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Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales

ArXiv 2406.16947 (2024)

Authors:

Peter Manshausen, Yair Cohen, Peter Harrington, Jaideep Pathak, Mike Pritchard, Piyush Garg, Morteza Mardani, Karthik Kashinath, Simon Byrne, Noah Brenowitz
Details from ArXiV

Isolating aerosol-climate interactions in global kilometre-scale simulations

EGUsphere (2024)

Authors:

Ross Herbert, Andrew Williams, Philipp Weiss, Duncan Watson-Parris, Elisabeth Dingley, Daniel Klocke, Philip Stier

Abstract:

Anthropogenic aerosols are a primary source of uncertainty in future climate projections. Changes to aerosol concentrations modify cloud radiative properties, radiative fluxes and precipitation from the micro to the global scale. Due to computational constraints, we have been unable to explicitly simulate cloud dynamics, leaving key processes, such as convective updrafts parameterized. This has significantly limited our understanding of aerosol impacts on convective clouds and climate. However, new state-of-the-art climate models running on exascale supercomputers are capable of representing these scales. In this study, we use the kilometre-scale earth system model ICON to explore, for the first time, the global response of clouds and precipitation to anthropogenic aerosol via aerosol-cloud-interactions (ACI) and aerosol-radiation-interactions (ARI). In our month-long simulations, we find that the aerosol impact on clouds and precipitation exhibits strong regional dependence, highlighting the complex interplay with atmospheric dynamics. The impact of ARI and ACI on clouds in isolation shows some consistent behaviour, but the magnitude and additive nature of the effects are regionally dependent. This behaviour suggests that the findings of isolated case studies from regional simulations may not be representative, and that ARI and ACI processes should both be accounted for in modelling studies. The simulations also highlight some limitations to be considered in future studies. Differences in internal variability between the simulations makes large-scale comparison difficult after the initial 10 – 15 days. Longer averaging periods or ensemble simulations will be beneficial for perturbation experiments in future kilometre-scale model simulations.
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Multi-Label Guided Soft Contrastive Learning for Efficient Earth Observation Pretraining

ArXiv 2405.20462 (2024)

Authors:

Yi Wang, Conrad M Albrecht, Xiao Xiang Zhu
Details from ArXiV

Combined impacts of temperature, sea ice coverage, and mixing ratios of sea spray and dust on cloud phase over the Arctic and Southern Oceans

(2024)

Authors:

Barbara Dietel, Hendrik Andersen, Jan Cermak, Philip Stier, Corinna Hoose
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AutoLCZ: Towards Automatized Local Climate Zone Mapping from Rule-Based Remote Sensing

ArXiv 2405.13993 (2024)

Authors:

Chenying Liu, Hunsoo Song, Anamika Shreevastava, Conrad M Albrecht
Details from ArXiV