Browsing by Author "Bhatla, Rajeev"

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    Evidence of asymmetric change in diurnal temperature range in recent decades over different agro-climatic zones of India
    (John Wiley and Sons Ltd, 2021) Mall, Rajesh Kumar; Chaturvedi, Manisha; Singh, Nidhi; Bhatla, Rajeev; Singh, Ravi Shankar; Gupta, Akhilesh; Niyogi, Dev
    Diurnal temperature range (DTR) is an important indicator of climatic change and a critical thermal metric to assess the impact on agriculture and human health. This study investigates the seasonal, annual and decadal changes in the spatio-temporal trend in DTR and air temperatures (maximum: Tmax and minimum: Tmin) during 1951�2016 and solar radiation (Srad) during 1984�2016 over 14 different agro-climatic zones (ACZs) in India. The changes in the DTR trend between two time periods:1951�2016 and 1991�2016 (recent period) are also assessed. The results indicate an overall increasing trend in DTR (0.038�C/decade), Tmax (0.078�C/decade, significant), Tmin (0.049�C/decade) during 1951�2016 and Srad (0.10 MJ/m2/day/decade) during 1984�2016. However, a decreasing trend in DTR (?0.02�C/decade) and a significant increasing trend in Tmin (0.210�C/decade) was noted during 1991�2016. The decadal changes showed an evident decline in DTR during the recent period since 1991. The relative increase in Tmin (0.21�C/decade, significant) compared to Tmax (0.18�C/decade) resulted in a decreasing DTR trend. This was evident across the 5 out of the 14 agro-climatic zones for the 1991�2016 period. The seasonal analysis showed a significant (95%) increasing trend in DTR during pre-monsoon and monsoon (1951�2016), and a negative trend for the post-monsoon and monsoon since 1991. There were also interesting spatial differences found with the ACZs in the north-west, parts of Gangetic plain, north-east, and central India exhibiting negative DTR trends. The effect of Srad is larger on Tmax than Tmin; therefore, the decrease in Srad in parts of Gangetic plain likely contributed to a smaller increase in Tmax relative to Tmin and led to a decreasing trend in DTR. At the same time, the west coast, east coast, and southern region show positive trends. The observational analysis finds a distinct increase in the Tmin and also highlights the need for future assessments to continue investigate the causes of these spatio-temporal changes found in this study. � 2020 Royal Meteorological Society
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    Impact of climate change and water quality degradation on food security and agriculture
    (Elsevier, 2021) Gupta, Priyanshu; Singh, Janhavi; Verma, Sunita; Chandel, Amit Singh; Bhatla, Rajeev
    The gradual increase in climate change leads to a serious concern toward food security and agriculture production. Despite considerable progress, around 800 million people are malnourished, 161 million under age of five are considered obese and 2 billion do not receive the essential micronutrients in their healthy life. � 2021 Elsevier Inc. All rights reserved.
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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
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    Studying the evolution of Uttarkashi cloudburst event from reanalysis datasets�A case study
    (Elsevier Ltd, 2023) Patel, Shivaji Singh; Routray, A.; Dutta, Devajyoti; Bhatla, Rajeev; Singh, Vivek; George, John P.
    In recent years, the frequency and severity of cloudburst considerably increased over southern rim of Himalayas due to hot climate that leads to loss of human lives and damage properties. The observed rainfall data shows that cloudburst events with heavy rainfall ? 100�200 mm/day are common over the Himalayan region during the summer monsoon period. It is very necessary to understand the mechanisms associated with such type of short span of high impact localised weather events over the regions where observations are limited. Therefore, one of best way to study the mechanism associated with the formation and development of cloudburst is using the available high resolution reanalysis datasets. An effort is made to understand the role of atmospheric conditions that control the evolution of cloudburst event by considering two reanalyses datasets such as high resolution IMDAA and ERA5 reanalyses. The present study analysed a cloudburst case that occurred on 3rd August 2012 at 10 pm with heavy rainfall of ? 100 mm in a very short span of time over the Uttarkashi district. Various dynamic and thermodynamic parameters are calculated from the two datasets with an aim of determining the best representation of severity of the cloudburst event. It is noticed that the evolution of dynamic and thermodynamic variables is well represented in the high resolution IMDAA dataset as compared to the ERA5 dataset. The amount and spatial distribution of rainfall from IMDAA reanalyses are well comparable with satellite estimated rainfall (GPM), having better correlation (0.60) with the observed rainfall as compared to the ERA5 (0.28). The rainfall time bias over the Uttarkashi district is larger in ERA5 reanalyses (? 5 h) than in the IMDAA (? 3 h). The ERA5 is not able to capture such type of localise high rainfall event due to its low resolution, compared to high resolution reanalyses (12 km) of IMDAA. The observations also indicate that the moisture flux from the Bay of Bengal (BoB) and Arabian Sea interacted with northwesterly dry air over Uttarkashi and the orographic uplifting resulted the cloudburst. Overall, results show that the eveolution and mechanism associated with the cloudburst is better represented in IMDAA than the ERA5. More cases are required to be studied to further support the findings of this study. � 2023 Elsevier B.V.
