In this paper we describe the development and motivation behind the development of a NASA-sponsored airborne instrument, SNOWWI (Snow Water-equivalent Wide Swath Interferometer) that is being developed for exploring the volume scattering and penetration depth characteristics of the snowpack at three different frequencies (5.4 GHz, C-band; 13.64 GHz known as Ku-low; 17.24 GHz known as Ku-high). The system, as it is being constructed is able to receive co- and cross-polarized (VV and VH) returns in an interferometric configuration. By implementing these components of the radar signature on the same platform, we will be able to explore the relationship between snow depth, density and snow water equivalent on the overall radar signature. This work is being done in conjunction with a strong modeling component being led by the University of Michigan, a ground campaign component supported by Boise State University and the US Army Corps of Engineers Cold Regions Research and Engineering Laboratory (CRREL), and a spaceborne concept development being led by Capella Space.

This article presents the first results of the newly conceived airborne Synthetic Aperture Radar system, SNOWWI.SNOWWI is a dual Ku- and C-Band interferometric and dualpolarized (VV and VH) system operating at 13.64 GHz, 17.24 GHz, and 5.39 GHz. The system aims to deliver snowpack observations to quantify Snow Depth (SD) and Snow Water Equivalent (SWE), which have been included as Targeted Observables in the National Academies’ 2017 Decadal Strategy for Earth Observation from Space. This manuscript includes results from the system’s first deployment in Grand Mesa, CO, in January and March 2024.

[Context:] Society increasingly values sustainable corporate behaviour, impacting corporate reputation and customer trust. Hence, companies regularly publish sustainability reports to shed light on their impact on environmental, social, and governance (ESG) factors. [Problem:] Sustainability reports are written by companies and therefore considered a company-controlled source. Contrarily, studies reveal that non-corporate channels (e.g., media coverage) represent the main driver for ESG transparency. However, analysing media coverage regarding ESG factors is challenging since (1) the amount of published news articles grows daily, (2) media coverage data does not necessarily deal with an ESG-relevant topic, meaning that it must be carefully filtered, and (3) the majority of media coverage data is unstructured. [Research Goal:] We aim to automatically extract ESG-relevant information from textual media reactions to calculate an ESG score for a given company. Our goal is to reduce the cost of ESG data collection and make ESG information available to the general public. [Contribution:] Our contributions are three-fold: First, we publish a corpus of 432,411 news headlines annotated as being environmental-, governance-, social-related, or ESG-irrelevant. Second, we present our tool-supported approach called ESG-Miner, capable of automatically analysing and evaluating corporate ESG performance headlines. Third, we demonstrate the feasibility of our approach in an experiment and apply the ESG-Miner on 3000 manually labelled headlines. Our approach correctly processes 96.7% of the headlines and shows great performance in detecting environmental-related headlines and their correct sentiment.

The Ka-band wind scatterometry is a relatively new methodology to retrieve ocean surface winds. Modeling the Ka-band ocean surface backscatter is challenging, especially because of the lack of in-situ measurements. In the framework of the NASA Earth Ventures Suborbital-3 Submesoscale Ocean Dynamics Experiment (S-MODE) mission, a new data set of ocean surface backscatter has been collected. These measurements were obtained from a Ka-band Doppler scatterometer (KaBODS) located on the Woods Hole Oceanographic Institution (WHOI) Air-Sea Interaction Tower (ASIT). In this work we present our analysis and findings on the KaBODS backscatter measurements based on the development of a wind empirical backscatter model. We show that the data are characterized by a large variability, which is mainly due to intrinsic geophysical effects. The source of this geophysical variability is currently under investigation.

In this paper we present processing and analysis results of an airborne Ku-band InSAR, constructed at the University of Massachusetts, and flown on a Cessna 208 Caravan over the Trail Valley Creek region in Canada's Northwest Territories during the 2018–19 snow season. In this paper, we describe the Ku-band InSAR, provide some intermediate results and discuss on how these data can be used for furthering the science in the remote sensing of snow.

The University of Massachusetts is implementing a testbed to evaluate phased-array weather radar polarimetry at X-band. The project seeks to determine the impacts of electronic scanning and associated polarization errors on weather radar measurables to analyze methods for polarimetric bias correction. The testbed consists of a planar dual-polarization X-band phased-array radar operated in tandem with a mechanically scanned polarimetric reference radar. The projection of tilted phased-array aperture polarizations to world coordinates are outlined, and direct comparisons of simultaneous weather observations by both radar systems are made along with quasi-vertical measurements of light precipitation which should reveal the array response to precipitation in the absence of differential reflectivity or differential phase.