Anjali Thomas

A seasoned Data Scientist, skilled in Python programming, excels in managing extensive datasets and visualizing data effectively. Proficient in employing advanced statistical and analytical techniques, particularly in the analysis of climate change and extreme weather events. Proficiency includes expertise in unsupervised machine learning, especially SOMs, and adept utilization of BI tools for comprehensive data interpretation. Recognized for delivering impactful insights by translating complex data into actionable solutions through strong problem-solving, communication, and quantitative analysis skills

• Anthropogenic influence on precipitation in Aotearoa New Zealand with differing circulation types, Thomas, A., McDonald, A., Renwick, J., Rosier, S, Tradowsky, J. S., and Bodeker, G. E., Weather and Climate Extremes, Under review, 2023, http://dx.doi.org/10.2139/ssrn.4599090
• Increasing temperature extremes in New Zealand and their connection to synoptic circulation features, Thomas, A., McDonald, A., Renwick, J., Tradowsky, J. S., Bodeker, G. E., and Rosier, S., International Journal of Climatology, 2022, https://doi.org/10.1007/s40808-018-0520-3
• A study on the capability of the NCEP-CFS model in simulating the frequency and intensity of high-intensity rainfall events over Indian region in the high and low resolutions, Chattopadhyay, R., Thomas, A., Phani, R. et al., Model. Earth Syst. Environ., 2018, https://doi.org/10.1007/s40808-018-0520-3

• Prof. Adrian McDonald, Professor, School of Physical and Chemical Sciences, University of Canterbury, adrian.mcdonald@canterbury.ac.nz
• Prof. James Renwick, Professor, School of Geography, Environment and Earth Sciences, Victoria University of Wellington, james.renwick@vuw.ac.nz