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At least 325 records · Page 18

Online Visualization and Analysis of Merged Global Geostationary Satellite Infrared Dataset

The NASA Goddard Earth Sciences Data Information Services Center (GES DISC) is home of Tropical Rainfall Measuring Mission (TRMM) data archive. The global merged IR product also known as the NCEP/CPC 4-km Global (60 degrees N - 60 degrees S) IR Dataset, is one of TRMM ancillary datasets. They are globally merged (60 degrees N - 60 degrees S) pixel-resolution (4 km) IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 and GMS). The availability of data from METEOSAT-5, which is located at 63E at the present time, yields a unique opportunity for total global (60 degrees N- 60 degrees S) coverage. The GES DISC has collected over 8 years of the data beginning from February of 2000. This high temporal resolution dataset can not only provide additional background information to TRMM and other satellite missions, but also allow observing a wide range of meteorological phenomena from space, such as, mesoscale convection systems, tropical cyclones, hurricanes, etc. The dataset can also be used to verify model simulations. Despite that the data can be downloaded via ftp, however, its large volume poses a challenge for many users. A single file occupies about 70 MB disk space and there is a total of approximately 73,000 files (approximately 4.5 TB) for the past 8 years. In order to facilitate data access, we have developed a web prototype to allow users to conduct online visualization and analysis of this dataset. With a web browser and few mouse clicks, users can have a full access to over 8 year and over 4.5 TB data and generate black and white IR imagery and animation without downloading any software and data. In short, you can make your own images! Basic functions include selection of area of interest, single imagery or animation, a time skip capability for different temporal resolution and image size. Users can save an animation as a file (animated gif) and import it in other presentation software, such as, Microsoft PowerPoint. The prototype will be integrated into GIOVANNI and existing GIOVANNI capabilities, such as, data download, Google Earth KMZ, etc will be available. Users will also be able to access other data products in the GIOVANNI family.

Liu, Zhong↗

Will We Soon Have a Geostationary Microwave Sounder and What Can We Do with It?

This slide presentation reviews the Geostationary Microwave Sounder (GEO/MW). GEO/MW applications include weather forecasting, hurricane diagnostics, rain, tropospheric wind profiling, and climate research. The presentation also includes information on prototype development, system tests, the notational PATH mission, and data products.

hurricanes↗

Geostationary Coastal Ecosystem Dynamics Imager (GEO CEDI) for the GEO Coastal and Air Pollution Events (GEO CAPE) Mission. Concept Presentation

This slide presentation reviews the concepts of the Geostationary Coastal Ecosystem Dynamics Imager (GEO CEDI) which will be used on the GEO Coastal and Air Pollution Events (GEO CAPE) Mission. The primary science requirements require scans of the U.S. Coastal waters 3 times per day during the daylight hours. Included in the overview are presentations about the systems, the optics, the detectors, the mechanical systems, the electromechanical systems, the electrical design, the flight software, the thermal systems, and the contamination prevention requirements.

Janz, Scott↗

Radar for Monitoring Hurricanes from Geostationary Orbit

A document describes a scanning Doppler radar system to be placed in a geostationary orbit for monitoring the three-dimensional structures of hurricanes, cyclones, and severe storms in general. The system would operate at a frequency of 35 GHz. It would include a large deployable spherical antenna reflector, instead of conventional paraboloidal reflectors, that would allow the reflector to remain stationary while moving the antenna feed(s), and thus, create a set of scanning antenna beams without degradation of performance. The radar would have separate transmitting and receiving antenna feeds moving in spiral scans over an angular excursion of 4 from the boresight axis to providing one radar image per hour of a circular surface area of 5,300-km diameter. The system would utilize a real-time pulse-compression technique to obtain 300-m vertical resolution without sacrificing detection sensitivity and without need for a high-peakpower transmitter. An onboard data-processing subsystem would generate three-dimensional rainfall reflectivity and Doppler observations with 13-km horizontal resolution and line-of-sight Doppler velocity at a precision of 0.3 m/s.

