Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 287-290, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
28 Nov 2014
Evaluation of NOAA Carbon Tracker Global Carbon Dioxide Products
R. K. Nayak1, E. N. Deepthi2, V. K. Dadhwal1, K. H. Rao1, and C. B. S. Dutt1 1National Remote Sensing Center (NRSC), ISRO, Balanagar, Hyderabad, 500625, India
2Centre for Atmosphere and Ocean Sciences, Kochin University of Science and Technology, India
Keywords: Carbon dioxide, greenhouse gas, global warming, AIRS, GOSAT, NOAA Carbon Tracker Abstract. Inter-comparison between National Oceanic and Atmospheric Administration Carbon Tracker (NOAACT) CO2 with satellite observations were carried out in this study. The satellite observations used here are mid troposphere CO2 based on Atmosphere Infrared Sounder (AIRS) on board NASA’s Aqua and lower troposphere CO2 based on Greenhouse-gas Observing Satellite (GOSAT) of Japanese Aerospace Exploration Agency (JAXA). There exists good agreement between the seasonal cycles as estimated by NOAACT and Satellite observations. The mid troposphere CO2 exhibits distinct annual cycle in the northern hemisphere with positive detrended value during January–June and negative values during July–December. In the southern hemisphere, the annual cycle is less prominent and opposite phase with respect to the northern hemisphere. The lower tropospheric CO2 in both the hemispheres exhibits mixed signature of annual and semi-annual cycle. The amplitudes of the variability are significantly larger in the northern hemisphere than the southern hemisphere. The inter-annual variability of annual growth rates from the NOAACT is comparable with satellite observations however NOAACT could not resolved the spatial patterns of long-term growth rate as observed in the satellite observations.
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Citation: Nayak, R. K., Deepthi, E. N., Dadhwal, V. K., Rao, K. H., and Dutt, C. B. S.: Evaluation of NOAA Carbon Tracker Global Carbon Dioxide Products, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-8, 287-290,, 2014.

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