Related papers: A Stochastic Conceptual Model for the Coupled ENSO…
We suggest a way of rationalizing an intra-seasonal oscillations (IOs) of the Earth atmospheric flow as four meteorological relevant triads of interacting planetary waves, isolated from the system of all the rest planetary waves. Our model…
We show that the monthly recorded history (1878-2013) of the Southern Oscillation Index (SOI), a descriptor of the El Ni\~no Southern Oscillation (ENSO) phenomenon, can be well described as a dynamic system that supports an average…
Faithful uncertainty quantification (UQ) is paramount in high stakes climate prediction. Deep ensembles, or ensembles of probabilistic neural networks, are state of the art for UQ in machine learning (ML) and are growing increasingly…
We investigate a low-dimensional slow-fast model to understand the dynamical origin of El Ni\~no-Southern Oscillation. A close inspection of the system dynamics using several bifurcation plots reveals that a sudden large expansion of the…
Many phenomena in the climate system lie in the gray zone between weather and climate: they are not amenable to deterministic forecast, but they still depend on the initial condition. A natural example is medium-range forecasting, which is…
El Ni\~no-Southern Oscillation global (ENSO) imprint on sea surface temperature comes in many guises. To identify its tropical fingerprints and impacts on the rest of the climate system, we propose a global approach based on archetypal…
In this study we used the sea surface temperature (SST), El-Nino southern oscillation (ENSO) and Pacific decadal oscillation (PDO) time-series for the time period 1900-2012 in order to investigate plausible manifestation of sharp increases…
Many record-breaking climate extremes arise from both greenhouse gas-induced warming and natural climate variability. Marine cloud brightening, a solar geoengineering strategy originally proposed to reduce long-term warming, could…
A flexible spatio-temporal model is implemented to analyse extreme extra-tropical cyclones objectively identified over the Atlantic and Europe in 6-hourly re-analyses from 1979-2009. Spatial variation in the extremal properties of the…
While most spatial data can be modeled with the assumption that distant points are uncorrelated, some problems require dependence at both far and short distances. We introduce a model to directly incorporate dependence in phenomena that…
A method is provided for designing and training noise-driven recurrent neural networks as models of stochastic processes. The method unifies and generalizes two known separate modeling approaches, Echo State Networks (ESN) and Linear…
The seamless forecast approach of subseasonal to seasonal scale variability has been succeeding in the forecast of multiple meteorological scales in a uniform framework. In this paradigm, it is hypothesized that reduction in initial error…
Much work has been done on relaxation oscillations and other simple oscillators in conceptual climate models. However, the oscillatory patterns in climate data are often more complicated than what can be described by such mechanisms. This…
Severe thunderstorms cause substantial economic and human losses in the United States. Simultaneous high values of convective available potential energy (CAPE) and storm relative helicity (SRH) are favorable to severe weather, and both they…
El Nino is probably the most influential climate phenomenon on interannual time scales. It affects the global climate system and is associated with natural disasters and serious consequences in many aspects of human life. However, the…
Spatiotemporal variations in thunderstorm occurrence frequency are considered here using an environmental dataset derived from ERA5 reanalysis data. Interannual variability in the thunderstorm environments is examined for the period…
On average once every four years, the Tropical Pacific warms considerably during events called El Ni\~no, leading to weather disruptions over many regions on Earth. Recent machine-learning approaches to El Ni\~no prediction, in particular…
Accurate representation of atmosphere-ocean boundary layers, including the interplay of turbulence, surface waves, and air-sea fluxes, remains a challenge in geophysical fluid dynamics, particularly for climate simulations. This study…
El Ni\~no-Southern Oscillation (ENSO) exerts global climate and societal impacts, but real-time prediction with lead times beyond one year remains challenging. Dynamical models suffer from large biases and uncertainties, while deep learning…
In a statistical analysis of more than a century of data we find a strong connection between strong warm El Nino winter events and high spring precipitation in a band from Southern England eastwards into Asia. This relationship is an…