Analogy-Based Assessment of Domain-Specific Word Embeddings

No abstract availabl

A Comparison of Techniques for Estimating NDVI for Agricultural Intervention Impact Assessment

No abstract availabl

Data-Intensive Science Meets Inquiry-Driven Pedagogy: Interactive Big Data Exploration, Threshold Concepts, and Liminality

No abstract availabl

Deep Learning for Transverse Cirrus Bands Detection and Analysis

No abstract availabl

Roles of atmospheric and land surface data in dynamic regional downscaling

In studies dealing with the impact of land use changes on atmospheric processes, a key methodological step is the validation of simulated current conditions. However, regions lacking detailed atmospheric and land use data provide limited information with which to accurately generate control simulations. In this situation, the difference between baseline control simulations and different land use change simulations can be quite different owing to the quality of the atmospheric and land use data sets. Using multiple simulations at the Monteverde cloud forest region of Costa Rica as an example, we show that when a regional climate model is used to study the effect of land use change, it can produce distinctly different results at regional scales, depending on the amount of data available to run the climate simulations. We show that for the specific case of land use change impact studies, the simulation results are very sensitive to the prescribed atmospheric information (e.g., lateral boundary conditions) compared to the land use (surface boundary) information

Pixel-Based Smoke Detection Using Machine Learning for the Next Generation Geostationary Satellite Imagery

No abstract availabl

Evaluating a New Machine Learning-Based Methodology for Assessing the Impact of Agricultural Interventions in Nepal

No abstract availabl

A New Machine Learning-Based Methodology for Assessing the Impact of Agricultural Interventions in Nepal

No abstract availabl

Influence of Land Cover and Soil Moisture based Brown Ocean Effect on an Extreme Rainfall Event from a Louisiana Gulf Coast Tropical System

Extreme flooding over southern Louisiana in mid-August of 2016 resulted from an unusual tropical low that formed and intensified over land. We used numerical experiments to highlight the role of the ‘Brown Ocean’ effect (where saturated soils function similar to a warm ocean surface) on intensification and it’s modulation by land cover change. A numerical modeling experiment that successfully captured the flood event (control) was modified to alter moisture availability by converting wetlands to open water, wet croplands, and dry croplands. Storm evolution in the control experiment with wet antecedent soils most resembles tropical lows that form and intensify over oceans. Irrespective of soil moisture conditions, conversion of wetlands to croplands reduced storm intensity, and also, nonsaturated soils reduced rain by 20% and caused shorter durations of high intensity wind conditions. Developing agricultural croplands and more so restoring wetlands and not converting them into open water can impede intensification of tropical systems that affect the area

Drought Information Supported by Citizen Scientists (DISCS)

No abstract availabl