Satellite- and ground-based measurements of CO2 over the Indian region: its seasonal dependencies, spatial variability, and model estimates. Issue 22 (17th November 2018)

• Record Type: Journal Article
• Authors: Nalini, K.; Uma, K. N.; Sijikumar, S.; Tiwari, Yogesh K.; Ramachandran, Radhika
• Is Part Of: International journal of remote sensing. Volume 39:Issue 22(2018)
• Page Start: 7881
• Page End: 7900
• Publication Date: 2018-11-17
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2018.1479787
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: The present study demonstrates the distribution of carbon dioxide (CO2 ) concentration over the Indian region and the surrounding oceanic regions during 2009–2012, using measurements from satellites viz., Greenhouse Gases Observing Satellite (GOSAT) and Atmospheric Infrared Sounder, Carbon Tracker (CT) model simulations and flask measurements from two Indian stations Sinhagad (SNG) (73°45′ E, 18°21′36″ N) and Cape Rama (CRI) (73°54′ E, 15°6′ N). The concentration of CO2 is observed to be maximum during pre-monsoon and shows a decreasing phase during the post-monsoon season. In a regional scale, it is found that Indo-Gangetic Plain and northern India have relatively higher concentrations compared to the other regions. The probability distribution of the concentration differences shows that for most of the time, the differences lie between ±3 ppmv between GOSAT and CT. The comparison between the CO2 flask measurements over SNG and CRI with respect to that of GOSAT and CT clearly reveals that the differences in CO2 are as high as 10 ppmv between the ground- and satellite-based measurements. Further, we utilized the Lagrangian model FLEXible PARTicle (FLEXPART) to understand the source‒receptor relationship over CRI, SNG, and over the equatorial Indian Ocean (IO). The source contributions from the northern and eastern continental regions of the Indian region are found to be more influential over SNG compared to CRI. It is also found from simulations that the equatorial IO has less influence from the continental source and therefore has a reduced seasonal variability compared to the other regions considered in the present study.