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The simple 3-D radiative transfer model in the atmosphere of the Earth is built for numerical comparison of direct solar radiation and limb scattering background at the definite layer during the deep twilight period at the middle and upper…
The complexity of atmospheric retrieval models is largely data-driven and one-dimensional models have generally been considered adequate with current data quality. However, recent studies have suggested that using 1D models in retrievals…
Climate models lack the necessary resolution for urban climate studies, requiring computationally intensive processes to estimate high resolution air temperatures. In contrast, Data-driven approaches offer faster and more accurate air…
Machine learning is now used in many areas of astrophysics, from detecting exoplanets in Kepler transit signals to removing telescope systematics. Recent work demonstrated the potential of using machine learning algorithms for atmospheric…
In order to extract cosmological information from observations of the millimeter and submillimeter sky, foreground components must first be removed to produce an estimate of the cosmic microwave background (CMB). We developed a…
Ambient backscatter communication (AmBC) leverages the existing ambient radio frequency (RF) environment to implement communication with battery-free devices. The key challenge in the development of AmBC is the very weak RF signals…
Fluctuating atmospheric emission is a dominant source of noise for ground-based millimeter-wave observations of the CMB temperature anisotropy at angular scales $\gtrsim 0.5^{\circ}$. We present a model of the atmosphere as a discrete set…
Existing all-in-one image restoration approaches, which aim to handle multiple weather degradations within a single framework, are predominantly trained and evaluated using mixed single-weather synthetic datasets. However, these datasets…
Forests play a critical role in global ecosystems by supporting biodiversity and mitigating climate change via carbon sequestration. Accurate aboveground biomass (AGB) estimation is essential for assessing carbon storage and wildfire fuel…
Climate science studies the structure and dynamics of Earth's climate system and seeks to understand how climate changes over time, where the data is usually stored in the format of time series, recording the climate features, geolocation,…
Reliable building height estimation is essential for various urban applications. Spaceborne SAR tomography (TomoSAR) provides weather-independent, side-looking observations that capture facade-level structure, offering a promising…
High resolution spectroscopy has opened the way for new, detailed study of exoplanet atmospheres. There is evidence that this technique can be sensitive to the complex, three-dimensional (3D) atmospheric structure of these planets. In this…
Aerosols found in the atmosphere affect the climate and worsen air quality. To mitigate these adverse impacts, aerosol formation and aerosol chemistry in the atmosphere need to be better mapped out and understood. Currently, mass…
Traditional numerical global climate models simulate the full Earth system by exchanging boundary conditions between separate simulators of the atmosphere, ocean, sea ice, land surface, and other geophysical processes. This paradigm allows…
One significant difference between the atmospheres of stars and exoplanets is the presence of condensed particles (clouds or hazes) in the atmosphere of the latter. The main goal of this paper is to develop a self-consistent microphysical…
Airborne acquisition and on-road mobile mapping provide complementary 3D information of an urban landscape: the former acquires roof structures, ground, and vegetation at a large scale, but lacks the facade and street-side details, while…
Ultrasonic backscatter measurements are widely used for microstructural characterisation. However, in materials containing strong anisotropy and spatial heterogeneity, the interpretation of backscatter signals becomes challenging because…
The state of the art for physical hazard prediction from weather and climate requires expensive km-scale numerical simulations driven by coarser resolution global inputs. Here, a generative diffusion architecture is explored for downscaling…
Most planets currently amenable to transit spectroscopy are close enough to their host star to exhibit a relatively strong day to night temperature gradient. For hot planets, this leads to cause a chemical composition dichotomy between the…
The formation of aerosol particles in the atmosphere impacts air quality and climate change, but many of the organic molecules involved remain unknown. Machine learning could aid in identifying these compounds through accelerated analysis…