Variability of Monsoon Over Homogeneous Regions of India Using Regional Climate Model and Impact on Crop Production

Bhatla, R.; Ghosh, Soumik; Verma, Shruti; Mall, R. K.; Gharde, Gaurav R.

doi:10.1007/s40003-018-0368-9

Cited by 20 publications

(12 citation statements)

References 39 publications

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“…The simulation of ENSO events using six convection schemes of RegCM4.3 has been done during the period of 1986–2010. The interannual variability of rainfall associated with El Nino and La Nina is studied by comparing observed gridded rainfall data set of IMD over India and its subregions as Northwest India (R1) , Northcentral India (R2) , Western peninsular India (R3) , Eastern peninsular India (R4) , and Southern peninsular India (R5) (Figure 1) (Bhatla et al., 2019). The selection of best fit model CPS has been done Skill Score (Zou et al., 2014).…”

Section: Data Description and Methodologymentioning

confidence: 99%

Performance of RegCM4 for Dynamically Downscaling of El Nino/La Nina Events During Southwest Monsoon Over India and Its Regions

Verma

Bhatla

2021

Earth and Space Science

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The southwest monsoon (SWM) is the world's most important monsoon system that affects nearly one third of the world population. The SWM maintains a periodicity annually in which more than 80% of the annual precipitation occurs during June-September and represents significant spatial and temporal variation which is dependent upon climatic and topographical features of the Indian subcontinent. The spatial and temporal interannual variability of Indian summer monsoon rainfall (ISMR) leads to large-scale drought and flood, resulting in a major effect on agriculture and the economy of the country (Guhathakurta & Rajeevan, 2006; Naidu et al., 2015; Parthasarathy et al., 1994; Turner & Annamalai, 2012). The strong influence of the Tropical Ocean on the variability of ISMR has been studied and epitomized by the El Nino Southern Oscillation (ENSO) phenomena (Shukla, 1987; Sikka, 1980; Webster & Yang, 1992). ENSO is a phenomenon of coupled ocean-atmosphere used to explain unusual climatic and weather patterns and also disrupt the ecosystem, agriculture, tropical cyclone, drought and flood, and other extreme weather events across the globe. The large-scale ocean-atmosphere climate interaction is linked to the periodic warming in the sea surface temperature (SST) across central and east equatorial Pacific Ocean termed as El Nino. On the other hand, La Nina (a cold event) represents

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Section: Data Description and Methodologymentioning

confidence: 99%

Performance of RegCM4 for Dynamically Downscaling of El Nino/La Nina Events During Southwest Monsoon Over India and Its Regions

Verma

Bhatla

2021

Earth and Space Science

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“…We perform spatial analysis for five homogeneous zones of India. Different zones consider for spatial analysis are North-West India (NWI), North-Central India (NCI), West Peninsular India (WPI), Eastern Peninsular India (EPI), and Southern Peninsular India (SPI) (Figure S1) (Bhatla et al, 2019(Bhatla et al, , 2020 shown in Figure 6. We observe that the average zonal mean RL 100 estimated from all realizations for WPI is comparable for MICE and MME.…”

Section: Zonal Analysis For 100 Years Rlmentioning

confidence: 99%

Depth‐Duration‐Frequency of Extreme Precipitation Events Under Internal Climate Variability: Indian Summer Monsoon

2021

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“…Due to the complex interaction between the yield of crop and climate change, it is the challenging assignment to tackle climate change and its impact on agricultural productivity. Many previous studies have done by using various climate models over the Indian region to examine the impact of increasing temperature and changing rainfall patterns during the twenty-first century (Bhatla et al, 2019). However, this study's main objectives are to explore whether the dynamic relationship is symmetrical and asymmetrical between rice productivity and climate change in India over the period 1990 to 2017 by using both ARDL and NARDL approaches.…”

Section: Introductionmentioning

confidence: 99%

Does Climate Change Asymmetrically Affect Rice Productivity In India? New Insight From NARDL Cointegration Approach

Baig

Chandio

Salam

2021

Preprint

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This article attempt to answer the question "whether the dynamic relationship between climate change and rice productivity is symmetrical or asymmetrical" using data from 1990-2017 in India. First, we test the symmetrical and long-run dynamic relationship using the Autoregressive Distributed Lags (ARDL) model and test the asymmetrical and cointegration relationship based on Nonlinear Auto-Regressive Distributed Lag (NARDL) technique. The results of the ARDL model indicates that no symmetrical relationship between the variables in long-run. Whereas outcomes of the NARDL bound test reveal that there is long-run asymmetrical impact of climate change on rice productivity. The positive and negative shock of climate change has affected the rice productivity by different magnitude in India. The Wald statistics confirm asymmetric relationship between rice productivity and climate change in the long-run while only short-run asymmetrical relationships exist between rainfall and rice productivity in India.Furthermore, dynamic multipliers indicate that negative component of rainfall and temperature has a dominant effect over the positive component on rice productivity. To the best of the author's knowledge, no studies have been done to assess both symmetrical and asymmetrical dynamic relationships between climate change and rice productivity using ARDL and NARDL cointegration approaches in India's context. This study will help frame the environmental policies and strategy to cope with climate change in India's agriculture productivity.

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Variability of Monsoon Over Homogeneous Regions of India Using Regional Climate Model and Impact on Crop Production

Cited by 20 publications

References 39 publications

Performance of RegCM4 for Dynamically Downscaling of El Nino/La Nina Events During Southwest Monsoon Over India and Its Regions

Performance of RegCM4 for Dynamically Downscaling of El Nino/La Nina Events During Southwest Monsoon Over India and Its Regions

Depth‐Duration‐Frequency of Extreme Precipitation Events Under Internal Climate Variability: Indian Summer Monsoon

Does Climate Change Asymmetrically Affect Rice Productivity In India? New Insight From NARDL Cointegration Approach

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