Im, Eastwood↗

Global Assessment of Land Surface Temperature From Geostationary Satellites and Model Estimates

Land surface (or 'skin') temperature (LST) lies at the heart of the surface energy balance and is a key variable in weather and climate models. In this research we compare two global and independent data sets: (i) LST retrievals from five geostationary satellites generated at the NASA Langley Research Center (LaRC) and (ii) LST estimates from the quasi-operational NASA GEOS-5 global modeling and assimilation system. The objective is to thoroughly understand both data sets and their systematic differences in preparation for the assimilation of the LaRC LST retrievals into GEOS-5. As expected, mean differences (MD) and root-mean-square differences (RMSD) between modeled and retrieved LST vary tremendously by region and time of day. Typical (absolute) MD values range from 1-3 K in Northern Hemisphere mid-latitude regions to near 10 K in regions where modeled clouds are unrealistic, for example in north-eastern Argentina, Uruguay, Paraguay, and southern Brazil. Typically, model estimates of LST are higher than satellite retrievals during the night and lower during the day. RMSD values range from 1-3 K during the night to 2-5 K during the day, but are larger over the 50-120 W longitude band where the LST retrievals are derived from the FY2E platform

Reichle, Rolf H.↗

Crew Transfer Options for Servicing of Geostationary Satellites

In 2011, NASA and DARPA undertook a study to examine capabilities and system architecture options which could be used to provide manned servicing of satellites in Geostationary Earth Orbit (GEO). The study focused on understanding the generic nature of the problem and examining technology requirements, it was not for the purpose of proposing or justifying particular solutions. A portion of this study focused on assessing possible capabilities to efficiently transfer crew between Earth, Low Earth Orbit (LEO), and GEO satellite servicing locations. This report summarizes the crew transfer aspects of manned GEO satellite servicing. Direct placement of crew via capsule vehicles was compared to concepts of operation which divided crew transfer into multiple legs, first between earth and LEO and second between LEO and GEO. In space maneuvering via purely propulsive means was compared to in-space maneuvering which utilized aerobraking maneuvers for return to LEO from GEO. LEO waypoint locations such as equatorial, Kennedy Space Center, and International Space Station inclinations were compared. A discussion of operational concepts is followed by a discussion of appropriate areas for technology development.

Cerro, Jeffrey A.↗

Lightning Jump Algorithm Development for the GOES·R Geostationary Lightning Mapper

Current work on the lightning jump algorithm to be used in GOES‐R Geostationary Lightning Mapper (GLM)'s data stream is multifaceted due to the intricate interplay between the storm tracking, GLM proxy data, and the performance of the lightning jump itself. This work outlines the progress of the last year, where analysis and performance of the lightning jump algorithm with automated storm tracking and GLM proxy data were assessed using over 700 storms from North Alabama. The cases analyzed coincide with previous semi‐objective work performed using total lightning mapping array (LMA) measurements in Schultz et al. (2011). Analysis shows that key components of the algorithm (flash rate and sigma thresholds) have the greatest influence on the performance of the algorithm when validating using severe storm reports. Automated objective analysis using the GLM proxy data has shown probability of detection (POD) values around 60% with false alarm rates (FAR) around 73% using similar methodology to Schultz et al. (2011). However, when applying verification methods similar to those employed by the National Weather Service, POD values increase slightly (69%) and FAR values decrease (63%). The relationship between storm tracking and lightning jump has also been tested in a real‐time framework at NSSL. This system includes fully automated tracking by radar alone, real‐time LMA and radar observations and the lightning jump. Results indicate that the POD is strong at 65%. However, the FAR is significantly higher than in Schultz et al. (2011) (50‐80% depending on various tracking/lightning jump parameters) when using storm reports for verification. Given known issues with Storm Data, the performance of the real‐time jump algorithm is also being tested with high density radar and surface observations from the NSSL Severe Hazards Analysis & Verification Experiment (SHAVE).

