Related papers: Intercomparison of Brown Dwarf Model Grids and Atm…
Using SofI on the 3.5m New Technology Telescope, we have conducted an extensive near-infrared monitoring survey of an unbiased sample of 69 brown dwarfs spanning the L0 and T8 spectral range, with at least one example of each spectral type.…
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…
Understanding forest health is of great importance for the conservation of the integrity of forest ecosystems. In this regard, evaluating the amount and quality of dead wood is of utmost interest as they are favorable indicators of…
This study presents the first comprehensive comparison of rule-based methods, traditional machine learning models, and deep learning models in radio wave sensing with frequency modulated continuous wave multiple input multiple output radar.…
We study rotation-robust learning for image inputs using Convolutional Model Trees (CMTs) [1], whose split and leaf coefficients can be structured on the image grid and transformed geometrically at deployment time. In a controlled MNIST…
Building a sustainable burn platform in inertial confinement fusion (ICF) requires an understanding of the complex coupling of physical processes and the effects that key experimental design changes have on implosion performance. While…
We present a uniform forward-modeling analysis of 90 late-M and L dwarfs in nearby young (~$10-200$ Myr) moving groups, the Pleiades, and the Hyades using low-resolution ($R\approx150$) near-infrared ($0.9-2.4$ $\mathrm{\mu m}$) spectra and…
An invasive species of grass known as "buffelgrass" contributes to severe wildfires and biodiversity loss in the Southwest United States. We tackle the problem of predicting buffelgrass "green-ups" (i.e. readiness for herbicidal treatment).…
Climate models play a critical role in understanding and projecting climate change. Due to their complexity, their horizontal resolution of about 40-100 km remains too coarse to resolve processes such as clouds and convection, which need to…
We present the SPHEREx Ultracool Dwarf spectral Atlas (SUDA), a homogeneous sample of 1675 ultracool dwarfs with continuous 0.75--5 $\mu$m spectroscopy from SPHEREx QR2. Using the SAND and ATMO2020++ atmospheric model grids, we derive…
Climate models are essential to understand and project climate change, yet long-standing biases and uncertainties in their projections remain. This is largely associated with the representation of subgrid-scale processes, particularly…
One of the impacts of climate change is the difficulty of tree regrowth after wildfires over areas that traditionally were covered by certain tree species. Here a deep learning model is customized to classify land covers from four-band…
A random forest prediction can be computed by the scalar product of the labels of the training examples and a set of weights that are determined by the leafs of the forest into which the test object falls; each prediction can hence be…
Disequilibrium chemistry due to vertical mixing in the atmospheres of many brown dwarfs and giant exoplanets is well-established. Atmosphere models for these objects typically parameterize mixing with the highly uncertain $K_{\rm zz}$…
Quantifying long-term historical climate is fundamental to understanding recent climate change. Most instrumentally recorded climate data are only available for the past 200 years, so proxy observations from natural archives are often…
The third data release of Gaia has provided approximately 220 million low resolution spectra. Among these, about 100,000 correspond to white dwarfs. The magnitude of this quantity of data precludes the possibility of performing spectral…
Significant populations of field L and T dwarfs are now known, and we anticipate the discovery of even cooler dwarfs by Spitzer and ground-based infrared surveys. However, as the number of known L and T dwarfs increases so does the range in…
In this brief contribution, I touch on a subset of recent efforts in spectral and opacity modeling aimed at improving our understanding of brown dwarfs, L dwarfs, and T dwarfs. I discuss theoretical calculations of the alkali line profiles,…
Since model bias and associated initialization shock are serious shortcomings that reduce prediction skills in state-of-the-art decadal climate prediction efforts, we pursue a complementary machine-learning-based approach to climate…
Urgent applications like wildfire management and renewable energy generation require precise, localized weather forecasts near the Earth's surface. However, forecasts produced by machine learning models or numerical weather prediction…