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UAS Applications for Hurricane Science, Hurrican and Severe Storm Sentinel (HS3)
Earth Science Industry Update: UAS Applications for Hurricane Science Unmanned systems can significantly transform hurricane observations and monitoring, improving our knowledge about and ability to forecast storm formation, track, and intensity change. NASA's use of the Global Hawk has demonstrated the scientific value of this platform and provided a proof-of-concept for operational applications. However, science flight operations face several challenges and constraints. In this session, learn about how NASA adapted the Global Hawk to do science; How NASA conducts its hurricane missions, and some of the challenges and constraints they face; Science results from NASA's recent hurricane field campaigns using the Global Hawk. How assimilation of dropsonde and radar data into weather prediction models may improve forecast accuracy; Other Earth science problems that could be addressed with Global Hawks.
Examining Severe Weather Damage and Flood Impacts Through Synthetic Aperture Radar and Optical Imagery from the ESA Sentinel Missions
No abstract available
Eddy covariance towers as sentinels of abnormal radioactive material releases
Ensuring accurate detection and attribution of abnormal releases of radioactive material is critical for protecting human health and safety. Most commonly, such detection is accomplished via active monitoring approaches involving the collection of physical samples. Further, this is labor intensive and limits the temporal and spatial resolution of any detected events to a relatively coarse level. As an alternative first step towards passive monitoring, we developed an approach using eddy flux tower data records to identify signals from a known abnormal release and quantify the extent to which that signal also occurs at other times in the data record. Through two case studies, one of which targeted the Fukushima nuclear disaster and the other targeting an abnormal release event at a radioisotope production facility in Fleurus, Belgium, we tested our approach and identified several potential heretofore unidentified abnormal events that were consistent with atmospheric circulation patterns and/or wind direction from known release sites. Because our approach is relatively simple and is resistant to systematic errors in the observational record, it has broad applicability beyond specific constituents and ecosystem types to identify a wide variety of limited-duration anomalies in flux tower data to ensure human health and industrial safety.
Point-of-use filtration units as drinking water distribution system sentinels
Abstract Municipal drinking water distribution systems (DWDSs) and associated premise plumbing (PP) systems are vulnerable to proliferation of opportunistic pathogens, even when chemical disinfection residuals are present, thus presenting a public health risk. Monitoring the structure of microbial communities of drinking water is challenging because of limited continuous access to faucets, pipes, and storage tanks. We propose a scalable household sampling method, which uses spent activated carbon and reverse osmosis (RO) membrane point-of-use (POU) filters to evaluate mid- to long-term occurrence of microorganisms in PP systems that are relevant to consumer exposure. As a proof of concept, POU filter microbiomes were collected from four different locations and analyzed with 16S rRNA gene amplicon sequencing. The analyses revealed distinct microbial communities, with occasional detection of potential pathogens. The findings highlight the importance of local, and if possible, continuous monitoring within and across distribution systems. The continuous operation of POU filters offers an advantage in capturing species that may be missed by instantaneous sampling methods. We suggest that water utilities, public institutions, and regulatory agencies take advantage of end-of-life POU filters for microbial monitoring. This approach can be easily implemented to ensure drinking water safety, especially from microbes of emerging concerns; e.g., pathogenic Legionella and Mycobacterium species.
Hawaii - Wind Sentinel (120), Oahu, Hawaii / Processed Data
The purpose of the dataset is to provide preliminary filtered, averaged lidar data and standardize the data format of various datastreams from the buoy into NetCDF. The attached Lidar Buoy Data Dictionary provides further details on the various instruments mounted on the buoys, parameters measured by each instrument, and the frequency of data collection.
Buoy - WFIP3 - Wind Sentinel (140) / Raw Data
These data were collected during the WFIP3 project period, initially deployed near the Martha's Vineyard region for validation and later deployed at the WFIP3 location.
