Data Products

Data Products from the Climate Research Lab

Chlorophyll Data for the tropical Indian Ocean
The study titled “Gap-filling of ocean color over the tropical Indian Ocean using Monte-Carlo method” by Modi et al. (2022) proposes a novel technique for addressing the problem of missing data in remote-sensed ocean color measurements in the tropical Indian Ocean. The method utilizes a Monte Carlo approach, which involves generating multiple possible values for the missing data based on the probability distribution of the available data. The key contribution of this research is the estimation of uncertainty in the parameters derived from these gap-filled datasets, a unique feature not present in conventional gap-filling methods. This study is an important step in advancing our understanding of ocean ecosystem processes using ocean color data in the tropical Indian Ocean. Data: Gap-filled ocean surface chlorophyll data for the tropical Indian Ocean for 1998–2019 is available from our lab. The climatological data is available for direct download from Aditi’s GitHub. The gap-filled data for the entire period is available on request. Reference: Modi A., Roxy M. K., Ghosh S., 2022, Gap-Filling of Ocean Color Over the Tropical Indian Ocean Using Monte-Carlo Method, Scientific Reports, 12, 18395 [link].
Reconstructed MJO historical indices for the 20^th Century
Reconstructed MJO historical (1905-2015) indices. Data: GitHub Reference: Dasgupta, P., Metya, A., Naidu, C. V., Singh, M., and Roxy, M. K. (2020). Exploring the long-term changes in the Madden Julian Oscillation using machine learning. Scientific Reports, 10(1), 18567 [link].
Monsoon Interannual Timeseries
Data for the Monsoon Interannual Timeseries: iitm_aismr.txt Roxy M. K. and S. T. Chaithra, 2018: Impacts of Climate Change on the Indian Summer Monsoon. Climate Change and Water Resources in India, Vimal Mishra, and J. R. Bhatt, Eds., Ministry of Environment Forest and Climate Change, 21-37, ISBN: 978-81-933131-6-9 [pdf].