Highly Pertinent Algorithm for the Market of Business Intelligence, Context and Native Advertising

This article presents the study results of the business intelligence markets, the promote products on social media, and a new method for increasing the information pertinence in the scientific recommender systems, scientific information systems, analysis of the recommender systems that contain information about scientific publications, is represented. The prospects of using this method in the Business Intelligence systems, content management systems for native advertising systems to find content on the Internet and assessed the current state of the market such systems. Keywords: context and native advertising market, Business Intelligence market, highly pertinent algorithms, recommender systems JEL Classifications: A11, M30, M3

Applications of a Forward-Looking Interferometer for the On-board Detection of Aviation Weather Hazards

The Forward-Looking Interferometer (FLI) is a new instrument concept for obtaining measurements of potential weather hazards to alert flight crews. The FLI concept is based on high-resolution Infrared (IR) Fourier Transform Spectrometry (FTS) technologies that have been developed for satellite remote sensing, and which have also been applied to the detection of aerosols and gases for other purposes. It is being evaluated for multiple hazards including clear air turbulence (CAT), volcanic ash, wake vortices, low slant range visibility, dry wind shear, and icing, during all phases of flight. Previous sensitivity and characterization studies addressed the phenomenology that supports detection and mitigation by the FLI. Techniques for determining the range, and hence warning time, were demonstrated for several of the hazards, and a table of research instrument parameters was developed for investigating all of the hazards discussed above. This work supports the feasibility of detecting multiple hazards with an FLI multi-hazard airborne sensor, and for producing enhanced IR images in reduced visibility conditions; however, further research must be performed to develop a means to estimate the intensities of the hazards posed to an aircraft and to develop robust algorithms to relate sensor measurables to hazard levels. In addition, validation tests need to be performed with a prototype system

Airborne Forward-Looking Interferometer for the Detection of Terminal-Area Hazards

The Forward Looking Interferometer (FLI) program was a multi-year cooperative research effort to investigate the use of imaging radiometers with high spectral resolution, using both modeling/simulation and field experiments, along with sophisticated data analysis techniques that were originally developed for analysis of data from space-based radiometers and hyperspectral imagers. This investigation has advanced the state of knowledge in this technical area, and the FLI program developed a greatly improved understanding of the radiometric signal strength of aviation hazards in a wide range of scenarios, in addition to a much better understanding of the real-world functionality requirements for hazard detection instruments. The project conducted field experiments on three hazards (turbulence, runway conditions, and wake vortices) and analytical studies on several others including volcanic ash, reduced visibility conditions, in flight icing conditions, and volcanic ash

Experimental Validation of a Forward Looking Interferometer for Detection of Clear Air Turbulence due to Mountain Waves

The Forward-Looking Interferometer (FLI) is an airborne sensor concept for detection and estimation of potential atmospheric hazards to aircraft. The FLI concept is based on high-resolution Infrared Fourier Transform Spectrometry technologies that have been developed for satellite remote sensing. The FLI is being evaluated for its potential to address multiple hazards, during all phases of flight, including clear air turbulence, volcanic ash, wake vortices, low slant range visibility, dry wind shear, and icing. In addition, the FLI is being evaluated for its potential to detect hazardous runway conditions during landing, such as wet or icy asphalt or concrete. The validation of model-based instrument and hazard simulation results is accomplished by comparing predicted performance against empirical data. In the mountain lee wave data collected in the previous FLI project, the data showed a damped, periodic mountain wave structure. The wave data itself will be of use in forecast and nowcast turbulence products such as the Graphical Turbulence Guidance and Graphical Turbulence Guidance Nowcast products. Determining how turbulence hazard estimates can be derived from FLI measurements will require further investigation

Hazard Detection Analysis for a Forward-Looking Interferometer

The Forward-Looking Interferometer (FLI) is a new instrument concept for obtaining the measurements required to alert flight crews to potential weather hazards to safe flight. To meet the needs of the commercial fleet, such a sensor should address multiple hazards to warrant the costs of development, certification, installation, training, and maintenance. The FLI concept is based on high-resolution Infrared Fourier Transform Spectrometry (FTS) technologies that have been developed for satellite remote sensing. These technologies have also been applied to the detection of aerosols and gases for other purposes. The FLI concept is being evaluated for its potential to address multiple hazards including clear air turbulence (CAT), volcanic ash, wake vortices, low slant range visibility, dry wind shear, and icing during all phases of flight (takeoff, cruise, and landing). The research accomplished in this second phase of the FLI project was in three major areas: further sensitivity studies to better understand the potential capabilities and requirements for an airborne FLI instrument, field measurements that were conducted in an effort to provide empirical demonstrations of radiometric hazard detection, and theoretical work to support the development of algorithms to determine the severity of detected hazard

