Evaluation of precipitation estimates over CONUS derived from satellite, radar, and rain gauge data sets at daily to annual scales (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2015-04-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, and surface observations to derive precipitation characteristics over the contiguous United States (CONUS) for the period 2002-2012. This comparison effort includes satellite multi-sensor data sets (bias-adjusted TMPA 3B42, near-real-time 3B42RT), radar estimates (NCEP Stage IV), and rain gauge observations. Remotely sensed precipitation data sets are compared with surface observations from the Global Historical Climatology Network-Daily (GHCN-D) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model). The comparisons are performed at the annual, seasonal, and daily scales over the River Forecast Centers (RFCs) for CONUS. Annual average rain rates present a satisfying agreement with GHCN-D for all products over CONUS (±6%). However, differences at the RFC are more important in particular for near-real-time 3B42RT precipitation estimates (-33 to +49%). At annual and seasonal scales, the bias-adjusted 3B42 presented important improvement when compared to its near-real-time counterpart 3B42RT. However, large biases remained for 3B42 over the western USA for higher average accumulation (≥ 5 mm day-1) with respect to GHCN-D surface observations. At the daily scale, 3B42RT performed poorly in capturing extreme daily precipitation (> 4 in. day-1) over the Pacific Northwest. Furthermore, the conditional analysis and a contingency analysis conducted illustrated the challenge in retrieving extreme precipitation from remote sensing estimates.

Observing the Earth from Afar with NASA's Worldview

NASA Technical Reports Server (NTRS)

Wong, Min Minnie; Boller, Ryan; Baynes, Kathleen; King, Benjamin; Rice, Zachary

2017-01-01

NASA's Worldview interactive web map application delivers global, near real-time imagery from NASA's fleet of Earth Observing System (EOS) satellites. Within hours of satellite overpass, discover where the latest wildfires, severe storms, volcanic eruptions, dust and haze, ice shelves calving as well as many other events are occurring around the world. Near real-time imagery is made available in Worldview through the Land, Atmosphere Near real-time Capability for EOS (LANCE) via the Global Imagery Browse Services (GIBS). This poster will explore new near real-time imagery available in Worldview, the current ways in which the imagery is used in research, the news and social media and future improvements to Worldview that will enhance the availability and viewing of NASA EOS imagery.

Observing the Earth from afar with NASA's Worldview

NASA Astrophysics Data System (ADS)

Wong, M. M.; Boller, R. A.; King, B. A.; Baynes, K.; Rice, Z.

2017-12-01

NASA's Worldview interactive web map application delivers global, near real-time imagery from NASA's fleet of Earth Observing System (EOS) satellites. Within hours of satellite overpass, discover where the latest wildfires, severe storms, volcanic eruptions, dust and haze, ice shelves calving as well as many other events are occurring around the world. Near real-time imagery is made available in Worldview through the Land Atmosphere Near real-time Capability for EOS (LANCE) via the Global Imagery Browse Services (GIBS). This poster will explore new near real-time imagery available in Worldview, the current ways in which the imagery is used in research, the news and social media and future improvements to Worldview that will enhance the availability and viewing of NASA EOS imagery.

Flood and Landslide Applications of Near Real-time Satellite Rainfall Products

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Negri, Andrew; Huffman, George J.

2007-01-01

Floods and associated landslides are one of the most widespread natural hazards on Earth, responsible for tens of thousands of deaths and billions of dollars in property damage every year. During 1993-2002, over 1000 of the more than 2,900 natural disasters reported were due to floods. These floods and associated landslides claimed over 90,000 lives, affected over 1.4 billion people and cost about $210 billion. The impact of these disasters is often felt most acutely in less developed regions. In many countries around the world, satellite-based precipitation estimation may be the best source of rainfall data due to lack of surface observing networks. Satellite observations can be of essential value in improving our understanding of the occurrence of hazardous events and possibly in lessening their impact on local economies and in reducing injuries, if they can be used to create reliable warning systems in cost-effective ways. This article addressed these opportunities and challenges by describing a combination of satellite-based real-time precipitation estimation with land surface characteristics as input, with empirical and numerical models to map potential of landslides and floods. In this article, a framework to detect floods and landslides related to heavy rain events in near-real-time is proposed. Key components of the framework are: a fine resolution precipitation acquisition system; a comprehensive land surface database; a hydrological modeling component; and landslide and debris flow model components. A key precipitation input dataset for the integrated applications is the NASA TRMM-based multi-satellite precipitation estimates. This dataset provides near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg. By careful integration of remote sensing and in-situ observations, and assimilation of these observations into hydrological and landslide/debris flow models with surface topographic information, prediction of useful probabilistic maps of landslide and floods for emergency management in a timely manner is possible. Early results shows that the potential exists for successful application of satellite precipitation data in improving/developing global monitoring systems for flood/landslide disaster preparedness and management. The scientific and technological prototype can be first applied in a representative test-bed and then the information deliverables for the region can be tailored to the societal and economic needs of the represented affected countries.

Remotely Characterizing the Topographic and Thermal Evolution of Kīlauea's Lava Flow Field

NASA Astrophysics Data System (ADS)

Rumpf, M. E.; Vaughan, R. G.; Poland, M. P.

2017-12-01

New technologies in satellite data acquisition and the continuous development of analysis software capabilities are greatly improving the ability of scientists to monitor volcanoes in near-real-time. Satellite-based thermal infrared (TIR) data are used to monitor and analyze new and ongoing volcanic activity by identifying and quantifying surface thermal characteristics and lava flow discharge rates. Improved detector sensitivities provide unprecedented spatial detail in visible to shortwave infrared (VSWIR) satellite imagery. The acquisition of stereo and tri-stereo visible imagery, as well as SAR, by an increasing number of satellite systems enables the creation of digital elevation models (DEMs) at higher temporal frequencies and resolutions than in the past. Free, user-friendly software programs, such as NASA's Ames Stereo Pipeline and Google Earth Engine, ease the accessibility and usability of satellite data to users unfamiliar with traditional analysis techniques. An effective and efficient integration of these technologies can be utilized towards volcano monitoring.Here, we use the active lava flows from the East Rift Zone vents of Kīlauea Volcano, Hawai`i as a testing ground for developing new techniques in multi-sensor volcano remote sensing. We use DEMs generated from stereo and tri-stereo images captured by the WorldView3 and Pleiades satellite systems to assess topographic changes over time at the active flow fields. Time-series data of lava flow area, thickness, and discharge rate developed from thermal emission measurements collected by ASTER, Landsat 8, and WorldView3 are compared to satellite-detected topographic changes and to ground observations of flow development to identify behavioral patterns and to monitor flow field evolution. We explore methods of combining these visual and TIR data sets collected by multiple satellite systems with a variety of resolutions and repeat times. Our ultimate goal is to develop integrative tools for near-real-time volcano monitoring. In addition, we recommend improvements to future satellite mission capabilities (e.g., repeat times, resolutions) to improve lava flow monitoring techniques.

Real-time Kinematic Positioning of INS Tightly Aided Multi-GNSS Ionospheric Constrained PPP

PubMed Central

Gao, Zhouzheng; Shen, Wenbin; Zhang, Hongping; Niu, Xiaoji; Ge, Maorong

2016-01-01

Real-time Precise Point Positioning (PPP) technique is being widely applied for providing precise positioning services with the significant improvement on satellite precise products accuracy. With the rapid development of the multi-constellation Global Navigation Satellite Systems (multi-GNSS), currently, about 80 navigation satellites are operational in orbit. Obviously, PPP performance is dramatically improved with all satellites compared to that of GPS-only PPP. However, the performance of PPP could be evidently affected by unexpected and unavoidable severe observing environments, especially in the dynamic applications. Consequently, we apply Inertial Navigation System (INS) to the Ionospheric-Constrained (IC) PPP to overcome such drawbacks. The INS tightly aided multi-GNSS IC-PPP model can make full use of GNSS and INS observations to improve the PPP performance in terms of accuracy, availability, continuity, and convergence speed. Then, a set of airborne data is analyzed to evaluate and validate the improvement of multi-GNSS and INS on the performance of IC-PPP. PMID:27470270

Real-time Kinematic Positioning of INS Tightly Aided Multi-GNSS Ionospheric Constrained PPP.

PubMed

Gao, Zhouzheng; Shen, Wenbin; Zhang, Hongping; Niu, Xiaoji; Ge, Maorong

2016-07-29

Real-time Precise Point Positioning (PPP) technique is being widely applied for providing precise positioning services with the significant improvement on satellite precise products accuracy. With the rapid development of the multi-constellation Global Navigation Satellite Systems (multi-GNSS), currently, about 80 navigation satellites are operational in orbit. Obviously, PPP performance is dramatically improved with all satellites compared to that of GPS-only PPP. However, the performance of PPP could be evidently affected by unexpected and unavoidable severe observing environments, especially in the dynamic applications. Consequently, we apply Inertial Navigation System (INS) to the Ionospheric-Constrained (IC) PPP to overcome such drawbacks. The INS tightly aided multi-GNSS IC-PPP model can make full use of GNSS and INS observations to improve the PPP performance in terms of accuracy, availability, continuity, and convergence speed. Then, a set of airborne data is analyzed to evaluate and validate the improvement of multi-GNSS and INS on the performance of IC-PPP.

GNSS global real-time augmentation positioning: Real-time precise satellite clock estimation, prototype system construction and performance analysis

NASA Astrophysics Data System (ADS)

Chen, Liang; Zhao, Qile; Hu, Zhigang; Jiang, Xinyuan; Geng, Changjiang; Ge, Maorong; Shi, Chuang

2018-01-01

Lots of ambiguities in un-differenced (UD) model lead to lower calculation efficiency, which isn't appropriate for the high-frequency real-time GNSS clock estimation, like 1 Hz. Mixed differenced model fusing UD pseudo-range and epoch-differenced (ED) phase observations has been introduced into real-time clock estimation. In this contribution, we extend the mixed differenced model for realizing multi-GNSS real-time clock high-frequency updating and a rigorous comparison and analysis on same conditions are performed to achieve the best real-time clock estimation performance taking the efficiency, accuracy, consistency and reliability into consideration. Based on the multi-GNSS real-time data streams provided by multi-GNSS Experiment (MGEX) and Wuhan University, GPS + BeiDou + Galileo global real-time augmentation positioning prototype system is designed and constructed, including real-time precise orbit determination, real-time precise clock estimation, real-time Precise Point Positioning (RT-PPP) and real-time Standard Point Positioning (RT-SPP). The statistical analysis of the 6 h-predicted real-time orbits shows that the root mean square (RMS) in radial direction is about 1-5 cm for GPS, Beidou MEO and Galileo satellites and about 10 cm for Beidou GEO and IGSO satellites. Using the mixed differenced estimation model, the prototype system can realize high-efficient real-time satellite absolute clock estimation with no constant clock-bias and can be used for high-frequency augmentation message updating (such as 1 Hz). The real-time augmentation message signal-in-space ranging error (SISRE), a comprehensive accuracy of orbit and clock and effecting the users' actual positioning performance, is introduced to evaluate and analyze the performance of GPS + BeiDou + Galileo global real-time augmentation positioning system. The statistical analysis of real-time augmentation message SISRE is about 4-7 cm for GPS, whlile 10 cm for Beidou IGSO/MEO, Galileo and about 30 cm for BeiDou GEO satellites. The real-time positioning results prove that the GPS + BeiDou + Galileo RT-PPP comparing to GPS-only can effectively accelerate convergence time by about 60%, improve the positioning accuracy by about 30% and obtain averaged RMS 4 cm in horizontal and 6 cm in vertical; additionally RT-SPP accuracy in the prototype system can realize positioning accuracy with about averaged RMS 1 m in horizontal and 1.5-2 m in vertical, which are improved by 60% and 70% to SPP based on broadcast ephemeris, respectively.

US GEOLOGICAL SURVEY'S NATIONAL SYSTEM FOR PROCESSING AND DISTRIBUTION OF NEAR REAL-TIME HYDROLOGICAL DATA.

USGS Publications Warehouse

Shope, William G.; ,

1987-01-01

The US Geological Survey is utilizing a national network of more than 1000 satellite data-collection stations, four satellite-relay direct-readout ground stations, and more than 50 computers linked together in a private telecommunications network to acquire, process, and distribute hydrological data in near real-time. The four Survey offices operating a satellite direct-readout ground station provide near real-time hydrological data to computers located in other Survey offices through the Survey's Distributed Information System. The computerized distribution system permits automated data processing and distribution to be carried out in a timely manner under the control and operation of the Survey office responsible for the data-collection stations and for the dissemination of hydrological information to the water-data users.

Seismic displacements monitoring for 2015 Mw 7.8 Nepal earthquake with GNSS data

NASA Astrophysics Data System (ADS)

Geng, T.; Su, X.; Xie, X.

2017-12-01

The high-rate Global Positioning Satellite System (GNSS) has been recognized as one of the powerful tools for monitoring ground motions generated by seismic events. The high-rate GPS and BDS data collected during the 2015 Mw 7.8 Nepal earthquake have been analyzed using two methods, that are the variometric approach and Precise point positioning (PPP). The variometric approach is based on time differenced technique using only GNSS broadcast products to estimate velocity time series from tracking observations in real time, followed by an integration procedure on the velocities to derive the seismic event induced displacements. PPP is a positioning method to calculate precise positions at centimeter- or even millimeter-level accuracy with a single GNSS receiver using precise satellite orbit and clock products. The displacement motions with accuracy of 2 cm at far-field stations and 5 cm at near-field stations with great ground motions and static offsets up to 1-2 m could be achieved. The multi-GNSS, GPS + BDS, could provide higher accuracy displacements with the increasing of satellite numbers and the improvement of the Position Dilution of Precision (PDOP) values. Considering the time consumption of clock estimates and the precision of PPP solutions, 5 s GNSS satellite clock interval is suggested. In addition, the GNSS-derived displacements are in good agreement with those from strong motion data. These studies demonstrate the feasibility of real-time capturing seismic waves with multi-GNSS observations, which is of great promise for the purpose of earthquake early warning and rapid hazard assessment.

Understanding and Analyzing Latency of Near Real-time Satellite Data

NASA Astrophysics Data System (ADS)

Han, W.; Jochum, M.; Brust, J.

2016-12-01

Acquiring and disseminating time-sensitive satellite data in a timely manner is much concerned by researchers and decision makers of weather forecast, severe weather warning, disaster and emergency response, environmental monitoring, and so on. Understanding and analyzing the latency of near real-time satellite data is very useful and helpful to explore the whole data transmission flow, indentify the possible issues, and connect data providers and users better. The STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR) is a central repository to acquire, manipulate, and disseminate various types of near real-time satellite datasets to internal and external users. In this system, important timestamps, including observation beginning/end, processing, uploading, downloading, and ingestion, are retrieved and organized in the database, so the time length of each transmission phase can be figured out easily. Open source NoSQL database MongoDB is selected to manage the timestamp information because of features of dynamic schema, aggregation and data processing. A user-friendly user interface is developed to visualize and characterize the latency interactively. Taking the Himawari-8 HSD (Himawari Standard Data) file as an example, the data transmission phases, including creating HSD file from satellite observation, uploading the file to HimawariCloud, updating file link in the webpage, downloading and ingesting the file to SCDR, are worked out from the above mentioned timestamps. The latencies can be observed by time of period, day of week, or hour of day in chart or table format, and the anomaly latencies can be detected and reported through the user interface. Latency analysis provides data providers and users actionable insight on how to improve the data transmission of near real-time satellite data, and enhance its acquisition and management.

The TRMM Multi-Satellite Precipitation Analysis (TMPA)

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Nelkin, Eric J.

2008-01-01

The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is intended to provide a "best" estimate of quasi-global precipitation from the wide variety of modern satellite-borne precipitation-related sensors. Estimates are provided at relatively fine scales (0.25degx0.25deg, 3-hourly) in both real and post-real time to accommodate a wide range of researchers. However, the errors inherent in the finest scale estimates are large. The most successful use of the TMPA data is when the analysis takes advantage of the fine-scale data to create time/space averages appropriate to the user s application. We review the conceptual basis for the TMPA, summarize the processing sequence, and focus on two new activities. First, a recent upgrade to the real-time version incorporates several additional satellite data sources and employs monthly climatological adjustments to approximate the bias characteristics of the research quality post-real-time product. Second, an upgrade of the research quality post-real-time TMPA from Version 6 to Version 7 (in beta test at press time) is designed to provide a variety of improvements that increase the list of input data sets and correct several issues. Future enhancements for the TMPA will include improved error estimation, extension to higher latitudes, and a shift to a Lagrangian time interpolation scheme.

The TRMM Multi-Satellite Precipitation Analysis (TMPA)

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Nelkin, Eric J.

2010-01-01

The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is intended to provide a "best" estimate of quasi-global precipitation from the wide variety of modern satellite-borne precipitation-related sensors. Estimates are provided at relatively fine scales (0.25 deg x 0.25 deg. 3-h) in both real and post-real time to accommodate a wide range of researchers. However, the errors inherent in the finest scale estimates are large. The most successful use of the TMPA data is when the analysis takes advantage of the fine-scale data to create time/space averages appropriate to the user fs application. We review the conceptual basis for the TMPA, summarize the processing sequence, and focus on two new activities. First, a recent upgrade for the real-time version incorporates several additional satellite data sources and employs monthly climatological adjustments to approximate the bias characteristics of the research quality post-real-time product. Second, an upgrade for the research quality post-real-time TMPA from Versions 6 to 7 (in beta test at press time) is designed to provide a variety of improvements that increase the list of input data sets and correct several issues. Future enhancements for the TMPA will include improved error estimation, extension to higher latitudes, and a shift to a Lagrangian time interpolation scheme.

Application of Multi-Satellite Precipitation Analysis to Floods and Landslides

NASA Technical Reports Server (NTRS)

Adler, Robert; Hong, Yang; Huffman, George

2007-01-01

Satellite data acquired and processed in real time now have the potential to provide the spacetime information on rainfall needed to monitor flood and landslide events around the world. This can be achieved by integrating the satellite-derived forcing data with hydrological models and landslide algorithms. Progress in using the TRMM Multi-satellite Precipitation Analysis (TMPA) as input to flood and landslide forecasts is outlined, with a focus on understanding limitations of the rainfall data and impacts of those limitations on flood/landslide analyses. Case studies of both successes and failures will be shown, as well as comparison with ground comparison data sets both in terms of rainfall and in terms of flood/landslide events. In addition to potential uses in real-time, the nearly ten years of TMPA data allow retrospective running of the models to examine variations in extreme events. The flood determination algorithm consists of four major components: 1) multi-satellite precipitation estimation; 2) characterization of land surface including digital elevation from NASA SRTM (Shuttle Radar Terrain Mission), topography-derived hydrologic parameters such as flow direction, flow accumulation, basin, and river network etc.; 3) a hydrological model to infiltrate rainfall and route overland runoff; and 4) an implementation interface to relay the input data to the models and display the flood inundation results to potential users and decision-makers. In terms of landslides, the satellite rainfall information is combined with a global landslide susceptibility map, derived from a combination of global surface characteristics (digital elevation topography, slope, soil types, soil texture, and land cover classification etc.) using a weighted linear combination approach. In those areas identified as "susceptible" (based on the surface characteristics), landslides are forecast where and when a rainfall intensity/duration threshold is exceeded. Results are described indicating general agreement with landslide occurrences. However, difficulties in comparing landslide event information (mostly from news reports) with the satellite-based forecasts are analyzed.

A Real-Time Robust Method to Detect BeiDou GEO/IGSO Orbital Maneuvers

PubMed Central

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Fan, Lihong; Wang, Xiaolei

2017-01-01

The frequent maneuvering of BeiDou Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites affects the availability of real-time orbit, and decreases the accuracy and performance of positioning, navigation and time (PNT) services. BeiDou satellite maneuver information cannot be obtained by common users. BeiDou broadcast ephemeris is the only indicator of the health status of satellites, which are broadcast on an hourly basis, easily leading to ineffective observations. Sometimes, identification errors of satellite abnormity also appear in the broadcast ephemeris. This study presents a real-time robust detection method for a satellite orbital maneuver with high frequency and high reliability. By using the broadcast ephemeris and pseudo-range observations, the time discrimination factor and the satellite identification factor were defined and used for the real-time detection of start time and the pseudo-random noise code (PRN) of satellites was used for orbital maneuvers. Data from a Multi-GNSS Experiment (MGEX) was collected and analyzed. The results show that the start time and the PRN of the satellite orbital maneuver could be detected accurately in real time. In addition, abnormal start times and satellite abnormities caused by non-maneuver factors also could be detected using the proposed method. The new method not only improves the utilization of observations for users with the data effective for about 92 min, but also promotes the reliability of real-time PNT services. PMID:29186058

A Real-Time Robust Method to Detect BeiDou GEO/IGSO Orbital Maneuvers.

PubMed

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Fan, Lihong; Wang, Xiaolei

2017-11-29

The frequent maneuvering of BeiDou Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO) satellites affects the availability of real-time orbit, and decreases the accuracy and performance of positioning, navigation and time (PNT) services. BeiDou satellite maneuver information cannot be obtained by common users. BeiDou broadcast ephemeris is the only indicator of the health status of satellites, which are broadcast on an hourly basis, easily leading to ineffective observations. Sometimes, identification errors of satellite abnormity also appear in the broadcast ephemeris. This study presents a real-time robust detection method for a satellite orbital maneuver with high frequency and high reliability. By using the broadcast ephemeris and pseudo-range observations, the time discrimination factor and the satellite identification factor were defined and used for the real-time detection of start time and the pseudo-random noise code (PRN) of satellites was used for orbital maneuvers. Data from a Multi-GNSS Experiment (MGEX) was collected and analyzed. The results show that the start time and the PRN of the satellite orbital maneuver could be detected accurately in real time. In addition, abnormal start times and satellite abnormities caused by non-maneuver factors also could be detected using the proposed method. The new method not only improves the utilization of observations for users with the data effective for about 92 min, but also promotes the reliability of real-time PNT services.

Multi-GNSS real-time precise orbit/clock/UPD products and precise positioning service at GFZ

NASA Astrophysics Data System (ADS)

Li, Xingxing; Ge, Maorong; Liu, Yang; Fritsche, Mathias; Wickert, Jens; Schuh, Harald

2016-04-01

The rapid development of multi-constellation GNSSs (Global Navigation Satellite Systems, e.g., BeiDou, Galileo, GLONASS, GPS) and the IGS (International GNSS Service) Multi-GNSS Experiment (MGEX) bring great opportunities and challenges for real-time precise positioning service. In this contribution, we present a GPS+GLONASS+BeiDou+Galileo four-system model to fully exploit the observations of all these four navigation satellite systems for real-time precise orbit determination, clock estimation and positioning. A rigorous multi-GNSS analysis is performed to achieve the best possible consistency by processing the observations from different GNSS together in one common parameter estimation procedure. Meanwhile, an efficient multi-GNSS real-time precise positioning service system is designed and demonstrated by using the Multi-GNSS Experiment (MGEX) and International GNSS Service (IGS) data streams including stations all over the world. The addition of the BeiDou, Galileo and GLONASS systems to the standard GPS-only processing, reduces the convergence time almost by 70%, while the positioning accuracy is improved by about 25%. Some outliers in the GPS-only solutions vanish when multi-GNSS observations are processed simultaneous. The availability and reliability of GPS precise positioning decrease dramatically as the elevation cutoff increases. However, the accuracy of multi-GNSS precise point positioning (PPP) is hardly decreased and few centimeters are still achievable in the horizontal components even with 40° elevation cutoff.

Multi-GNSS real-time precise positioning service and Initial assessment of BDS-3 (G Division Outstanding ECS Award Lecture)

NASA Astrophysics Data System (ADS)

Li, Xingxing; Ge, Maaorong; Li, Xin; Zhang, Xiuaohong; Wu, Mingkui; Wickert, Jens; Schuh, Harald

2017-04-01

The rapid development of multi-constellation GNSSs (Global Navigation Satellite Systems, e.g., BeiDou, Galileo, GLONASS, GPS) and the IGS (International GNSS Service) Multi-GNSS Experiment (MGEX) bring great opportunities and challenges for real-time precise positioning service. In this contribution, we present a GPS+GLONASS+BeiDou+Galileo four-system model to fully exploit the observations of all these four navigation satellite systems for real-time precise orbit determination, clock estimation and positioning. Meanwhile, an efficient multi-GNSS real-time precise positioning service system is designed and demonstrated by using the Multi-GNSS Experiment (MGEX) and International GNSS Service (IGS) data streams including stations all over the world. The addition of the BeiDou, Galileo and GLONASS systems to the standard GPS-only processing, reduces the convergence time almost by 70%, while the positioning accuracy is improved by about 25%. The successful launch of five new-generation satellites of the Chinese BeiDou Navigation Satellite System (BDS-3) marks a significant step in expanding BeiDou into a navigation system with global coverage. We present an initial characterization and performance assessment for these new-generation BeiDou-3 satellites and their signals. The characteristics of the B1C, B1I, B2a, B2b and B3I signals are evaluated in terms of observed carrier-to-noise density ratio, pseudorange multipath and noise, triple-frequency carrier phase ionosphere-free and geometry-free combination, and double-differenced carrier phase and code residuals. With respect to BeiDou-2 satellites, the analysis of code multipath shows that the elevation-dependent code biases, which have been previously identified to exist in the code observations of BeiDou-2 satellites, seem to be not obvious for all the available signals of new-generation BeiDou-3 satellites. This will significantly benefit precise applications that resolve wide-lane ambiguity based on Melbourne-Wübbena (MW) linear combinations and other applications such as single-frequency Precise Point Positioning (PPP) based on the ionosphere free code-carrier combinations. With regard to the triple-frequency carrier phase ionosphere-free and geometry-free combinations, it is found that different from BeiDou-2 and GPS Block IIF satellites, no apparent bias variations could be observed in all the new-generation BeiDou-3 satellites, which show a good consistency of the new-generation BeiDou-3 signals. The absence of such triple-frequency biases will make it convenient for the future processing of multi-frequency PPP using observations from new-generation BeiDou-3 satellites.

