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HLXiON δ Ω Intent Σ Logic Ψ Synth Π Reason Γ Memory Processing: climate change
iON AI Synthesis
Climate change is causing significant shifts in environmental systems, impacting ocean currents like the Antarctic Circumpolar Current and altering precipitation patterns through changes in the intertropical convergence zone (ITCZ). These changes are not fully understood, highlighting the need for advanced modeling techniques like physics-guided machine learning and deep learning for better prediction and communication. Additionally, effective public communication and visualization of climate change data are crucial for promoting sustainability and understanding the impacts on global ecosystems.
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arxiv.org
Southern Ocean Dynamics Under Climate Change: New Knowledge Through Physics-Guided Machine Learning

Complex ocean systems such as the Antarctic Circumpolar Current play key roles in the climate, and current models predict shifts in their strength and area under climate change. However, the physical processes underlying these changes are not well understood, in part due to the difficulty of charact…

physics.ao-ph cs.LG
semanticscholar.org
Impacts of Climate Change

Climate change is already affecting the environment and people around the world. We have seen changes in the air, in water, and in plants and animals. These impacts include things like warmer temperatures, sea-level rise, heavy rainfall and more intense storms. Hundreds of plants and animals on the …

arxiv.org
"The main message is that sustainability would help" -- Reflections on takeaway messages of climate change data visualizations

How do different audiences make sense of climate change data visualizations and what do they take away as a main message? To investigate this question, we are building on the results of a previous study, focusing on expert opinions regarding public climate change communication and the role of data v…

cs.HC
arxiv.org
Deep Ensembles to Improve Uncertainty Quantification of Statistical Downscaling Models under Climate Change Conditions

Recently, deep learning has emerged as a promising tool for statistical downscaling, the set of methods for generating high-resolution climate fields from coarse low-resolution variables. Nevertheless, their ability to generalize to climate change conditions remains questionable, mainly due to the s…

cs.LG physics.ao-ph
arxiv.org
Zonally opposing shifts of the intertropical convergence zone in response to climate change

Future changes in the location of the intertropical convergence zone (ITCZ) due to climate change are of high interest since they could substantially alter precipitation patterns in the tropics and subtropics. Although models predict a future narrowing of the ITCZ during the 21st century in response…

physics.ao-ph physics.geo-ph
arxiv.org
Learning Radiative Transfer Models for Climate Change Applications in Imaging Spectroscopy

According to a recent investigation, an estimated 33-50% of the world's coral reefs have undergone degradation, believed to be as a result of climate change. A strong driver of climate change and the subsequent environmental impact are greenhouse gases such as methane. However, the exact relation cl…

cs.LG astro-ph.IM physics.comp-ph stat.ML
arxiv.org
Active Amplification of the Terrestrial Albedo to Mitigate Climate Change: An Exploratory Study

This study explores the potential to enhance the reflectance of solar insolation by the human settlement and grassland components of the Earth's terrestrial surface as a climate change mitigation measure. Preliminary estimates derived using a static radiative transfer model indicate that such effort…

physics.ao-ph physics.geo-ph
arxiv.org
A fractal climate response function can simulate global average temperature trends of the modern era and the past millennium

A climate response function is introduced that consists of six exponential (low-pass) filters with weights depending as a power law on their e-folding times. The response of this two-parameter function to the combined forcings of solar irradiance, greenhouse gases, and SO2-related aerosols is fitted…

physics.ao-ph
arxiv.org
Precipitation extremes under climate change

The response of precipitation extremes to climate change is considered using results from theory, modeling, and observations, with a focus on the physical factors that control the response. Observations and simulations with climate models show that precipitation extremes intensify in response to a w…

physics.ao-ph
arxiv.org
An Interpretable Model of Climate Change Using Correlative Learning

Determining changes in global temperature and precipitation that may indicate climate change is complicated by annual variations. One approach for finding potential climate change indicators is to train a model that predicts the year from annual means of global temperatures and precipitations. Such …

physics.ao-ph cs.LG