Search

Shallow water waves are seen in oceanography, atmospheric science, and other fields. In this paper, we investigate an extended (3+1)-dimensional shallow water wave equation. We get the travelling-wave solutions via the polynomial-expansion method. Applying the Hirota method and symbolic computation, we derive some mixed-lump-kink and mixed-rogue-wave-kink solutions. Based on the mixed-lump-kink solutions, we graphically show the interaction between a lump and a kink soliton, and find two different cases: (1) the lump merges into the kink soliton; (2) the lump separates from the kink soliton. Based on the mixed-rogue-wave-kink solutions, we graphically analyze the interaction between the rogue wave and two-kink solitons, and find that the rogue wave emerges from the one kink soliton and merges into the other kink soliton. [ABSTRACT FROM AUTHOR]

This paper analyzes how the atmospheric science of transboundary air pollution was employed as a technopolitical strategy to secure a nation’s volumetric territory. In South Korea, border-crossing particulate matter from China has emerged as a controversial diplomatic concern. The Korean government heavily funded atmospheric science to monitor the transboundary incursion and quantify the amount of Chinese influence. The geoscience of polluted air was mobilized to restore the nation’s aerial sovereignty when transboundary materiality threatened its political authority to regulate atmospheric territory. The paper further examines how nationalistic science was challenged by an international air quality survey called KORUS-AQ, a study co-organized by NASA and Korea’s National Institute for Environmental Research. Korean experts used the joint mission with NASA to verify the transboundary impact on Seoul’s air quality and hold China responsible. US scientists, however, challenged this nation-centered vision by highlighting the underestimated domestic sources of air pollution. As a result, the aerial survey did not generate a unilateral understanding of nature but produced multiple and even contrasting territorial imaginations on a single airshed. Atmospheric science, I argue, functioned as a geopolitical arena where different visions on volumetric governance were enacted and competed. [ABSTRACT FROM AUTHOR]

High‐Resolution Multi‐scale Modeling Frameworks (HR)—global climate models that embed separate, convection‐resolving models with high enough resolution to resolve boundary layer eddies—have exciting potential for investigating low cloud feedback dynamics due to reduced parameterization and ability for multidecadal throughput on modern computing hardware. However low clouds in past HR have suffered a stubborn problem of over‐entrainment due to an uncontrolled source of mixing across the marine subtropical inversion manifesting as stratocumulus dim biases in present‐day climate, limiting their scientific utility. We report new results showing that this over‐entrainment can be partly offset by using hyperviscosity and cloud droplet sedimentation. Hyperviscosity damps small‐scale momentum fluctuations associated with the formulation of the momentum solver of the embedded large eddy simulation. By considering the sedimentation process adjacent to default one‐moment microphysics in HR, condensed phase particles can be removed from the entrainment zone, which further reduces entrainment efficiency. The result is an HR that can produce more low clouds with a higher liquid water path and a reduced stratocumulus dim bias. Associated improvements in the explicitly simulated sub‐cloud eddy spectrum are observed. We report these sensitivities in multi‐week tests and then explore their operational potential alongside microphysical retuning in decadal simulations at operational 1.5° exterior resolution. The result is a new HR having desired improvements in the baseline present‐day low cloud climatology, and a reduced global mean bias and root mean squared error of absorbed shortwave radiation. We suggest it should be promising for examining low cloud feedbacks with minimal approximation. Plain Language Summary: Stratocumulus clouds cover a large fraction of the globe but are very challenging to reproduce in computer simulations of Earth's atmosphere because of their unique complexity. Previous studies find the model produces too few Stratocumulus clouds as we increase the model resolution, which, in theory, should improve the simulation of important motions for the clouds. This is because the clouds are exposed to more conditions that make them evaporate away. On Earth, stratocumulus clouds reflect a lot of sunlight. In the computer model of Earth, too much sunlight reaches the surface because of too few stratocumulus clouds, which makes it warmer. This study tests two methods to thicken Stratocumulus clouds in the computer model Earth. The first method smooths out some winds, which helps reduce the exposure of clouds to the conditions that make them evaporate. The second method moves water droplets in the cloud away from the conditions that would otherwise make them evaporate. In long simulations, combining these methods helps the model produce thicker stratocumulus clouds with more water. Key Points: We improve a long‐standing stratocumulus (Sc) dim bias in a high‐resolution Multiscale Modeling FrameworkIncorporating intra‐CRM hyperviscosity hedges against the numerics of its momentum solver, reducing entrainment vicinityFurther adding sedimentation boosts Sc brightness close to observed, opening path to more faithful low cloud feedback analysis [ABSTRACT FROM AUTHOR]

A cutting-edge global model of the atmosphere combines machine learning with a numerical model based on the laws of physics. This 'hybrid' system accurately predicts the weather — and even shows promise for climate simulations. Numerical modelling and machine learning unite to emulate the atmosphere. [ABSTRACT FROM AUTHOR]