Evaluation of Integrated Multi-satellitE Retrievals for GPM with All Weather Gauge Observations over CONUS

NASA Astrophysics Data System (ADS)

Chen, S.; Qi, Y.; Hu, B.; Hu, J.; Hong, Y.

2015-12-01

The Global Precipitation Measurement (GPM) mission is composed of an international network of satellites that provide the next-generation global observations of rain and snow. Integrated Multi-satellitE Retrievals for GPM (IMERG) is the state-of-art precipitation products with high spatio-temporal resolution of 0.1°/30min. IMERG unifies precipitation measurements from a constellation of research and operational satellites with the core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI) on board a "Core" satellite. Additionally, IMERG blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. In this study, the final run post real-time IMERG is evaluated with all-weather manual gauge observations over CONUS from June 2014 through May 2015. Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) are used to quantify the performance of IMERG. The performance of IMERG in estimating snowfall precipitation is highlighted in the study. This timely evaluation with all-weather gauge observations is expected to offer insights into performance of IMERG and thus provide useful feedback to the algorithm developers as well as the GPM data users.

Performance of Precipitation Algorithms During IPHEx and Observations of Microphysical Characteristics in Complex Terrain

NASA Astrophysics Data System (ADS)

Erlingis, J. M.; Gourley, J. J.; Kirstetter, P.; Anagnostou, E. N.; Kalogiros, J. A.; Anagnostou, M.

2015-12-01

An Intensive Observation Period (IOP) for the Integrated Precipitation and Hydrology Experiment (IPHEx), part of NASA's Ground Validation campaign for the Global Precipitation Measurement Mission satellite took place from May-June 2014 in the Smoky Mountains of western North Carolina. The National Severe Storms Laboratory's mobile dual-pol X-band radar, NOXP, was deployed in the Pigeon River Basin during this time and employed various scanning strategies, including more than 1000 Range Height Indicator (RHI) scans in coordination with another radar and research aircraft. Rain gauges and disdrometers were also positioned within the basin to verify precipitation estimates and estimation of microphysical parameters. The performance of the SCOP-ME post-processing algorithm on NOXP data is compared with real-time and near real-time precipitation estimates with varying spatial resolutions and quality control measures (Stage IV gauge-corrected radar estimates, Multi-Radar/Multi-Sensor System Quantitative Precipitation Estimates, and CMORPH satellite estimates) to assess the utility of a gap-filling radar in complex terrain. Additionally, the RHI scans collected in this IOP provide a valuable opportunity to examine the evolution of microphysical characteristics of convective and stratiform precipitation as they impinge on terrain. To further the understanding of orographically enhanced precipitation, multiple storms for which RHI data are available are considered.

Near Real Time MISR Wind Observations for Numerical Weather Prediction

NASA Astrophysics Data System (ADS)

Mueller, K. J.; Protack, S.; Rheingans, B. E.; Hansen, E. G.; Jovanovic, V. M.; Baker, N.; Liu, J.; Val, S.

2014-12-01

The Multi-angle Imaging SpectroRadiometer (MISR) project, in association with the NASA Langley Atmospheric Science Data Center (ASDC), has this year adapted its original production software to generate near-real time (NRT) cloud-motion winds as well as radiance imagery from all nine MISR cameras. These products are made publicly available at the ASDC with a latency of less than 3 hours. Launched aboard the sun-synchronous Terra platform in 1999, the MISR instrument continues to acquire near-global, 275 m resolution, multi-angle imagery. During a single 7 minute overpass of any given area, MISR retrieves the stereoscopic height and horizontal motion of clouds from the multi-angle data, yielding meso-scale near-instantaneous wind vectors. The ongoing 15-year record of MISR height-resolved winds at 17.6 km resolution has been validated against independent data sources. Low-level winds dominate the sampling, and agree to within ±3 ms-1 of collocated GOES and other observations. Low-level wind observations are of particular interest to weather forecasting, where there is a dearth of observations suitable for assimilation, in part due to reliability concerns associated with winds whose heights are assigned by the infrared brightness temperature technique. MISR cloud heights, on the other hand, are generated from stereophotogrammetric pattern matching of visible radiances. MISR winds also address data gaps in the latitude bands between geostationary satellite coverage and polar orbiting instruments that obtain winds from multiple overpasses (e.g. MODIS). Observational impact studies conducted by the Naval Research Laboratory (NRL) and by the German Weather Service (Deutscher Wetterdienst) have both demonstrated forecast improvements when assimilating MISR winds. An impact assessment using the GEOS-5 system is currently in progress. To benefit air quality forecasts, the MISR project is currently investigating the feasibility of generating near-real time aerosol products.

Performance of near real-time Global Satellite Mapping of Precipitation estimates during heavy precipitation events over northern China

NASA Astrophysics Data System (ADS)

Chen, Sheng; Hu, Junjun; Zhang, Asi; Min, Chao; Huang, Chaoying; Liang, Zhenqing

2018-02-01

This study assesses the performance of near real-time Global Satellite Mapping of Precipitation (GSMaP_NRT) estimates over northern China, including Beijing and its adjacent regions, during three heavy precipitation events from 21 July 2012 to 2 August 2012. Two additional near real-time satellite-based products, the Climate Prediction Center morphing method (CMORPH) and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), were used for parallel comparison with GSMaP_NRT. Gridded gauge observations were used as reference for a performance evaluation with respect to spatiotemporal variability, probability distribution of precipitation rate and volume, and contingency scores. Overall, GSMaP_NRT generally captures the spatiotemporal variability of precipitation and shows promising potential in near real-time mapping applications. GSMaP_NRT misplaced storm centers in all three storms. GSMaP_NRT demonstrated higher skill scores in the first high-impact storm event on 21 July 2015. GSMaP_NRT passive microwave only precipitation can generally capture the pattern of heavy precipitation distributions over flat areas but failed to capture the intensive rain belt over complicated mountainous terrain. The results of this study can be useful to both algorithm developers and the scientific end users, providing a better understanding of strengths and weaknesses to hydrologists using satellite precipitation products.

Near Real Time Operational Satellite Ocean Color Products From NOAA OSPO CoastWatch Okeanos System:: Status and Challenges

NASA Astrophysics Data System (ADS)

Banghua Yan, B.

2016-02-01

Near real-time (NRT) ocean color (OC) satellite operation products are generated and distributed in NOAA Okeanos Operational Product System, by using the CWAPS including the Multi-Sensor Level (MSL) 12 and the chlorophyll-a frontal algorithms. Current OC operational products include daily chlorophyll concentration (anomaly), water turbidity, remote sensing reflectance and chlorophyll frontal products from Moderate-resolution Imaging Spectroradiometer (MODIS)/Aqua. The products have been widely applied to USA local and state ecosystem research, ecosystem observations, and fisheries managements for coastal and regional forecasting of ocean water quality, phytoplankton concentrations, and primary production. Users of the products have the National Ocean Service, National Marine Fisheries Service, National Weather Service, and Oceanic and Atmospheric Research. Recently, the OC products are being extended to S-NPP VIIRS to provide global NRT ocean color products to user community suh as National Weatrher Service for application for Global Data Assimilation System and Real-Time Ocean Forecast System. However, there remain some challenges in application of the products due to certain product quality and coverage issues. Recent efforts were made to provide a comprehensive web-based Quality Assurance (QA) tool for monitoring OC products quality in near real time mode, referring to http://www.ospo.noaa.gov/Products/ocean/color_new/color.htm. The new QA monitoring tool includes but not limited to the following advanced features applicable for MODIS/Aqua and NPP/VIIRS OC products: 1) Monitoring product quality in NRT mode; 2) Monitoring the availability and quality of OC products with time; 3) Detecting anomalous OC products due to low valid pixels and other quality issues. As an example, potential application and challenges of the ocean color products to oceanic oil spill detection are investigated. It is thus expected that the Okeanos ocean color operational system in combination with the new QA monitoring tool will more efficiently ensure availability and quality of satellite operational OC products from Okeanos system to the user community. The QA tool also will provide much useful information of OC products quality and statistics to the OC user community.

Quality assessment of multi-GNSS real-time orbits and clocks

NASA Astrophysics Data System (ADS)

Kaźmierski, Kamil; Sośnica, Krzysztof; Hadaś, Tomasz

2017-04-01

A continuously increasing number of satellites of Global Navigation Satellites Systems (GNSS) and their constant modernization allow improving the positioning accuracy and enables performing the GNSS measurements in challenging environments. The constant development of GNSS, among which GPS, GLONASS, Galileo and BeiDou can be distinguished, contributes to improvements in GNSS usage in areas desired by common users or GNSS community. The Multi-GNSS experiment (MGEX) of the International GNSS Service (IGS) has been established for tracking, collating and analyzing all available GNSS signals. Provided precise orbits and clocks do not allow users to process data in real-time due to the significant latency of provided products which may reach up to even 18 days. In order to satisfy needs of real-time users IGS Real-Time Service (RTS) was launched in 2013. The service is currently insufficient for Multi-GNSS applications as it provides products for GPS and GLONASS only. One of the publicly available real-time corrections for the all GNSS, including the new systems, are those provided by the Centre National d'etudes Spatiales (CNES). Presented works evaluate clocks and orbit corrections, i.e., the availability and quality of real-time products provided by CNES (mountpoint CLK93). As a decoder of the RTCM streams the BNC software v2.12 is used. All computations are performed using the GNSS-WARP software which is developed by Institute of Geodesy and Geoinformatics (IGG) at Wroclaw University of Environmental and Life Sciences (WUELS). The final products provided by the Center of Orbit Determination in Europe (CODE) are used for the evaluation of the real-time CNES orbits and clocks. Moreover, the Satellite Laser Ranging (SLR) data are employed as an independent way of the orbit quality assessment. The availability of the real-time corrections is at the level of about 90%, when excluding BeiDou, for which the availability is at the level of about 80%. The obtained results with reference to CODE products indicate that satellites' position quality is different for different systems. The best performance is obtained for GPS (about 3 cm) and the worst for BeiDou (about 30 cm). A similar situation occurred for GPS clocks with the clock residues RMSE at the level of 15 cm. The greatest clock residues RMSE was obtained for GLONASS and reached up to 1 m. Conducted works allow us to perform a further study related to the real-time GNSS data processing, e.g., using the system-specific observation weighting. Keywords: Multi-GNSS, real-time processing, clocks, orbits

A Multimodel Global Drought Information System (GDIS) for Near Real-Time Monitoring of Surface Water Conditions (Invited)

NASA Astrophysics Data System (ADS)

Nijssen, B.

2013-12-01

While the absolute magnitude of economic losses associated with weather and climate disasters such as droughts is greatest in the developed world, the relative impact is much larger in the developing world, where agriculture typically constitutes a much larger percentage of the labor force and food insecurity is a major concern. Nonetheless, our ability to monitor and predict the development and occurrence of droughts at a global scale in near real-time is limited and long-term records of soil moisture are essentially non-existent globally The problem is particularly critical given that many of the most damaging droughts occur in parts of the world that are most deficient in terms of in situ precipitation observations. In recent years, a number of near real-time drought monitoring systems have been developed with regional or global extent. While direct observations of key variables such as moisture storage are missing, the evolution of land surface models that are globally applicable provides a means of reconstructing them. The implementation of a multi-model drought monitoring system is described, which provides near real-time estimates of surface moisture storage for the global land areas between 50S and 50N with a time lag of about one day. Near real-time forcings are derived from satellite-based precipitation estimates and modeled air temperatures. The system is distinguished from other operational systems in that it uses multiple land surface models to simulate surface moisture storage, which are then combined to derive a multi-model estimate of drought. Previous work has shown that while land surface models agree in broad context, particularly in terms of soil moisture percentiles, important differences remain, which motivates a multi-model ensemble approach. The system is an extension of similar systems developed by at the University of Washington for the Pacific Northwest and for the United States, but global application of the protocols used in the U.S. systems poses new challenges, particularly with respect to the generation of meteorological forcings that drive the land surface models. Agricultural and hydrological droughts are inherently defined in the context of a long-term climatology. Changes in observing platforms can be misinterpreted as droughts (or as excessively wet periods). This problem cannot simply be addressed through the addition of more observations or through the development of new observing platforms. Instead, it will require careful (re)construction of long-term records that are updated in near real-time in a consistent manner so that changes in surface meteorological forcings reflect actual conditions rather than changes in methods or sources.

An investigation into the performance of real-time GPS+GLONASS Precise Point Positioning (PPP) in New Zealand

NASA Astrophysics Data System (ADS)

Harima, Ken; Choy, Suelynn; Rizos, Chris; Kogure, Satoshi

2017-09-01

This paper presents an investigation into the performance of real-time Global Navigation Satellite Systems (GNSS) Precise Point Positioning (PPP) in New Zealand. The motivation of the research is to evaluate the feasibility of using PPP technique and a satellite based augmentation system such as the Japanese Quasi-Zenith Satellite System (QZSS) to deliver a real-time precise positioning solution in support of a nation-wide high accuracy GNSS positioning coverage in New Zealand. Two IGS real-time correction streams are evaluated alongside with the PPP correction messages transmitted by the QZSS satellite known as MDC1. MDC1 corrections stream is generated by Japan Aerospace Exploration Agency (JAXA) using the Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis (MADOCA) software and are currently transmitted in test mode by the QZSS satellite. The IGS real-time streams are the CLK9B real-time corrections stream generated by the French Centre National D'études Spatiales (CNES) using the PPP-Wizard software, and the CLK81 real-time corrections stream produced by GMV using their MagicGNSS software. GNSS data is collected from six New Zealand CORS stations operated by Land Information New Zealand (LINZ) over a one-week period in 2015. GPS and GLONASS measurements are processed in a real-time PPP mode using the satellite orbit and clock corrections from the real-time streams. The results show that positioning accuracies of 6 cm in horizontal component and 15 cm in vertical component can be achieved in real-time PPP. The real-time GPS+GLONASS PPP solution required 30 minutes to converge to within 10 cm horizontal positioning accuracy.

NASA-Langley Web-Based Operational Real-time Cloud Retrieval Products from Geostationary Satellites

NASA Technical Reports Server (NTRS)

Palikonda, Rabindra; Minnis, Patrick; Spangenberg, Douglas A.; Khaiyer, Mandana M.; Nordeen, Michele L.; Ayers, Jeffrey K.; Nguyen, Louis; Yi, Yuhong; Chan, P. K.; Trepte, Qing Z.;

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

NASA Technical Reports Server (NTRS)

Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

2007-01-01

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for constraining the use of the passive retrieval data in models and for improving the accuracy of the retrievals.

Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo

NASA Astrophysics Data System (ADS)

Li, Xingxing; Ge, Maorong; Dai, Xiaolei; Ren, Xiaodong; Fritsche, Mathias; Wickert, Jens; Schuh, Harald

2015-06-01

In this contribution, we present a GPS+GLONASS+BeiDou+Galileo four-system model to fully exploit the observations of all these four navigation satellite systems for real-time precise orbit determination, clock estimation and positioning. A rigorous multi-GNSS analysis is performed to achieve the best possible consistency by processing the observations from different GNSS together in one common parameter estimation procedure. Meanwhile, an efficient multi-GNSS real-time precise positioning service system is designed and demonstrated by using the multi-GNSS Experiment, BeiDou Experimental Tracking Network, and International GNSS Service networks including stations all over the world. The statistical analysis of the 6-h predicted orbits show that the radial and cross root mean square (RMS) values are smaller than 10 cm for BeiDou and Galileo, and smaller than 5 cm for both GLONASS and GPS satellites, respectively. The RMS values of the clock differences between real-time and batch-processed solutions for GPS satellites are about 0.10 ns, while the RMS values for BeiDou, Galileo and GLONASS are 0.13, 0.13 and 0.14 ns, respectively. The addition of the BeiDou, Galileo and GLONASS systems to the standard GPS-only processing, reduces the convergence time almost by 70 %, while the positioning accuracy is improved by about 25 %. Some outliers in the GPS-only solutions vanish when multi-GNSS observations are processed simultaneous. The availability and reliability of GPS precise positioning decrease dramatically as the elevation cutoff increases. However, the accuracy of multi-GNSS precise point positioning (PPP) is hardly decreased and few centimeter are still achievable in the horizontal components even with 40 elevation cutoff. At 30 and 40 elevation cutoffs, the availability rates of GPS-only solution drop significantly to only around 70 and 40 %, respectively. However, multi-GNSS PPP can provide precise position estimates continuously (availability rate is more than 99.5 %) even up to 40 elevation cutoff (e.g., in urban canyons).

Near-Real-Time Satellite Cloud Products for Icing Detection and Aviation Weather over the USA

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Smith, William L., Jr.; Nguyen, Louis; Murray, J. J.; Heck, Patrick W.; Khaiyer, Mandana M.

2003-01-01

A set of physically based retrieval algorithms has been developed to derive from multispectral satellite imagery a variety of cloud properties that can be used to diagnose icing conditions when upper-level clouds are absent. The algorithms are being applied in near-real time to the Geostationary Operational Environmental Satellite (GOES) data over Florida, the Southern Great Plains, and the midwestern USA. The products are available in image and digital formats on the world-wide web. The analysis system is being upgraded to analyze GOES data over the CONUS. Validation, 24-hour processing, and operational issues are discussed.

High-resolution near real-time drought monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, Saran; Mishra, Vimal

2017-10-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning, and management of water resources at sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. We develop a high-resolution (0.05°) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat and cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature, which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05°. The bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub-basin levels.

Validating GPM-based Multi-satellite IMERG Products Over South Korea

NASA Astrophysics Data System (ADS)

Wang, J.; Petersen, W. A.; Wolff, D. B.; Ryu, G. H.

2017-12-01

Accurate precipitation estimates derived from space-borne satellite measurements are critical for a wide variety of applications such as water budget studies, and prevention or mitigation of natural hazards caused by extreme precipitation events. This study validates the near-real-time Early Run, Late Run and the research-quality Final Run Integrated Multi-Satellite Retrievals for GPM (IMERG) using Korean Quantitative Precipitation Estimation (QPE). The Korean QPE data are at a 1-hour temporal resolution and 1-km by 1-km spatial resolution, and were developed by Korea Meteorological Administration (KMA) from a Real-time ADjusted Radar-AWS (Automatic Weather Station) Rainrate (RAD-RAR) system utilizing eleven radars over the Republic of Korea. The validation is conducted by comparing Version-04A IMERG (Early, Late and Final Runs) with Korean QPE over the area (124.5E-130.5E, 32.5N-39N) at various spatial and temporal scales during March 2014 through November 2016. The comparisons demonstrate the reasonably good ability of Version-04A IMERG products in estimating precipitation over South Korea's complex topography that consists mainly of hills and mountains, as well as large coastal plains. Based on this data, the Early Run, Late Run and Final Run IMERG precipitation estimates higher than 0.1mm h-1 are about 20.1%, 7.5% and 6.1% higher than Korean QPE at 0.1o and 1-hour resolutions. Detailed comparison results are available at https://wallops-prf.gsfc.nasa.gov/KoreanQPE.V04/index.html

Near-Real-Time Detection and Monitoring of Dust Events by Satellite (SeaWIFS, MODIS, and TOMS)

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Tsay, Si-Chee; Herman, Jay R.; Kaufman, Yoram

2002-01-01

Over the last few years satellites have given us increasingly detailed information on the size, location, and duration of dust events around the world. These data not only provide valuable feedback to the modelling community as to the fidelity of their aerosol models but are also finding increasing use in near real-time applications. In particular, the ability to locate and track the development of aerosol dust clouds on a near real-time basis is being used by scientists and government to provide warning of air pollution episodes over major urban area. This ability has also become a crucial component of recent coordinated campaigns to study the characteristics of tropospheric aerosols such as dust and their effect on climate. One such recent campaign was ACE-Asia, which was designed to obtain the comprehensive set of ground, aircraft, and satellite data necessary to provide a detailed understanding of atmospheric aerosol particles over the Asian-Pacific region. As part of ACE-Asia, we developed a near real-time data processing and access system to provide satellite data from the polar-orbiting instruments Earth Probe TOMS (in the form of absorbing aerosol index) and SeaWiFS (in the form of aerosol optical thickness, AOT, and Angstrom exponent). The results were available via web access. The location and movement information provided by these data were used both in support of the day-to-day flight planning of ACE-Asia and as input into aerosol transport models. While near real-time SeaWiFS data processing can be performed using either the normal global data product or data obtained via direct broadcast to receiving stations close to the area of interest, near real-time MODIS processing of data to provide aerosol retrievals is currently only available using its direct broadcast capability. In this paper, we will briefly discuss the algorithms used to generate these data. The retrieved aerosol optical thickness and Angstrom exponent from SeaWiFS will be compared with those obtained from various AERONET sites over the Asian-Pacific region. The TOMS aerosol index will also be compared with AERONET aerosol optical thickness over different aerosol conditions, and comparisons between the MODIS and SeaWiFS data will also be presented. Finally, we will discuss the climate implication of our studies using the combined satellite and AERONET observations.

A multi-scale hybrid neural network retrieval model for dust storm detection, a study in Asia

NASA Astrophysics Data System (ADS)

Wong, Man Sing; Xiao, Fei; Nichol, Janet; Fung, Jimmy; Kim, Jhoon; Campbell, James; Chan, P. W.

2015-05-01

Dust storms are known to have adverse effects on human health and significant impact on weather, air quality, hydrological cycle, and ecosystem. Atmospheric dust loading is also one of the large uncertainties in global climate modeling, due to its significant impact on the radiation budget and atmospheric stability. Observations of dust storms in humid tropical south China (e.g. Hong Kong), are challenging due to high industrial pollution from the nearby Pearl River Delta region. This study develops a method for dust storm detection by combining ground station observations (PM10 concentration, AERONET data), geostationary satellite images (MTSAT), and numerical weather and climatic forecasting products (WRF/Chem). The method is based on a hybrid neural network (NN) retrieval model for two scales: (i) a NN model for near real-time detection of dust storms at broader regional scale; (ii) a NN model for detailed dust storm mapping for Hong Kong and Taiwan. A feed-forward multilayer perceptron (MLP) NN, trained using back propagation (BP) algorithm, was developed and validated by the k-fold cross validation approach. The accuracy of the near real-time detection MLP-BP network is 96.6%, and the accuracies for the detailed MLP-BP neural network for Hong Kong and Taiwan is 74.8%. This newly automated multi-scale hybrid method can be used to give advance near real-time mapping of dust storms for environmental authorities and the public. It is also beneficial for identifying spatial locations of adverse air quality conditions, and estimates of low visibility associated with dust events for port and airport authorities.

TerraSAR-X precise orbit determination with real-time GPS ephemerides

NASA Astrophysics Data System (ADS)

Wermuth, Martin; Hauschild, Andre; Montenbruck, Oliver; Kahle, Ralph

TerraSAR-X is a German Synthetic Aperture Radar (SAR) satellite, which was launched in June 2007 from Baikonour. Its task is to acquire radar images of the Earth's surface. In order to locate the radar data takes precisely, the satellite is equipped with a high-quality dual-frequency GPS receiver -the Integrated Geodetic and Occultation Receiver (IGOR) provided by the GeoForschungsZentrum Potsdam (GFZ). Using GPS observations from the IGOR instrument in a reduced dynamic precise orbit determination (POD), the German Space Operations Center (DLR/GSOC) is computing rapid and science orbit products on a routine basis. The rapid orbit products arrive with a latency of about one hour after data reception with an accuracy of 10-20 cm. Science orbit products are computed with a latency of five days achieving an accuracy of about 5cm (3D-RMS). For active and future Earth observation missions, the availability of near real-time precise orbit information is becoming more and more important. Other applications of near real-time orbit products include the processing of GNSS radio occulation measurements for atmospheric sounding as well as altimeter measurements of ocean surface heights, which are nowadays employed in global weather and ocean circulation models with short latencies. For example after natural disasters it is necessary to evaluate the damage by satellite images as soon as possible. The latency and quality of POD results is mainly driven by the availability of precise GPS ephemerides. In order to have high-quality GPS ephemerides available at real-time, GSOC has developed the real-time clock estimation system RETICLE. The system receives NTRIP-data streams with GNSS observations from the global tracking network of IGS in real-time. Using the known station position, RETICLE estimates precise GPS satellite clock offsets and drifts based on the most recent available IGU predicted orbits. The clock offset estimates have an accuracy of better than 0.3 ns and are globally valid. The latency of the estimated clocks is approximately 7 seconds. Another limiting factor is the frequency of satellite downlinks and the latency of the data transfer from the ground station to the computation center. Therefore a near real-time scenario is examined in which the satellite has about one ground station contact per orbit or respectively one contact in 90 minutes. The results of the near real-time POD are evaluated in an internal consistency check and compared against the science orbit solution and laser ranging observations.