Processing and Validation of the STAR COSMIC-2 Temperature and Water Vapor Profiles in the Neutral Atmosphere

The global navigation satellite system (GNSS) radio occultation (RO) is becoming an essential component of National Oceanic and Atmospheric Administration (NOAA) observation systems. The constellation observing system for meteorology, ionosphere, and climate (COSMIC) 2 mission and the Formosa satellite mission 7, a COSMIC follow-on mission, is now the NOAA’s backbone RO mission. The NOAA’s dedicated GNSS RO SAtellite processing and science Application Center (RO-SAAC) was established at the Center for Satellite Applications and Research (STAR). To better quantify how the observation uncertainty from clock error and geometry determination may propagate to bending angle and refractivity profiles, STAR has developed the GNSS RO data processing and validation system. This study describes the COSMIC-2 neutral atmospheric temperature and moisture profile inversion algorithms at STAR. We used RS41 and ERA5, and UCAR 1D-Var products (wetPrf2) to validate the accuracy and uncertainty of the STAR 1D-Var thermal profiles. The STAR-RS41 temperature differences are less than a few tenths of 1 K from 8 km to 30 km altitude with a standard deviation (std) of 1.5–2 K. The mean STAR-RS41 water vapor specific humidity difference and the standard deviation are −0.35 g/kg and 1.2 g/kg, respectively. We also used the 1D-Var-derived temperature and water vapor profiles to compute the simulated brightness temperature (BTs) for advanced technology microwave sounder (ATMS) and cross-track infrared sounder (CrIS) channels and compared them to the collocated ATMS and CrIS measurements. The BT differences of STAR COSMIC-2-simulated BTs relative to SNPP ATMS are less than 0.1 K over all ATMS channels

Processing and Validation of the STAR COSMIC-2 Temperature and Water Vapor Profiles in the Neutral Atmosphere

The global navigation satellite system (GNSS) radio occultation (RO) is becoming an essential component of National Oceanic and Atmospheric Administration (NOAA) observation systems. The constellation observing system for meteorology, ionosphere, and climate (COSMIC) 2 mission and the Formosa satellite mission 7, a COSMIC follow-on mission, is now the NOAA’s backbone RO mission. The NOAA’s dedicated GNSS RO SAtellite processing and science Application Center (RO-SAAC) was established at the Center for Satellite Applications and Research (STAR). To better quantify how the observation uncertainty from clock error and geometry determination may propagate to bending angle and refractivity profiles, STAR has developed the GNSS RO data processing and validation system. This study describes the COSMIC-2 neutral atmospheric temperature and moisture profile inversion algorithms at STAR. We used RS41 and ERA5, and UCAR 1D-Var products (wetPrf2) to validate the accuracy and uncertainty of the STAR 1D-Var thermal profiles. The STAR-RS41 temperature differences are less than a few tenths of 1 K from 8 km to 30 km altitude with a standard deviation (std) of 1.5–2 K. The mean STAR-RS41 water vapor specific humidity difference and the standard deviation are −0.35 g/kg and 1.2 g/kg, respectively. We also used the 1D-Var-derived temperature and water vapor profiles to compute the simulated brightness temperature (BTs) for advanced technology microwave sounder (ATMS) and cross-track infrared sounder (CrIS) channels and compared them to the collocated ATMS and CrIS measurements. The BT differences of STAR COSMIC-2-simulated BTs relative to SNPP ATMS are less than 0.1 K over all ATMS channels

Metop-C AMSU-A and AVHRR Sensor Data Recorder (SDR) Data Calibration/Validation (CalVal): Status & Prospective