Evaluation of cloud height, optical thickness, and phase retrievals from the CHROMA algorithm applied to Sentinel-3 OLCI data
We previously developed the Cloud Height Retrieval from O 2 Molecular Absorption (CHROMA) algorithm for the Ocean Color Instrument (OCI) on the new NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission. Here, we apply CHROMA to observations from the Ocean Land Colour Instrument (OLCI) to guide expectations for PACE, as it will take some time to obtain large-scale validation data for OCI. We use cloud top height (CTH), phase, and (for liquid clouds) cloud optical thickness (COT) data from the ground-based Atmospheric Radiation Measurement (ARM) network to evaluate the OLCI retrievals. We found that OLCI and Moderate Resolution Imaging Spectroradiometer (MODIS) CTH compare similarly well to the ARM reference. OLCI has a tendency to underestimate CTH as CTH increases, and algorithm assumptions about cloud geometric thickness may contribute to this. ARM COT from multifilter shadowband radiometers (MFRSR) and Sun photometers are well-correlated with one another, albeit with a roughly 30 % offset on average; OLCI and MODIS COT agree more closely with the MFRSR data. OLCI retrieval uncertainty estimates show skill at telling low-uncertainty cases from high-uncertainty ones, although CTH uncertainties are underestimated. Additionally, we compare the OLCI data to satellite retrievals based on thermal infrared measurements from MODIS and Sea and Land Surface Temperature Radiometer (SLSTR) data. Differences are broadly consistent with physical expectations based on the A-band vs. thermal techniques, although one key challenge in such aggregated comparisons is different cloud masking sensitivities and algorithm failure rates meaning additional sampling differences are introduced. We conclude by discussing the transition to and possible enhancements for PACE OCI.
Retrieving Ocean Surface Winds and Waves from Augmented Dual-Polarization Sentinel-1 SAR Data Using Deep Convolutional Residual Networks
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Deep Self-Supervised Disturbance Mapping With the OPERA Sentinel-1 Radiometric Terrain Corrected SAR Backscatter Product
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Comparative Analysis of Empirical and Machine Learning Models for Chl a Extraction Using Sentinel-2 and Landsat OLI Data: Opportunities, Limitations, and Challenges
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Satellites as Sentinels for Health
Remotely-sensed data and observations are providing powerful new tools for addressing the human health aspects of sustainability by enabling improved understanding of the relationships and linkages between health-related environmental parameters and society as well as techniques for early warning of potential health problems. Remote sensing, geographic information systems, improved computational capabilities, and interdisciplinary research between the Earth and health science communities are being combined in rich collaborative efforts resulting in more rapid problem-solving, early warning, and prevention in global health issues. This paper provides a number of recent examples of applications of these technologies to health issues related to the following: infectious and vector-borne diseases; urban, regional and global air pollution; heat stress; UV radiation; water-borne disease; extreme weather; contaminant pathways (ocean, atmosphere, ice).
NASA's Sentinels Monitoring Weather and Climate: Past, Present, and Future
Weatherwise is probably the most popular newstand magazine focusing on the subject of weather. It is published six times per year and includes features on weather, climate, and technology. This article (to appear in the January/February Issue) provides a comprehensive review of NASA s past, present, and future contributions in satellite remote sensing for weather and climate processes. The article spans the historical strides of the TIROS program through the scientific and technological innovation of Earth Observer-3 and Global Precipitation Measurement (GPM). It is one of the most thorough reviews of NASA s weather and climate satellite efforts to appear in the popular literature.
Planetary Lake Lander - A Robotic Sentinel to Monitor a Remote Lake
The Planetary Lake Lander Project is studying the impact of rapid deglaciation at a high altitude alpine lake in the Andes, where disrupted environmental, physical, chemical, and biological cycles result in newly emerging natural patterns. The solar powered Lake Lander robot is designed to monitor the lake system and characterize both baseline characteristics and impacts of disturbance events such as storms and landslides. Lake Lander must use an onboard adaptive science-on-the-fly approach to return relevant data about these events to mission control without exceeding limited energy and bandwidth resources. Lake Lander carries weather sensors, cameras and a sonde that is winched up and down the water column to monitor temperature, dissolved oxygen, turbidity and other water quality parameters. Data from Lake Lander is returned via satellite and distributed to an international team of scientists via web-based ground data systems. Here, we describe the Lake Lander Project scientific goals, hardware design, ground data systems, and preliminary data from 2011. The adaptive science-on-the-fly system will be described in future papers.
Distinction of Drivers of Deforestation in the Amazon Using SAR Sentinel-1
No abstract available
Applicability of SAR Sentinel-1 Data to Distinguish Drivers of Deforestation in the Amazon
No abstract available
A Network Approach for Precise Coregistration of the Sentinel-1 TOPS Data
No abstract available
New Directions for SMAP: Combining SMAP and Sentinel Data for High-Resolution Soil Moisture Product
No abstract available