New Approaches To Off-Shore Wind Energy Management Exploiting Satellite EO Data

NASA Astrophysics Data System (ADS)

Morelli, Marco; Masini, Andrea; Venafra, Sara; Potenza, Marco Alberto Carlo

2013-12-01

Wind as an energy resource has been increasingly in focus over the past decades, starting with the global oil crisis in the 1970s. The possibility of expanding wind power production to off-shore locations is attractive, especially in sites where wind levels tend to be higher and more constant. Off-shore high-potential sites for wind energy plants are currently being looked up by means of wind atlases, which are essentially based on NWP (Numerical Weather Prediction) archive data and that supply information with low spatial resolution and very low accuracy. Moreover, real-time monitoring of active off- shore wind plants is being carried out using in-situ installed anemometers, that are not very reliable (especially on long time periods) and that should be periodically substituted when malfunctions or damages occur. These activities could be greatly supported exploiting archived and near real-time satellite imagery, that could provide accurate, global coverage and high spatial resolution information about both averaged and near real-time off-shore windiness. In this work we present new methodologies aimed to support both planning and near-real-time monitoring of off-shore wind energy plants using satellite SAR(Synthetic Aperture Radar) imagery. Such methodologies are currently being developed in the scope of SATENERG, a research project funded by ASI (Italian Space Agency). SAR wind data are derived from radar backscattering using empirical geophysical model functions, thus achieving greater accuracy and greater resolution with respect to other wind measurement methods. In detail, we calculate wind speed from X-band and C- band satellite SAR data, such as Cosmo-SkyMed (XMOD2) and ERS and ENVISAT (CMOD4) respectively. Then, using also detailed models of each part of the wind plant, we are able to calculate the AC power yield expected behavior, which can be used to support either the design of potential plants (using historical series of satellite images) or the monitoring and performance analysis of active plants (using near- real-time satellite imagery). We have applied these methods in several test cases and obtained successful results in comparison with standard methodologies.

Implementing a combined polar-geostationary algorithm for smoke emissions estimation in near real time

NASA Astrophysics Data System (ADS)

Hyer, E. J.; Schmidt, C. C.; Hoffman, J.; Giglio, L.; Peterson, D. A.

2013-12-01

Polar and geostationary satellites are used operationally for fire detection and smoke source estimation by many near-real-time operational users, including operational forecast centers around the globe. The input satellite radiance data are processed by data providers to produce Level-2 and Level -3 fire detection products, but processing these data into spatially and temporally consistent estimates of fire activity requires a substantial amount of additional processing. The most significant processing steps are correction for variable coverage of the satellite observations, and correction for conditions that affect the detection efficiency of the satellite sensors. We describe a system developed by the Naval Research Laboratory (NRL) that uses the full raster information from the entire constellation to diagnose detection opportunities, calculate corrections for factors such as angular dependence of detection efficiency, and generate global estimates of fire activity at spatial and temporal scales suitable for atmospheric modeling. By incorporating these improved fire observations, smoke emissions products, such as NRL's FLAMBE, are able to produce improved estimates of global emissions. This talk provides an overview of the system, demonstrates the achievable improvement over older methods, and describes challenges for near-real-time implementation.

Flood modelling with global precipitation measurement (GPM) satellite rainfall data: a case study of Dehradun, Uttarakhand, India

NASA Astrophysics Data System (ADS)

Sai Krishna, V. V.; Dikshit, Anil Kumar; Pandey, Kamal

2016-05-01

Urban expansion, water bodies and climate change are inextricably linked with each other. The macro and micro level climate changes are leading to extreme precipitation events which have severe consequences on flooding in urban areas. Flood simulations shall be helpful in demarcation of flooded areas and effective flood planning and preparedness. The temporal availability of satellite rainfall data at varying spatial scale of 0.10 to 0.50 is helpful in near real time flood simulations. The present research aims at analysing stream flow and runoff to monitor flood condition using satellite rainfall data in a hydrologic model. The satellite rainfall data used in the research was NASA's Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG), which is available at 30 minutes temporal resolution. Landsat data was used for mapping the water bodies in the study area. Land use land cover (LULC) data was prepared using Landsat 8 data with maximum likelihood technique that was provided as an input to the HEC-HMS hydrological model. The research was applied to one of the urbanized cities of India, viz. Dehradun, which is the capital of Uttarakhand State. The research helped in identifying the flood vulnerability at the basin level on the basis of the runoff and various socio economic parameters using multi criteria analysis.

POD experiments using real and simulated time-sharing observations for GEO satellites in C-band transfer ranging system

NASA Astrophysics Data System (ADS)

Fen, Cao; XuHai, Yang; ZhiGang, Li; ChuGang, Feng

2016-08-01

The normal consecutive observing model in Chinese Area Positioning System (CAPS) can only supply observations of one GEO satellite in 1 day from one station. However, this can't satisfy the project need for observing many GEO satellites in 1 day. In order to obtain observations of several GEO satellites in 1 day like GPS/GLONASS/Galileo/BeiDou, the time-sharing observing model for GEO satellites in CAPS needs research. The principle of time-sharing observing model is illuminated with subsequent Precise Orbit Determination (POD) experiments using simulated time-sharing observations in 2005 and the real time-sharing observations in 2015. From time-sharing simulation experiments before 2014, the time-sharing observing 6 GEO satellites every 2 h has nearly the same orbit precision with the consecutive observing model. From POD experiments using the real time-sharing observations, POD precision for ZX12# and Yatai7# are about 3.234 m and 2.570 m, respectively, which indicates the time-sharing observing model is appropriate for CBTR system and can realize observing many GEO satellites in 1 day.

Improving multi-GNSS ultra-rapid orbit determination for real-time precise point positioning

NASA Astrophysics Data System (ADS)

Li, Xingxing; Chen, Xinghan; Ge, Maorong; Schuh, Harald

2018-03-01

Currently, with the rapid development of multi-constellation Global Navigation Satellite Systems (GNSS), the real-time positioning and navigation are undergoing dramatic changes with potential for a better performance. To provide more precise and reliable ultra-rapid orbits is critical for multi-GNSS real-time positioning, especially for the three merging constellations Beidou, Galileo and QZSS which are still under construction. In this contribution, we present a five-system precise orbit determination (POD) strategy to fully exploit the GPS + GLONASS + BDS + Galileo + QZSS observations from CDDIS + IGN + BKG archives for the realization of hourly five-constellation ultra-rapid orbit update. After adopting the optimized 2-day POD solution (updated every hour), the predicted orbit accuracy can be obviously improved for all the five satellite systems in comparison to the conventional 1-day POD solution (updated every 3 h). The orbit accuracy for the BDS IGSO satellites can be improved by about 80, 45 and 50% in the radial, cross and along directions, respectively, while the corresponding accuracy improvement for the BDS MEO satellites reaches about 50, 20 and 50% in the three directions, respectively. Furthermore, the multi-GNSS real-time precise point positioning (PPP) ambiguity resolution has been performed by using the improved precise satellite orbits. Numerous results indicate that combined GPS + BDS + GLONASS + Galileo (GCRE) kinematic PPP ambiguity resolution (AR) solutions can achieve the shortest time to first fix (TTFF) and highest positioning accuracy in all coordinate components. With the addition of the BDS, GLONASS and Galileo observations to the GPS-only processing, the GCRE PPP AR solution achieves the shortest average TTFF of 11 min with 7{°} cutoff elevation, while the TTFF of GPS-only, GR, GE and GC PPP AR solution is 28, 15, 20 and 17 min, respectively. As the cutoff elevation increases, the reliability and accuracy of GPS-only PPP AR solutions decrease dramatically, but there is no evident decrease for the accuracy of GCRE fixed solutions which can still achieve an accuracy of a few centimeters in the east and north components.

Hydrologic Evaluation of Integrated Multi-satellite Retrivals for GPM over Nanliu River Basin in Southern China

NASA Astrophysics Data System (ADS)

Zhenqing, L.; Sheng, C.; Chaoying, H.

2017-12-01

The core satellite of Global Precipitation Measurement (GPM) mission was launched on 27 February2014 with two core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI). The algorithm of Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH) ADDIN EN.CITE ADDIN EN.CITE.DATA , Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS).Therefore, IMERG is deemed to be the state-of-art precipitation product with high spatio-temporal resolution of 0.1°/30min. The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. Early studies about assessment of IMERG with gauge observations or analysis products show that the current version GPM Day-1 product IMERG demonstrates promising performance over China [1], Europe [2], and United States [3]. However, few studies are found to study the IMERG' potentials of hydrologic utility.In this study, the real-time and final run post real-time IMERG products are hydrologically evaluated with gauge analysis product as reference over Nanliu River basin (Fig.1) in Southern China since March 2014 to February 2017 with Xinanjiang model. Statistics metrics Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), and Nash-Sutcliffe (NSCE) index will be used to compare the stream flow simulated with IMERG to the observed stream flow. This timely hydrologic evaluation is expected to offer insights into IMERG' potentials in hydrologic utility and thus provide useful feedback to the IMERG algorithm developers and the hydrologic users.

Evaluation of NWP-based Satellite Precipitation Error Correction with Near-Real-Time Model Products and Flood-inducing Storms

NASA Astrophysics Data System (ADS)

Zhang, X.; Anagnostou, E. N.; Schwartz, C. S.

2017-12-01

Satellite precipitation products tend to have significant biases over complex terrain. Our research investigates a statistical approach for satellite precipitation adjustment based solely on numerical weather simulations. This approach has been evaluated in two mid-latitude (Zhang et al. 2013*1, Zhang et al. 2016*2) and three topical mountainous regions by using the WRF model to adjust two high-resolution satellite products i) National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center morphing technique (CMORPH) and ii) Global Satellite Mapping of Precipitation (GSMaP). Results show the adjustment effectively reduces the satellite underestimation of high rain rates, which provides a solid proof-of-concept for continuing research of NWP-based satellite correction. In this study we investigate the feasibility of using NCAR Real-time Ensemble Forecasts*3 for adjusting near-real-time satellite precipitation datasets over complex terrain areas in the Continental United States (CONUS) such as Olympic Peninsula, California coastal mountain ranges, Rocky Mountains and South Appalachians. The research will focus on flood-inducing storms occurred from May 2015 to December 2016 and four satellite precipitation products (CMORPH, GSMaP, PERSIANN-CCS and IMERG). The error correction performance evaluation will be based on comparisons against the gauge-adjusted Stage IV precipitation data. *1 Zhang, Xinxuan, et al. "Using NWP simulations in satellite rainfall estimation of heavy precipitation events over mountainous areas." Journal of Hydrometeorology 14.6 (2013): 1844-1858. *2 Zhang, Xinxuan, et al. "Hydrologic Evaluation of NWP-Adjusted CMORPH Estimates of Hurricane-Induced Precipitation in the Southern Appalachians." Journal of Hydrometeorology 17.4 (2016): 1087-1099. *3 Schwartz, Craig S., et al. "NCAR's experimental real-time convection-allowing ensemble prediction system." Weather and Forecasting 30.6 (2015): 1645-1654.

High-Resolution Near Real-Time Drought Monitoring in South Asia

NASA Astrophysics Data System (ADS)

Aadhar, S.; Mishra, V.

2017-12-01

Drought in South Asia affect food and water security and pose challenges for millions of people. For policy-making, planning and management of water resources at the sub-basin or administrative levels, high-resolution datasets of precipitation and air temperature are required in near-real time. Here we develop a high resolution (0.05 degree) bias-corrected precipitation and temperature data that can be used to monitor near real-time drought conditions over South Asia. Moreover, the dataset can be used to monitor climatic extremes (heat waves, cold waves, dry and wet anomalies) in South Asia. A distribution mapping method was applied to correct bias in precipitation and air temperature (maximum and minimum), which performed well compared to the other bias correction method based on linear scaling. Bias-corrected precipitation and temperature data were used to estimate Standardized precipitation index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) to assess the historical and current drought conditions in South Asia. We evaluated drought severity and extent against the satellite-based Normalized Difference Vegetation Index (NDVI) anomalies and satellite-driven Drought Severity Index (DSI) at 0.05˚. We find that the bias-corrected high-resolution data can effectively capture observed drought conditions as shown by the satellite-based drought estimates. High resolution near real-time dataset can provide valuable information for decision-making at district and sub- basin levels.

Improving AirNow Air Quality Products with NASA Near-Real-Time Remote Sensing Data (Invited)

NASA Astrophysics Data System (ADS)

Dye, T.; Pasch, A. N.; DeWinter, J. L.; Haderman, M.; Szykman, J.; White, J. E.; van Donkelaar, A.; Martin, R.

2013-12-01

The U.S. Environmental Protection Agency's (EPA) AirNow program provides the public with real-time and forecasted air quality conditions. Millions of people each day use it to protect their health. The AirNow program (http://www.airnow.gov), reports ground-level ozone (O3) and fine particulate matter (PM2.5) in a standardized index called the Air Quality Index (AQI). AirNow aggregates information from over 130 state, local, and federal air quality agencies and provides tools for over 2,000 agency staff responsible for monitoring, forecasting, and communicating local air quality. Each hour, AirNow systems generate thousands of maps and products. This presentation will describe how AirNow is benefiting from NASA's remote sensing data. We will describe two applications of NASA near-real-time remote sensing data within AirNow through case studies, focusing specifically on days when large spatial gradients in AQI and wildfire smoke impacts were observed. The first case study will show how AirNow is merging satellite-estimated PM2.5 concentrations into the AQI maps via the AirNow Satellite Data Processor (ASDP). AirNow derives these satellite estimates using NASA/NOAA satellite aerosol optical depth (AOD) retrievals and GEOS-Chem modeled ratios of surface PM2.5 concentrations to AOD. The second case study will show how NASA's Global Image Browse Services (GIBS) provides a near-real-time satellite product in AirNow-Tech for agency users to quickly identify smoke plumes and access air quality conditions in data-sparse areas during wildland fires.

Progress in Near Real-Time Volcanic Cloud Observations Using Satellite UV Instruments

NASA Astrophysics Data System (ADS)

Krotkov, N. A.; Yang, K.; Vicente, G.; Hughes, E. J.; Carn, S. A.; Krueger, A. J.

2011-12-01

Volcanic clouds from explosive eruptions can wreak havoc in many parts of the world, as exemplified by the 2010 eruption at the Eyjafjöll volcano in Iceland, which caused widespread disruption to air traffic and resulted in economic impacts across the globe. A suite of satellite-based systems offer the most effective means to monitor active volcanoes and to track the movement of volcanic clouds globally, providing critical information for aviation hazard mitigation. Satellite UV sensors, as part of this suite, have a long history of making unique near-real time (NRT) measurements of sulfur dioxide (SO2) and ash (aerosol Index) in volcanic clouds to supplement operational volcanic ash monitoring. Recently a NASA application project has shown that the use of near real-time (NRT,i.e., not older than 3 h) Aura/OMI satellite data produces a marked improvement in volcanic cloud detection using SO2 combined with Aerosol Index (AI) as a marker for ash. An operational online NRT OMI AI and SO2 image and data product distribution system was developed in collaboration with the NOAA Office of Satellite Data Processing and Distribution. Automated volcanic eruption alarms, and the production of volcanic cloud subsets for multiple regions are provided through the NOAA website. The data provide valuable information in support of the U.S. Federal Aviation Administration goal of a safe and efficient National Air Space. In this presentation, we will highlight the advantages of UV techniques and describe the advances in volcanic SO2 plume height estimation and enhanced volcanic ash detection using hyper-spectral UV measurements, illustrated with Aura/OMI observations of recent eruptions. We will share our plan to provide near-real-time volcanic cloud monitoring service using the Ozone Mapping and Profiler Suite (OMPS) on the Joint Polar Satellite System (JPSS).

Real Time GPS- Satellite Clock Estimation Development of a RTIGS Web Service

NASA Astrophysics Data System (ADS)

Opitz, M.; Weber, R.; Caissy, M.

2006-12-01

Since 3 years the IGS (International GNSS Service) Real-Time Working Group disseminates via Internet raw observation data of a subset of stations of the IGS network. This observation data can be used to establish a real-time integrity monitoring of the IGS predicted orbits (Ultra Rapid (IGU-) Orbits) and clocks, according to the recommendations of the IGS Workshop 2004 in Bern. The Institute for "Geodesy and Geophysics" of the TU-Vienna develops in cooperation with the IGS Real-Time Working Group the software "RTR- Control", which currently provides a real-time integrity monitoring of predicted IGU Clock Corrections to GPS Time. Our poster presents the results of a prototype version which is in operation since August this year. Besides RTR-Control allows for the comparison of pseudoranges measured at any permanent station in the global network with theoretical pseudoranges calculated on basis of the IGU- orbits. Thus, the programme can diagnose incorrectly predicted satellite orbits and clocks as well as detect multi-path distorted pseudoranges in real- time. RTR- Control calculates every 15 seconds Satellite Clock Corrections with respect to the most recent IGU- clocks (updated in a 6 hours interval). The clock estimations are referenced to a stable station clock (H-maser) with a small offset to GPS- time. This real-time Satellite Clocks are corrected for individual outliers and modelling errors. The most recent GPS- Satellite Clock Corrections (updated every 60 seconds) are published in Real Time via the Internet. The user group interested in a rigorous integrity monitoring comprises on the one hand the components of IGS itself to qualify the issued orbital data and on the other hand all users of the IGS Ultra Rapid Products (e.g. for PPP in Real Time).

Advances in Spatial Data Infrastructure, Acquisition, Analysis, Archiving and Dissemination

NASA Technical Reports Server (NTRS)

Ramapriyan, Hampapuran K.; Rochon, Gilbert L.; Duerr, Ruth; Rank, Robert; Nativi, Stefano; Stocker, Erich Franz

2010-01-01

The authors review recent contributions to the state-of-thescience and benign proliferation of satellite remote sensing, spatial data infrastructure, near-real-time data acquisition, analysis on high performance computing platforms, sapient archiving, multi-modal dissemination and utilization for a wide array of scientific applications. The authors also address advances in Geoinformatics and its growing ubiquity, as evidenced by its inclusion as a focus area within the American Geophysical Union (AGU), European Geosciences Union (EGU), as well as by the evolution of the IEEE Geoscience and Remote Sensing Society's (GRSS) Data Archiving and Distribution Technical Committee (DAD TC).

Near-real time Monitoring of the widespread winter Fog over the Indo-Gangetic Plains using satellite data

NASA Astrophysics Data System (ADS)

Patil, D. L.; Gautam, R.; Rizvi, S.; Singh, M. K.

2016-12-01

The persistent and widespread winter fog impacts the Indo-Gangetic Plains (IGP) on an annual basis, disrupting day-to-day lives of millions of people in parts of northern India, Pakistan, Nepal and Bangladesh. The IGP is a densely-populated region located south of the Himalaya, in the northern parts of south Asia. During the past three decades or so, associated with growing population and energy demands, the IGP has witnessed strong upward trends in air pollution, particularly leading to poor air quality in the winter months. Co-occurring with the dense haze over the IGP, severe fog episodes persist throughout the months of December and January. Building on our recent work on satellite-based detection of fog, we have further extended the detection capability towards the development of a near-real time (NRT) fog monitoring system using satellite radiances and products. Here, we use multi-spectral radiances and aerosol/cloud retrievals from Terra/Aqua MODIS data for NRT fog monitoring over the IGP for both daytime as well as nighttime. Specifically, the nighttime fog detection algorithm employs a bi-spectral brightness temperature difference technique between two spectral channels: 3.9 μm and 11 μm. Our ongoing efforts also include extending fog detection capability in NRT to geostationary satellites, for providing continuous monitoring of the onset, evolution and spatial-temporal variation of fog, as well as the geospatial integration of surface meteorological observations of visibility, relative humidity, temperature. We anticipate that the ongoing and future development of a fog monitoring system may be of particular assistance to air and rail transportation management, as well as of general interest to the public. The outputs of fog detection algorithm and related aerosol/cloud parameters are operationally disseminated via http://fogsouthasia.com/.

Global multi-sensor satellite monitoring of volcanic SO2 and ash emissions in support to aviation control

NASA Astrophysics Data System (ADS)

Brenot, H.; Theys, N.; van Gent, J.; Van Roozendael, M.; van der A, R.; Clarisse, L.; Hurtmans, D.; Ngadi, Y.; Coheur, P.-F.; Clerbaux, C.

2012-04-01

The "Support to Aviation Control Service" (SACS; http://sacs.aeronomie.be) is an ESA-funded project hosted by the Belgian Institute for Space Aeronomy. The service provides near real-time (NRT) global SO2 and volcanic ash data, as well as alerts in case of volcanic eruptions. The SACS service is primarily designed to support the Volcanic Ash Advisory Centers (VAACs) in their mandate to gather information on volcanic clouds and give advice to airline and air traffic control organisations. SACS also serves other users that subscribe to the service, in particular local volcano observatories and research scientists. SACS is based on the combined use of UV-visible (SCIAMACHY, OMI, GOME-2) and infrared (AIRS, IASI) satellite instruments. When a volcanic eruption is detected, SACS issues an alert that takes the form of a notification sent by e-mail to users. This notification points to a dedicated web page where all relevant information is available and can be visualized with user-friendly tools. The strength of a multi-sensor approach relies in the use of satellite data with different overpasses times, minimizing the time-lag for detection and enhancing the reliability of such alerts. This paper will give a general presentation of the SACS service, different techniques used to detect volcanic plumes. It will also highlight the strengths and limitations of the service and measurements.

U. S. GEOLOGICAL SURVEY'S NATIONAL REAL-TIME HYDROLOGIC INFORMATION SYSTEM USING GOES SATELLITE TECHNOLOGY.

USGS Publications Warehouse

Shope, William G.

1987-01-01

The U. S. Geological Survey maintains the basic hydrologic data collection system for the United States. The Survey is upgrading the collection system with electronic communications technologies that acquire, telemeter, process, and disseminate hydrologic data in near real-time. These technologies include satellite communications via the Geostationary Operational Environmental Satellite, Data Collection Platforms in operation at over 1400 Survey gaging stations, Direct-Readout Ground Stations at nine Survey District Offices and a network of powerful minicomputers that allows data to be processed and disseminate quickly.

Predicting Near Real-Time Inundation Occurrence from Complimentary Satellite Microwave Brightness Temperature Observations

NASA Astrophysics Data System (ADS)

Fisher, C. K.; Pan, M.; Wood, E. F.

2017-12-01

Throughout the world, there is an increasing need for new methods and data that can aid decision makers, emergency responders and scientists in the monitoring of flood events as they happen. In many regions, it is possible to examine the extent of historical and real-time inundation occurrence from visible and infrared imagery provided by sensors such as MODIS or the Landsat TM; however, this is not possible in regions that are densely vegetated or are under persistent cloud cover. In addition, there is often a temporal mismatch between the sampling of a particular sensor and a given flood event, leading to limited observations in near real-time. As a result, there is a need for alternative methods that take full advantage of complimentary remotely sensed data sources, such as available microwave brightness temperature observations (e.g., SMAP, SMOS, AMSR2, AMSR-E, and GMI), to aid in the estimation of global flooding. The objective of this work was to develop a high-resolution mapping of inundated areas derived from multiple satellite microwave sensor observations with a daily temporal resolution. This system consists of first retrieving water fractions from complimentary microwave sensors (AMSR-2 and SMAP) which may spatially and temporally overlap in the region of interest. Using additional information in a Random Forest classifier, including high resolution topography and multiple datasets of inundated area (both historical and empirical), the resulting retrievals are spatially downscaled to derive estimates of the extent of inundation at a scale relevant to management and flood response activities ( 90m or better) instead of the relatively coarse resolution water fractions, which are limited by the microwave sensor footprints ( 5-50km). Here we present the training and validation of this method for the 2015 floods that occurred in Houston, Texas. Comparing the predicted inundation against historical occurrence maps derived from the Landsat TM record and MODIS imagery, we find good agreement for most areas and are able to provide a daily mapping given the increased temporal coverage. These results illustrate the feasibility of a near real-time inundation prediction system driven by multi-sensor satellite microwave observations, which can be extended to provide a daily estimate of global flooding.

Characteristics of recent dust storms over the Indian region using real time multi-satellite observations from the direct broadcast receiving system at IMD

NASA Astrophysics Data System (ADS)

Mitra, A. K.; Sharma, A. K.; Soni, V. K.; Kundu, P. K.