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    Temporal and spatial variability in aerosol optical depth (550 nm) over four major cities of India using data from MODIS onboard the Terra and Aqua satellites
    (Springer Science and Business Media Deutschland GmbH, 2021) Payra, Swagata; Gupta, Priyanshu; Bhatla, Rajeev; El Amraoui, Laaziz; Verma, Sunita
    The paper evaluates long-term (2007�2018) temporal and spatial variations in aerosol optical depth (AOD) over four major cities of India, i.e., Delhi, Kolkata, Chennai, and Jaipur, by using Collection 6, Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua Level-3, 1��1� gridded dataset. Annual analysis reveals a significant increasing trend from 2007 to 2018 and aerosol loading in the Indo-Gangetic Plain (IGP). Interestingly, in Northern India, i.e., Delhi, AOD values peaked during monsoon season (0.95�1.05), whereas over Kolkata, Eastern India, higher AOD is observed in winter season (0.95�1.05). Chennai, Southern India, reflects low to moderate mean AOD during all the seasons. A prominent increase in AOD percentage from 2007 to 2018 is observed over Kolkata (39%), followed by Delhi (27.34%), Chennai (26.30%), and Jaipur (16.53%). Further, cumulative effects of different meteorological parameters along with 12-year mean AOD reflected a peak in aerosol concentration (0.82 � 0.06) over Delhi, closely followed by Kolkata (0.81 � 0.08) and then Chennai (0.43 � 0.03) and Jaipur (0.43 � 0.03). Results depict a significant increase in AOD due to a wide range of anthropogenic events and call for improved policy programs to tackle the increasing AOD emissions over these megacities in India. � 2021, Saudi Society for Geosciences.
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    Use and Impact of Satellite-Derived SST Data in a Global Ocean Assimilation System Over the Tropical Indian Ocean
    (Springer, 2023) Momin, Imranali M.; Mitra, Ashis K.; Waters, Jennifer; Lea, Daniel; Martin, Matthew James; Bhatla, Rajeev
    The ocean analysis is crucial for monitoring and predicting�the ocean and also provides an initial condition to coupled atmosphere�ocean model. Due to the lack of in-situ observations, the satellite with high spatial and temporal coverage plays a vital role in improving�the data coverage as well as improving global ocean analysis. In this study, the global Nucleus European Modelling of the Ocean (NEMO)-based three-dimensional variational assimilation system called NEMOVAR is used to understand the impact of satellite-derived sea surface temperature (SST) data assimilation in the Tropical Indian Ocean (TIO). Two different experiments, such as no assimilation of satellite-derived SST called CNTR and assimilation of satellite-derived SST called EXPSST, were carried out during the winter and summer monsoon. The SST increment is much smooth for the�CNTR experiment as compared to the EXPSST experiment. The comparison of daily SST from both experiments with the Research Moored Array for African�Asian�Australian Monsoon Analysis and Prediction (RAMA) buoy observations clearly showed less RMSE and high correlation in the EXPSST experiment in the western part of the southern Indian Ocean and Arabian Sea (AS) regions during the winter monsoon. Further, the EXPSST experiment is cooler than the CNTR experiment in the Bay of Bengal (BoB) and southern Indian Ocean (10��20� S) regions for winter monsoon and AS, BoB and Equatorial Indian Ocean (EIO) regions for summer monsoon. Due to this, the EXPSST experiment lost the net heat flux (NHF) much less than the CNTR experiment. The impact of satellite-derived SST observations on the variational assimilation system through the air�sea interaction is relatively larger during summer monsoon as compared to winter monsoon. Further, it is also suggested that the impact is relatively higher in the BoB region compared to the northern AS and EIO regions extending up to 40�60�m depth during both monsoon seasons. � 2022, Indian Society of Remote Sensing.