YESS, lead by the Online Events WG, hosted a Science webinar series between June and July.
The first webinar was titled From global mean sea level changes to land-atmosphere interactions and the speaker was Dr. Min-Hui Lo, from the National Taiwan University.
Global mean sea level (GMSL) variations are closely linked to the anthropogenic impacts and natural climate variability, such as the El Niño Southern Oscillation (ENSO). We use multiple sources of observational data from satellite altimetry (Gravity Recovery and Climate Experiment, GRACE), and in-situ ocean floats (Argo) to demonstrate that the mass and steric ocean states have specific temporal characteristics during ENSO events. This webinar highlights the essential role of land hydrological processes in GMSL changes.
The second webinar, Viewing Climate Signals through an AI lens, was lead by Dr. Elizabeth A. Barnes, from Colorado State University.
Much of Earth science is often viewed as a signal-to-noise problem. Because of this, our fields have many statistical methods for extracting the signal of interest. Here, we argue that artificial neural networks (ANNs) are an additional useful tool for the “earth science toolbox”. As an example, we demonstrate their utility for extracting forced climate patterns from model simulations and observations. By identifying spatial patterns that serve as indicators of change, the ANN is able to determine the year from which the simulations came, without first separating the forced climate change signal from the noise of both internal climate variability and model uncertainty.