Related papers: Understanding cirrus clouds using explainable mach…
Due to computational constraints, running global climate models (GCMs) for many years requires a lower spatial grid resolution (${\gtrsim}50$ km) than is optimal for accurately resolving important physical processes. Such processes are…
The purpose of this study is to provide more insight into the role of anthropogenic cirrus formation through air traffic, by investigating the high-density European airspace over a period spanning several recent years including the start of…
Observations have shown that the optical colors of Galactic cirrus clouds differ significantly from those of extragalactic sources; thus, they can be used to distinguish Galactic cirrus from extragalactic low surface brightness (LSB)…
Understanding of clouds is instrumental in interpreting current and future spectroscopic observations of exoplanets. Modelling clouds consistently is complex, since it involves many facets of chemistry, nucleation theory, condensation…
Thermal management in the hyper-scale cloud data centers is a critical problem. Increased host temperature creates hotspots which significantly increases cooling cost and affects reliability. Accurate prediction of host temperature is…
The atmospheres of substellar objects contain clouds of oxides, iron, silicates, and other refractory condensates. Water clouds are expected in the coolest objects. The opacity of these `dust' clouds strongly affects both the atmospheric…
Most brown dwarfs have atmospheres with temperatures cold enough to form clouds. A variety of materials likely condense, including refractory metal oxides and silicates; the precise compositions and crystal structures of predicted cloud…
Context. Determining properties of dust formed in and around supernovae from observations remains challenging. This may be due to either incomplete coverage of data in wavelength or time but also due to often inconspicuous signatures of…
The midlatitude climate and weather are shaped by storms, yet the factors governing their predictability remain insufficiently understood. Here, we use a Convolutional Neural Network (CNN) to predict and quantify uncertainty in the…
The present work is aimed to examine the potential of advanced machine learning strategies to predict the monthly rainfall (precipitation) for the Indus Basin, using climatological variables such as air temperature, geo-potential height,…
In this proof-of-concept study, we conduct multivariate timeseries forecasting for the concentrations of nitrogen dioxide (NO2), ozone (O3), and (fine) particulate matter (PM10 & PM2.5) with meteorological covariates between two locations…
We aim to characterize the relationship between dust properties. We also aim to provide equations to estimate accurate dust properties from limited observational datasets. We assemble a sample of 1,630 nearby (z<0.1) galaxies-over a large…
Clouds classification is a great challenge in meteorological research. The different types of clouds, currently known and present in our skies, can produce radioactive effects that impact on the variation of atmospheric conditions, with the…
Horizontal atmospheric wind shear causes wind velocity fields to have different directions and speeds. In images of clouds acquired using ground-based sky imagers, clouds may be moving in different wind layers. To increase the performance…
We present clumps of dust emission from Herschel observations of the Large Magellanic Cloud (LMC) and their physical and statistical properties. We catalog cloud features seen in the dust emission from Herschel observations of the LMC, the…
Climate system models (CSMs), through integrating cross-sphere interactions among the atmosphere, ocean, land, and cryosphere, have emerged as pivotal tools for deciphering climate dynamics and improving forecasting capabilities. Recent…
We apply gravity-based and density-based methods to identify clouds in numerical simulations of the star-forming, three-phase interstellar medium (ISM), and compare their properties and their global correlation with the star formation rate…
Using a general circulation model (GCM), we investigate trends in simulated hot Jupiter atmospheres for a range of irradiation temperatures (1,500 - 4,000 K), surface gravities (10 and 40 m s-2), and cloud conditions. Our models include…
Mineral dust aerosols impact Earth's radiation budget through interactions with clouds, ecosystems, and radiation, which constitutes a substantial uncertainty in understanding past and predicting future climate changes. One of the causes of…
The growth, lifetime, number density, and size of water droplets in warm atmospheric clouds determine the evolution, lifetime and light transmission properties of those clouds. These small-scale cloud properties, in addition to…