the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Fire–precipitation interactions amplify the quasi-biennial variability in fires over southern Mexico and Central America
Yawen Liu
Yun Qian
Philip J. Rasch
Kai Zhang
Lai-yung Ruby Leung
Yuhang Wang
Minghuai Wang
Hailong Wang
Xin Huang
Xiu-Qun Yang
Related authors
Marine cloud brightening (MCB) is a proposal to emit sea salt aerosols to make clouds more reflective and cool the climate. Here, we use three climate models to study a hypothetical future where MCB is used to maintain temperatures near 2020–2039 conditions. The simulation results indicate that using MCB in midlatitude ocean regions can keep the climate close to present day conditions. This reduces many of the negative impacts shown in previous studies, informing future modeling efforts.
Climate models are crucial for predicting climate change in detail. This paper proposes a balanced approach to improving their accuracy by combining traditional process-based methods with modern artificial intelligence (AI) techniques while maximizing the resolution to allow for ensemble simulations. The authors propose using AI to learn from both observational and simulated data while incorporating existing physical knowledge to reduce data demands and improve climate prediction reliability.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
hiddensource of inter-model variability and may be leading to bias in some climate model results.