01-05 December 2025
INCOIS, Hyderabad, India.
| Abstract Submission No. | ABS-04-0179 |
| Title of Abstract | Climate-driven seasonal surface pCO2 amplification in the Indian Ocean: Insights from a machine learning⿿based improved data product |
| Authors | Apurva Padamnabh Joshi*, Prasanna Kanti Ghoshal, Kunal Chakraborty |
| Organisation | Indian National Center for Ocean Information Services, INCOIS |
| Address | Indian National Centre for Ocean Information Services Ocean Valley Paragathi Nagar(BO) Nizampet(SO) Hyderabad, Telangana, India Pincode: 500090 E-mail: ap.joshi-p@incois.gov.in |
| Country | India |
| Presentation | Oral |
| Abstract | The increase in atmospheric CO2 impacts the seasonal variability of the inorganic carbon in the global oceans. However, in the Indian Ocean (IO), the quantification of seasonal amplification of surface pCO2 and its drivers has not yet been explored. In this study, we use a machine learning (ML) approach to correct the biases in high-resolution (1/12°) surface pCO2 simulations from the INCOIS-BIO-ROMS model (pCO2model) over the period 1980-2019. We train the ML model using the differences between observed surface pCO2 (pCO2obs) from SOCAT and the Indian Scientific Expeditions and modeled pCO2 to generate the spatio-temporal pCO2 deviants (pCO2obs ⿿ pCO2model). The climatology of these deviations is then added back to the original model output, which results in an improved pCO2 data product. To study the strengthening of pCO2 seasonality using this improved pCO2 product, we first create a climatology of the first (1980-89) and fourth (2010-2019) decades. We find seasonal amplification of pCO2 between the first and fourth decades in each of the sub-regions (Arabian Sea (AS), Bay of Bengal (BoB), Equatorial Indian Ocean (EIO), and Southern tropical Indian Ocean (SIO)) of the IO. The maximum seasonal amplification is found in the SIO (5.20±0.15 µatm), while the minimum amplification is found in the AS (2.56±0.43 µatm). The amplification of the thermal component (driven by temperature) of the pCO2 seasonality primarily drives the seasonal amplification. The amplitude of the bio-physical (driven by biological and physical ocean characteristics except temperature) component also contributes to the seasonal amplification of pCO2 in all sub-regions except AS. Although AS shows minimum pCO2 amplification, the amplification of the thermal component is maximum in AS (8.3±0.30 µatm), and is opposed by the attenuation of the bio-physical component (-3.86±0.35 µatm). This attenuation of the bio-physical component could be attributed to enhanced stratification due to the increased ocean warming. |
| Are you part of IIOE-2 endorsed project | no |
| Keywords | Machine Learning, Climate Change, pCO2, seasonal amplification |
| For Awards | yes |
| Date Of Birth | 16-12-1989 |
| ECSN Registration Number | IIOE2-ECSN-0134 |