Numerical analysis concepts for balloon analysis

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77240/1/AIAA-1994-511-453.pd

Generating Accurate and Consistent Top-Of-Atmosphere Reflectance Products from the New Generation Geostationary Satellite Sensors

GeoNEX is a collaborative project by scientists from NASA, NOAA, JAXA, and other organizations around the world with the purpose of generating a suite of Earth-monitoring products using data streams from the latest geostationary (GEO) sensors including the GOES-16/17 ABI and the Himawari-8/9 AHI. An accurate and consistent top-of-atmosphere (TOA) reflectance product, in particular the bidirectional reflectance factor (BRF), is the starting point in the scientific processing chain. We describe the main considerations and corresponding algorithms in generating the GeoNEX TOA BRF product. First, a special advantage of geostationary data streams is their high temporal resolution (~10 minutes per full-disk scan), providing a key source of information for many downstream products. To fully utilize this high temporal frequency demands a high georegistration accuracy for every acquired image. Our analysis shows that there can be substantial georegistration uncertainties in both GOES and Himawari L1b data which we addressed by implementing a phase-based correction algorithm to remove residual errors. Second, geostationary sensors have distinct illumination-view geometry features in that the solar angle changes for every pixel. Therefore, to accurately derive a BRF requires a solar position algorithm and the estimation of the pixel-wise acquisition time within an uncertainty of 10 seconds. Third, we discuss the measures we adopted to check and correct residual radiometric calibration issues of individual sensors to enable time-series analysis as well as the cross calibration between different satellite sensors (including those from low-Earth orbit). Finally, we also explain the rationale for the choice of the global grid/tile system of the GeoNEX TOA BRF product

Acoustic vibration model for a composite shell with sound absorption material

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/76741/1/AIAA-1996-1348-145.pd

GeoNEX: A Cloud Gateway for Near Real-time Processing of Geostationary Satellite Products

The emergence of a new generation of geostationary satellite sensors provides land andatmosphere monitoring capabilities similar to MODIS and VIIRS with far greater temporal resolution (5-15 minutes). However, processing such large volume, highly dynamic datasets requires computing capabilities that (1) better support data access and knowledge discovery for scientists; (2) provide resources to enable real-time processing for emergency response (wildfire, smoke, dust, etc.); and (3) provide reliable and scalable services for the broader user community. This paper presents an implementation of GeoNEX (Geostationary NASA-NOAA Earth Exchange) services that integrate scientific algorithms with Amazon Web Services (AWS) to provide near realtime monitoring (~5 minute latency) capability in a hybrid cloud-computing environment. It offers a user-friendly, manageable and extendable interface and benefits from the scalability provided by Amazon Web Services. Four use cases are presented to illustrate how to (1) search and access geostationary data; (2) configure computing infrastructure to enable near real-time processing; (3) disseminate and utilize research results, visualizations, and animations to concurrent users; and (4) use a Jupyter Notebook-like interface for data exploration and rapid prototyping. As an example of (3), the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) was implemented on GOES-16 and -17 data to produce an active fire map every 5 minutes over the conterminous US. Details of the implementation strategies, architectures, and challenges of the use cases are discussed

Planning a large‐scale tabletop exercise to test Qatar's healthcare system readiness to respond to a major incident during the 2022 FIFA World Cup

© 2023 The Authors, This is an open access article distributed under the Creative Commons Attribution License (CC BY), to view a copy of the license, see: https://creativecommons.org/licenses/by/4.0/This article is an illustration of ‘Lessons from the Field’. The Journal of Contingencies and Crisis Management has begun to present lessons coming from professionals engaged in crisis management. ‘Lessons for the Field’ provides insights that can be useful to other professionals. Moreover, ‘Lessons from the Field’ can stimulate ideas for researchers and provide resources for educators. Hosting a mega‐sporting event such as the International Federation of Football Associations (FIFA) World Cup presents many healthcare challenges, especially when organized over a small geographical area with many international supporters potentially increasing the country's normal population by 50%. This article presents how a system‐wide tabletop simulation exercise was planned to test Qatar's healthcare system's readiness to respond to a potential major incident during the FIFA World Cup. The healthcare system‐wide tabletop exercise lasted about 4 h with participants engaging in all the various facilities as expected. It provided opportunities for everyone to put their knowledge of major incident response and mass casualty management into practice. The exercise preparation ensured it ran smoothly for all participants who quickly understood how to engage in the activity. It enabled organizers and participants to identify potential gaps in systems and processes, but also in their own ability to manage such situation.Peer reviewe