2013-04-01

In this study, observations from microwave satellites, visible and infrared instruments have been analyzed to detect dust storm over north and north-west part of India during 18-23 March 2012. This study investigated the approach to utilize the multi satellite data of Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the Terra and Aqua satellite and the Advanced Microwave Sounding Unit (AMSU) on-board NOAA satellite to study the characteristics of dust storms from real time direct broadcast (DB) receiving system installed at three places of India Meteorological Department (IMD). The dust storm detection is based on the infrared brightness temperature (BT) difference between channels at 11 and 12 μm and polarized BT difference between two channels of 89 and 23.8 GHz. It is found that the significant differences between the BT of channel 89 and 23.8 can be used as a discriminator of identifying dust storm. The Total Ozone Mapping Spectroradiometer (TOMS) Aerosol Index (AI) and AMSU-A 23 GHz channel BT from NOAA satellite over the north and north-west part of India have also been analyzed. The result indicated the characteristic behavior between BT and AI during the different phases of the dust storm. Finally, the occurrence of dust outbreaks has also been validated with sky radiometer of IMD, which confirms the presence of a dust storm over the Indian region. Further, the findings of the study and its approaches apply to the other dust storm cases which occurred during the months of April and June 2012. The integrated approach suggested the potential to use high resolution data of microwave as well as thermal-infrared using multi-satellite observations from real time direct broadcast system for the detection of severe, moderate or weak dust storms very well. The approach is found to be promising for operational application.

Use of NASA Near Real-Time and Archived Satellite Data to Support Disaster Assessment

NASA Technical Reports Server (NTRS)

McGrath, Kevin M.; Molthan, Andrew L.; Burks, Jason E.

2014-01-01

NASA's Short-term Prediction Research and Transition (SPoRT) Center partners with the NWS to provide near realtime data in support of a variety of weather applications, including disasters. SPoRT supports NASA's Applied Sciences Program: Disasters focus area by developing techniques that will aid the disaster monitoring, response, and assessment communities. SPoRT has explored a variety of techniques for utilizing archived and near real-time NASA satellite data. An increasing number of end-users - such as the NWS Damage Assessment Toolkit (DAT) - access geospatial data via a Web Mapping Service (WMS). SPoRT has begun developing open-standard Geographic Information Systems (GIS) data sets via WMS to respond to end-user needs.

Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa

NASA Astrophysics Data System (ADS)

Demaria, E. M.; Valdes, J. B.; Wi, S.; Serrat-Capdevila, A.; Valdés-Pineda, R.; Durcik, M.

2016-12-01

In under-instrumented basins around the world, accurate and timely forecasts of river streamflows have the potential of assisting water and natural resource managers in their management decisions. The Upper Zambezi river basin is the largest basin in southern Africa and its water resources are critical to sustainable economic growth and poverty reduction in eight riparian countries. We present a real-time streamflow forecast for the basin using a multi-model-multi-satellite approach that allows accounting for model and input uncertainties. Three distributed hydrologic models with different levels of complexity: VIC, HYMOD_DS, and HBV_DS are setup at a daily time step and a 0.25 degree spatial resolution for the basin. The hydrologic models are calibrated against daily observed streamflows at the Katima-Mulilo station using a Genetic Algorithm. Three real-time satellite products: Climate Prediction Center's morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Tropical Rainfall Measuring Mission (TRMM-3B42RT) are bias-corrected with daily CHIRPS estimates. Uncertainty bounds for predicted flows are estimated with the Inverse Variance Weighting method. Because concentration times in the basin range from a few days to more than a week, we include the use of precipitation forecasts from the Global Forecasting System (GFS) to predict daily streamflows in the basin with a 10-days lead time. The skill of GFS-predicted streamflows is evaluated and the usefulness of the forecasts for short term water allocations is presented.

SIMSAT: An object oriented architecture for real-time satellite simulation

NASA Technical Reports Server (NTRS)

Williams, Adam P.

1993-01-01

Real-time satellite simulators are vital tools in the support of satellite missions. They are used in the testing of ground control systems, the training of operators, the validation of operational procedures, and the development of contingency plans. The simulators must provide high-fidelity modeling of the satellite, which requires detailed system information, much of which is not available until relatively near launch. The short time-scales and resulting high productivity required of such simulator developments culminates in the need for a reusable infrastructure which can be used as a basis for each simulator. This paper describes a major new simulation infrastructure package, the Software Infrastructure for Modelling Satellites (SIMSAT). It outlines the object oriented design methodology used, describes the resulting design, and discusses the advantages and disadvantages experienced in applying the methodology.

Fast-PPP assessment in European and equatorial region near the solar cycle maximum

NASA Astrophysics Data System (ADS)

Rovira-Garcia, Adria; Juan, José Miguel; Sanz, Jaume

2014-05-01

The Fast Precise Point Positioning (Fast-PPP) is a technique to provide quick high-accuracy navigation with ambiguity fixing capability, thanks to an accurate modelling of the ionosphere. Indeed, once the availability of real-time precise satellite orbits and clocks is granted to users, the next challenge is the accuracy of real-time ionospheric corrections. Several steps had been taken by gAGE/UPC to develop such global system for precise navigation. First Wide-Area Real-Time Kinematics (WARTK) feasibility studies enabled precise relative continental navigation using a few tens of reference stations. Later multi-frequency and multi-constellation assessments in different ionospheric scenarios, including maximum solar-cycle conditions, were focussed on user-domain performance. Recently, a mature evolution of the technique consists on a dual service scheme; a global Precise Point Positioning (PPP) service, together with a continental enhancement to shorten convergence. A end to end performance assessment of the Fast-PPP technique is presented in this work, focussed in Europe and in the equatorial region of South East Asia (SEA), both near the solar cycle maximum. The accuracy of the Central Processing Facility (CPF) real-time precise satellite orbits and clocks is respectively, 4 centimetres and 0.2 nanoseconds, in line with the accuracy of the International GNSS Service (IGS) analysis centres. This global PPP service is enhanced by the Fast-PPP by adding the capability of global undifferenced ambiguity fixing thanks to the fractional part of the ambiguities determination. The core of the Fast-PPP is the capability to compute real-time ionospheric determinations with accuracies at the level or better than 1 Total Electron Content Unit (TECU), improving the widely-accepted Global Ionospheric Maps (GIM), with declared accuracies of 2-8 TECU. This large improvement in the modelling accuracy is achieved thanks to a two-layer description of the ionosphere combined with the carrier-phase ambiguity fixing performed in the Fast-PPP CPF. The Fast-PPP user domain positioning takes benefit of such precise ionospheric modelling. Convergence time of dual-frequency classic PPP solutions is reduced from the best part of an hour to 5-10 minutes not only in European mid-latitudes but also in the much more challenging equatorial region. The improvement of ionospheric modelling is directly translated into the accuracy of single-frequency mass-market users, achieving 2-3 decimetres of error after any cold start. Since all Fast-PPP corrections are broadcast together with their confidence level (sigma), such high-accuracy navigation is protected with safety integrity bounds.

Operational Use of Near Real Time Remote sensing Data at the U.S. National Ice Center (NIC)

NASA Astrophysics Data System (ADS)

Clemente-Colon, P.

2012-12-01

The National Ice Center (NIC) is a U.S. Government agency that brings together the Department of Defense - Navy, Department of Commerce - National Oceanic and Atmospheric Administration (NOAA), and the Department of Homeland Security - U.S. Coast Guard (USCG) to support coastal and marine sea ice operations and research in the Polar Regions. The NIC provides specialized strategic and tactical ice analyses to meet the operational needs of the U.S. government and is the only operational ice service in the world that monitors sea ice in both the Arctic, Antarctic regions as well as in other ice infested waters. NIC utilizes multiple sources of near real time satellite and in-situ observations as well as NWP and ocean-sea ice model output to produce sea ice analyses. Key users of NIC products in the Arctic include the Navy submarine force, National Weather Service, USCG and Canadian Coast Guard icebreakers, Military Sealift Command on re-supply missions to Antarctica and Greenland, and NOAA research vessels operating near sea ice cover in both hemispheres as well. Time series of NIC weekly or bi-weekly ice analysis charts, daily marginal ice zone and ice edge routine products, as well as tactical support annotated imagery are generated by expert analysts with wide access to near real time satellite imagery from VIS/IR to passive and active microwave sensors. The status of these satellite data streams and the expected availability of new capabilities in the near future will be discussed.

Soil Moisture Drought Monitoring and Forecasting Using Satellite and Climate Model Data over Southwestern China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xuejun; Tang, Qiuhong; Liu, Xingcai

Real-time monitoring and predicting drought development with several months in advance is of critical importance for drought risk adaptation and mitigation. In this paper, we present a drought monitoring and seasonal forecasting framework based on the Variable Infiltration Capacity (VIC) hydrologic model over Southwest China (SW). The satellite precipitation data are used to force VIC model for near real-time estimate of land surface hydrologic conditions. As initialized with satellite-aided monitoring, the climate model-based forecast (CFSv2_VIC) and ensemble streamflow prediction (ESP)-based forecast (ESP_VIC) are both performed and evaluated through their ability in reproducing the evolution of the 2009/2010 severe drought overmore » SW. The results show that the satellite-aided monitoring is able to provide reasonable estimate of forecast initial conditions (ICs) in a real-time manner. Both of CFSv2_VIC and ESP_VIC exhibit comparable performance against the observation-based estimates for the first month, whereas the predictive skill largely drops beyond 1-month. Compared to ESP_VIC, CFSv2_VIC shows better performance as indicated by the smaller ensemble range. This study highlights the value of this operational framework in generating near real-time ICs and giving a reliable prediction with 1-month ahead, which has great implications for drought risk assessment, preparation and relief.« less

Volcview: A Web-Based Platform for Satellite Monitoring of Volcanic Activity and Eruption Response

NASA Astrophysics Data System (ADS)

Schneider, D. J.; Randall, M.; Parker, T.

2014-12-01

The U.S. Geological Survey (USGS), in cooperation with University and State partners, operates five volcano observatories that employ specialized software packages and computer systems to process and display real-time data coming from in-situ geophysical sensors and from near-real-time satellite sources. However, access to these systems both inside and from outside the observatory offices are limited in some cases by factors such as software cost, network security, and bandwidth. Thus, a variety of Internet-based tools have been developed by the USGS Volcano Science Center to: 1) Improve accessibility to data sources for staff scientists across volcano monitoring disciplines; 2) Allow access for observatory partners and for after-hours, on-call duty scientists; 3) Provide situational awareness for emergency managers and the general public. Herein we describe VolcView (volcview.wr.usgs.gov), a freely available, web-based platform for display and analysis of near-real-time satellite data. Initial geographic coverage is of the volcanoes in Alaska, the Russian Far East, and the Commonwealth of the Northern Mariana Islands. Coverage of other volcanoes in the United States will be added in the future. Near-real-time satellite data from NOAA, NASA and JMA satellite systems are processed to create image products for detection of elevated surface temperatures and volcanic ash and SO2 clouds. VolcView uses HTML5 and the canvas element to provide image overlays (volcano location and alert status, annotation, and location information) and image products that can be queried to provide data values, location and measurement capabilities. Use over the past year during the eruptions of Pavlof, Veniaminof, and Cleveland volcanoes in Alaska by the Alaska Volcano Observatory, the National Weather Service, and the U.S. Air Force has reinforced the utility of shared situational awareness and has guided further development. These include overlay of volcanic cloud trajectory and dispersion models, atmospheric temperature profiles, and incorporation of monitoring alerts from ground and satellite-based algorithms. Challenges for future development include reducing the latency in satellite data reception and processing, and increasing the geographic coverage from polar-orbiting satellite platforms.

Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Smith, William L., Jr.; Bedka, Kristopher M.; Nguyen, Louis; Palikonda, Rabindra; Hong, Gang; Trepte, Qing Z.; Chee, Thad; Scarino, Benjamin; Spangenberg, Douglas A.;

Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

NASA Astrophysics Data System (ADS)

Minnis, P.; Smith, W., Jr.; Bedka, K. M.; Nguyen, L.; Palikonda, R.; Hong, G.; Trepte, Q.; Chee, T.; Scarino, B. R.; Spangenberg, D.; Sun-Mack, S.; Fleeger, C.; Ayers, J. K.; Chang, F. L.; Heck, P. W.

2014-12-01

Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-real time globally from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

Near-real-time global biomass burning emissions product from geostationary satellite constellation

NASA Astrophysics Data System (ADS)

Zhang, Xiaoyang; Kondragunta, Shobha; Ram, Jessica; Schmidt, Christopher; Huang, Ho-Chun

2012-07-01

Near-real-time estimates of biomass burning emissions are crucial for air quality monitoring and forecasting. We present here the first near-real-time global biomass burning emission product from geostationary satellites (GBBEP-Geo) produced from satellite-derived fire radiative power (FRP) for individual fire pixels. Specifically, the FRP is retrieved using WF_ABBA V65 (wildfire automated biomass burning algorithm) from a network of multiple geostationary satellites. The network consists of two Geostationary Operational Environmental Satellites (GOES) which are operated by the National Oceanic and Atmospheric Administration, the Meteosat second-generation satellites (Meteosat-09) operated by the European Organisation for the Exploitation of Meteorological Satellites, and the Multifunctional Transport Satellite (MTSAT) operated by the Japan Meteorological Agency. These satellites observe wildfires at an interval of 15-30 min. Because of the impacts from sensor saturation, cloud cover, and background surface, the FRP values are generally not continuously observed. The missing observations are simulated by combining the available instantaneous FRP observations within a day and a set of representative climatological diurnal patterns of FRP for various ecosystems. Finally, the simulated diurnal variation in FRP is applied to quantify biomass combustion and emissions in individual fire pixels with a latency of 1 day. By analyzing global patterns in hourly biomass burning emissions in 2010, we find that peak fire season varied greatly and that annual wildfires burned 1.33 × 1012 kg dry mass, released 1.27 × 1010 kg of PM2.5 (particulate mass for particles with diameter <2.5 μm) and 1.18 × 1011kg of CO globally (excluding most parts of boreal Asia, the Middle East, and India because of no coverage from geostationary satellites). The biomass burning emissions were mostly released from forest and savanna fires in Africa, South America, and North America. Evaluation of emission result reveals that the GBBEP-Geo estimates are comparable with other FRP-derived estimates in Africa, while the results are generally smaller than most of the other global products that were derived from burned area and fuel loading. However, the daily emissions estimated from GOES FRP over the United States are generally consistent with those modeled from GOES burned area and MODIS (Moderate Resolution Imaging Spectroradiometer) fuel loading, which produces an overall bias of 5.7% and a correlation slope of 0.97 ± 0.2. It is expected that near-real-time hourly emissions from GBBEP-Geo could provide a crucial component for atmospheric and chemical transport modelers to forecast air quality and weather conditions.

Uncloaking the Scientific Process

NASA Astrophysics Data System (ADS)

Leitzell, K.; Meier, W.

2009-12-01

Since April 2008, NSIDC has offered daily updates of sea ice data on our Arctic Sea Ice News & Analysis Web page (http://nsidc.org/arcticseaicenews). The images provide near-real-time data to the general public and policy makers, accompanied by monthly or more frequent analysis updates. In February 2009, a crucial channel of the Special Sensor Microwave/Imager (SSM/I) sensor on the Defense Meteorological Satellite Program (DMSP) F15 satellite, from which NSIDC was obtaining near-real-time Arctic sea ice data, suddenly failed. The daily image, which is automatically updated, showed a sudden drop in ice extent of over 50,000 square kilometers. Even after taking the images down, skeptical blogs jumped on the event, posting headlines such as “Errors in publicly presented data - Worth blogging about?” and “NSIDC pulls the plug on sea ice data.” In fact, NSIDC data managers and scientists were well aware that the F15 satellite sensor would eventually fail. NSIDC switched to a previously used back-up sensor, F13, and work to transition to a newer sensor on the F17 satellite had been underway for several weeks. While the deluge of questions from readers and bloggers were frustrating to NSIDC communications staff and scientists, they also presented a chance to give readers a window into the scientific process, and specifically into the collection of satellite data. We decided to publish a clear account of the process used to transition between sensors, as well as a basic explanation of the satellites used to measure sea ice data. While most scientists are familiar with the limitations of near-real-time data, the concept is unfamiliar to many in the general public. The Web page includes links to information on near-real-time data, including notes that images sometimes contain missing or erroneous data, and that delays can occur. However, to a skeptical person, the words that scientists use to describe the processing of final data, including “adjustment,” “bias,” and “correction,” can convey a sinister or political motive. How much information is really necessary for the general public? How much should we share about our processes and motives? This poster/presentation will address some of the dangers and opportunities of presenting near-real-time data to the public, and share some of strategies we used to respond to attacks on our data quality. In order to develop effective responses to climate change, it is important for policymakers to focus on complete data records and not short-term variability in near-real-time data, which may not be indicative of long-term trends or, as in the case presented here, may have errors that need to be corrected. NSIDC clearly states that its near-real-time images and data should not be used for significant conclusions about the long-term state of the climate, but are an initial snapshot for informational purposes. Nonetheless, NSIDC did hear from some policymakers that our data was regularly being used in various briefs within governmental agencies. This has led to greater attention to how our data may be used. However, we hope that our transparency and clear explanations will be valuable in guiding how policymakers employ our data and images in the future.

An efficient solution of real-time data processing for multi-GNSS network

NASA Astrophysics Data System (ADS)

Gong, Xiaopeng; Gu, Shengfeng; Lou, Yidong; Zheng, Fu; Ge, Maorong; Liu, Jingnan

2017-12-01

Global navigation satellite systems (GNSS) are acting as an indispensable tool for geodetic research and global monitoring of the Earth, and they have been rapidly developed over the past few years with abundant GNSS networks, modern constellations, and significant improvement in mathematic models of data processing. However, due to the increasing number of satellites and stations, the computational efficiency becomes a key issue and it could hamper the further development of GNSS applications. In this contribution, this problem is overcome from the aspects of both dense linear algebra algorithms and GNSS processing strategy. First, in order to fully explore the power of modern microprocessors, the square root information filter solution based on the blocked QR factorization employing as many matrix-matrix operations as possible is introduced. In addition, the algorithm complexity of GNSS data processing is further decreased by centralizing the carrier-phase observations and ambiguity parameters, as well as performing the real-time ambiguity resolution and elimination. Based on the QR factorization of the simulated matrix, we can conclude that compared to unblocked QR factorization, the blocked QR factorization can greatly improve processing efficiency with a magnitude of nearly two orders on a personal computer with four 3.30 GHz cores. Then, with 82 globally distributed stations, the processing efficiency is further validated in multi-GNSS (GPS/BDS/Galileo) satellite clock estimation. The results suggest that it will take about 31.38 s per epoch for the unblocked method. While, without any loss of accuracy, it only takes 0.50 and 0.31 s for our new algorithm per epoch for float and fixed clock solutions, respectively.

An improved RST approach for timely alert and Near Real Time monitoring of oil spill disasters by using AVHRR data

NASA Astrophysics Data System (ADS)

Grimaldi, C. S. L.; Casciello, D.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

2011-05-01

Information acquired and provided in Near Real Time is fundamental in contributing to reduce the impact of different sea pollution sources on the maritime environment. Optical data acquired by sensors aboard meteorological satellites, thanks to their high temporal resolution as well as to their delivery policy, can be profitably used for a Near Real Time sea monitoring, provided that accurate and reliable methodologies for analysis and investigation are designed, implemented and fully assessed. In this paper, the results achieved by the application of an improved version of RST (Robust Satellite Technique) to oil spill detection and monitoring will be shown. In particular, thermal infrared data acquired by the NOAA-AVHRR (National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer) have been analyzed and a new RST-based change detection index applied to the case of the oil spills that occurred off the Kuwait and Saudi Arabian coasts in January 1991 and during the Lebanon War in July 2006. The results obtained, even in comparison with those achieved by other AVHRR-based techniques, confirm the unique performance of the proposed approach in automatically detecting the presence of oil spill with a high level of reliability and sensitivity. Moreover, the potential of the extension of the proposed technique to sensors onboard geostationary satellites will be discussed within the context of oil spill monitoring systems, integrating products generated by high temporal (optical) and high spatial (radar) resolution satellite systems.

Approaches and Data Quality for Global Precipitation Estimation

NASA Astrophysics Data System (ADS)

Huffman, G. J.; Bolvin, D. T.; Nelkin, E. J.

2015-12-01

The space and time scales on which precipitation varies are small compared to the satellite coverage that we have, so it is necessary to merge "all" of the available satellite estimates. Differing retrieval capabilities from the various satellites require inter-calibration for the satellite estimates, while "morphing", i.e., Lagrangian time interpolation, is used to lengthen the period over which time interpolation is valid. Additionally, estimates from geostationary-Earth-orbit infrared data are plentiful, but of sufficiently lower quality compared to low-Earth-orbit passive microwave estimates that they are only used when needed. Finally, monthly surface precipitation gauge data can be used to reduce bias and improve patterns of occurrence for monthly satellite data, and short-interval satellite estimates can be improved with a simple scaling such that they sum to the monthly satellite-gauge combination. The presentation will briefly consider some of the design decisions for practical computation of the Global Precipitation Measurement (GPM) mission product Integrated Multi-satellitE Retrievals for GPM (IMERG), then examine design choices that maximize value for end users. For example, data fields are provided in the output file that provide insight into the basis for the estimated precipitation, including error, sensor providing the estimate, precipitation phase (solid/liquid), and intermediate precipitation estimates. Another important initiative is successive computations for the same data date/time at longer latencies as additional data are received, which for IMERG is currently done at 6 hours, 16 hours, and 3 months after observation time. Importantly, users require long records for each latency, which runs counter to the data archiving practices at most archive sites. As well, the assignment of Digital Object Identifiers (DOI's) for near-real-time data sets (at 6 and 16 hours for IMERG) is not a settled issue.

All-weather ice information system for Alaskan arctic coastal shipping

NASA Technical Reports Server (NTRS)

Gedney, R. T.; Jirberg, R. J.; Schertler, R. J.; Mueller, R. A.; Chase, T. L.; Kramarchuk, I.; Nagy, L. A.; Hanlon, R. A.; Mark, H.

1977-01-01

A near real-time ice information system designed to aid arctic coast shipping along the Alaskan North Slope is described. The system utilizes a X-band Side Looking Airborne Radar (SLAR) mounted aboard a U.S. Coast Guard HC-130B aircraft. Radar mapping procedures showing the type, areal distribution and concentration of ice cover were developed. In order to guide vessel operational movements, near real-time SLAR image data were transmitted directly from the SLAR aircraft to Barrow, Alaska and the U.S. Coast Guard icebreaker Glacier. In addition, SLAR image data were transmitted in real time to Cleveland, Ohio via the NOAA-GOES Satellite. Radar images developed in Cleveland were subsequently facsimile transmitted to the U.S. Navy's Fleet Weather Facility in Suitland, Maryland for use in ice forecasting and also as a demonstration back to Barrow via the Communications Technology Satellite.

Near real time observational data collection for SPRUCE experiment- PakBus protocol for slow satellite connections

NASA Astrophysics Data System (ADS)

Krassovski, Misha; Hanson, Paul; Riggs, Jeff

2017-04-01

Climate change studies are one of the most important aspects of modern science and related experiments are getting bigger and more complex. One such experiment is the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE, http://mnspruce.ornl.gov) conducted in in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. This manipulation experiment generates a lot of observational data and requires a reliable onsite data collection system, dependable methods to transfer data to a robust scientific facility, and real-time monitoring capabilities. This publication shares our experience of establishing near real time data collection and monitoring system via a satellite link using PakBus protocol.

Rainfall estimation for real time flood monitoring using geostationary meteorological satellite data

NASA Astrophysics Data System (ADS)

Veerakachen, Watcharee; Raksapatcharawong, Mongkol

2015-09-01

Rainfall estimation by geostationary meteorological satellite data provides good spatial and temporal resolutions. This is advantageous for real time flood monitoring and warning systems. However, a rainfall estimation algorithm developed in one region needs to be adjusted for another climatic region. This work proposes computationally-efficient rainfall estimation algorithms based on an Infrared Threshold Rainfall (ITR) method calibrated with regional ground truth. Hourly rain gauge data collected from 70 stations around the Chao-Phraya river basin were used for calibration and validation of the algorithms. The algorithm inputs were derived from FY-2E satellite observations consisting of infrared and water vapor imagery. The results were compared with the Global Satellite Mapping of Precipitation (GSMaP) near real time product (GSMaP_NRT) using the probability of detection (POD), root mean square error (RMSE) and linear correlation coefficient (CC) as performance indices. Comparison with the GSMaP_NRT product for real time monitoring purpose shows that hourly rain estimates from the proposed algorithm with the error adjustment technique (ITR_EA) offers higher POD and approximately the same RMSE and CC with less data latency.

Application of satellite radar altimetry for near-real time monitoring of floods

NASA Astrophysics Data System (ADS)

Lee, H.; Calmant, S.; Shum, C.; Kim, J.; Huang, Z.; Bettadpur, S. V.; Alsdorf, D. E.

