHOR]

Published
2024
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46. A new paradigm for short-range forecasting of severe weather over the Indian region

Author

Sen Roy, Soma, Sharma, Pradeep, Sen, Bikram, Sathi Devi, K., Sunitha Devi, S., Gopal, Neetha K., Kumar, Naresh, Mishra, Krishna, Katyar, Shobhit, Singh, Surendra Pratap, Balakrishnan, Shibin, Singh, Charan, Srivastava, Kuldeep, Lotus, Sonam, Paul, Surendra, Singh, Bikram, Gupta, J. P., Bandopadhyay, S., Das, Ganesh, Shankar, Anand, Kotal, S. D., Biswas, H. R., Shaw, S. O’Neil, Das, Sunit, Phukan, Ranjan, Nagarathna, K., Balachandran, S., Puviarasan, N., Stella, S., Bibraj, R., Mini, V. K., Rahul, M., Agnihotri, G., Sarkar, J., Mohanty, M., Singh, Ved Prakash, Hosalikar, K., Nitha, T. S., Sahu, M. L., Kumari, Bhawna, Kashyapi, Anupam, Singh, Manmohan, Singh, H. A. K., Sharma, Radhey Shyam, Raha, G. N., Reddy, Y. K., Ramesh, K. J., and Mohapatra, M.

Published
2021
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49. Development of India’s first integrated expert urban flood forecasting system for Chennai

Author

Ghosh, Subimal, Karmakar, Subhankar, Saha, Anamitra, Mohanty, Mohit Prakash, Ali, Shees, Raju, Satya Kiran, Krishnakumar, Vrinda, Sebastian, Maneesha, Behera, Manasa Ranjan, Ashrit, R., Murty, P. L. N., Srinivas, K., Narasimhan, B., Usha, Tune, Murthy, M. V. Ramana, Thiruvengadam, P., Indu, J., Thirumalaivasan, D., George, John P., Gedam, S., Inamdar, A. B., Murty, B. S., Mujumdar, P. P., Mohapatra, M., Bhardwaj, Arun, Basu, Swati, and Nayak, Shailesh

Published
2019

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