Active control of aircraft engine inlet noise using compact sound sources and distributed error sensors

An active noise control system using a compact sound source is effective to reduce aircraft engine duct noise. The fan noise from a turbofan engine is controlled using an adaptive filtered-x LMS algorithm. Single multi channel control systems are used to control the fan blade passage frequency (BPF) tone and the BPF tone and the first harmonic of the BPF tone for a plane wave excitation. A multi channel control system is used to control any spinning mode. The multi channel control system to control both fan tones and a high pressure compressor BPF tone simultaneously. In order to make active control of turbofan inlet noise a viable technology, a compact sound source is employed to generate the control field. This control field sound source consists of an array of identical thin, cylindrically curved panels with an inner radius of curvature corresponding to that of the engine inlet. These panels are flush mounted inside the inlet duct and sealed on all edges to prevent leakage around the panel and to minimize the aerodynamic losses created by the addition of the panels. Each panel is driven by one or more piezoelectric force transducers mounted on the surface of the panel. The response of the panel to excitation is maximized when it is driven at its resonance; therefore, the panel is designed such that its fundamental frequency is near the tone to be canceled, typically 2000-4000 Hz

Active control of aircraft engine inlet noise using compact sound sources and distributed error sensors

An active noise control system using a compact sound source is effective to reduce aircraft engine duct noise. The fan noise from a turbofan engine is controlled using an adaptive filtered-x LMS algorithm. Single multi channel control systems are used to control the fan blade passage frequency (BPF) tone and the BPF tone and the first harmonic of the BPF tone for a plane wave excitation. A multi channel control system is used to control any spinning mode. The multi channel control system to control both fan tones and a high pressure compressor BPF tone simultaneously. In order to make active control of turbofan inlet noise a viable technology, a compact sound source is employed to generate the control field. This control field sound source consists of an array of identical thin, cylindrically curved panels with an inner radius of curvature corresponding to that of the engine inlet. These panels are flush mounted inside the inlet duct and sealed on all edges to prevent leakage around the panel and to minimize the aerodynamic losses created by the addition of the panels. Each panel is driven by one or more piezoelectric force transducers mounted on the surface of the panel. The response of the panel to excitation is maximized when it is driven at its resonance; therefore, the panel is designed such that its fundamental frequency is near the tone to be canceled, typically 2000-4000 Hz

Spliced Leader RNAs, Mitochondrial Gene Frameshifts and Multi-Protein Phylogeny Expand Support for the Genus Perkinsus as a Unique Group of Alveolates

The genus Perkinsus occupies a precarious phylogenetic position. To gain a better understanding of the relationship between perkinsids, dinoflagellates and other alveolates, we analyzed the nuclear-encoded spliced-leader (SL) RNA and mitochondrial genes, intron prevalence, and multi-protein phylogenies. In contrast to the canonical 22-nt SL found in dinoflagellates (DinoSL), P. marinus has a shorter (21-nt) and a longer (22-nt) SL with slightly different sequences than DinoSL. The major SL RNA transcripts range in size between 80–83 nt in P. marinus, and ∼83 nt in P. chesapeaki, significantly larger than the typical ≤56-nt dinoflagellate SL RNA. In most of the phylogenetic trees based on 41 predicted protein sequences, P. marinus branched at the base of the dinoflagellate clade that included the ancient taxa Oxyrrhis and Amoebophrya, sister to the clade of apicomplexans, and in some cases clustered with apicomplexans as a sister to the dinoflagellate clade. Of 104 Perkinsus spp. genes examined 69.2% had introns, a higher intron prevalence than in dinoflagellates. Examination of Perkinsus spp. mitochondrial cytochrome B and cytochrome C oxidase subunit I genes and their cDNAs revealed no mRNA editing, but these transcripts can only be translated when frameshifts are introduced at every AGG and CCC codon as if AGGY codes for glycine and CCCCU for proline. These results, along with the presence of the numerous uncharacterized ‘marine alveolate group I' and Perkinsus-like lineages separating perkinsids from core dinoflagellates, expand support for the affiliation of the genus Perkinsus with an independent lineage (Perkinsozoa) positioned between the phyla of Apicomplexa and Dinoflagellata

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km by 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future