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At least 343 records · Page 19

Validation, Comparison, and Integration of GOCI, AHI, MODIS, MISR, and VIIRS Aerosol Optical Depth Over East Asia During the 2016 KORUS-AQ Campaign

Recently launched multichannel geostationary Earth orbit (GEO) satellite sensors, such as the Geostationary Ocean Color Imager (GOCI) and the Advanced Himawari Imager (AHI), provide aerosol products over East Asia with high accuracy, which enables the monitoring of rapid diurnal variations and the transboundary transport of aerosols. Most aerosol studies to date have used low Earth orbit (LEO) satellite sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multi-angle Imaging Spectroradiometer (MISR), with a maximum of one or two overpass daylight times per day from midlatitudes to low latitudes. Thus, the demand for new GEO observations with high temporal resolution and improved accuracy has been significant. In this study the latest versions of aerosol optical depth (AOD) products from three LEO sensors – MODIS (Dark Target, Deep Blue, and MAIAC), MISR, and the Visible/Infrared Imager Radiometer Suite (VIIRS), along with two GEO sensors (GOCI and AHI), are validated, compared, and integrated for a period during the Korea–United States Air Quality Study (KORUS-AQ) field campaign from 1 May to 12 June 2016 over East Asia. The AOD products analyzed here generally have high accuracy with high R (0.84–0.93) and low RMSE (0.12–0.17), but their error characteristics differ according to the use of several different surface-reflectance estimation methods. High-accuracy near-real-time GOCI and AHI measurements facilitate the detection of rapid AOD changes, such as smoke aerosol transport from Russia to Japan on 18–21 May 2016, heavy pollution transport from China to the Korean Peninsula on 25 May 2016, and local emission transport from the Seoul Metropolitan Area to the Yellow Sea in South Korea on 5 June 2016. These high-temporal-resolution GEO measurements result in more representative daily AOD values and make a greater contribution to a combined daily AOD product assembled by median value selection with a 0.5∘×0.5∘ grid resolution. The combined AOD is spatially continuous and has a greater number of pixels with high accuracy (fraction within expected error range of 0.61) than individual products. This study characterizes aerosol measurements from LEO and GEO satellites currently in operation over East Asia, and the results presented here can be used to evaluate satellite measurement bias and air quality models.

Myungje Choi↗

NASA-NOAA Feasibility Report

The western stock of Steller sea lions and the Aleutian stock of harbor seals both experienced dramatic declines in abundance during the past few decades, particularly in the central and western Aleutian Islands. Both stocks have continued to decline in recent years, thus are a high priority for routine monitoring. NOAA’s Marine Mammal laboratory (MML) has conducted aerial surveys of marine mammals throughout coastal Alaska to monitor trends in population abundance and distribution for more than 20 years. These surveys have typically been conducted from a twinengine aircraft, such as a DHC-6 Twin Otter, operated by NOAA pilots and crewmembers. Aerial surveys in the Aleutian Islands present significant challenges and higher risks due to their remoteness, rugged terrain, and extreme weather. To evaluate the feasibility of transitioning from manned to unmanned aerial surveys in this region, thereby reducing risks to NOAA personnel and high-value aircraft, we propose to conduct test survey flights in the Near Islands of Alaska using a medium-sized, fixed-wing UAV (NASA’s SIERRA-B aircraft) with a nadir-aimed imaging payload. Survey flights are planned to be conducted during daylight hours on days with VFR conditions and less than ~20 knot winds at altitudes of 800-1200 feet. Survey imagery, including thermal video and high-resolution color photos, would be collected at known Steller sea lion and harbor seal sites along the coastlines of Shemya, Nizki, Alaid, Agattu, and Attu Islands. The planning team will request approval and support from the US Air Force to conduct this project at Eareckson Air Station (Shemya Island, AK) during the month of September 2022 when weather conditions in the western Aleutian Islands are expected to be optimal.