2011-12-01

According to the 2004 UNESCO World Disasters Report, it is estimated that flooding affected 116 million people globally, causing about 7000 deaths and leading to $7.5 billion in losses. The report also indicates that flood is the most frequently occurring disaster type among all other natural disasters. Hence, timely monitoring of changing of river, wetland and lake/reservoir levels is important to support disaster monitoring and proper response. Yet, we have surprisingly poor knowledge of the spatial and temporal dynamics of surface water discharge and storage changes globally. Although satellite radar altimetry has been successfully used to observe water height changes over rivers, lakes, reservoirs, and wetlands, there have been few studies for near-real time monitoring of floods mainly due to its limited spatial and temporal sampling of surface water elevations. In this study, we monitor flood by examining its spatial and temporal origin of the flooding and its timely propagation using multiple altimeter-river intersections over the entire hydrologic basin. We apply our method to the Amazon 2009 flood event that caused the most severe flooding in more than two decades. We also compare our results with inundated areas estimated from ALOS PALSAR ScanSAR measurements and GRACE 15-day Quick-Look (QL) gravity field data product. Our developed method would potentially enhance the capability of satellite altimeter toward near-real time monitoring of floods and mitigating their hazards.

Evaluation and analysis of real-time precise orbits and clocks products from different IGS analysis centers

NASA Astrophysics Data System (ADS)

Zhang, Liang; Yang, Hongzhou; Gao, Yang; Yao, Yibin; Xu, Chaoqian

2018-06-01

To meet the increasing demands from the real-time Precise Point Positioning (PPP) users, the real-time satellite orbit and clock products are generated by different International GNSS Service (IGS) real-time analysis centers and can be publicly received through the Internet. Based on different data sources and processing strategies, the real-time products from different analysis centers therefore differ in availability and accuracy. The main objective of this paper is to evaluate availability and accuracy of different real-time products and their effects on real-time PPP. A total of nine commonly used Real-Time Service (RTS) products, namely IGS01, IGS03, CLK01, CLK15, CLK22, CLK52, CLK70, CLK81 and CLK90, will be evaluated in this paper. Because not all RTS products support multi-GNSS, only GPS products are analyzed in this paper. Firstly, the availability of all RTS products is analyzed in two levels. The first level is the epoch availability, indicating whether there is outage for that epoch. The second level is the satellite availability, which defines the available satellite number for each epoch. Then the accuracy of different RTS products is investigated on nominal accuracy and the accuracy degradation over time. Results show that Root-Mean-Square Error (RMSE) of satellite orbit ranges from 3.8 cm to 7.5 cm for different RTS products. While the mean Standard Deviations of Errors (STDE) of satellite clocks range from 1.9 cm to 5.6 cm. The modified Signal In Space Range Error (SISRE) for all products are from 1.3 cm to 5.5 cm for different RTS products. The accuracy degradation of the orbit has the linear trend for all RTS products and the satellite clock degradation depends on the satellite clock types. The Rb clocks on board of GPS IIF satellites have the smallest degradation rate of less than 3 cm over 10 min while the Cs clocks on board of GPS IIF have the largest degradation rate of more than 10 cm over 10 min. Finally, the real-time kinematic PPP is carried out to investigate the effects of different real-time products. The CLK90 has the best performance and mean RMSE of 26 globally distributed IGS stations in three components are 3.2 cm, 6.6 cm and 8.5 cm. And the second-best positioning results are using IGS03 products.

A Global Landslide Nowcasting System using Remotely Sensed Information

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Stanely, Thomas

2017-04-01

A global Landslide Hazard Assessment model for Situational Awareness (LHASA) has been developed that combines susceptibility information with satellite-based precipitation to provide an indication of potential landslide activity at the global scale every 30 minutes. This model utilizes a 1-km global susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. A multi-satellite dataset from the Global Precipitation Measurement (GPM) mission is used to identify the current and antecedent rainfall conditions from the past 7 days. When both rainfall and susceptibility are high, a "nowcast" is issued to indicate areas where a landslide may be likely. The global LHASA model is currently being run in near real-time every 30 minutes and the outputs are available in several different formats at https://pmm.nasa.gov/precip-apps. This talk outlines the LHASA system, discusses the performance metrics and potential applications of the LHASA system.

The University of Colorado OSO-8 spectrometer experiment. IV - Mission operations

NASA Technical Reports Server (NTRS)

Hansen, E. R.; Bruner, E. C., Jr.

1979-01-01

The remote operation of two high-resolution ultraviolet spectrometers on the OSO-8 satellite is discussed. Mission operations enabled scientific observers to plan observations based on current solar data, interact with the observing program using real- or near real-time data and commands, evaluate quick-look instrument data, and analyze the observations for publication. During routine operations, experiments were planned a day prior to their execution, and the data from these experiments received a day later. When a shorter turnaround was required, a real-time mode was available. Here, the real-time data and command links into the remote control center were used to evaluate experiment operation and make satellite pointing or instrument configuration changes with a 1-90 minute turnaround.

Earth Observation Data Quality Monitoring and Control: A Case Study of STAR Central Data Repository

NASA Astrophysics Data System (ADS)

Han, W.; Jochum, M.

2017-12-01

Earth observation data quality is very important for researchers and decision makers involved in weather forecasting, severe weather warning, disaster and emergency response, environmental monitoring, etc. Monitoring and control earth observation data quality, especially accuracy, completeness, and timeliness, is very useful in data management and governance to optimize data flow, discover potential transmission issues, and better connect data providers and users. Taking a centralized near real-time satellite data repository, STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR), as an example, this paper describes how to develop new mechanism to verify data integrity, check data completeness, and monitor data latency in an operational data management system. Such quality monitoring and control of large volume satellite data help data providers and managers improve data transmission of near real-time satellite data, enhance its acquisition and management, and overcome performance and management issues to better serve research and development activities.

Near real-time estimation of ionosphere vertical total electron content from GNSS satellites using B-splines in a Kalman filter

NASA Astrophysics Data System (ADS)

Erdogan, Eren; Schmidt, Michael; Seitz, Florian; Durmaz, Murat

2017-02-01

Although the number of terrestrial global navigation satellite system (GNSS) receivers supported by the International GNSS Service (IGS) is rapidly growing, the worldwide rather inhomogeneously distributed observation sites do not allow the generation of high-resolution global ionosphere products. Conversely, with the regionally enormous increase in highly precise GNSS data, the demands on (near) real-time ionosphere products, necessary in many applications such as navigation, are growing very fast. Consequently, many analysis centers accepted the responsibility of generating such products. In this regard, the primary objective of our work is to develop a near real-time processing framework for the estimation of the vertical total electron content (VTEC) of the ionosphere using proper models that are capable of a global representation adapted to the real data distribution. The global VTEC representation developed in this work is based on a series expansion in terms of compactly supported B-spline functions, which allow for an appropriate handling of the heterogeneous data distribution, including data gaps. The corresponding series coefficients and additional parameters such as differential code biases of the GNSS satellites and receivers constitute the set of unknown parameters. The Kalman filter (KF), as a popular recursive estimator, allows processing of the data immediately after acquisition and paves the way of sequential (near) real-time estimation of the unknown parameters. To exploit the advantages of the chosen data representation and the estimation procedure, the B-spline model is incorporated into the KF under the consideration of necessary constraints. Based on a preprocessing strategy, the developed approach utilizes hourly batches of GPS and GLONASS observations provided by the IGS data centers with a latency of 1 h in its current realization. Two methods for validation of the results are performed, namely the self consistency analysis and a comparison with Jason-2 altimetry data. The highly promising validation results allow the conclusion that under the investigated conditions our derived near real-time product is of the same accuracy level as the so-called final post-processed products provided by the IGS with a latency of several days or even weeks.

Oil Spill Disasters Detection and Monitoring by RST Analysis of Optical Satellite Radiances: the Case of Deepwater Horizon Platform in the Gulf of Mexico

NASA Astrophysics Data System (ADS)

Pergola, N.; Grimaldi, S. C.; Coviello, I.; Faruolo, M.; Lacava, T.; Tramutoli, V.

2010-12-01

Marine oil spill disasters may have devastating effects on the marine and coastal environment. For monitoring and mitigation purposes, timely detection and continuously updated information on polluted areas are required. Satellite remote sensing can give a significant contribution in such a direction. Nowadays, SAR (Synthetic Aperture Radar) technology has been recognized as the most efficient for oil spill detection and mapping, thanks to the high spatial resolution and all-time/all-weather capability of the present operational sensors. Anyway, the present SARs revisiting time does not allow for a rapid detection and a near real-time monitoring of these phenomena at global scale. Passive optical sensors, on board meteorological satellites, thanks to their high temporal resolution (from a few hours to 15 minutes, depending on the characteristics of the platform/sensor), may represent, at this moment, a suitable SAR alternative/complement for oil spill detection and monitoring. Up to now, some techniques, based on optical satellite data, have been proposed for “a posteriori” mapping of already known oil spill discharges. On the other hand, reliable satellite methods for an automatic and timely detection of oil spills, for surveillance and warning purposes, are still currently missing. Recently, an innovative technique for automatic and near real time oil spill detection and monitoring has been proposed. The technique is based on the general RST (Robust Satellite Technique) approach which exploits multi-temporal satellite records in order to obtain a former characterization of the measured signal, in terms of expected value and natural variability, providing a further identification of signal anomalies by an automatic, unsupervised change detection step. Results obtained by using AVHRR (Advanced Very High Resolution Radiometer) Thermal Infrared data, in different geographic areas and observational conditions, demonstrated excellent detection capabilities both in term of sensitivity (to the presence even of thin/old oil films) and reliability (up to zero occurrence of false alarms), mainly due to the RST invariance regardless of local and environmental conditions. Exploiting its complete independence on the specific satellite platform, RST approach has been successfully exported to the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua satellites. In this paper, results obtained applying the proposed methodology to the recent oil spill disaster of Deepwater Horizon Platform in the gulf of Mexico, that discharged over 5 million barrels (550 million litres) in the ocean, will be shown. A dense temporal series of RST-based oil spill maps, obtained by using MODIS TIR records, are commented, emphasizing and discussing main peculiarities and specific characteristics of this event. Preliminary findings, possible residual limits and future perspectives will be also presented and discussed.

Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites

NASA Astrophysics Data System (ADS)

Naeger, Aaron R.; Gupta, Pawan; Zavodsky, Bradley T.; McGrath, Kevin M.

2016-06-01

The primary goal of this study was to generate a near-real time (NRT) aerosol optical depth (AOD) product capable of providing a comprehensive understanding of the aerosol spatial distribution over the Pacific Ocean, in order to better monitor and track the trans-Pacific transport of aerosols. Therefore, we developed a NRT product that takes advantage of observations from both low-earth orbiting and geostationary satellites. In particular, we utilize AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) satellites. Then, we combine these AOD products with our own retrieval algorithms developed for the NOAA Geostationary Operational Environmental Satellite (GOES-15) and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT-2) to generate a NRT daily AOD composite product. We present examples of the daily AOD composite product for a case study of trans-Pacific transport of Asian pollution and dust aerosols in mid-March 2014. Overall, the new product successfully tracks this aerosol plume during its trans-Pacific transport to the west coast of North America as the frequent geostationary observations lead to a greater coverage of cloud-free AOD retrievals equatorward of about 35° N, while the polar-orbiting satellites provide a greater coverage of AOD poleward of 35° N. However, we note several areas across the domain of interest from Asia to North America where the GOES-15 and MTSAT-2 retrieval algorithms can introduce significant uncertainties into the new product.

Evaluation and intercomparison of GPM-IMERG and TRMM 3B42 daily precipitation products over Greece

NASA Astrophysics Data System (ADS)

Kazamias, A. P.; Sapountzis, M.; Lagouvardos, K.

2017-09-01

Accurate precipitation data at high temporal and spatial resolutions are needed for numerous applications in hydrology, water resources management and flood risk management. Satellite-based precipitation estimations/products offer a potential alternative source of rainfall data for regions with sparse rain gauge network. The recently launched Global Precipitation Measurement (GPM) mission is the successor of Tropical Rainfall Measuring Mission (TRMM) providing global precipitation estimates at spatial resolution of 0.1 degree x 0.1 degree and half-hourly temporal resolution. This study aims at evaluating the accuracy of the Integrated Multi-satellite Retrievals for GPM (IMERG) near-real-time daily product (GPM-3IMERGDL) against rain gauge observations from a network of stations distributed across Greece for the year 2016. Moreover, the GPM-IMERG product is also compared with its predecessor, the Version-7 near-real-time (3B42RT) daily product of TRMM Multisatellite Precipitation Analysis (TMPA). Several statistical metrics are used to quantitatively evaluate the performance of the satellite-based precipitation estimates against rain gauge observations. In addition, categorical statistical indices are used to assess rain detection capabilities of the two satellite products. The GPM-IMERG daily product shows reasonable agreement (CC=0.60) against rain gauge observations, with the exception of coastal areas in which low correlations are achieved. The GPM-IMERG daily precipitation product tends to overestimate rainfall, especially in complex terrain areas with high annual precipitation. In particular, rainfall estimates in western Greece have a strong positive bias. On the other hand, the TRMM 3B42 product shows low correlation (CC=0.45) against rain gauge observations and slightly underestimates rainfall. This study is a first attempt to evaluate and compare the newly introduced GPM-IMERG and the TRMM 3B42 rainfall products at daily timescale over Greece.

Establishing an operational waterhole monitoring system using satellite data and hydrologic modelling: Application in the pastoral regions of East Africa

USGS Publications Warehouse

Senay, Gabriel B.; Velpuri, Naga Manohar; Alemu, Henok; Pervez, Shahriar Md; Asante, Kwabena O; Karuki, Gatarwa; Taa, Asefa; Angerer, Jay

2013-01-01

Timely information on the availability of water and forage is important for the sustainable development of pastoral regions. The lack of such information increases the dependence of pastoral communities on perennial sources, which often leads to competition and conflicts. The provision of timely information is a challenging task, especially due to the scarcity or non-existence of conventional station-based hydrometeorological networks in the remote pastoral regions. A multi-source water balance modelling approach driven by satellite data was used to operationally monitor daily water level fluctuations across the pastoral regions of northern Kenya and southern Ethiopia. Advanced Spaceborne Thermal Emission and Reflection Radiometer data were used for mapping and estimating the surface area of the waterholes. Satellite-based rainfall, modelled run-off and evapotranspiration data were used to model daily water level fluctuations. Mapping of waterholes was achieved with 97% accuracy. Validation of modelled water levels with field-installed gauge data demonstrated the ability of the model to capture the seasonal patterns and variations. Validation results indicate that the model explained 60% of the observed variability in water levels, with an average root-mean-squared error of 22%. Up-to-date information on rainfall, evaporation, scaled water depth and condition of the waterholes is made available daily in near-real time via the Internet (http://watermon.tamu.edu). Such information can be used by non-governmental organizations, governmental organizations and other stakeholders for early warning and decision making. This study demonstrated an integrated approach for establishing an operational waterhole monitoring system using multi-source satellite data and hydrologic modelling.

An Optimized Method to Detect BDS Satellites' Orbit Maneuvering and Anomalies in Real-Time.

PubMed

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Wang, Xiaolei

2018-02-28

The orbital maneuvers of Global Navigation Satellite System (GNSS) Constellations will decrease the performance and accuracy of positioning, navigation, and timing (PNT). Because satellites in the Chinese BeiDou Navigation Satellite System (BDS) are in Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO), maneuvers occur more frequently. Also, the precise start moment of the BDS satellites' orbit maneuvering cannot be obtained by common users. This paper presented an improved real-time detecting method for BDS satellites' orbit maneuvering and anomalies with higher timeliness and higher accuracy. The main contributions to this improvement are as follows: (1) instead of the previous two-steps method, a new one-step method with higher accuracy is proposed to determine the start moment and the pseudo random noise code (PRN) of the satellite orbit maneuvering in that time; (2) BDS Medium Earth Orbit (MEO) orbital maneuvers are firstly detected according to the proposed selection strategy for the stations; and (3) the classified non-maneuvering anomalies are detected by a new median robust method using the weak anomaly detection factor and the strong anomaly detection factor. The data from the Multi-GNSS Experiment (MGEX) in 2017 was used for experimental analysis. The experimental results and analysis showed that the start moment of orbital maneuvers and the period of non-maneuver anomalies can be determined more accurately in real-time. When orbital maneuvers and anomalies occur, the proposed method improved the data utilization for 91 and 95 min in 2017.

Development and testing of controller performance evaluation methodology for multi-input/multi-output digital control systems

NASA Technical Reports Server (NTRS)

Pototzky, Anthony; Wieseman, Carol; Hoadley, Sherwood Tiffany; Mukhopadhyay, Vivek

1991-01-01

Described here is the development and implementation of on-line, near real time controller performance evaluation (CPE) methods capability. Briefly discussed are the structure of data flow, the signal processing methods used to process the data, and the software developed to generate the transfer functions. This methodology is generic in nature and can be used in any type of multi-input/multi-output (MIMO) digital controller application, including digital flight control systems, digitally controlled spacecraft structures, and actively controlled wind tunnel models. Results of applying the CPE methodology to evaluate (in near real time) MIMO digital flutter suppression systems being tested on the Rockwell Active Flexible Wing (AFW) wind tunnel model are presented to demonstrate the CPE capability.

Farm Management Support on Cloud Computing Platform: A System for Cropland Monitoring Using Multi-Source Remotely Sensed Data

NASA Astrophysics Data System (ADS)

Coburn, C. A.; Qin, Y.; Zhang, J.; Staenz, K.

2015-12-01

Food security is one of the most pressing issues facing humankind. Recent estimates predict that over one billion people don't have enough food to meet their basic nutritional needs. The ability of remote sensing tools to monitor and model crop production and predict crop yield is essential for providing governments and farmers with vital information to ensure food security. Google Earth Engine (GEE) is a cloud computing platform, which integrates storage and processing algorithms for massive remotely sensed imagery and vector data sets. By providing the capabilities of storing and analyzing the data sets, it provides an ideal platform for the development of advanced analytic tools for extracting key variables used in regional and national food security systems. With the high performance computing and storing capabilities of GEE, a cloud-computing based system for near real-time crop land monitoring was developed using multi-source remotely sensed data over large areas. The system is able to process and visualize the MODIS time series NDVI profile in conjunction with Landsat 8 image segmentation for crop monitoring. With multi-temporal Landsat 8 imagery, the crop fields are extracted using the image segmentation algorithm developed by Baatz et al.[1]. The MODIS time series NDVI data are modeled by TIMESAT [2], a software package developed for analyzing time series of satellite data. The seasonality of MODIS time series data, for example, the start date of the growing season, length of growing season, and NDVI peak at a field-level are obtained for evaluating the crop-growth conditions. The system fuses MODIS time series NDVI data and Landsat 8 imagery to provide information of near real-time crop-growth conditions through the visualization of MODIS NDVI time series and comparison of multi-year NDVI profiles. Stakeholders, i.e., farmers and government officers, are able to obtain crop-growth information at crop-field level online. This unique utilization of GEE in combination with advanced analytic and extraction techniques provides a vital remote sensing tool for decision makers and scientists with a high-degree of flexibility to adapt to different uses.

Multi Scale Multi Temporal Near Real Time Approach for Volcanic Eruptions monitoring, Test Case: Mt Etna eruption 2017

NASA Astrophysics Data System (ADS)

Buongiorno, M. F.; Silvestri, M.; Musacchio, M.

2017-12-01

In this work a complete processing chain from the detection of the beginning of eruption to the estimation of lava flow temperature on active volcanoes using remote sensing data is presented showing the results for the Mt. Etna eruption on March 2017. The early detection of new eruption is based on the potentiality ensured by geostationary very low spatial resolution satellite (3x3 km in nadiral view), the hot spot/lava flow evolution is derived by S2 polar medium/high spatial resolution (20x20 mt) while the surface temperature is estimated by polar medium/low spatial resolution such as L8, ASTER and S3 (from 90 mt up to 1km).This approach merges two outcome derived by activity performed for monitoring purposes within INGV R&D activities and the results obtained by Geohazards Exploitation Platform ESA funded project (GEP) aimed to the development of shared platform for providing services based on EO data. Because the variety of phenomena to be analyzed a multi temporal multi scale approach has been used to implement suitable and robust algorithms for the different sensors. With the exception of Sentinel 2 (MSI) data, for which the algorithm used is based on NIR-SWIR bands, we exploit the MIR-TIR channels of L8, ASTER, S3 and SEVIRI for generating automatically the surface thermal state analysis. The developed procedure produces time series data and allows to extract information from each single co-registered pixel, to highlight variation of temperatures within specific areas. The final goal is to implement an easy tool which enables scientists and users to extract valuable information from satellite time series at different scales produced by ESA and EUMETSAT in the frame of Europe's Copernicus program and other Earth observation satellites programs such as LANDSAT (USGS) and GOES (NOAA).

Intercomparison of Near-Real-Time Biomass Burning Emissions Estimates Constrained by Satellite Fire Data

EPA Science Inventory

We compare biomass burning emissions estimates from four different techniques that use satellite based fire products to determine area burned over regional to global domains. Three of the techniques use active fire detections from polar-orbiting MODIS sensors and one uses detec...

Land and Atmosphere Near-Real-Time Capability for Earth Observing System

NASA Technical Reports Server (NTRS)

Murphy, Kevin J.

2011-01-01

The past decade has seen a rapid increase in availability and usage of near-real-time data from satellite sensors. The EOSDIS (Earth Observing System Data and Information System) was not originally designed to provide data with sufficiently low latency to satisfy the requirements for near-real-time users. The EOS (Earth Observing System) instruments aboard the Terra, Aqua and Aura satellites make global measurements daily, which are processed into higher-level 'standard' products within 8-40 hours of observation and then made available to users, primarily earth science researchers. However, applications users, operational agencies, and even researchers desire EOS products in near-real-time to support research and applications, including numerical weather and climate prediction and forecasting, monitoring of natural hazards, ecological/invasive species, agriculture, air quality, disaster relief and homeland security. These users often need data much sooner than routine science processing allows, usually within 3 hours, and are willing to trade science product quality for timely access. While Direct Broadcast provides more timely access to data, it does not provide global coverage. In 2002, a joint initiative between NASA (National Aeronautics and Space Administration), NOAA (National Oceanic and Atmospheric Administration), and the DOD (Department of Defense) was undertaken to provide data from EOS instruments in near-real-time. The NRTPE (Near Real Time Processing Effort) provided products within 3 hours of observation on a best-effort basis. As the popularity of these near-real-time products and applications grew, multiple near-real-time systems began to spring up such as the Rapid Response System. In recognizing the dependence of customers on this data and the need for highly reliable and timely data access, NASA's Earth Science Division sponsored the Earth Science Data and Information System Project (ESDIS)-led development of a new near-real-time system called LANCE (Land, Atmosphere Near-Real-Time Capability for EOS) in 2009. LANCE consists of special processing elements, co-located with selected EOSDIS data centers and processing facilities. A primary goal of LANCE is to bring multiple near-real-time systems under one umbrella, offering commonality in data access, quality control, and latency. LANCE now processes and distributes data from the Moderate Resolution Imaging Spectroradiometer (MODIS), Atmospheric Infrared Sounder (AIRS), Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), Microwave Limb Sounder (MLS) and Ozone Monitoring Instrument (OMI) instruments within 3 hours of satellite observation. The Rapid Response System and the Fire Information for Resource Management System (FIRMS) capabilities will be incorporated into LANCE in 2011. LANCE maintains a central website to facilitate easy access to data and user services. LANCE products are extensively tested and compared with science products before being made available to users. Each element also plans to implement redundant network, power and server infrastructure to ensure high availability of data and services. Through the user registration system, users are informed of any data outages and when new products or services will be available for access. Building on a significant investment by NASA in developing science algorithms and products, LANCE creates products that have a demonstrated utility for applications requiring near-real-time data. From lower level data products such as calibrated geolocated radiances to higher-level products such as sea ice extent, snow cover, and cloud cover, users have integrated LANCE data into forecast models and decision support systems. The table above shows the current near-real-time product categories by instrument. The ESDIS Project continues to improve the LANCE system and use the experience gained through practice to seek adjustments to improve the quality and performance of the system. For example, anGC-compliant Web Map Service (WMS) will be added shortly that will allow users to download geo-referenced MODIS images for arbitrary bounding boxes. Further, an OGC-compliant Web Coverage Service (WCS) will be added later this year that will expedite user access to arbitrary data subsets or re-formatted products. AIRS images are now served through WMS and available in multiple formats (PNG, GeoTIFF, KMZ). NASA has established a LANCE User Working Group to steer the development of the system and create a forum for sharing ideas and experiences that are expected to further improve the LANCE capabilities. The LANCE system has proved a success by satisfying the growing needs of the applications and operational communities for land and atmosphere data in near-real-time. NASA's Earth Sciences Division was able to leverage existing science research capabilities to provide the near-real-time community with products and imagery that support monitoring of disasters in a timely manner.

Monitoring Natural Events Globally in Near Real-Time Using NASA's Open Web Services and Tools

NASA Technical Reports Server (NTRS)

Boller, Ryan A.; Ward, Kevin Alan; Murphy, Kevin J.

2015-01-01

Since 1960, NASA has been making global measurements of the Earth from a multitude of space-based missions, many of which can be useful for monitoring natural events. In recent years, these measurements have been made available in near real-time, making it possible to use them to also aid in managing the response to natural events. We present the challenges and ongoing solutions to using NASA satellite data for monitoring and managing these events.

