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Your search keyword '"Nagamani, P. V."' showing total 106 results
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106 results on '"Nagamani, P. V."'

8. Improved estimation of global surface ocean total alkalinity fields using in-situ and satellite observations.

Author

Shaik, Ibrahim, Manmode, Yash, Vamsi Krishna, Kande, Yadav, Sandesh, M., Haritha, P., Mahesh, Krishna, Gowtham, Nagamani, P. V., Rao, G. Srinivasa, Begum, S. K., and Srinivasa Rao, M.

Subjects
STANDARD deviations, OCEAN temperature, OCEAN acidification, OCEAN dynamics, CLIMATE change
Abstract

Total Alkalinity (TA) is identified as one of the EssentialClimateVariable (ECV) by the GlobalClimateObservingSystem (GCOS) for climate change impact assessment studies. This also plays an important role in understanding the oceanic carbon cycle, and ocean acidification. The existing global algorithms are Sea Surface Salinity (SSS) based and inadequate for precise estimation of TA fields and their dynamics due to precluding physical and biological parameters such as Sea Surface Temperature (SST), Chlorophyll-a concentration (Chl-a) and its influencing parameters (nutrients). In the present study, a novel algorithm known as the ImprovedSingleLinearRegression (ISLR) was devised based on SSS and Nitrate (Ni) concentration. The ISLR was formulated using simultaneous in-situ measurements of SSS and Ni acquired across the global oceans. The primary objective was to mitigate uncertainties and generate consistent TA fields for the global surface ocean. ISLR performance was assessed with independent satellite and in-situ TA observations. The validation results demonstrate the ISLR approach superior performance, characterized by significant low errors (mean relative error (MRE) = 0.04 µmol kg−1; mean normalized bias (MNB) = -0.0003 µmol kg−1; and root mean square error (RMSE) = 10.08 µmol kg−1) with a high correlation coefficient (R2 = 0.96). The ISLR derived TA fields were used to study the spatiotemporal variability and seasonal dynamics of the global oceans. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Estimation of Spatiotemporal Variability of Global Surface Ocean DIC Fields Using Ocean Color Remote Sensing Data

Author

Shaik, Ibrahim, Krishna, Kande Vamsi, Nagamani, P. V., Begum, S. K., Shanmugam, Palanisamy, Mathew, Reema, Pathakoti, Mahesh, Bothale, Rajashree V., Chauhan, Prakash, and Osama, Mohammed

Abstract

The estimation of dissolved inorganic carbon (DIC) in global surface ocean waters is crucial for understanding air-sea carbon dioxide (CO2) flux rates, ocean acidification, and climate change. DIC magnitude and spatiotemporal variability are influenced by various physical and biogeochemical processes. Due to dynamic variations in ocean surface water, estimating DIC through in situ data alone is challenging. Ocean color remote sensing offers high spatial and temporal resolution data with extensive synoptic views. Over decades, multiple DIC approaches have emerged using in situ and satellite observations but are limited to specific regions due to improper model parameter selection and sparse in situ measurements. To address this, we propose a novel multiparametric regression (MPR) approach that relates DIC as a function of sea surface temperature (SST), sea surface salinity (SSS), and chlorophyll-a (Chla) concentration. Utilizing in situ data from the Global Ocean Data Analysis Project (GLODAP), the trends of DIC with SST, SSS, and Chla were analyzed to develop MPR regression equations. The validation results indicated that the proposed regression approach accurately estimates DIC in global surface ocean waters. This approach offers benefits, such as DIC estimates at any spatiotemporal resolutions, easy implementation, and cost-effective alternatives to in situ measurements. Additionally, seasonal and interannual variations of global DIC fields were demonstrated through satellite oceanographic data, enhancing monitoring of ocean acidification and climate change scenarios.

Published
2024
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37. Short-Term Variability of Physico-Chemical Properties and pCO2 fluxes off Dhamra estuary from north-eastern India.