Schultz. E.↗

The GOES-R Geostationary Lightning Mapper (GLM) and the Global Observing System for Total Lightning

for the existing GOES system currently operating over the Western Hemisphere. New and improved instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved temporal, spatial, and spectral resolution for the next generation Advanced Baseline Imager (ABI). The GLM will map total lightning continuously day and night with near-uniform spatial resolution of 8 km with a product latency of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. The GLM will help address the National Weather Service requirement for total lightning observations globally to support warning decision-making and forecast services. Science and application development along with pre-operational product demonstrations and evaluations at NWS national centers, forecast offices, and NOAA testbeds will prepare the forecasters to use GLM as soon as possible after the planned launch and check-out of GOES-R in 2016. New applications will use GLM alone, in combination with the ABI, or integrated (fused) with other available tools (weather radar and ground strike networks, nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing more timely and accurate forecasts and warnings.

Goodman, Steven J.↗

Spacecraft Charging in Geostationary Transfer Orbit

The 700 km x 5.8 Re orbit of the two Van Allen Probes spacecraft provide a unique opportunity to investigate spacecraft charging in geostationary transfer orbits. We use records from the Helium Oxygen Proton Electron (HOPE) plasma spectrometer to identify candidate surface charging events based on the "ion line" charging signature in the ion records. We summarize the energetic particle environment and the conditions necessary for charging to occur in this environment. We discuss the altitude, duration, and magnitude of events observed in the Van Allen Probes from the beginning of the mission to present time. In addition, we explore what information the dual satellites provide on the spatial and temporal variations in the charging environments.

Parker, Linda Neergaard↗

Geostationary Microwave Sounders: Science, Applications and the Geostar Instrument Concept

Microwave atmospheric sounders have long provided some of the most imporant data for use in numerical weather prediction (NWP) and have played an important role in atmospheric weather and climate research. With 7 US satellites now carrying such sensors, we are in a 'golden age' of microwave remote sensing of the atmosphere. However, as this fleet ages and is replaced by a smaller number of new sensors in the coming yars, the main shortcoming of sensors in low Earth orbit -i.e. poor spacial and temporal converage and sampling - will become more apparent. Placing such sensors on geostationary satellites, enabling time-continuous views of large portions of the Earth disc, would solve this problem. but the GEO orbit is approximately 40 times higher than a typical LEO orbit, which requires antenna apertures also about 40 times larger than for LEO systems to maintain spatial resolution, and it has not been feasible to develop such systems. Recently, a solution to this problem has appeared in the form of aperture synthesis.

numerical weather prediction (NWP)↗

A Panchromatic Imaging Fourier Transform Spectrometer for the NASA Geostationary Coastal and Air Pollution Events Mission

This paper summarizes the design and development of the Panchromatic Imaging Fourier Transform Spectrometer (PanFTS) for the NASA Geostationary Coastal and Air Pollution Events (GEO-CAPE) Mission. The PanFTS instrument will advance the understanding of the global climate and atmospheric chemistry by measuring spectrally resolved outgoing thermal and reflected solar radiation. With continuous spectral coverage from the near-ultraviolet through the thermal infrared, this instrument is designed to measure pollutants, greenhouse gases, and aerosols as called for by the U.S. National Research Council Decadal Survey; Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond1. The PanFTS instrument is a hybrid instrument based on spectrometers like the Tropospheric Emissions Spectrometer (TES) that measures thermal emission, and those like the Orbiting Carbon Observatory (OCO), and the Ozone Monitoring Instrument (OMI) that measure scattered solar radiation. Simultaneous measurements over the broad spectral range from IR to UV is accomplished by a two sided interferometer with separate optical trains and detectors for the ultraviolet-visible and infrared spectral domains. This allows each side of the instrument to be independently optimized for its respective spectral domain. The overall interferometer design is compact because the two sides share a single high precision cryogenic optical path difference mechanism (OPDM) and metrology laser as well as a number of other instrument systems including the line-of-sight pointing mirror, the data management system, thermal control system, electrical system, and the mechanical structure. The PanFTS breadboard instrument has been tested in the laboratory and demonstrated the basic functionality for simultaneous measurements in the visible and infrared. It is set to begin operations in the field at the California Laboratory for Atmospheric Remote Sensing (CLARS) observatory on Mt. Wilson measuring the atmospheric chemistry across the Los Angeles basin. Development has begun on a flight size PanFTS engineering model (EM) that addresses all critical scaling issues and demonstrates operation over the full spectral range of the flight instrument which will show the PanFTS instrument design is mature.