Efficient high-rate satellite clock estimation for PPP ambiguity resolution using carrier-ranges.

PubMed

Chen, Hua; Jiang, Weiping; Ge, Maorong; Wickert, Jens; Schuh, Harald

2014-11-25

In order to catch up the short-term clock variation of GNSS satellites, clock corrections must be estimated and updated at a high-rate for Precise Point Positioning (PPP). This estimation is already very time-consuming for the GPS constellation only as a great number of ambiguities need to be simultaneously estimated. However, on the one hand better estimates are expected by including more stations, and on the other hand satellites from different GNSS systems must be processed integratively for a reliable multi-GNSS positioning service. To alleviate the heavy computational burden, epoch-differenced observations are always employed where ambiguities are eliminated. As the epoch-differenced method can only derive temporal clock changes which have to be aligned to the absolute clocks but always in a rather complicated way, in this paper, an efficient method for high-rate clock estimation is proposed using the concept of "carrier-range" realized by means of PPP with integer ambiguity resolution. Processing procedures for both post- and real-time processing are developed, respectively. The experimental validation shows that the computation time could be reduced to about one sixth of that of the existing methods for post-processing and less than 1 s for processing a single epoch of a network with about 200 stations in real-time mode after all ambiguities are fixed. This confirms that the proposed processing strategy will enable the high-rate clock estimation for future multi-GNSS networks in post-processing and possibly also in real-time mode.

The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global Precipitation Estimates at Fine Scales

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Gu, Guojun; Nelkin, Eric J.; Bowman, Kenneth P.; Stocker, Erich; Wolff, David B.

2006-01-01

The TRMM Multi-satellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining multiple precipitation estimates from satellites, as well as gauge analyses where feasible, at fine scales (0.25 degrees x 0.25 degrees and 3-hourly). It is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The data set covers the latitude band 50 degrees N-S for the period 1998 to the delayed present. Early validation results are as follows: The TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate dependent low bias due to lack of sensitivity to low precipitation rates in one of the input products (based on AMSU-B). At finer scales the TMPA is successful at approximately reproducing the surface-observation-based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other fine-scale estimators. Examples are provided of a flood event and diurnal cycle determination.

The new version 2.12 of BKG Ntrip Client (BNC)

NASA Astrophysics Data System (ADS)

Stürze, Andrea; Mervart, Leos; Weber, Georg; Rülke, Axel; Wiesensarter, Erwin; Neumaier, Peter

2016-04-01

A new version of the BKG Ntrip Client (BNC) has been released. Originally developed in cooperation of the Federal Agency for Cartography and Geodesy (BKG) and the Czech Technical University (CTU) with a focus on multi-stream real-time access to GPS observations, the software has once again been substantially extended. Promoting Open Standards as recommended by the Radio Technical Commission for Maritime Services (RTCM) remains the prime subject. Beside its Graphical User Interface (GUI), the real-time software for Windows, Linux, Mac, and Linux platforms now comes with complete Command Line Interface (CLI) and considerable post processing functionality. RINEX Version 3 file editing & Quality Check (QC) with full support of Galileo, BeiDou, and SBAS - besides GPS and GLONASS - is part of the new features. Comparison of satellite orbit/clock files in SP3 format is another fresh ability of BNC. Simultaneous multi-station Precise Point Positioning (PPP) for real-time displacement-monitoring of entire reference station networks is one more recent addition to BNC. Implemented RTCM messages for PPP (under development) comprise satellite orbit and clock corrections, code and phase observation biases, and the Vertical Total Electron Content (VTEC) of the ionosphere. The well established, mature codebase is mostly written in C++ language. Its publication under GNU GPL is thought to be well-suited for test, validation and demonstration of new approaches in precise real-time satellite navigation when IP streaming is involved. The poster highlights BNC features which are new in version 2.12 and beneficial to IAG institutions and services such as IGS/RT-IGS and to the interested public in general.

Operational System-Impact Products for the Space Situational Awareness Environmental Effects Fusion System (SEEFS)

NASA Astrophysics Data System (ADS)

Quigley, S.; Scro, K.

2006-12-01

The Space Vehicles Directorate of the Air Force Research Laboratory (AFRL/VSBX) and the Technology Applications Division of the Space and Missile Systems Center (SMC/WXT) have combined efforts under the Rapid Prototyping Center (RPC) to design, develop, test, implement, and validate numerical and graphical products for the Air Force Space Command (AFSPC) Space Situational Awareness Environmental Effects Fusion System (SEEFS). These products are generated to analyze, specify, and forecast the effects of the near-earth space environment on Department of Defense weapons, navigation, communications, and surveillance systems. Jointly developed projects that have been completed as prototypes and are undergoing development for real-time operations include a SEEFS architecture and database, five system-impact products, and a high-level decision aid product. This first round of SEEFS products includes Solar Radio Burst Effects (SoRBE) on radar and satellite communications, Radar Auroral Clutter (RAC), Scintillation Effects on radar and satellite communications (RadScint and SatScint), and Satellite Surface and Deep Charge/Discharge (Char/D). The SEEFS architecture and database enable modular use and execution of SEEFS products, and the high-level Decision Aid shows the combined effects of all SEEFS product output on a given asset and on multi-asset missions. This presentation provides a general overview of the SEEFS program, along with details of the first round of products expected to be operational for use in exercises and/or real-time operations in 2007-2008.

A GeoServices Infrastructure for Near-Real-Time Access to Suomi NPP Satellite Data

NASA Astrophysics Data System (ADS)

Evans, J. D.; Valente, E. G.; Hao, W.; Chettri, S.

2012-12-01

The new Suomi National Polar-orbiting Partnership (NPP) satellite extends NASA's moderate-resolution, multispectral observations with a suite of powerful imagers and sounders to support a broad array of research and applications. However, NPP data products consist of a complex set of data and metadata files in highly specialized formats; which NPP's operational ground segment delivers to users only with several hours' delay. This severely limits their use in critical applications such as weather forecasting, emergency / disaster response, search and rescue, and other activities that require near-real-time access to satellite observations. Alternative approaches, based on distributed Direct Broadcast facilities, can reduce the delay in NPP data delivery from hours to minutes, and can make products more directly usable by practitioners in the field. To assess and fulfill this potential, we are developing a suite of software that couples Direct Broadcast data feeds with a streamlined, scalable processing chain and geospatial Web services, so as to permit many more time-sensitive applications to use NPP data. The resulting geoservices infrastructure links a variety of end-user tools and applications to NPP data from different sources, and to other rapidly-changing geospatial data. By using well-known, standard software interfaces (such as OGC Web Services or OPeNDAP), this infrastructure serves a variety of end-user analysis and visualization tools, giving them access into datasets of arbitrary size and resolution and allowing them to request and receive tailored products on demand. The standards-based approach may also streamline data sharing among independent satellite receiving facilities, thus helping them to interoperate in providing frequent, composite views of continent-scale or global regions. To enable others to build similar or derived systems, the service components we are developing (based in part on the Community Satellite Processing Package (CSPP) from the University of Wisconsin and the International Polar-Orbiter Processing Package (IPOPP) from NASA) are being released as open source software. Furthermore, they are configured to operate in a cloud computing environment, so as to allow even small organizations to process and serve NPP data without large hardware investments; and to maintain near-real-time performance cost-effectively by growing and shrinking their use of computing resources to meet large, rapid fluctuations in end-user demand, data availability, and processing needs. (This is especially important for polar-orbiting satellites like NPP, which pass within range of a receiver only a few times each day.) We will discuss the design of the infrastructure, highlight its capabilities, and sketch its potential to facilitate broad access to satellite data processing and visualization, and to enhance near-real-time applications via distributed NPP data streams.

Assimilation of SMOS (and SMAP) Retrieved Soil Moisture into the Land Information System

NASA Technical Reports Server (NTRS)

Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey

2016-01-01

Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.

The SSABLE system - Automated archive, catalog, browse and distribution of satellite data in near-real time

NASA Technical Reports Server (NTRS)

Simpson, James J.; Harkins, Daniel N.

1993-01-01

Historically, locating and browsing satellite data has been a cumbersome and expensive process. This has impeded the efficient and effective use of satellite data in the geosciences. SSABLE is a new interactive tool for the archive, browse, order, and distribution of satellite date based upon X Window, high bandwidth networks, and digital image rendering techniques. SSABLE provides for automatically constructing relational database queries to archived image datasets based on time, data, geographical location, and other selection criteria. SSABLE also provides a visual representation of the selected archived data for viewing on the user's X terminal. SSABLE is a near real-time system; for example, data are added to SSABLE's database within 10 min after capture. SSABLE is network and machine independent; it will run identically on any machine which satisfies the following three requirements: 1) has a bitmapped display (monochrome or greater); 2) is running the X Window system; and 3) is on a network directly reachable by the SSABLE system. SSABLE has been evaluated at over 100 international sites. Network response time in the United States and Canada varies between 4 and 7 s for browse image updates; reported transmission times to Europe and Australia typically are 20-25 s.

Demonstrating Acquisition of Real-Time Thermal Data Over Fires Utilizing UAVs

NASA Technical Reports Server (NTRS)

Ambrosia, Vincent G.; Wegener, Steven S.; Brass, James A.; Buechel, Sally W.; Peterson, David L. (Technical Monitor)

2002-01-01

A disaster mitigation demonstration, designed to integrate remote-piloted aerial platforms, a thermal infrared imaging payload, over-the-horizon (OTH) data telemetry and advanced image geo-rectification technologies was initiated in 2001. Project FiRE incorporates the use of a remotely piloted Uninhabited Aerial Vehicle (UAV), thermal imagery, and over-the-horizon satellite data telemetry to provide geo-corrected data over a controlled burn, to a fire management community in near real-time. The experiment demonstrated the use of a thermal multi-spectral scanner, integrated on a large payload capacity UAV, distributing data over-the-horizon via satellite communication telemetry equipment, and precision geo-rectification of the resultant data on the ground for data distribution to the Internet. The use of the UAV allowed remote-piloted flight (thereby reducing the potential for loss of human life during hazardous missions), and the ability to "finger and stare" over the fire for extended periods of time (beyond the capabilities of human-pilot endurance). Improved bit-rate capacity telemetry capabilities increased the amount, structure, and information content of the image data relayed to the ground. The integration of precision navigation instrumentation allowed improved accuracies in geo-rectification of the resultant imagery, easing data ingestion and overlay in a GIS framework. We focus on these technological advances and demonstrate how these emerging technologies can be readily integrated to support disaster mitigation and monitoring strategies regionally and nationally.

Real-time Transmission and Distribution of NOAA Tail Doppler Radar Data and Other Data Products

NASA Astrophysics Data System (ADS)

Carswell, J.; Chang, P.; Robinson, D.; Gamache, J.; Hill, J.

2011-12-01

The NOAA WP-3D and G-IV aircraft have conducted and continue to conduct numerous research and operational measurement missions. However, typically only a fraction of the data collected aboard each flight is transmitted to the ground in near real-time utilizing low bandwidth satellite data links. The advancements in aircraft satellite phones have increased available bandwidth and reliability to a point where these systems can be utilized for near real-time data flow in support of decision making. A robust and flexible data delivery system has been developed by Remote Sensing Solutions with support from NOAA's National Environmental Satellite, Data and Information Service (NESDIS), Aircraft Operations Center (AOC) and Hurricane Forecast Improvement Project (HFIP). X-band Doppler/reflectivity measurements of tropical storms and cyclones collected from the NOAA WP-3D aircraft have been the most recent focus. Doppler measurements from volume backscatter precipitation profiles can provide critical observations of the horizontal winds as the precipitation advects with these winds. The data delivery system captures these profiles and send the radial Doppler profile observations to National Weather Service in near real-time over satellite communication data link. The design of this transmission system included features to enhance the reliability and robustness of the data flow from the P-3 aircraft to the end user. Routine real-time transmission, using this system, of the full resolution Tail Doppler Radar profile data to the ground and distribution to the NOAA's Hurricane Research Division for analysis and processing in support of initializing the operational HWRF model is planned. The end objective is to provide these Doppler profiles in a routine fashion to NWS and others in the forecasting community for operational utilization in support of hurricane forecasting and warning. Other data sources that are being collected and transmitted to the ground with this system for distribution in near real-time, include but are not limited to, the NOAA Lower Fuselage Radar reflectivity profiles, SFMR retrievals, flight level data, AXBT profiles and Imaging Wind and Rain Airborne Profiler data. The transmission and distribution of these data has a latency of only several seconds from initial acquisition on the aircraft to end users accessing the data through the Internet enabling end users to have a virtual seat on the aircraft and quick dissemination critical observations to the hurricane research, forecasting and modeling communities. In this presentation, the system capabilities and architecture will be described. Examples of the data products and data visualization tools (client applications) will be shown.

Expanding the Estimation of Surface PM2.5 from Aqua and Terra MODIS Aerosol Optical Depth in the EPA's AirNow Satellite Data Processor to Suomi NPP VIIRS

NASA Astrophysics Data System (ADS)

Szykman, J.; Kondragunta, S.; Zhang, H.; Dickerson, P.; van Donkelaar, A.; Martin, R. V.; Pasch, A. N.; White, J. E.; DeWinter, J. L.; Zahn, P. H.; Dye, T. S.; Haderman, M. D.

2012-12-01

The U.S. Environmental Protection Agency's (EPA) Air Quality Index (AQI) relies on hourly measurements of ground-based surface PM2.5 (particles smaller than 2.5 μm in median diameter) to develop daily AQI index maps. The EPA is improving the accuracy of AQI information and extending its coverage for reporting to the public by incorporating National Aeronautics and Space Administration (NASA) satellite-derived surface PM2.5 concentrations into daily AQI maps. The additional coverage will provide air quality information in regions without dense monitoring networks. The AirNow Satellite Data Processor (ASDP) uses daily PM2.5 estimates and uncertainties derived from average Aqua and Terra MODerate resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) in near real-time over the United States. The algorithm to derive surface PM2.5 from MODIS AOD relies on linear relationships between AOD and PM2.5 generated from multi-year GEOS-Chem model simulations (van Donkelaar et al., 2012). Parameters from the regression equation (slopes and intercepts) are saved in a lookup table (LUT) with 4 km spatial resolution for each day of a given year. To improve data accuracy and continuity, a filter is applied to remove MODIS AOD with low accuracy (e.g., over bright surfaces) and an inverse distance weighted average is applied to fill in gaps created by cloud coverage. Daily surface PM2.5 estimates and their uncertainties are generated at the National Oceanic and Atmospheric Administration (NOAA) using the van Donkelaar et al. algorithm and near real-time MODIS AOD products from Terra and Aqua and are provided to the EPA through its Infusing satellite Data into Environmental Applications (IDEA) website. The Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on October 28, 2011, and similar to MODIS, provides AOD products for real-time applications. NOAA plans to explore the value of VIIRS AOD products to improve AQI. This presentation will focus on a description of ASDP, including an overview of the algorithm used to estimate surface PM2.5 using satellite data and examples of high resolution VIIRS AOD products and their value to the ASDP. Disclaimer: Although this work was reviewed by the U.S. Environmental Protection Agency and approved for publication, it may not necessarily reflect official Agency policy.

A near real time regional JPSS and GOES-R data assimilation system for high impact weather research and applications

NASA Astrophysics Data System (ADS)

Li, J.; Wang, P.; Han, H.; Schmit, T. J.

2014-12-01

JPSS and GOES-R observations play important role in numerical weather prediction (NWP). However, how to best represent the information from satellite observations and how to get value added information from these satellite data into regional NWP models, including both radiance and derived products, still need investigations. In order to enhance the applications of JPSS and GOES-R data in regional NWP for high impact weather forecasts, scientists from Cooperative Institute of Meteorological Satellite Studies (CIMSS) at University of Wisconsin-Madison have recently developed a near realtime regional Satellite Data Assimilation system for Tropical storm forecasts (SDAT) (http://cimss.ssec.wisc.edu/sdat). The system consists of the community Gridpoint Statistical Interpolation (GSI) assimilation system and the advanced Weather Research Forecast (WRF) model. In addition to assimilate GOES, AMSUA/AMSUB, HIRS, MHS, ATMS (Suomi-NPP), AIRS and IASI radiances, the SDAT is also able to assimilate satellite-derived products such as hyperspectral IR retrieved temperature and moisture profiles, total precipitable water (TPW), GOES Sounder (and future GOES-R) layer precipitable water (LPW) and GOES Imager atmospheric motion vector (AMV) products into the system. Real time forecasted GOES infrared (IR) images simulated from SDAT output have also been part of the SDAT system for applications and forecast evaluations. To set up the system parameters, a series of experiments have been carried out to test the impacts of different initialization schemes, including different background error matrix, different NCEP global model date sets, and different WRF model horizontal resolutions. Using SDAT as a research testbed, researches have been conducted for different satellite data impacts study, as well as different techniques for handling clouds in radiance assimilation. Since the fall of 2013, the SDAT system has been running in near real time. The results from historical cases and 2014 hurricane season cases will be compared with the operational GFS and HWRF, and presented at the meeting.

MISR at 15: Multiple Perspectives on Our Changing Earth

NASA Astrophysics Data System (ADS)

Diner, D. J.; Ackerman, T. P.; Braverman, A. J.; Bruegge, C. J.; Chopping, M. J.; Clothiaux, E. E.; Davies, R.; Di Girolamo, L.; Garay, M. J.; Jovanovic, V. M.; Kahn, R. A.; Kalashnikova, O.; Knyazikhin, Y.; Liu, Y.; Marchand, R.; Martonchik, J. V.; Muller, J. P.; Nolin, A. W.; Pinty, B.; Verstraete, M. M.; Wu, D. L.

2014-12-01

Launched aboard NASA's Terra satellite in December 1999, the Multi-angle Imaging SpectroRadiometer (MISR) instrument has opened new vistas in remote sensing of our home planet. Its 9 pushbroom cameras provide as many view angles ranging from 70 degrees forward to 70 degrees backward along Terra's flight track, in four visible and near-infrared spectral bands. MISR's well-calibrated, accurately co-registered, and moderately high spatial resolution radiance images have been coupled with novel data processing algorithms to mine the information content of angular reflectance anisotropy and multi-camera stereophotogrammetry, enabling new perspectives on the 3-D structure and dynamics of Earth's atmosphere and surface in support of climate and environmental research. Beginning with "first light" in February 2000, the nearly 15-year (and counting) MISR observational record provides an unprecedented data set with applications to multiple disciplines, documenting regional, global, short-term, and long-term changes in aerosol optical depths, aerosol type, near-surface particulate pollution, spectral top-of-atmosphere and surface albedos, aerosol plume-top and cloud-top heights, height-resolved cloud fractions, atmospheric motion vectors, and the structure of vegetated and ice-covered terrains. Recent computational advances include aerosol retrievals at finer spatial resolution than previously possible, and production of near-real time tropospheric winds with a latency of less than 3 hours, making possible for the first time the assimilation of MISR data into weather forecast models. In addition, recent algorithmic and technological developments provide the means of using and acquiring multi-angular data in new ways, such as the application of optical tomography to map 3-D atmospheric structure; building smaller multi-angle instruments in the future; and extending the multi-angular imaging methodology to the ultraviolet, shortwave infrared, and polarimetric realms. Such advances promise further enhancements to the observational power of the remote sensing approaches that MISR has pioneered.

Cloud-based Web Services for Near-Real-Time Web access to NPP Satellite Imagery and other Data

NASA Astrophysics Data System (ADS)

Evans, J. D.; Valente, E. G.

2010-12-01

We are building a scalable, cloud computing-based infrastructure for Web access to near-real-time data products synthesized from the U.S. National Polar-Orbiting Environmental Satellite System (NPOESS) Preparatory Project (NPP) and other geospatial and meteorological data. Given recent and ongoing changes in the the NPP and NPOESS programs (now Joint Polar Satellite System), the need for timely delivery of NPP data is urgent. We propose an alternative to a traditional, centralized ground segment, using distributed Direct Broadcast facilities linked to industry-standard Web services by a streamlined processing chain running in a scalable cloud computing environment. Our processing chain, currently implemented on Amazon.com's Elastic Compute Cloud (EC2), retrieves raw data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and synthesizes data products such as Sea-Surface Temperature, Vegetation Indices, etc. The cloud computing approach lets us grow and shrink computing resources to meet large and rapid fluctuations (twice daily) in both end-user demand and data availability from polar-orbiting sensors. Early prototypes have delivered various data products to end-users with latencies between 6 and 32 minutes. We have begun to replicate machine instances in the cloud, so as to reduce latency and maintain near-real time data access regardless of increased data input rates or user demand -- all at quite moderate monthly costs. Our service-based approach (in which users invoke software processes on a Web-accessible server) facilitates access into datasets of arbitrary size and resolution, and allows users to request and receive tailored and composite (e.g., false-color multiband) products on demand. To facilitate broad impact and adoption of our technology, we have emphasized open, industry-standard software interfaces and open source software. Through our work, we envision the widespread establishment of similar, derived, or interoperable systems for processing and serving near-real-time data from NPP and other sensors. A scalable architecture based on cloud computing ensures cost-effective, real-time processing and delivery of NPP and other data. Access via standard Web services maximizes its interoperability and usefulness.

Software defined radio (SDR) architecture for concurrent multi-satellite communications

NASA Astrophysics Data System (ADS)

Maheshwarappa, Mamatha R.

SDRs have emerged as a viable approach for space communications over the last decade by delivering low-cost hardware and flexible software solutions. The flexibility introduced by the SDR concept not only allows the realisation of concurrent multiple standards on one platform, but also promises to ease the implementation of one communication standard on differing SDR platforms by signal porting. This technology would facilitate implementing reconfigurable nodes for parallel satellite reception in Mobile/Deployable Ground Segments and Distributed Satellite Systems (DSS) for amateur radio/university satellite operations. This work outlines the recent advances in embedded technologies that can enable new communication architectures for concurrent multi-satellite or satellite-to-ground missions where multi-link challenges are associated. This research proposes a novel concept to run advanced parallelised SDR back-end technologies in a Commercial-Off-The-Shelf (COTS) embedded system that can support multi-signal processing for multi-satellite scenarios simultaneously. The initial SDR implementation could support only one receiver chain due to system saturation. However, the design was optimised to facilitate multiple signals within the limited resources available on an embedded system at any given time. This was achieved by providing a VHDL solution to the existing Python and C/C++ programming languages along with parallelisation so as to accelerate performance whilst maintaining the flexibility. The improvement in the performance was validated at every stage through profiling. Various cases of concurrent multiple signals with different standards such as frequency (with Doppler effect) and symbol rates were simulated in order to validate the novel architecture proposed in this research. Also, the architecture allows the system to be reconfigurable by providing the opportunity to change the communication standards in soft real-time. The chosen COTS solution provides a generic software methodology for both ground and space applications that will remain unaltered despite new evolutions in hardware, and supports concurrent multi-standard, multi-channel and multi-rate telemetry signals.

LANCE in ECHO - Merging Science and Near Real-Time Data Search and Order

NASA Astrophysics Data System (ADS)

Kreisler, S.; Murphy, K. J.; Vollmer, B.; Lighty, L.; Mitchell, A. E.; Devine, N.

2012-12-01

NASA's Earth Observing System (EOS) Data and Information System (EOSDIS) Land Atmosphere Near real-time Capability for EOS (LANCE) project provides expedited data products from the Terra, Aqua, and Aura satellites within three hours of observation. In order to satisfy latency requirements, LANCE data are produced with relaxed ancillary data resulting in a product that may have minor differences from its science quality counterpart. LANCE products are used by a number of different groups to support research and applications that require near real-time earth observations, such as disaster relief, hazard and air quality monitoring, and weather forecasting. LANCE elements process raw rate-buffered and/or session-based production datasets into higher-level products, which are freely available to registered users via LANCE FTP sites. The LANCE project also generates near real-time full resolution browse imagery from these products, which can be accessed through the Global Imagery Browse Services (GIBS). In an effort to support applications and services that require timely access to these near real-time products, the project is currently implementing the publication of LANCE product metadata to the EOS ClearingHouse (ECHO), a centralized EOSDIS registry of EOS data. Metadata within ECHO is made available through an Application Program Interface (API), and applications can utilize the API to allow users to efficiently search and order LANCE data. Publishing near real-time data to ECHO will permit applications to access near real-time product metadata prior to the release of its science quality counterpart and to associate imagery from GIBS with its underlying data product.

Navigation Performance of Global Navigation Satellite Systems in the Space Service Volume

NASA Technical Reports Server (NTRS)

Force, Dale A.

