I am interested in non-linear dynamics of complex chaotic turbulent flows and systems. My education and research have cemented this interest into a passion. I greatly enjoy carrying out fundamental theoretical research with potential practical applications. I am keen on furthering my research while improving my understanding of chaotic complex systems, their predictability limits, the theoretical frameworks of scale invariance, fractals, and multifractals, as well as their application in the areas of turbulence, weather, climate and hydrology.

Current Project:

Hydrology is not an outlier from generalized scale invariance and multifractal cascade dynamics. Scaling laws are ubiquitous in nature and especially in geophysical fields such as rainfall. The objective of the current project is to develop a zero-discharge green roof solution over the study area in collaboration with our industrial partner SOPREMA. Since multifractal based methods are preferred for simulating rain fields, my background, research experience and interest will be useful here. Moreover the scaling laws within hydrology too aren’t that different in their general form compared to those of atmospheric fields (a property we can thankfully attribute to the universality of scaling laws in nature). By figuring out the exact scaling laws in play here (both in the meteorological module and hydrological module) multifractal FIF (fractionally integrated fluxes) based simulations can be performed for various rainfall scenarios (intensity, duration and frequency by varying suitable parameters or variables in the simulations) and different green roof parameters (thickness, composition of substrate, plant cover etc.). Proceeding this way a zero-discharge solution or a solution close to zero-discharge can be obtained for the study area. A marketable prototype of this green roof can then be developed and the proper functioning of this commercial solution can finally be monitored, and any changes necessary can be implemented.


M.Tech-Ph.D. dual degree (Silver Medal) in Earth System science and Technology from the Indian Institute of Technology Kharagpur. My Ph.D. research focussed on storm-scale or mesoscale atmospheric predictability using simplified theoretical spatially anisotropic universal multifractal cascade models, and the multiscaling behaviour of Generalized Scale-Invariant continuous-in-scale universal multifractal simulations of atmospheric fields.

Past Research:

My Ph.D. work involved

  • Mathematically deriving a correlation-spectra based analytical expression for the theoretical predictability limits of spatially anisotropic multifractal fields to investigate the effect of spatial anisotropy of atmospheric fields on their intrinsic predictability limits.
  • Generalizing this spectra-based analytical expression for predictability limits to higher-orders using a polyspectral approach.
  • Empirically determining (using satellite radar reflectivity data) the yearly spheroscale values over northeast India for five different years and using these estimates in the analytical expression for theoretical predictability limits to obtain a semi-empirical estimate of the storm-scale atmospheric predictability limits over this region.
  • Using finite-size correction methods and nesting techniques that were initially proposed and tested on isotropic cases, for anisotropic cases and statistically analysing these anisotropic multifractal cascade simulations.

I also gained some experience in numerical weather prediction during my M.Tech project, in which I simulated downbursts associated with thunderstorms using a customized setup of the WRF (Weather Research and Forecasting) model.

Journal Articles:

Ramanathan, A., Versini, P., Schertzer, D., Perrin, R., Sindt, L., & Tchiguirinskaia, I. (2023). A universal multifractal-based method to model pore size distribution, water retention and hydraulic conductivity of granular green roof substrates. Geoderma, 438, 116640.

Ramanathan, A., Satyanarayana, A.N.V. (2021). Satellite-based estimate of intrinsic predictability limits at convective scales over northeast India. Earth and Space Science, 8, e2019EA000797. Doi:10.1029/2019EA000797

Ramanathan, A., Satyanarayana, A.N.V. (2019). Higher-order statistics based multifractal predictability measures for anisotropic turbulence and the theoretical limits of aviation weather forecasting. Scientific Reports, Nature, 9(1): 19829. Doi:10.1038/s41598-019-56304-2

Ramanathan, A., Satyanarayana, A.N.V., Mandal, M. (2019). Theoretical Predictability Limits of Spatially Anisotropic Multifractal Processes: Implications for Weather Prediction. Earth and Space Science, 6(7): 1067-1080. Doi:10.1029/2018EA000528

Ramanathan, A., Satyanarayana, A.N.V., Mandal, M. (2018). Anisotropic Continuous-in-Scale Universal Multifractal Cascades – Simulation, Analysis and Correction Methods. Mathematical Geosciences, 50(7): 827-859. Doi:10.1007/s11004-018-9746-x

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