Imaging spectrometer(↗

Prospects for Geostationary Doppler Weather Radar

A novel mission concept, namely NEXRAD in Space (NIS), was developed for detailed monitoring of hurricanes, cyclones, and severe storms from a geostationary orbit. This mission concept requires a space deployable 35-m diameter reflector that operates at 35-GHz with a surface figure accuracy requirement of 0.21 mm RMS. This reflector is well beyond the current state-of-the-art. To implement this mission concept, several potential technologies associated with large, lightweight, spaceborne reflectors have been investigated by this study. These spaceborne reflector technologies include mesh reflector technology, inflatable membrane reflector technology and Shape Memory Polymer reflector technology.

Precipitation Radar↗

Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation↗

Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Registration↗

Validation of Cloud Parameters Derived from Geostationary Satellites, AVHRR, MODIS, and VIIRS Using SatCORPS Algorithms

Validation is a key component of remote sensing that can take many different forms. The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) is applied to many different imager datasets including those from the geostationary satellites, Meteosat, Himiwari-8, INSAT-3D, GOES, and MTSAT, as well as from the low-Earth orbiting satellite imagers, MODIS, AVHRR, and VIIRS. While each of these imagers have similar sets of channels with wavelengths near 0.65, 3.7, 11, and 12 micrometers, many differences among them can lead to discrepancies in the retrievals. These differences include spatial resolution, spectral response functions, viewing conditions, and calibrations, among others. Even when analyzed with nearly identical algorithms, it is necessary, because of those discrepancies, to validate the results from each imager separately in order to assess the uncertainties in the individual parameters. This paper presents comparisons of various SatCORPS-retrieved cloud parameters with independent measurements and retrievals from a variety of instruments. These include surface and space-based lidar and radar data from CALIPSO and CloudSat, respectively, to assess the cloud fraction, height, base, optical depth, and ice water path; satellite and surface microwave radiometers to evaluate cloud liquid water path; surface-based radiometers to evaluate optical depth and effective particle size; and airborne in-situ data to evaluate ice water content, effective particle size, and other parameters. The results of comparisons are compared and contrasted and the factors influencing the differences are discussed.

Minnis, P.↗

Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system's performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system's performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.

lightning jump↗

The Intercalibration of Geostationary Visible Imagers Using Operational Hyperspectral SCIAMACHY Radiances

Spectral band differences between sensors can complicate the process of intercalibration of a visible sensor against a reference sensor. This can be best addressed by using a hyperspectral reference sensor whenever possible because they can be used to accurately mitigate the band differences. This paper demonstrates the feasibility of using operational Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) large-footprint hyperspectral radiances to calibrate geostationary Earth-observing (GEO) sensors. Near simultaneous nadir overpass measurements were used to compare the temporal calibration of SCIAMACHY with Aqua Moderate Resolution Imaging Spectroradiometer band radiances, which were found to be consistent to within 0.44% over seven years. An operational SCIAMACHY/GEO ray-matching technique was presented, along with enhancements to improve radiance pair sampling. These enhancements did not bias the underlying intercalibration and provided enough sampling to allow up to monthly monitoring of the GEO sensor degradation. The results of the SCIAMACHY/GEO intercalibration were compared with other operational four-year Meteosat-9 0.65-μm calibration coefficients and were found to be within 1% of the gain, and more importantly, it had one of the lowest temporal standard errors of all the methods. This is more than likely that the GEO spectral response function could be directly applied to the SCIAMACHY radiances, whereas the other operational methods inferred a spectral correction factor. This method allows the validation of the spectral corrections required by other methods.

Doelling, David R.↗