These past few years, the Earth appears to be defying climate model expectations. The question as to what drives the unusual nature of extreme events still baffles climate scientists. The key to answering some of these questions is to look at the actual observed data and understand what they can tell us about the spatial distribution, intensity, frequency, and duration of extreme events on a variety of scales. This would require new data analysis and new approaches that have yet to be developed. My research works to reduce uncertainty in climate modeling in the following ways:
- Model climate processes at a local scale. Climate models suffer from not being able to model small-scale features. This is because climate models typically represent the Earth as a mesh with cell size of 25 kilometers on a side. But much of what happens on the planet arises at scales smaller than those grids. Nowadays, newer models have finer grid sizes up to 10 kilometers. Accurate modelling of these small-scale features is of utmost important because an erroneous modelling of one climate variable will adversely affect the other climate variables. We will develop statistical models and inference methods for climate processes at a local scale. The models will enable us to understand how various atmospheric, land, ocean, biomass, and cryosphere components interact and to study more closely how different phenomena, such as precipitation, passage of weather fronts, hurricanes, cloud formation, and indirect solar effects, unveil under different kinds of topography, for example, mountain plateaus, low-land deserts, temperate coastal rainforests, farmlands, and wetlands. Modelling at a local scale is also most suitable for capturing microclimatic conditions that occur in very small regions which can significantly influence the global climate. Furthermore, we will be able to assess whether different instruments such as ground-based thermometers, weather balloons, and global satellite observations are positioned accordingly to capture data very well.
- Consolidate the models at the local scale to model global climate processes. Large scale climatic phenomena, such as, the monsoon systems, the tropical phenomena, the El Niño-Southern Oscillation (ENSO), the annular and dipolar modes, and the large-scale storm systems, are the results of the interplay of local climate processes. The climate models are still producing errors in simulating these global phenomena and predictions differ from one model to another since the models are highly sensitive to the initial conditions and parameter values. Models of climate processes at the local scale must hold the key to answering some of the open questions surrounding the formation of these global phenomena. For example, a localized ministorm (< 1km in diameter) can transition into a megastorm (200 km in diameter) and ENSO, the most prominent phenomenon in the Pacific Ocean, is a result of a complex interaction between local atmospheric and oceanic processes. After modelling the climate processes at a local scale, we will model how these localized events can coalesce and build up to mega scale phenomena.