2013-01-01

This paper extends the results I reported at this year's ION International Technical Meeting on multi-constellation GNSS coverage by showing how the use of multi-constellation GNSS improves Geometric Dilution of Precision (GDOP). Originally developed to provide position, navigation, and timing for terrestrial users, GPS has found increasing use for in space for precision orbit determination, precise time synchronization, real-time spacecraft navigation, and three-axis attitude control of Earth orbiting satellites. With additional Global Navigation Satellite Systems (GNSS) coming into service (GLONASS, Galileo, and Beidou) and the development of Satellite Based Augmentation Services, it is possible to obtain improved precision by using evolving multi-constellation receiver. The Space Service Volume formally defined as the volume of space between three thousand kilometers altitude and geosynchronous altitude ((is) approximately 36,500 km), with the volume below three thousand kilometers defined as the Terrestrial Service Volume (TSV). The USA has established signal requirements for the Space Service Volume (SSV) as part of the GPS Capability Development Documentation (CDD). Diplomatic efforts are underway to extend Space service Volume commitments to the other Position, Navigation, and Timing (PNT) service providers in an effort to assure that all space users will benefit from the enhanced capabilities of interoperating GNSS services in the space domain.

Satellite-based Flood Modeling Using TRMM-based Rainfall Products

PubMed Central

Harris, Amanda; Rahman, Sayma; Hossain, Faisal; Yarborough, Lance; Bagtzoglou, Amvrossios C.; Easson, Greg

2007-01-01

Increasingly available and a virtually uninterrupted supply of satellite-estimated rainfall data is gradually becoming a cost-effective source of input for flood prediction under a variety of circumstances. However, most real-time and quasi-global satellite rainfall products are currently available at spatial scales ranging from 0.25° to 0.50° and hence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scale flood events. This study assesses the question: what are the hydrologic implications of uncertainty of satellite rainfall data at the coarse scale? We investigated this question on the 970 km2 Upper Cumberland river basin of Kentucky. The satellite rainfall product assessed was NASA's Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) product called 3B41RT that is available in pseudo real time with a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data can improve application in flood prediction to some extent with the trade-off of more false alarms in peak flow. However, a more rational and regime-based adjustment procedure needs to be identified before the use of satellite data can be institutionalized among flood modelers. PMID:28903302

A Near Real-time Decision Support System Improving Forest Management in the Tropics

NASA Astrophysics Data System (ADS)

Tabor, K.; Musinsky, J.; Ledezma, J.; Rasolohery, A.; Mendoza, E.; Kistler, H.; Steininger, M.; Morton, D. C.; Melton, F. S.; Manwell, J.; Koenig, K.

2013-12-01

Conservation International (CI) has a decade of experience developing near real-time fire and deforestation monitoring and forecasting systems that channel monitoring information from satellite observations directly to national and sub-national government agencies, Non-Government Organizations (NGOs), and local communities. These systems are used to strengthen forest surveillance and monitoring, fire management and prevention, protected areas management and sustainable land use planning. With support from a NASA Wildland Fires grant, in September 2013 CI will launch a brand new near real-time alert system (FIRECAST) to better meet the outstanding needs and challenges users face in addressing ecosystem degradation from wildland fire and illegal forest activities. Outreach efforts and user feedback have indicated the need for seasonal fire forecasts for effective land use planning, faster alert delivery to enhance response to illegal forest activities, and expanded forest monitoring capabilities that enable proactive responses and that strengthen forest conservation and sustainable development actions. The new FIRECAST system addresses these challenges by integrating the current fire alert and deforestation systems and adding improved ecological forecasting of fire risk; expanding data exchange capabilities with mobile technologies; and delivering a deforestation alert product that can inform policies related to land use management and Reduced Emissions from Deforestation and forest Degradation (REDD+). In addition to demonstrating the capabilities of this new real-time alert system, we also highlight how coordination with host-country institutions enhances the system's capacity to address the implementation needs of REDD+ forest carbon projects, improve tropical forest management, strengthen environmental law enforcement, and facilitate the uptake of near real-time satellite monitoring data into business practices of these national/sub-national institutions.

Improving User Access to the Integrated Multi-Satellite Retrievals for GPM (IMERG) Products

NASA Astrophysics Data System (ADS)

Huffman, George; Bolvin, David; Nelkin, Eric; Kidd, Christopher

2016-04-01

The U.S. Global Precipitation Measurement mission (GPM) team has developed the Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm to take advantage of the international constellation of precipitation-relevant satellites and the Global Precipitation Climatology Centre surface precipitation gauge analysis. The goal is to provide a long record of homogeneous, high-resolution quasi-global estimates of precipitation. While expert scientific researchers are major users of the IMERG products, it is clear that many other user communities and disciplines also desire access to the data for wide-ranging applications. Lessons learned during the Tropical Rainfall Measuring Mission, the predecessor to GPM, led to some basic design choices that provided the framework for supporting multiple user bases. For example, two near-real-time "runs" are computed, the Early and Late (currently 5 and 15 hours after observation time, respectively), then the Final Run about 3 months later. The datasets contain multiple fields that provide insight into the computation of the complete precipitation data field, as well as diagnostic (currently) estimates of the precipitation's phase. In parallel with this, the archive sites are working to provide the IMERG data in a variety of formats, and with subsetting and simple interactive analysis to make the data more easily available to non-expert users. The various options for accessing the data are summarized under the pmm.nasa.gov data access page. The talk will end by considering the feasibility of major user requests, including polar coverage, a simplified Data Quality Index, and reduced data latency for the Early Run. In brief, the first two are challenging, but under the team's control. The last requires significant action by some of the satellite data providers.

Geospatial Information from Satellite Imagery for Geovisualisation of Smart Cities in India

NASA Astrophysics Data System (ADS)

Mohan, M.

2016-06-01

In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

Near-Real-Time Monitoring and Reporting of Crop Growth Condition and Harvest Status Using an Integrated Optical and Radar Approach at the National-Scale in Canada

NASA Astrophysics Data System (ADS)

Shang, J.

2015-12-01

There has been an increasing need to have accurate and spatially detailed information on crop growth condition and harvest status over Canada's agricultural land so that the impacts of environmental conditions, market supply and demand, and transportation network limitations on crop production can be understood fully and acted upon in a timely manner. Presently, Canada doesn't have a national dataset that can provide near-real-time geospatial information on crop growth stage and harvest systematically so that reporting on risk events can be linked directly to the grain supply chain and crop production fluctuations. The intent of this study is to develop an integrated approach using Earth observation (EO) technology to provide a consistent, comprehensive picture of crop growth cycles (growth conditions and stages) and agricultural management activities (field preparation for seeding, harvest, and residue management). Integration of the optical and microwave satellite remote sensing technologies is imperative for robust methodology development and eventually for operational implementation. Particularly, the current synthetic aperture radar (SAR) system Radarsat-2 and to be launched Radarsat Constellation Mission (RCM) are unique EO resources to Canada. Incorporating these Canadian SAR resources with international SAR missions such as the Cosmesky-Med and TerraSAR, could be of great potential for developing change detection technologies particularly useful for monitoring harvest as well as other types of agricultural management events. The study revealed that radar and multi-scale (30m and 250m) optical satellite data can directly detect or infer 1) seeding date, 2) crop growth stages and gross primary productivity (GPP), and 3) harvest progress. Operational prototypes for providing growing-season information at the crop-specific level will be developed across the Canadian agricultural land base.

Application of troposphere model from NWP and GNSS data into real-time precise positioning

NASA Astrophysics Data System (ADS)

Wilgan, Karina; Hadas, Tomasz; Kazmierski, Kamil; Rohm, Witold; Bosy, Jaroslaw

2016-04-01

The tropospheric delay empirical models are usually functions of meteorological parameters (temperature, pressure and humidity). The application of standard atmosphere parameters or global models, such as GPT (global pressure/temperature) model or UNB3 (University of New Brunswick, version 3) model, may not be sufficient, especially for positioning in non-standard weather conditions. The possible solution is to use regional troposphere models based on real-time or near-real time measurements. We implement a regional troposphere model into the PPP (Precise Point Positioning) software GNSS-WARP (Wroclaw Algorithms for Real-time Positioning) developed at Wroclaw University of Environmental and Life Sciences. The software is capable of processing static and kinematic multi-GNSS data in real-time and post-processing mode and takes advantage of final IGS (International GNSS Service) products as well as IGS RTS (Real-Time Service) products. A shortcoming of PPP technique is the time required for the solution to converge. One of the reasons is the high correlation among the estimated parameters: troposphere delay, receiver clock offset and receiver height. To efficiently decorrelate these parameters, a significant change in satellite geometry is required. Alternative solution is to introduce the external high-quality regional troposphere delay model to constrain troposphere estimates. The proposed model consists of zenith total delays (ZTD) and mapping functions calculated from meteorological parameters from Numerical Weather Prediction model WRF (Weather Research and Forecasting) and ZTDs from ground-based GNSS stations using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays) developed at ETH Zurich.

Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System.

PubMed

Pratihast, Arun Kumar; DeVries, Ben; Avitabile, Valerio; de Bruin, Sytze; Herold, Martin; Bergsma, Aldo

2016-01-01

This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications.

Near Real Time Detection and Tracking of the EYJAFJÖLL (iceland) Ash Cloud by the RST (robust Satellite Technique) Approach

NASA Astrophysics Data System (ADS)

Tramutoli, V.; Filizzola, C.; Marchese, F.; Paciello, R.; Pergola, N.; Sannazzaro, F.

2010-12-01

Volcanic ash clouds, besides to be an environmental issue, represent a serious problem for air traffic and an important economic threat for aviation companies. During the recent volcanic crisis due to the April-May 2010 eruption of Eyjafjöll (Iceland), ash clouds became a real problem for common citizens as well: during the first days of the eruption thousands of flights were cancelled disrupting hundred of thousands of passengers. Satellite remote sensing confirmed to be a crucial tool for monitoring this kind of events, spreading for thousands of kilometres with a very rapid space-time dynamics. Especially weather satellites, thanks to their high temporal resolution, may furnish a fundamental contribution, providing frequently updated information. However, in this particular case ash cloud was accompanied by a sudden and significant emission of water vapour, due to the ice melting of Eyjafjallajökull glacier, making satellite ash detection and discrimination very hard, especially in the first few days of the eruption, exactly when accurate information were mostly required in order to support emergency management. Among the satellite-based techniques for near real-time detection and tracking of ash clouds, the RST (Robust Satellite Technique) approach, formerly named RAT - Robust AVHRR Technique, has been long since proposed, demonstrating high performances both in terms of reliability and sensitivity. In this paper, results achieved by using RST-based detection schemes, applied during the Eyjafjöll eruption were presented. MSG-SEVIRI (Meteosat Second Generation - Spinning Enhanced and Visible Infrared Imager) records, with a temporal sampling of 15 minutes, were used applying a standard as well as an advanced RST configuration, which includes the use of SO2 absorption band together with TIR and MIR channels. Main outcomes, limits and possible future improvements were also discussed.

MARVEL: A knowledge-based productivity enhancement tool for real-time multi-mission and multi-subsystem spacecraft operations

NASA Astrophysics Data System (ADS)

Schwuttke, Ursula M.; Veregge, John, R.; Angelino, Robert; Childs, Cynthia L.

1990-10-01

The Monitor/Analyzer of Real-time Voyager Engineering Link (MARVEL) is described. It is the first automation tool to be used in an online mode for telemetry monitoring and analysis in mission operations. MARVEL combines standard automation techniques with embedded knowledge base systems to simultaneously provide real time monitoring of data from subsystems, near real time analysis of anomaly conditions, and both real time and non-real time user interface functions. MARVEL is currently capable of monitoring the Computer Command Subsystem (CCS), Flight Data Subsystem (FDS), and Attitude and Articulation Control Subsystem (AACS) for both Voyager spacecraft, simultaneously, on a single workstation. The goal of MARVEL is to provide cost savings and productivity enhancement in mission operations and to reduce the need for constant availability of subsystem expertise.

Near Real Time Structural Health Monitoring with Multiple Sensors in a Cloud Environment

NASA Astrophysics Data System (ADS)

Bock, Y.; Todd, M.; Kuester, F.; Goldberg, D.; Lo, E.; Maher, R.

2017-12-01

A repeated near real time 3-D digital surrogate representation of critical engineered structures can be used to provide actionable data on subtle time-varying displacements in support of disaster resiliency. We describe a damage monitoring system of optimally-integrated complementary sensors, including Global Navigation Satellite Systems (GNSS), Micro-Electro-Mechanical Systems (MEMS) accelerometers coupled with the GNSS (seismogeodesy), light multi-rotor Unmanned Aerial Vehicles (UAVs) equipped with high-resolution digital cameras and GNSS/IMU, and ground-based Light Detection and Ranging (LIDAR). The seismogeodetic system provides point measurements of static and dynamic displacements and seismic velocities of the structure. The GNSS ties the UAV and LIDAR imagery to an absolute reference frame with respect to survey stations in the vicinity of the structure to isolate the building response to ground motions. The GNSS/IMU can also estimate the trajectory of the UAV with respect to the absolute reference frame. With these constraints, multiple UAVs and LIDAR images can provide 4-D displacements of thousands of points on the structure. The UAV systematically circumnavigates the target structure, collecting high-resolution image data, while the ground LIDAR scans the structure from different perspectives to create a detailed baseline 3-D reference model. UAV- and LIDAR-based imaging can subsequently be repeated after extreme events, or after long time intervals, to assess before and after conditions. The unique challenge is that disaster environments are often highly dynamic, resulting in rapidly evolving, spatio-temporal data assets with the need for near real time access to the available data and the tools to translate these data into decisions. The seismogeodetic analysis has already been demonstrated in the NASA AIST Managed Cloud Environment (AMCE) designed to manage large NASA Earth Observation data projects on Amazon Web Services (AWS). The Cloud provides distinct advantages in terms of extensive storage and computing resources required for processing UAV and LIDAR imagery. Furthermore, it avoids single points of failure and allows for remote operations during emergencies, when near real time access to structures may be limited.

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Peters-Lidard, Christa

2013-01-01

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

Improved Orbit Determination and Forecasts with an Assimilative Tool for Atmospheric Density and Satellite Drag Specification

NASA Astrophysics Data System (ADS)

Crowley, G.; Pilinski, M.; Sutton, E. K.; Codrescu, M.; Fuller-Rowell, T. J.; Matsuo, T.; Fedrizzi, M.; Solomon, S. C.; Qian, L.; Thayer, J. P.

2016-12-01

Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by the variability in density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of LEO satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. We describe ongoing work to build a comprehensive nowcast and forecast system for specifying the neutral atmospheric state related to orbital drag conditions. The system outputs include neutral density, winds, temperature, composition, and the satellite drag derived from these parameters. This modeling tool is based on several state-of-the-art coupled models of the thermosphere-ionosphere as well as several empirical models running in real-time and uses assimilative techniques to produce a thermospheric nowcast. This software will also produce 72 hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition and using near real-time and predicted space weather data and indices as the inputs. Features of this technique include: • Satellite drag specifications with errors lower than current models • Altitude coverage up to 1000km • Background state representation using both first principles and empirical models • Assimilation of satellite drag and other datatypes • Real time capability • Ability to produce 72-hour forecasts of the atmospheric state In this paper, we will summarize the model design and assimilative architecture, and present preliminary validation results. Validation results will be presented in the context of satellite orbit errors and compared with several leading atmospheric models including the High Accuracy Satellite Drag Model, which is currently used operationally by the Air Force to specify neutral densities. As part of the analysis, we compare the drag observed by a variety of satellites which were not used as part of the assimilation-dataset and whose perigee altitudes span a range from 200km to 700 km.

Impact of Scatterometer Ocean Wind Vector Data on NOAA Operations

NASA Astrophysics Data System (ADS)

Jelenak, Z.; Chang, P.; Brennan, M. J.; Sienkiewicz, J. M.

2015-12-01

Near real-time measurements of ocean surface vector winds (OSVW), including both wind speed and direction from non-NOAA satellites, are being widely used in critical operational NOAA forecasting and warning activities. The scatterometer wind data data have had major operational impact in: a) determining wind warning areas for mid-latitude systems (gale, storm,hurricane force); b) determining tropical cyclone 34-knot and 50-knot wind radii. c) tracking the center location of tropical cyclones, including the initial identification of their formation. d) identifying and warning of extreme gap and jet wind events at all latitudes. e) identifying the current location of frontal systems and high and low pressure centers. f) improving coastal surf and swell forecasts Much has been learned about the importance and utility of satellite OSVW data in operational weather forecasting and warning by exploiting OSVW research satellites in near real-time. Since December 1999 when first data from QuikSCAT scatterometer became available in near real time NOAA operations have been benefiting from ASCAT scatterometer observations on MetOp-A and B, Indian OSCAT scatterometer on OceanSat-3 and lately NASA's RapidScat mission on International Space Station. With oceans comprising over 70 percent of the earth's surface, the impacts of these data have been tremendous in serving society's needs for weather and water information and in supporting the nation's commerce with information for safe, efficient, and environmentally sound transportation and coastal preparedness. The satellite OSVW experience that has been gained over the past decade by users in the operational weather community allows for realistic operational OSVW requirements to be properly stated for future missions. Successful model of transitioning research data into operation implemented by Ocean Winds Team in NOAA's NESDIS/STAR office and subsequent data impacts will be presented and discussed.

Distributed Timing and Localization (DiGiTaL)

NASA Technical Reports Server (NTRS)

D'Amico, Simone; Hunter, Roger C.; Baker, Christopher

2017-01-01

The Distributed Timing and Localization (DiGiTaL) system provides nano satellite formations with unprecedented,centimeter-level navigation accuracy in real time and nanosecond-level time synchronization. This is achieved through the integration of a multi-constellation Global Navigation Satellite System (GNSS) receiver, a Chip-Scale Atomic Clock (CSAC), and a dedicated Inter-Satellite Link (ISL). In comparison, traditional single spacecraft GNSS navigation solutions are accurate only to the meter-level due to the sole usage of coarse pseudo-range measurements. To meet the strict requirements of future miniaturized distributed space systems, DiGiTaL uses powerful error-cancelling combinations of raw carrier-phase measurements which are exchanged between the swarming nano satellites through a decentralized network. A reduced-dynamics estimation architecture on board each individual nano satellite processes the resulting millimeter-level noise measurements to reconstruct the fullformation state with high accuracy.

Multi-Sensor Systems and Data Fusion for Telecommunications, Remote Sensing and Radar (les Systemes multi-senseurs et le fusionnement des donnees pour les telecommunications, la teledetection et les radars)

DTIC Science & Technology

1998-04-01

The result of the project is a demonstration of the fusion process, the sensors management and the real-time capabilities using simulated sensors...demonstrator (TAD) is a system that demonstrates the core ele- ment of a battlefield ground surveillance system by simulation in near real-time. The core...Management and Sensor/Platform simulation . The surveillance system observes the real world through a non-collocated heterogene- ous multisensory system

Real Time Radiation Exposure And Health Risks

NASA Technical Reports Server (NTRS)

Hu, Shaowen; Barzilla, Janet E.; Semones, Edward J.

2015-01-01

Radiation from solar particle events (SPEs) poses a serious threat to future manned missions outside of low Earth orbit (LEO). Accurate characterization of the radiation environment in the inner heliosphere and timely monitoring the health risks to crew are essential steps to ensure the safety of future Mars missions. In this project we plan to develop an approach that can use the particle data from multiple satellites and perform near real-time simulations of radiation exposure and health risks for various exposure scenarios. Time-course profiles of dose rates will be calculated with HZETRN and PDOSE from the energy spectrum and compositions of the particles archived from satellites, and will be validated from recent radiation exposure measurements in space. Real-time estimation of radiation risks will be investigated using ARRBOD. This cross discipline integrated approach can improve risk mitigation by providing critical information for risk assessment and medical guidance to crew during SPEs.

State of the Oceans: A Satellite Data Processing System for Visualizing Near Real-Time Imagery on Google Earth

NASA Astrophysics Data System (ADS)

Thompson, C. K.; Bingham, A. W.; Hall, J. R.; Alarcon, C.; Plesea, L.; Henderson, M. L.; Levoe, S.

2011-12-01

The State of the Oceans (SOTO) web tool was developed at NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC) at the Jet Propulsion Laboratory (JPL) as an interactive means for users to visually explore and assess ocean-based geophysical parameters extracted from the latest archived data products. The SOTO system consists of four extensible modules, a data polling tool, a preparation and imaging package, image server software, and the graphical user interface. Together, these components support multi-resolution visualization of swath (Level 2) and gridded Level 3/4) data products as either raster- or vector- based KML layers on Google Earth. These layers are automatically updated periodically throughout the day. Current parameters available include sea surface temperature, chlorophyll concentration, ocean winds, sea surface height anomaly, and sea surface temperature anomaly. SOTO also supports mash-ups, allowing KML feeds from other sources to be overlaid directly onto Google Earth such as hurricane tracks and buoy data. A version of the SOTO software has also been installed at Goddard Space Flight Center (GSFC) to support the Land Atmosphere Near real-time Capability for EOS (LANCE). The State of the Earth (SOTE) has similar functionality to SOTO but supports different data sets, among them the MODIS 250m data product.

Multi-sensor satellite monitoring of ash and SO2 volcanic plume in support to aviation control

NASA Astrophysics Data System (ADS)

Brenot, Hugues; Theys, Nicolas; Clarisse, Lieven; van Geffen, Jos; van Gent, Jeroen; Van Roozendael, Michel; van der A, Ronald; Hurtmans, Daniel; Coheur, Pierre-Francois; Clerbaux, Cathy; Valks, Pieter; Hedelt, Pascal; Prata, Fred; Rasson, Olivier; Sievers, Klaus; Zehner, Claus

2014-05-01

The 'Support to Aviation Control Service' (SACS; http://sacs.aeronomie.be) is an ESA-funded project hosted by the Belgian Institute for Space Aeronomy since 2007. The service provides near real-time (NRT) global volcanic ash and SO2 observations, as well as notifications in case of volcanic eruptions (success rate >95% for ash and SO2). SACS is based on the combined use of UV-visible (OMI, GOME-2 MetOp-A, GOME-2 MetOp-B) and infrared (AIRS, IASI MetOp-A, IASI MetOp-B) satellite instruments. The SACS service is primarily designed to support the Volcanic Ash Advisory Centers (VAACs) in their mandate to gather information on volcanic clouds and give advice to airline and air traffic control organisations. SACS also serves other users that subscribe to the service, in particular local volcano observatories, research scientists and airliner pilots. When a volcanic eruption is detected, SACS issues a warning that takes the form of a notification sent by e-mail to users. The SACS notification points to a dedicated web page where all relevant information is available and can be visualised with user-friendly tools. Information about the volcanic plume height from GOME-2 (MetOp-A and MetOp-B) are also available. The strength of a multi-sensor approach relies in the use of satellite data with different overpasses times, minimising the time-lag for detection and enhancing the reliability of such alerts. This presentation will give an overview of the SACS service, and of the different techniques used to detect volcanic plumes (ash, SO2 and plume height). It will also highlight the strengths and limitations of the service and measurements, and some perspectives.

Nowcasting, forecasting and hindcasting Harvey and Irma inundation in near-real time using a continental 2D hydrodynamic model

NASA Astrophysics Data System (ADS)

Sampson, C. C.; Wing, O.; Quinn, N.; Smith, A.; Neal, J. C.; Schumann, G.; Bates, P.

2017-12-01

During an ongoing natural disaster data are required on: (1) the current situation (nowcast); (2) its likely immediate evolution (forecast); and (3) a consistent view post-event of what actually happened (hindcast or reanalysis). We describe methods used to achieve all three tasks for flood inundation during the Harvey and Irma events using a continental scale 2D hydrodynamic model (Wing et al., 2017). The model solves the local inertial form of the Shallow Water equations over a regular grid of 1 arcsecond ( 30m). Terrain data are taken from the USGS National Elevation Dataset with known flood defences represented using the U.S. Army Corps of Engineers National Levee Dataset. Channels are treated as sub-grid scale features using the HydroSHEDS global hydrography data set. The model is driven using river flows, rainfall and coastal water levels. It simulates river flooding in basins > 50 km2, and fluvial and coastal flooding everywhere. Previous wide area validation tests show this model to be capable of matching FEMA maps and USGS local models built with bespoke data with hit rates of 86% and 92% respectively (Wing et al., 2017). Boundary conditions were taken from NOAA QPS data to produce nowcast and forecast simulations in near real time, before updating with NOAA observations to produce the hindcast. During the event simulation results were supplied to major insurers and multi-nationals who used them to estimate their likely capital exposure and to mitigate flood damage to their infrastructure whilst the event was underway. Simulations were validated against modelled flood footprints computed by FEMA and USACE, and composite satellite imagery produced by the Dartmouth Flood Observatory. For the Harvey event, hit rates ranged from 60-84% against these data sources, but a lack of metadata meant it was difficult to perform like-for-like comparisons. The satellite data also appeared to miss known flooding in urban areas that was picked up in the models. Despite these limitations, the validation was able to pick our areas, notably along the Colorado River near Houston, where our model under-performed and identify areas for future development. The study shows that high resolution near real-time inundation predictions over very large areas during complex events with multiple flood drivers are now a reality.

Central Satellite Data Repository Supporting Research and Development

NASA Astrophysics Data System (ADS)

Han, W.; Brust, J.