NOAA↗

Tracking Smoke from a Prescribed Fire and its Impacts on Local Air Quality using Temporally Resolved GOES-16 ABI Aerosol Optical Depth (AOD)

Aerosol optical depth (AOD) retrieved from the GOES-16 Advanced Baseline Imager (ABI) was used to track a smoke plume from a prescribed fire in northeastern Virginia on 8 March 2020. Weather and atmospheric conditions created a favorable environment to transport the plume through the Washington, D.C., and Baltimore, Maryland, metro areas in the afternoon and concentrate smoke near the surface, degrading air quality for several hours. ABI AOD with 5-min temporal resolution and 2-km spatial resolution definitively identified the timing and geographic extent of the plume during daylight hours. Comparison to AERONET AOD indicates that ABI AOD captured the relative change in AOD due to passage of the smoke, with a mean absolute error of 0.047. Ground-based measurements of fine particulate matter (PM2.5) confirm deteriorations in air quality coincident with the progression of the smoke. Ceilometer aerosol backscatter profiles verify plume transport timing and indicate that smoke aerosols were well mixed in a shallow boundary layer. This event illustrates the advantages of using multiple datasets to analyze the impacts of aerosols on ambient air quality. Given the quickly evolving nature of the event over several hours, ABI AOD provided information for the public and decision-makers that was not available from any other source, including polar-orbiting satellite sensors. This study suggests that PM2.5 concentrations estimated from ABI AOD can be used to fill in the gaps in nationwide regulatory PM2.5 monitor networks and may be a valuable addition to EPA’s PM2.5 NowCast of current air quality conditions.

satellite observations↗

Using Lunar Superconducting Magnetic Energy Storage (LSMES) for NASA Artemis Program

The development of High temperature Superconductors (HTS) with transition temperatures >91K allows for their application in the Permanently Shadowed Regions (PSRs) on the Moon, where temperatures range from ~40K-60K. These are well below the critical temperature, Tc for the YBa2Cu3O7-x HTS material. An HTS coil installed in a PSR would not require cooling to remain below Tc. The coil can be energized with solar panels during daylight and maintain a magnetic field during night. The coil can be loaded and unloaded in millisecond time scales. The long lifetime with minimal losses is an attractive option for NASA’s Artemis program to consider for energy management on the Moon.

High Temperature Superconductivity (HTS)↗

Ruggedizing a Commercial Depth Camera for Novel Lunar Exploration.

The novel contribution of this instrument is to take the first depth images on the moon. A commercial Kinect camera from Microsoft has been ruggedized for a CLPS mission to the Lunar South Pole. The 12-megapixel color camera is combined with a 1-megapixel color time-of-flight (ToF) depth sensor. The solid-state depth sensor/LIDAR provides greater resolution, a wider field of view, pixel binning, and reduced power consumption. The high-resolution data collected from the mission can be used to construct a near-field virtual environment of the lunar surface for scientific applications. The depth camera can provide a 360-degree view of the target area by combining ToF data with RGB imagery and rover turning. The unit was evaluated for space flight compliant materials and parts at NASA Ames. The microphone array, RF shield, front face, and outer body parts were removed to reduce mass. Plastic parts were replaced with vacuum-compatible materials; manufactured cables were added to properly interface with the host rover, built by Lunar Outpost. The environmental testing was performed on the Kinect with Random Vibration/Sine Testing (Fig 1a), per GEVS (NASA’s General Environmental Verification Standard for spaceflight launch survival). Thermal Vacuum testing cycled the instrument between expected hot (+ 85 C) and cold survival temperatures, as well as +50 C and -25 C operational temps (Fig 1b). The instrument functioned nominally at the conclusion of vibration and thermal cycling tests. The Azure Kinect is manifested on the Nova-C lander which flies on the Intuitive Machines mission IM-2, landing at the lunar south pole for a mission duration of 14 days (one lunar daylight cycle). The unit will be integrated to the MAPP (Mobile Autonomous Prospecting Platform) rover at Lunar Outpost. The Azure Kinect with ToF feature will improve the resolution of lunar geology data near the south pole and enable ground-based VR experience of details of the lunar surface (Fig 1c).

