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This popular article provides a short summary of the progress and prospects in Weather and Climate Modelling for the benefit of high school and undergraduate college students and early career researchers. Although this is not a comprehensive scientific article, the basic information provided here is intended to introduce students and researchers to the topic of Weather and Climate Modelling - which comes under the broad discipline of Atmospheric / Oceanic / Climate / Earth Sciences. This article briefly summarizes the historical developments, progress, scientific challenges in weather and climate modelling and career opportunities.
We apply an empirical, data-driven approach for describing crop yield as a function of monthly temperature and precipitation by employing generative probabilistic models with parameters determined through Bayesian inference. Our approach is applied t
We construct and analyze climate networks based on daily satellite measurements of temperatures and geopotential heights. We show that these networks are stable during time and are similar over different altitudes. Each link in our network is stable
The statistical behavior of weather variables of Antofagasta is described, especially the daily data of air as temperature, pressure and relative humidity measured at 08:00, 14:00 and 20:00. In this article, we use a time series deseasonalization tec
Modern weather and climate models share a common heritage, and often even components, however they are used in different ways to answer fundamentally different questions. As such, attempts to emulate them using machine learning should reflect this. W
Climate models are complicated software systems that approximate atmospheric and oceanic fluid mechanics at a coarse spatial resolution. Typical climate forecasts only explicitly resolve processes larger than 100 km and approximate any process occurr