Forecast-based attribution of a winter heatwave within the limit of predictability
Proceedings of the National Academy of Sciences National Academy of Sciences 118:49 (2021) e2112087118
Abstract:
The question of how humans have influenced individual extreme weather events is both scientifically and socially important. However, deficiencies in climate models’ representations of key mechanisms within the process chains that drive weather reduce our confidence in estimates of the human influence on extreme events. We propose that using forecast models that successfully predicted the event in question could increase the robustness of such estimates. Using a successful forecast means we can be confident that the model is able to faithfully represent the characteristics of the specific extreme event. We use this forecast-based methodology to estimate the direct radiative impact of increased CO2 concentrations (one component, but not the entirety, of human influence) on the European heatwave of February 2019.Compressing atmospheric data into its real information content
Nature Computational Science Springer Nature 1:11 (2021) 713-724
More accuracy with less precision
Quarterly Journal of the Royal Meteorological Society Wiley 147:741 (2021) 4358-4370
Projections of northern hemisphere extratropical climate underestimate internal variability and associated uncertainty
Communications Earth and Environment Springer Nature 2 (2021) 194
Abstract:
Internal climate variability will play a major role in determining change on regional scales under global warming. In the extratropics, large-scale atmospheric circulation is responsible for much of observed regional climate variability, from seasonal to multidecadal timescales. However, the extratropical circulation variability on multidecadal timescales is systematically weaker in coupled climate models. Here we show that projections of future extratropical climate from coupled model simulations significantly underestimate the projected uncertainty range originating from large-scale atmospheric circulation variability. Using observational datasets and large ensembles of coupled climate models, we produce synthetic ensemble projections constrained to have variability consistent with the large-scale atmospheric circulation in observations. Compared to the raw model projections, the synthetic observationally-constrained projections exhibit an increased uncertainty in projected 21st century temperature and precipitation changes across much of the Northern extratropics. This increased uncertainty is also associated with an increase of the projected occurrence of future extreme seasons.Building Tangent‐Linear and Adjoint Models for Data Assimilation With Neural Networks
Journal of Advances in Modeling Earth Systems American Geophysical Union (AGU) 13:9 (2021)