V. Jha↗

Overview of Nasa's Watts on the Moon Challenge Phase 1

As NASA works to extend human exploration of the solar system, unprecedented capacity for electrical and thermal energy will be needed to support sustained human presence and the beginning of industrial activity on the Moon. Solar energy is abundant on the lunar surface but extended night hours (up to 350 consecutive hours) and extreme temperature change from daylight to nighttime operation creates complexity for solar power use. Analogous issues arise on Earth, where demand for additional renewable energy generation, including solar, is rising, but better power management, distribution, and energy storage solutions are needed to address intermittency and resiliency, among other issues. To accelerate the development of technologies for power distribution and energy storage that can operate in extreme lunar conditions, NASA’s Centennial Challenges Program launched the Watts on the Moon Challenge in September 2020. Submissions for Phase 1 of the challenge were due in March 2021 and winners were announced in May 2021. This paper provides an overview of the challenge, key technical requirements, outcomes from Phase 1, and an update on Phase 2 of the challenge, which is currently ongoing.

Denise P. Morris↗

Open Source Application of Fusing Aerosol Products from GEO and LEO Satellites

Retrieving aerosol optical depths (AODs) from sun-synchronous polar orbiting (aka low earth orbit, LEO) satellites, such as MODISs, and VIIRSs, OMI, TROPOMI, etc, has become well-established as a tool for extracting information on particulate matter (PM) and related processes in the atmosphere. However, with recently launched geostationary satellites (GEO), such as GOES-16/17/18, and Himawari-8/9, and Meteosat Third Generation (MTG) they provide a much higher temporal resolution (order of 10 minutes), typically an image once or more per hour during daylight compared to LEO once per day. By combining these observations, we may be able to characterize the diurnal cycle of global AOD at the local, regional and global scale. While the science community is still exploring the new data from GEO observations, we have been thinking about how to properly combine/merge/fuse those data considering differences in their spatial and temporal resolutions. However, this poses a “Big Data” challenge. The big data challenge is not just about data storage, but also about data discoverability, and accessibility, and even more, about data migration/mirroring in the cloud-computing environment. This paper is merely showing some of the efforts and approaches we have attempted in fusing six satellites’ Level 2 aerosol data (three are from GEO (GOES-16/17 and Himawari-8), and the other three are from LEO (TERRA/MODIS, AQUA/MODIS, SNPP-VIIRS) from Dark Target (DT) aerosol retrieval algorithm. Having the on-demand capability of fusing remote sensing products onto the desired temporal and spatial domain enables researchers and application practitioners to better manipulate and work with satellite and sensor data. It is our hopeWe hope that by making such an open-source package, and the accompanying functionality, the scientific community will be granted easier access to aerosol data processing resources. The MEaSUREs Program (Making Earth System Data Records for Use in Research Environments) expands our understanding of the Earth's current system through atmospheric and surface measurements. In an effort to aid the scientific research component and improve open source methods, this project developed Python code for fusing six satellite Level 2 aerosol data (three are from geostationary satellites (GEO), and the other three are from low earth orbital satellites (LEO)) from Dark Target Aerosol Retrieval Algorithm.