European Meteorological Operational satellite program (Metop)-C was successfully launched into low Earth orbit at 00:47 UTC on November 7, 2018. METOP-C is the third and final spacecraft of the Metop. The Metop-C satellite carries a variety of instruments including three NOAA sensors: Advanced Microwave Sounding Unit-A (AMSU-A), Advanced Very High Resolution Radiometer (AVHRR), and the Space Environment Monitor (SEM). Both of AMSU-A and AVHRR will improve daily weather forecasts while continuing to monitor long-term changes in Earth’s climate. SEM provides measurements to determine the intensity of the Earth’s radiation belts and the flux of charged particles at satellite altitude. On November 12, 2018, the AVHRR onboard the METOP-C became the first instrument to acquire and disseminate its visible (0.64 µm) and near infrared (0.86 µm and 1.61 µm) data. Nine days after METOP-C was launched, the first day AMSU-A science data was received on November 15, 2018. The Center for Satellite Applications and Research (STAR) in NOAA A is leading a series of calibration and validations (CalVal) activities about AMSU-A and AVHRR Sensor Data Record (SDR) data. The Metop-C AMSU-A and AVHRR SDR CalVals have successfully reached to their beta maturity review on 15 February 2019. A briefing will be presented about status and prospective of Metop-C AMSU-A and AVHRR CalVal. In particular, we will introduce AMSU-A instrument noise performance, Lunar intrusion correction, antenna pattern correction, SDR data quality assessment for AMSU-A by using the JCSDA Community Radiative Model (CRTM), intersensor comparison and double difference methods. We will brief IR Noise Equivalent delta-Temperature (NEdT), Solar channels calibration and other CalVal results for AVHRR instrument and SDR data. Additionally, we will brief the STAR Integrated Calibration and Validation (ICVS) to provide near-real time monitoring for both AMSU-A and AVHRR instrument performance and SDR data quality

Validation Assessment Model for Atmospheric Retrievals

A linear mathematical error model for the assessment of validation activity of atmospheric retrievals is presented. The purpose of the validation activity is to assess the actual performance of the remote sensing validated system while in orbit by comparing its measurements to some relevant—validating—data sets. The validating system samples volumes of the atmosphere at times and locations that are different from the ones when and where the validated system makes its own observations. The location of the validating system can be either stationary, e.g. a ground ARM site, or movable, e.g. an aircraft or some other satellites. The true states may be correlated or not. The sampled volumes differ from each other by their location, timing, and size. The validated and validating systems have different vertical resolution and grid, absolute accuracy, and noise level. All the above factors cause apparent differences between the data to be compared. The validation assessment model makes the comparison accurate by allowing for the differences. The model can be used for assessment and interpretation of the validation results when the above mentioned sources of discrepancies are significant, as well as for evaluation of a particular validating data source

Initial Assessment of the COSMIC-2/FORMOSAT-7 Neutral Atmosphere Data Quality in NESDIS/STAR Using In Situ and Satellite Data

A COSMIC-1/FORMOSAT-3 (Constellation Observing System for Meteorology, Ionosphere, and Climate-1 and Formosa Satellite Mission 3) follow-on mission, COSMIC-2/FORMOSAT-7, had been successfully launched into low-inclination orbits on 25 June 2019. COSMIC-2 has a significantly increased Signal-to-Noise ratio (SNR) compared to other Radio Occultation (RO) missions. This study summarized the initial assessment of COSMIC-2 data quality conducted by the NOAA (National Oceanic and Atmospheric Administration) Center for Satellite Applications and Research (STAR). We use validated data from other RO missions to quantify the stability of COSMIC-2. In addition, we use the Vaisala RS41 radiosonde observations to assess the accuracy and uncertainty of the COSMIC-2 neutral atmospheric profiles. RS41 is currently the most accurate radiosonde observation system. The COSMIC-2 SNR ranges from 200 v/v to about 2800 v/v. To see if the high SNR COSMIC-2 signals lead to better retrieval results, we separate the COSMIC-2–RS41 comparisons into different SNR groups (i.e., 0–500 v/v group, 500–1000 v/v group, 1000–1500 v/v group, 1500–2000 v/v group, and >2000 v/v group). In general, the COSMIC-2 data quality in terms of stability, precision, accuracy, and uncertainty of the accuracy is very compatible with those from COSMIC-1. Results show that the mean COSMIC-2–RS41 water vapor difference from surface to 5 km altitude for each SNR groups are equal to −1.34 g/kg (0–500 v/v), −1.17 g/kg (500–1000 v/v), −1.33 g/kg (1000–1500 v/v), −0.93 g/kg (1500–2000 v/v), and −1.52 g/kg (>2000 v/v). Except for the >2000 v/v group, the high SNR measurements from COSMIC-2 seem to improve the mean water vapor difference for the higher SNR group slightly (especially for the 1500–2000 v/v group) comparing with those from lower SNR groups