Venugopal Thallam

Venugopal Reddy Thallam (he/him)

Forskare/Researcher

Air, Water and Landscape Science (LUVAL)

Department of Earth Science

Uppsala University, Sweden-75236.

About Me

My research centres on Earth and planetary system science, bridging the gap between physical laws and their socioeconomic impacts. I specialise in analysing the drivers and predictability of climate, ocean, and atmospheric dynamics, with a specific focus on extreme events and their impacts. By integrating machine learning techniques with advanced statistical, dynamical and numerical models, I work to decode complex interactions across varying scales, dimentions and sectors.

My primary objective is to advance weather and climate forecasting. I achieve this by optimising algorithms and parameterisations, deploying novel modelling techniques, and ensuring these advancements are supported by robust data management and high-performance computing.

Research Subjects

Earth and planetary sciences.

Greenhouse gases and climate feedback.

Atmospheric rivers, heat, momentum and moisture transports, and the global water cycle.

Drivers, predictability, and impacts of climate change and hydrometeorological extremes.

Upper ocean variability, cyclones, global monsoon system, and global radiation variability

Quantifying the human-driven climate change and natural variability

In-situ observations, GPSRO, remote sensing, reanalysis, hybrid, blended, and climate model datasets.

Climate, atmospheric, and ocean dynamics and thermodynamic processes.

Bayesian models, stochasticity, chaos, uncertainty, heuristics, and complexities.

Climate physics, Earth system modelling, and machine learning models.

Scientific programming, numerical modelling, statistical and dynamical models, ML and DL models.

Computational and applied physics.

Research Foci

Understanding carbon cycle dynamics and quantifying impacts on climate feedbacks using Earth system models.

Quantifying the importance of air-sea interaction on atmospheric rivers to better predict extreme events in coastal zones under the changing climate.

Studying the role of meridional heat, momentum and moisture transport on extreme hydro-meteorological and hydro-climate events.

Equilibrium climate sensitivity, planetary boundaries, tipping elements and triple planetary crisis in the Earth's climate system.

Understanding the role of ocean-atmospheric dynamics and thermodynamics on the concurrent and compound extremes

Role of upper-ocean variability and climate modes in monsoon dynamics and precipitation variability.

Quantifying uncertainties in data, heuristics, scaling, and impacts to better understand Earth's climate.

Evaluating the heuristics, uncertainties, and challenges in understanding the climate system's chaotic, complex, and stochastic physical phenomena.

Role of the variability of radiative heat fluxes on the global upper ocean and climate system.

Understanding the functioning of the atmosphere and its interactions with other components of the climate system.

Exploring various climate and weather extremes - from severe windstorms to urban pollution using different techniques, methods, models and tools.

Geoscientific model and software development for finding practical, applicable solutions for state estimation of complex dynamic systems.

NWP and climate modelling, statistical, dynamical and ML techniques for parameterising and forecasting weather and climate variables.

Climate model emulators, digital twins, coupling ESMs with AI, LAM, and AI for climate emulators (ACE).

Physics-informed climate indicators, XAI, surrogate modelling, Large ENSembles (LENS), Mega/Large networks, PINNs, PIML, ClimODE, and AI4ESP.

AI-ML tools, packages and libraries; NLP, Generative AI, Foundation models, Diffusion models, AI Agents and Agentic AI.