Jennifer Wei↗

Pyroscopegridding: Geo-Leo Aerosol Data Fusion (an Open-Source Package)

The retrieval of aerosol optical depths (AODs) from sun-synchronous polar orbiting satellites, such as MODISs, VIIRSs, OMI, TROPOMI, etc., has been widely adopted as a method for obtaining information regarding particulate matter (PM) and related atmospheric processes. However, the advent of recently launched geostationary satellites, such as GOES-16/17/18, Himawari-8/9, and Meteosat Third Generation (MTG), has led to an increased temporal resolution of AOD observations (order of 10 minutes), resulting in typically one or more images per hour during daylight hours, compared to the once-per-day observations obtained from LEO satellites. By integrating these observations, the diurnal cycle of global AOD can be characterized at local, regional, and global scales. The scientific community is still examining the novel data from geostationary satellite observations and evaluating methods for effectively merging these observations with differing spatial and temporal resolutions. This presents a significant ""Big Data"" challenge, encompassing not only data storage, but also data discoverability, accessibility, and migration within cloud computing environments. This study presents our attempts at fusing Level 2 aerosol data from six satellites, three of which are geostationary (GOES-16/17 and Himawari-8) and three of which are polar orbiting (TERRA/MODIS, AQUA/MODIS, and SNPP-VIIRS), using the Dark Target aerosol retrieval algorithm. The ability to fuse remote sensing products on demand into desired temporal and spatial domains empowers researchers and practitioners to more efficiently work with satellite and sensor data. It is our hope that through making our open-source package and accompanying functionality available, the scientific community will have improved access to aerosol data processing resources.

Jennifer Wei↗

High-Speed Video of Lightning Strikes to Communications Tower on 7 August 2023

NASA operates a high-speed camera (a MIRO M310 manufactured by Vision Research) on the fourth floor of the Operations and Checkout Building pointed at the communications tower that is in the Industrial Area of Kennedy Space Center. Figure 1 shows the location of the camera and tower. Figure 2 shows the camera view during daylight. On 7 August 2023 between 11 pm and 12 am eastern standard time, three lightning flashes to the tower were recorded.

lightning↗

Finding Your TEMPO: An Introduction to the Mission, Products, and Data Services for Air Quality Observations over North America

NASA's Tropospheric Emissions: Monitoring of Pollution (TEMPO) mission is the first space-based instrument to monitor major air pollutants across the North American continent every daylight hour at high spatial resolution. TEMPO is an ultraviolet and visible spectrometer that sits on a commercial satellite in a geostationary orbit about 22,000 miles above Earth's equator. This vantage point enables TEMPO to monitor daily variations in ozone, nitrogen dioxide, and other key elements of air pollution from the Atlantic to the Pacific, and from Mexico City and the Yucatan Peninsula to the Canadian oil sands. This webinar will provide an overview of the TEMPO mission and its data products and will show you how to discover and access TEMPO data products using NASA's Earthdata Search. This includes finding documentation, performing searches and filtering, using subsetting/concatenation services in Earthdata Search, and utilizing the Earthdata Forum.

Caroline Nowlan↗

ILEOS: A Novel Intelligent Observing System Enabled by High Altitude Long Endurance Uncrewed Aerial Systems

Most major global satellite surveyors of climate-relevant trace gases have relatively coarse spatial resolution or temporal sampling. While these data can be supplemented by fine-pointing satellites and aircraft, the spatial and temporal resolutions available from crewed aircraft is not sufficient to observe stochastic, ephemeral events that take place between observations. Emerging High Altitude Long Endurance (HALE) Uncrewed Aerial Systems (UAS) can operate for months at a time and loiter over targets to provide continuous daylight geostationary-like observations, allowing these new platforms to be integrated with existing satellites as part of a New Observing Strategy (NOS).To aid in the planning of future NOS missions, NASA is developing the Intelligent Long Endurance Observing System (ILEOS), a science activity planning system. ILEOS will help scientists build plans to improve spatio-temporal resolution of climate-relevant gases by fusing coarse-grained sensor data from satellites and other sources(e.g., terrain, forecasts), and plan HALE UAS flights to obtain finer-grain (high spatio-temporal) data. ILEOS will also enable observations for longer periods and of environments not accessible through in-situ observations and crewed aircraft field campaigns.

