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Isha Savani

Isha Savani

Home Institution: Ruden AS, Oslo

Host Institution: Earth Science Department, University of Oxford

Duration of stay(days): 19

Objectives: The project will be a collaboration between myself from Ruden AS, Norway and Dr. Claudia Bertoni from Oxford, UK, and her colleagues at the Department of Geography and/or Department of Atmospheric, Oceanic and Planetary Physics. I am working on estimating groundwater recharge and modelling physical phenomena like the movement of fluids through tiny grains of a porous medium, to large scale reservoir simulations of water through the sub-surface. Claudia Bertoni is a marine geologist with expertise in characterizing off-shore and on-shore fresh ground water resources. In the proposed project, we will combine our geological and modelling expertise to perform statistical modelling of historic rainfall over arid regions of Spain and Italy.
Rainfall can be understood as a chaotic phenomenon which is both random and predictable. Depending on the region of Europe, rain arrives somewhat predictably, in spring and autumn for instance, however neither the quantity nor the timing is the same every year. This randomness inherent in rainfall, together with yearly trends impacted by climate change can be better understood by identifying statistical
distributions that best characterize rainfall over a large scale. In this project, the probability distribution best describing rainfall over arid regions of Europe will be identified.

Summary of the work: Several atmospheric processes contribute to the occurrence of rainfall- the temperature of the air, land, sea, the magnitude of soil moisture and large-scale currents driving wind and moisture around the globe to name a few. The spatial variation of rainfall is a tangible fingerprint that can say something about the atmospheric processes at play. During my Short-Term-Scientific-Mission at the Department of Earth Sciences at Oxford, I focused on the regime of extreme rainfall, since unexpected amounts of rain in a short period of time can have dire consequences. I analysed the distribution of intense rainfall (daily rainfall > 100 mm) over Spain by fitting the distribution to existing statistical probability distributions. It is not always the case that the data in question can be described by a known statistical distribution, but in the case of Spain, the daily rainfall data over the last 60 years could indeed be captured in known statistical distributions. Similar analysis of extreme rainfall over other regions of the world has shown that exponential type distributions, and the power-law distribution are ubiquitous. Interestingly, I found that there was not just one but three distributions that described the data to a sufficiently good degree- Power-law, Weibull, and the Gamma distributions. What could be the relationship between these distributions and how one can begin to identify the atmospheric cause of such a signature is the topic of future research.