Author

Pattanaik, Suchismita, Acharya, Debeedatta, Sahoo, Rajesh Kumar, Satapathy, Deepti Ranjan, Panda, Chitta Ranjan, Choudhury, Saroj Bandhu, Nagamani, P. V., and Roy, Rajdeep

Abstract

Short-term variability in physico-chemical properties of Dhamra estuarine system located in north-eastern India was investigated to understand the inter-seasonal variability. The oxygen data show 89–92% saturation in winter months compared to 60–70% during summer. Overall, the nitrate ranged between < 1.0 and 22.0 µmol l−1; however, phosphate concentrations never exceeded 1 µmol l−1 during the whole study period. In general, the lowest nutrient values were recorded during March and December irrespective of the year sampled. Pearson correlation matrix shows poor relationships between inorganic nitrate and phosphate suggesting decoupling in the Dhamra estuary. However, relationship between surface chlorophyll and nitrate was significant highlighting modest control on phytoplankton population. Interestingly, pCO2(air) exhibited considerable monthly variability during the sampling period, thereby accentuating the sea–air CO2 gradient. The pCO2(air) varied between 370 and 421 µatm, whereas pCO2(water) ranged between 146 and 751 µatm. The ΔpCO2 therefore showed monthly fluctuation and acted as a weak to moderate source to the immediate atmosphere. Our observation from Dhamra estuary suggests large inter-annual variability which therefore necessitates the need for near real-time measurements which is now a possibility with emerging coastal biogeochemical buoys. [ABSTRACT FROM AUTHOR]

Published
2019
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38. Heat content of the Arabian Sea Mini Warm Pool is increasing

Author

Nagamani, P. V., Ali, M. M., Goni, Gustavo J., Udaya Bhaskar, T. V. S., McCreary, Julian P., Weller, Robert A., Rajeevan, Madhavan Nair, Gopalakrishna, V. V., Pezzullo, John C., Nagamani, P. V., Ali, M. M., Goni, Gustavo J., Udaya Bhaskar, T. V. S., McCreary, Julian P., Weller, Robert A., Rajeevan, Madhavan Nair, Gopalakrishna, V. V., and Pezzullo, John C.

Abstract

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Atmospheric Science Letters 17 (2016): 39-42, doi:10.1002/asl.596., Sea surface temperature in the Arabian Sea Mini Warm Pool has been suggested to be one of the factors that affects the Indian summer monsoon. In this paper, we analyze the annual ocean heat content (OHC) of this region during 1993–2010, using in situ data, satellite observations, and a model simulation. We find that OHC increases significantly in the region during this period relative to the north Indian Ocean, and propose that this increase could have caused the decrease in Indian Summer Monsoon Rainfall that occurred at the same time.

Published
2016

42. High-resolution shipboard measurements of phytoplankton: a way forward for enhancing the utility of satellite SST and chlorophyll for mapping microscale features and frontal zones in coastal waters

Author

Jenkins, Christy A., additional, Goes, Joaquim I., additional, McKee, Kali, additional, Gomes, Helga do R., additional, Arnone, Robert, additional, Wang, Menghua, additional, Ondrusek, Michael, additional, Nagamani, P. V., additional, Preethi Latha, T., additional, Rao, K. H., additional, and Dadhwal, V. K., additional

Published
2016
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44. Relationship between ocean mean temperatures and Indian summer monsoon rainfall

Author

Ali, M. M., Nagamani, P. V., Sharma, N., Thandlam, Venugopal, Rajeevan, M., Goni, G. J., Bourassa, Mark A., Ali, M. M., Nagamani, P. V., Sharma, N., Thandlam, Venugopal, Rajeevan, M., Goni, G. J., and Bourassa, Mark A.

Abstract

Besides improving the understanding of the physics of the challenging problem of monsoon prediction, it is necessary to evaluate the efficiency of the input parameters used in models.Sea-surface temperature (SST) is the only oceanographic parameter applied in most of the monsoon forecasting models, which many times do not represent the heat energy available to the atmosphere. We studied the impacts of ocean mean temperature (OMT), representing the heat energy of the upper ocean, and SST on the all India summer monsoon rainfall through statistical relation during 1993–2013 and found that OMT has a better link than SST

Published
2015
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