science planning pipeline↗

Rapid Response Landslide Detection Using ICEYE

Satellite synthetic aperture radar (SAR) data provides the best opportunity to quickly detect landslides for hazard response because SAR can image the ground regardless of weather or daylight conditions. The recent failure of the Sentinel-1B satellite has significantly reduced our ability to generate landslide maps in a timely manner across certain parts of the world leaving a gap in rapid response support. The ICEYE constellation may fill this gap because it can acquire repeat imagery over the same area every 24 hours and can be tasked to acquire data in specific areas. In addition, ICEYE acquires data with a higher spatial resolution, which is better suited for detecting smaller landslides. The high revisit time and high resolution of ICEYE significantly increases the capability to rapidly detect landslides and can provide key information to first responders. The main goal of this work was to test applicability/suitability of SAR imagery from ICEYE to generate rapid response landslide products.

Pukar Amatya↗

Ground-Based Microwave Measurements of ClO and O3 Over Scott Base, Antarctica

We present measurements from a new microwave instrument that has been deployed at Scott Base, Antarctica, primarily to measure ClO. The new instrument allows for the extension of the time series of lower stratospheric ClO measurements begun in 1996 at this site, while some of the technical improvements offer the possibility of making additional measurements. We show measurements of ClO and O 3 in both the upper and lower stratosphere near both the fall and spring equinox and document the diurnal variations of these measurements throughout the season. The ground-based measurements are compared with Aura Microwave Limb Sounder (MLS) measurements, which are available twice per day, and with a NASA Goddard 2D model (GSFC2D) simulation. We show that, in agreement with the GSFC2D model diurnal variations, upper stratospheric ClO mixing ratios gradually increase throughout the daylight hours, while in the lower stratospheric austral spring, when heterogeneous chemistry associated with polar stratospheric clouds occurs, daily maximum ClO mixing ratios of near 2 ppbv occur near noon. We also show measurements of stratospheric O 3 , primarily in the upper stratosphere, which, while exhibiting a low bias of ∼15%–20% relative to Aura MLS, show temporal variations in good agreement with MLS.

stratospheric ozone↗

Lifting the Garage Door on Spawn, An Open-Source BEM-Controls Engine

Spawn is the latest whole-building energy simulation engine developed by the US Department of Energy, National Labs and industry. Whereas EnergyPlus was designed as a successor to DOE-2, Spawn is not a direct successor of–nor is it intended as an imminent replacement for– EnergyPlus. Instead, Spawn reuses parts of EnergyPlus while supporting new use cases in HVAC and controls. Spawn is intended to provide several capabilities that significantly advance beyond EnergyPlus. It is intended to support the evaluation of novel HVAC and district energy systems in a more physically realistic way. Critically, it can model control in a physically realistic way, using portable specifications that can be compiled for execution on control platforms. Spawn is also intended to support co-simulation in an intrinsic way to enable integration with third-party models. This paper describes the software architecture of Spawn from model authoring to compilation and simulation. It explains how Spawn reuses the envelope and daylighting modules of EnergyPlus and couples them to HVAC and control models from the Modelica Buildings Library using the Functional Mockup Interface (FMI) standard. It presents a number of examples that: i) validate Spawn’s coupled simulation approach by comparing its results to those of EnergyPlus, ii) illustrate the Spawn methodology for modeling and simulating HVAC systems, and iii) evaluate the performance of Spawn’s Quantized State System (QSS) time integration algorithms

Wetter, Michael↗

A Python Library for Radiance Matrix-based Simulation Control and EnergyPlus Integration

Radiance matrix-based methods enable efficient parametric simulations, allowing users to vary sky conditions, fenestration systems, and other model parameters at a minimal cost to computation. However, the steep learning curve and complex workflow hinder the widespread adoption of matrix-based methods. The frads Python library with a series of command-line tools was developed to automate the entire matrix-based simulation process, lowering entry barriers and reducing human error. Co-simulation between EnergyPlus and Radiance was also enabled using the Python library from EnergyPlus. Key Innovations • Command-line based automation of Radiance matrix-based simulation methods • Python library facilitates broader adoption of Radiance matrix-based simulation methods • Radiance EnergyPlus run-time integration enabling the modeling of advanced control systems Practical Implications The frads library, with associated command-line tools, provides practitioners with the capability to easily adopt and use Radiance matrix-based simulation methods for various daylighting, solar control, and energy-related evaluations. Frads' current form is designed for 1) users familiar with a command-line interface and 2) software developers to integrate the matrix-based methods into existing software packages.

