Results 21 to 30 of about 561 (213)
FBNet: Feedback Network for Point Cloud Completion
, 2022 The rapid development of point cloud learning has driven point cloud completion into a new era. However, the information flows of most existing completion methods are solely feedforward, and high-level information is rarely reused to improve low-level feature learning. To this end, we propose a novel Feedback Network (FBNet) for point cloud completion,
Xuejun Yan +7 more
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Radiation feedback in dusty clouds [PDF]
Monthly Notices of the Royal Astronomical Society: Letters, 2017 Abstract We have investigated the impact of photoionization and radiation pressure on a dusty star-forming cloud using one-dimensional radiation hydrodynamic simulations, which include absorption and re-emission of photons by dust. We find that, in a cloud of mass 105 M⊙ and radius 17 pc, the effect of radiation pressure is negligible ...
Ishiki, Shohei, Okamoto, Takashi
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On the relationship between low cloud variability and lower tropospheric stability in the Southeast Pacific [PDF]
Atmospheric Chemistry and Physics, 2011 In this study, we examine marine low cloud cover variability in the Southeast Pacific and its association with lower-tropospheric stability (LTS) across a spectrum of timescales. On both daily and interannual timescales, LTS and low cloud amount are very
F. Sun, A. Hall, X. Qu
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Emergent Constraints for Cloud Feedbacks [PDF]
Current Climate Change Reports, 2015 Emergent constraints are physically explainable empirical relationships between characteristics of the current climate and long-term climate prediction that emerge in collections of climate model simulations. With the prospect of constraining long-term climate prediction, scientists have recently uncovered several emergent constraints related to long ...
Stephen A. Klein, Alex Hall
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Comparison of Clouds and Cloud Feedback between AMIP5 and AMIP6
Atmosphere, 2023 We examine the changes in clouds and cloud feedback between Phase 5 (AMIP5) and Phase 6 (AMIP6) of the Atmospheric Model Intercomparison Project. Each model is perturbed by uniformly increasing the sea surface temperature by 4 K. The simulated cloud fraction, the perturbed states and cloud radiative kernels are used to derive cloud feedback in the ...
Zhang, Yuanchong +2 more
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Climate Models Underestimate Dynamic Cloud Feedbacks in the Tropics
Geophysical Research Letters, 2023 Cloud feedbacks are the leading cause of uncertainty in climate sensitivity. The complex coupling between clouds and the large‐scale circulation in the tropics contributes to this uncertainty.
P. G. Hill +4 more
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Geophysical Research Letters, 2023 Radiative feedbacks govern the Earth's climate sensitivity and elucidate the geographic patterns of climate change in response to a carbon‐dioxide forcing.
Nicole Feldl, Timothy M. Merlis
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The Role of Mesoscale Cloud Morphology in the Shortwave Cloud Feedback
Geophysical Research Letters, 2022 A supervised neural network algorithm is used to categorize near-global satellite retrievals into three mesoscale cellular convective (MCC) cloud morphology patterns. At constant cloud amount, morphology patterns differ in brightness associated with the amount of optically-thin cloud features. Environmentally-driven transitions from closed MCC to other
Isabel L. McCoy +4 more
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Processes Responsible for Cloud Feedback [PDF]
Current Climate Change Reports, 2016 Cloud feedback on global climate is determined by the combined action of multiple processes that have different relevance in different cloud regimes. This review lays out the framework for cloud feedback and highlights recent advances and outstanding issues. A consensus is emerging on large-scale controls on cloud feedback.
Gettelman, A, Sherwood, SC
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Radiative forcing and feedback by forests in warm climates – a sensitivity study [PDF]
Earth System Dynamics, 2016 We evaluate the radiative forcing of forests and the feedbacks triggered by forests in a warm, basically ice-free climate and in a cool climate with permanent high-latitude ice cover using the Max Planck Institute for Meteorology Earth System Model. As a
U. Port, M. Claussen, V. Brovkin
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