Wang, Taoning↗

Survey of Time Shift Detection Algorithms for Measured PV Data

In this research, three variations of time shift detection algorithms were tested for their ability to detect time shift issues (including daylight savings time and random time shifts) in measured PV data sets. Two algorithms from the Python PVAnalytics package were assessed, and one algorithm from the Solar-Data-Tools package was assessed. Each algorithm's ability to accurately detect and measure time shifts was assessed.

automated preprocessing↗

Summary of the the 11th Symposium of the International Society of Root Research

11th Symposium of the International Society of Root Research (ISRR11) and the 9th International Symposium on Root Development (Rooting2021) - Root Biology Never Sleeps virtual meeting May 24 - 28. These meetings are generally held in separate years. However, because of travel restrictions imposed by the COVID-19 pandemic, the organizing committees of both symposia decided to host the two meetings as a fully-joint and virtual-only conference. Various time zones were considered when developing the schedule, as live interactions was an important focus. Scientific sessions were held from 3 a.m. to 10 p.m. US Central Daylight Time (CDT) to meet the international demand. More than 700 participants from 52 countries virtually attend both events which featured 74 talks in 16 sessions including: 10 plenary lectures, 16 keynote speakers and 48 selected talks. Additionally, nearly 300 posters were presented in nine poster sessions. The meeting also featured an Ambassador Program with 21 ambassadors from 10 countries. These ambassadors organized a half-day pre-symposium workshop and produced a review of the meeting for “New Phytologist”. The meeting also awarded a Lifetime Award to Dr. Wendy Silk (Prof. Emerita University of California, Davis). Committee Members: • Bob Sharp (Chair) – University of Missouri • Felix Fritschi (Chair, Int’l Program Committee) – University of Missouri • David Braun – University of Missouri • Vicki Bryan – University of Missouri • Rich Ferrieri – University of Missouri • Laura Greeley – University of Missouri (postdoctoral representative) • Ali Housh – University of Missouri (graduate student representative) • Allison Miller – Donald Danforth Plant Science Center and St Louis University • Mel Oliver – University of Missouri • Jonathan Stemmle – University of Missouri • Gus Thies – University of Missouri & Donald Danforth Plant Science Center (graduate student representative) • Chris Topp - Donald Danforth Plant Science Center

Root Biology↗

Characterization of Coal Refuse Sites in West Virginia: Stream Loss, Volume Estimation, and Land Cover Analysis for Restoration Feasibility

Coal refuse disposal across Appalachia has resulted in widespread environmental degradation, including stream burial, landscape destabilization, and long-term hydrologic impacts. This study provides a GIS-based spatial characterization of 623 coal refuse sites in West Virginia, evaluating their potential for ecological and economic restoration. Stream loss was quantified through digitization of historic topographic maps, revealing over 194,500 meters of historically present streams lost, with 105,000 meters directly buried beneath refuse piles. Volume estimation using empirical Bayesian kriging and modern LiDAR surfaces indicated approximately 1.96 billion cubic meters of deposited refuse. Land cover analysis based on NAIP-derived classification showed that 48% of the total site area was forested, while 15% remained barren. These results highlight not only the environmental footprint of legacy refuse deposits but also their potential for restoration through stream daylighting and beneficial reuse. Emerging opportunities, including rare earth element recovery and mitigation banking, may offer economic incentives to facilitate reclamation. This work establishes a spatial framework to prioritize refuse sites for restoration, balancing ecological uplift with feasible material management strategies.

58 GEOSCIENCES↗