2015-12-01

Near real-time satellite data is critical to many research and development activities of atmosphere, land, and ocean processes. Acquiring and managing huge volumes of satellite data without (or with less) latency in an organization is always a challenge in the big data age. An organization level data repository is a practical solution to meeting this challenge. The STAR (Center for Satellite Applications and Research of NOAA) Central Data Repository (SCDR) is a scalable, stable, and reliable repository to acquire, manipulate, and disseminate various types of satellite data in an effective and efficient manner. SCDR collects more than 200 data products, which are commonly used by multiple groups in STAR, from NOAA, GOES, Metop, Suomi NPP, Sentinel, Himawari, and other satellites. The processes of acquisition, recording, retrieval, organization, and dissemination are performed in parallel. Multiple data access interfaces, like FTP, FTPS, HTTP, HTTPS, and RESTful, are supported in the SCDR to obtain satellite data from their providers through high speed internet. The original satellite data in various raster formats can be parsed in the respective adapter to retrieve data information. The data information is ingested to the corresponding partitioned tables in the central database. All files are distributed equally on the Network File System (NFS) disks to balance the disk load. SCDR provides consistent interfaces (including Perl utility, portal, and RESTful Web service) to locate files of interest easily and quickly and access them directly by over 200 compute servers via NFS. SCDR greatly improves collection and integration of near real-time satellite data, addresses satellite data requirements of scientists and researchers, and facilitates their primary research and development activities.

One-Centimeter Orbits in Near-Real Time: The GPS Experience on OSTM/JASON-2

NASA Technical Reports Server (NTRS)

Haines, Bruce; Armatys, Michael; Bar-Sever, Yoaz; Bertiger, Willy; Desai, Shailen; Dorsey, Angela; Lane, Christopher; Weiss, Jan

2010-01-01

The advances in Precise Orbit Determination (POD) over the past three decades have been driven in large measure by the increasing demands of satellite altimetry missions. Since the launch of Seasat in 1978, both tracking-system technologies and orbit modeling capabilities have evolved considerably. The latest in a series of precise (TOPEX-class) altimeter missions is the Ocean Surface Topography Mission (OSTM, also Jason-2). GPS-based orbit solutions for this mission are accurate to 1-cm (radial RMS) within 3-5 hrs of real time. These GPS-based orbit products provide the basis for a near-real time sea-surface height product that supports increasingly diverse applications of operational oceanography and climate forecasting.

Temporal and modal characterization of DoD source air toxic emission factors: final report

EPA Science Inventory

This project tested three, real-/near real-time monitoring techniques to develop air toxic emission factors for Department of Defense (DoD) platform sources. These techniques included: resonance enhanced multi photon ionization time of flight mass spectrometry (REMPI-TOFMS) for o...

Supervised classification of aerial imagery and multi-source data fusion for flood assessment

NASA Astrophysics Data System (ADS)

Sava, E.; Harding, L.; Cervone, G.

2015-12-01

Floods are among the most devastating natural hazards and the ability to produce an accurate and timely flood assessment before, during, and after an event is critical for their mitigation and response. Remote sensing technologies have become the de-facto approach for observing the Earth and its environment. However, satellite remote sensing data are not always available. For these reasons, it is crucial to develop new techniques in order to produce flood assessments during and after an event. Recent advancements in data fusion techniques of remote sensing with near real time heterogeneous datasets have allowed emergency responders to more efficiently extract increasingly precise and relevant knowledge from the available information. This research presents a fusion technique using satellite remote sensing imagery coupled with non-authoritative data such as Civil Air Patrol (CAP) and tweets. A new computational methodology is proposed based on machine learning algorithms to automatically identify water pixels in CAP imagery. Specifically, wavelet transformations are paired with multiple classifiers, run in parallel, to build models discriminating water and non-water regions. The learned classification models are first tested against a set of control cases, and then used to automatically classify each image separately. A measure of uncertainty is computed for each pixel in an image proportional to the number of models classifying the pixel as water. Geo-tagged tweets are continuously harvested and stored on a MongoDB and queried in real time. They are fused with CAP classified data, and with satellite remote sensing derived flood extent results to produce comprehensive flood assessment maps. The final maps are then compared with FEMA generated flood extents to assess their accuracy. The proposed methodology is applied on two test cases, relative to the 2013 floods in Boulder CO, and the 2015 floods in Texas.

On the reliable use of satellite-derived surface water products for global flood monitoring

NASA Astrophysics Data System (ADS)

Hirpa, F. A.; Revilla-Romero, B.; Thielen, J.; Salamon, P.; Brakenridge, R.; Pappenberger, F.; de Groeve, T.

2015-12-01

Early flood warning and real-time monitoring systems play a key role in flood risk reduction and disaster response management. To this end, real-time flood forecasting and satellite-based detection systems have been developed at global scale. However, due to the limited availability of up-to-date ground observations, the reliability of these systems for real-time applications have not been assessed in large parts of the globe. In this study, we performed comparative evaluations of the commonly used satellite-based global flood detections and operational flood forecasting system using 10 major flood cases reported over three years (2012-2014). Specially, we assessed the flood detection capabilities of the near real-time global flood maps from the Global Flood Detection System (GFDS), and from the Moderate Resolution Imaging Spectroradiometer (MODIS), and the operational forecasts from the Global Flood Awareness System (GloFAS) for the major flood events recorded in global flood databases. We present the evaluation results of the global flood detection and forecasting systems in terms of correctly indicating the reported flood events and highlight the exiting limitations of each system. Finally, we propose possible ways forward to improve the reliability of large scale flood monitoring tools.

Automatic Cloud Detection from Multi-Temporal Satellite Images: Towards the Use of PLÉIADES Time Series

NASA Astrophysics Data System (ADS)

Champion, N.

2012-08-01

Contrary to aerial images, satellite images are often affected by the presence of clouds. Identifying and removing these clouds is one of the primary steps to perform when processing satellite images, as they may alter subsequent procedures such as atmospheric corrections, DSM production or land cover classification. The main goal of this paper is to present the cloud detection approach, developed at the French Mapping agency. Our approach is based on the availability of multi-temporal satellite images (i.e. time series that generally contain between 5 and 10 images) and is based on a region-growing procedure. Seeds (corresponding to clouds) are firstly extracted through a pixel-to-pixel comparison between the images contained in time series (the presence of a cloud is here assumed to be related to a high variation of reflectance between two images). Clouds are then delineated finely using a dedicated region-growing algorithm. The method, originally designed for panchromatic SPOT5-HRS images, is tested in this paper using time series with 9 multi-temporal satellite images. Our preliminary experiments show the good performances of our method. In a near future, the method will be applied to Pléiades images, acquired during the in-flight commissioning phase of the satellite (launched at the end of 2011). In that context, this is a particular goal of this paper to show to which extent and in which way our method can be adapted to this kind of imagery.

Web-Based Satellite Products Database for Meteorological and Climate Applications

NASA Technical Reports Server (NTRS)

Phan, Dung; Spangenberg, Douglas A.; Palikonda, Rabindra; Khaiyer, Mandana M.; Nordeen, Michele L.; Nguyen, Louis; Minnis, Patrick

2004-01-01

The need for ready access to satellite data and associated physical parameters such as cloud properties has been steadily growing. Air traffic management, weather forecasters, energy producers, and weather and climate researchers among others can utilize more satellite information than in the past. Thus, it is essential that such data are made available in near real-time and as archival products in an easy-access and user friendly environment. A host of Internet web sites currently provide a variety of satellite products for various applications. Each site has a unique contribution with appeal to a particular segment of the public and scientific community. This is no less true for the NASA Langley's Clouds and Radiation (NLCR) website (http://www-pm.larc.nasa.gov) that has been evolving over the past 10 years to support a variety of research projects This website was originally developed to display cloud products derived from the Geostationary Operational Environmental Satellite (GOES) over the Southern Great Plains for the Atmospheric Radiation Measurement (ARM) Program. It has evolved into a site providing a comprehensive database of near real-time and historical satellite products used for meteorological, aviation, and climate studies. To encourage the user community to take advantage of the site, this paper summarizes the various products and projects supported by the website and discusses future options for new datasets.

Satellite rainfall monitoring over Africa using multi-spectral MSG data in an artificial neural network approach

NASA Astrophysics Data System (ADS)

Chadwick, Robin; Grimes, David

2010-05-01

Rainfall monitoring over Africa is crucial for a variety of humanitarian and agricultural purposes, and satellites have been used for some time to provide real-time rainfall estimates over the region. Several recent applications of satellite rainfall estimates, such as flash-flood warning systems and crop-yield models, require accurate rainfall totals at daily timescales or below. Multi-spectral Meteosat Second Generation (MSG) data provide information on cloud properties such as optical depth and cloud particle size and phase. These parameters are all relevant to the probability of rainfall occurring from a cloud and the likely intensity of that rainfall, so the use of MSG data should lead to improved satellite rainfall estimates. An artificial neural network (ANN) using multi-spectral inputs from MSG has been trained to provide daily rainfall estimates over Ethiopia, using daily rain-gauge data for calibration. Although ANN methods have previously been applied to the problem of producing rainfall estimates from multi-spectral satellite data, in general precipitation radar data have been used for calibration. The advantage of using rain-gauge data is that gauges are far more widespread over Africa than radar networks, so this method can be easily transferred and if necessary re-calibrated in different climatological regions of the continent. The ANN estimates have been validated against independent Ethiopian gauge data at a variety of time and space scales. The ANN shows an improvement in accuracy at daily timescale when compared to rainfall estimates from the TAMSAT algorithm, which uses only single channel MSG data.

Development and Flight Results of a PC104/QNX-Based On-Board Computer and Software for the YES2 Tether Experiment

NASA Astrophysics Data System (ADS)

Spiliotopoulos, I.; Mirmont, M.; Kruijff, M.

2008-08-01

This paper highlights the flight preparation and mission performance of a PC104-based On-Board Computer for ESA's second Young Engineer's Satellite (YES2), with additional attention to the flight software design and experience of QNX as multi-process real-time operating system. This combination of Commercial-Of-The-Shelf (COTS) technologies is an accessible option for small satellites with high computational demands.

Multi-Satellite Observation Scheduling for Large Area Disaster Emergency Response

NASA Astrophysics Data System (ADS)

Niu, X. N.; Tang, H.; Wu, L. X.

2018-04-01

an optimal imaging plan, plays a key role in coordinating multiple satellites to monitor the disaster area. In the paper, to generate imaging plan dynamically according to the disaster relief, we propose a dynamic satellite task scheduling method for large area disaster response. First, an initial robust scheduling scheme is generated by a robust satellite scheduling model in which both the profit and the robustness of the schedule are simultaneously maximized. Then, we use a multi-objective optimization model to obtain a series of decomposing schemes. Based on the initial imaging plan, we propose a mixed optimizing algorithm named HA_NSGA-II to allocate the decomposing results thus to obtain an adjusted imaging schedule. A real disaster scenario, i.e., 2008 Wenchuan earthquake, is revisited in terms of rapid response using satellite resources and used to evaluate the performance of the proposed method with state-of-the-art approaches. We conclude that our satellite scheduling model can optimize the usage of satellite resources so as to obtain images in disaster response in a more timely and efficient manner.

Interagency Collaborators Develop and Implement ForWarn, a National, Near Real Time Forest Monitoring Tool

NASA Technical Reports Server (NTRS)

Underwood, Lauren

2013-01-01

ForWarn is a satellite-based forest monitoring tool that is being used to detect and monitor disturbances to forest conditions and forest health. It has been developed through the synergistic efforts, capabilities and contributions of four federal agencies, including the US Forest Service Eastern Forest and Western Wildland Environmental Threat Assessment Centers, NASA Stennis Space Center (SSC), Department of Energy's (DOE) Oak Ridge National Laboratory (ORNL) and US Geological Survey Earth (USGS) Earth Research Observation System (EROS), as well as university partners, including the University of North Carolina Asheville's National Environmental Modeling and Analysis Center (NEMAC). This multi-organizational partnership is key in producing a unique, path finding near real-time forest monitoring system that is now used by many federal, state and local government end-users. Such a system could not have been produced so effectively by any of these groups on their own. The forests of the United States provide many societal values and benefits, ranging from ecological, economic, cultural, to recreational. Therefore, providing a reliable and dependable forest and other wildland monitoring system is important to ensure the continued health, productivity, sustainability and prudent use of our Nation's forests and forest resources. ForWarn does this by producing current health indicator maps of our nation's forests based on satellite data from NASA's MODIS (Moderate Resolution Imaging Spectroradiometer) sensors. Such a capability can provide noteworthy value, cost savings and significant impact at state and local government levels because at those levels of government, once disturbances are evident and cause negative impacts, a response must be carried out. The observations that a monitoring system like ForWarn provide, can also contribute to a much broader-scale understanding of vegetation disturbances.

Enhancements to NASA's Land Atmosphere Near Real-Time Capability for EOS (LANCE)

NASA Technical Reports Server (NTRS)

Davies, Diane; Michael, Karen; Schmaltz, Jeffrey; Boller, Ryan A.; Masuoka, Ed; Ye, Gang; Roman, Miguel; Vermote, Eric; Harrison, Sherry; Rinsland, Pamela;

Direct Satellite Data Acquisition and its Application for Large -scale Monitoring Projects in Russia

NASA Astrophysics Data System (ADS)

Gershenzon, O.

2011-12-01

ScanEx RDC created an infrastructure (ground stations network) to acquire and process remote sensing data from different satellites: Terra, Aqua, Landsat, IRS-P5/P6, SPOT 4/5, FORMOSAT-2, EROS A/B, RADARSAT-1/2, ENVISAT-1. It owns image archives from these satellites as well as from SPOT-2 and CARTOSAT-2. ScanEx RDC builds and delivers remote sensing ground stations (working with up to 15 satellites); and owns the ground stations network to acquire data for Russia and surrounding territory. ScanEx stations are the basic component in departmental networks of remote sensing data acquisition for different state authorities (Roshydromet, Ministry of Natural Recourses, Emercom) and University- based remote sensing data acquisition and processing centers in Russia and abroad. ScanEx performs large-scale projects in collaboration with government agencies to monitor forests, floods, fires, sea surface pollution, and ice situation in Northern Russia. During 2010-2011 ScanEx conducted daily monitoring of wild fires in Russia detecting and registering thermal anomalies using data from Terra, Aqua, Landsat and SPOT satellites. Detailed SPOT 4/5 data is used to analyze burnt areas and to assess damage caused by fire. Satellite data along with other information about fire situation in Russia was daily updated and published via free-access Internet geoportal. A few projects ScanEx conducted together with environmental NGO. Project "Satellite monitoring of Especially Protected Natural Areas of Russia and its results visualization on geoportal was conducted in cooperation with NGO "Transparent World". The project's goal was to observe natural phenomena and economical activity, including illegal, by means of Earth remote sensing data. Monitoring is based on multi-temporal optical space imagery of different spatial resolution. Project results include detection of anthropogenic objects that appeared in the vicinity or even within the border of natural territories, that have never been touched by civilization before. "Satellite based technology for monitoring ship ice navigation and its influence on seal population in the White Sea" project was conducted in cooperation with IFAW. Results of the near real-time satellite monitoring were published on specially designed open web source. This allows project team to put image interpretation results in near real-time mode for on-line access to all interesting external stakeholders. During project realization Envisat, Radarsat, SPOT, EROS space images were used. In addition the methodology to locate seal population using EROS space images was developed. This methodology is based on detection of vital functions and displacement traces. Environmental satellite monitoring of Northern Russian territory and Arctic seas projects where the results are published via free-access Internet geoportal has a significant social importance.

Real-time science and outreach from the UNOLS fleet via HiSeasNet

NASA Astrophysics Data System (ADS)

Foley, S.; Berger, J.; Orcutt, J. A.; Brice, D.; Coleman, D. F.; Grabowski, E. M.

2010-12-01

The HiSeasNet satellite communications network has ben providing cost-effective, reliable, continuous Internet connectivity to the UNOLS oceanographic research fleet for nearly nine years. During that time, HiSeasNet has supported science and outreach programs with a variety of real-time interactions back to shore including videoconferencing, webcasting, shared whiteboards, and streaming high-definition video feeds. Solutions have varied in scale, cost, and capability. As real-time science and outreach becomes more common, experience with a variety of technologies continues to build, and more opportunities yet to explore.

Satellite-based Flood Modeling Using TRMM-based Rainfall Products.

PubMed

Harris, Amanda; Rahman, Sayma; Hossain, Faisal; Yarborough, Lance; Bagtzoglou, Amvrossios C; Easson, Greg

2007-12-20

Increasingly available and a virtually uninterrupted supply of satellite-estimatedrainfall data is gradually becoming a cost-effective source of input for flood predictionunder a variety of circumstances. However, most real-time and quasi-global satelliterainfall products are currently available at spatial scales ranging from 0.25 o to 0.50 o andhence, are considered somewhat coarse for dynamic hydrologic modeling of basin-scaleflood events. This study assesses the question: what are the hydrologic implications ofuncertainty of satellite rainfall data at the coarse scale? We investigated this question onthe 970 km² Upper Cumberland river basin of Kentucky. The satellite rainfall productassessed was NASA's Tropical Rainfall Measuring Mission (TRMM) Multi-satellitePrecipitation Analysis (TMPA) product called 3B41RT that is available in pseudo real timewith a latency of 6-10 hours. We observed that bias adjustment of satellite rainfall data canimprove application in flood prediction to some extent with the trade-off of more falsealarms in peak flow. However, a more rational and regime-based adjustment procedureneeds to be identified before the use of satellite data can be institutionalized among floodmodelers.

Evaluation of topographical and seasonal feature using GPM IMERG and TRMM 3B42 over Far-East Asia

NASA Astrophysics Data System (ADS)

Kim, Kiyoung; Park, Jongmin; Baik, Jongjin; Choi, Minha

2017-05-01

The acquisition of accurate precipitation data is essential for analyzing various hydrological phenomena and climate change. Recently, the Global Precipitation Measurement (GPM) satellites were launched as a next-generation rainfall mission for observing global precipitation characteristics. The main objective in this study is to assess precipitation products from GPM, especially the Integrated Multi-satellitE Retrievals (GPM-3IMERGHH) and the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), using gauge-based precipitation data from Far-East Asia during the pre-monsoon and monsoon seasons. Evaluation was performed by focusing on three different factors: geographical aspects, seasonal factors, and spatial distributions. In both mountainous and coastal regions, the GPM-3IMERGHH product showed better performance than the TRMM 3B42 V7, although both rainfall products showed uncertainties caused by orographic convection and the land-ocean classification algorithm. GPM-3IMERGHH performed about 8% better than TRMM 3B42 V7 during the pre-monsoon and monsoon seasons due to the improvement of loaded sensor and reinforcement in capturing convective rainfall, respectively. In depicting the spatial distribution of precipitation, GPM-3IMERGHH was more accurate than TRMM 3B42 V7 because of its enhanced spatial and temporal resolutions of 10 km and 30 min, respectively. Based on these results, GPM-3IMERGHH would be helpful for not only understanding the characteristics of precipitation with high spatial and temporal resolution, but also for estimating near-real-time runoff patterns.

Development of On-line Wildfire Emissions for the Operational Canadian Air Quality Forecast System

NASA Astrophysics Data System (ADS)

Pavlovic, R.; Menard, S.; Chen, J.; Anselmo, D.; Paul-Andre, B.; Gravel, S.; Moran, M. D.; Davignon, D.

2013-12-01

An emissions processing system has been developed to incorporate near-real-time emissions from wildfires and large prescribed burns into Environment Canada's real-time GEM-MACH air quality (AQ) forecast system. Since the GEM-MACH forecast domain covers Canada and most of the USA, including Alaska, fire location information is needed for both of these large countries. Near-real-time satellite data are obtained and processed separately for the two countries for organizational reasons. Fire location and fuel consumption data for Canada are provided by the Canadian Forest Service's Canadian Wild Fire Information System (CWFIS) while fire location and emissions data for the U.S. are provided by the SMARTFIRE (Satellite Mapping Automated Reanalysis Tool for Fire Incident Reconciliation) system via the on-line BlueSky Gateway. During AQ model runs, emissions from individual fire sources are injected into elevated model layers based on plume-rise calculations and then transport and chemistry calculations are performed. This 'on the fly' approach to the insertion of emissions provides greater flexibility since on-line meteorology is used and reduces computational overhead in emission pre-processing. An experimental wildfire version of GEM-MACH was run in real-time mode for the summers of 2012 and 2013. 48-hour forecasts were generated every 12 hours (at 00 and 12 UTC). Noticeable improvements in the AQ forecasts for PM2.5 were seen in numerous regions where fire activity was high. Case studies evaluating model performance for specific regions, computed objective scores, and subjective evaluations by AQ forecasters will be included in this presentation. Using the lessons learned from the last two summers, Environment Canada will continue to work towards the goal of incorporating near-real-time intermittent wildfire emissions within the operational air quality forecast system.

The Use of NASA near Real-time and Archived Satellite Data to Support Disaster Assessment

NASA Technical Reports Server (NTRS)

McGrath, Kevin M.; Molthan, Andrew; Burks, Jason

2014-01-01

With support from a NASA's Applied Sciences Program, The Short-term Prediction Research and Transition (SPoRT) Center has explored a variety of techniques for utilizing archived and near real-time NASA satellite data to support disaster assessment activities. MODIS data from the NASA Land Atmosphere Near Real-time Capability for EOS currently provides true color and other imagery for assessment and potential applications including, but not limited to, flooding, fires, and tornadoes. In May 2013, the SPoRT Center developed unique power outage composites using the VIIRS Day/Night Band to represent the first clear sky view of damage inflicted upon Moore and Oklahoma City, Oklahoma following the devastating EF-5 tornado that occurred on May 20. Pre-event imagery provided by the NASA funded Web-Enabled Landsat Data project offer a basis of comparison for monitoring post-disaster recovery efforts. Techniques have also been developed to generate products from higher resolution imagery from the recently available International Space Station SERVIR Environmental Research and Visualization System instrument. Of paramount importance is to deliver these products to end users expeditiously and in formats compatible with Decision Support Systems (DSS). Delivery techniques include a Tile Map Service (TMS) and a Web Mapping Service (WMS). These mechanisms allow easy integration of satellite products into DSS's, including the National Weather Service's Damage Assessment Toolkit for use by personnel conducting damage surveys. This poster will present an overview of the developed techniques and products and compare the strengths and weaknesses of the TMS and WMS.

GPS Satellite Orbit Prediction at User End for Real-Time PPP System.

PubMed

Yang, Hongzhou; Gao, Yang

2017-08-30

This paper proposed the high-precision satellite orbit prediction process at the user end for the real-time precise point positioning (PPP) system. Firstly, the structure of a new real-time PPP system will be briefly introduced in the paper. Then, the generation of satellite initial parameters (IP) at the sever end will be discussed, which includes the satellite position, velocity, and the solar radiation pressure (SRP) parameters for each satellite. After that, the method for orbit prediction at the user end, with dynamic models including the Earth's gravitational force, lunar gravitational force, solar gravitational force, and the SRP, are presented. For numerical integration, both the single-step Runge-Kutta and multi-step Adams-Bashforth-Moulton integrator methods are implemented. Then, the comparison between the predicted orbit and the international global navigation satellite system (GNSS) service (IGS) final products are carried out. The results show that the prediction accuracy can be maintained for several hours, and the average prediction error of the 31 satellites are 0.031, 0.032, and 0.033 m for the radial, along-track and cross-track directions over 12 h, respectively. Finally, the PPP in both static and kinematic modes are carried out to verify the accuracy of the predicted satellite orbit. The average root mean square error (RMSE) for the static PPP of the 32 globally distributed IGS stations are 0.012, 0.015, and 0.021 m for the north, east, and vertical directions, respectively; while the RMSE of the kinematic PPP with the predicted orbit are 0.031, 0.069, and 0.167 m in the north, east and vertical directions, respectively.

GPS Satellite Orbit Prediction at User End for Real-Time PPP System

PubMed Central

Yang, Hongzhou; Gao, Yang

2017-01-01

This paper proposed the high-precision satellite orbit prediction process at the user end for the real-time precise point positioning (PPP) system. Firstly, the structure of a new real-time PPP system will be briefly introduced in the paper. Then, the generation of satellite initial parameters (IP) at the sever end will be discussed, which includes the satellite position, velocity, and the solar radiation pressure (SRP) parameters for each satellite. After that, the method for orbit prediction at the user end, with dynamic models including the Earth’s gravitational force, lunar gravitational force, solar gravitational force, and the SRP, are presented. For numerical integration, both the single-step Runge–Kutta and multi-step Adams–Bashforth–Moulton integrator methods are implemented. Then, the comparison between the predicted orbit and the international global navigation satellite system (GNSS) service (IGS) final products are carried out. The results show that the prediction accuracy can be maintained for several hours, and the average prediction error of the 31 satellites are 0.031, 0.032, and 0.033 m for the radial, along-track and cross-track directions over 12 h, respectively. Finally, the PPP in both static and kinematic modes are carried out to verify the accuracy of the predicted satellite orbit. The average root mean square error (RMSE) for the static PPP of the 32 globally distributed IGS stations are 0.012, 0.015, and 0.021 m for the north, east, and vertical directions, respectively; while the RMSE of the kinematic PPP with the predicted orbit are 0.031, 0.069, and 0.167 m in the north, east and vertical directions, respectively. PMID:28867771

Design and Implementation of an Interactive Web-Based Near Real-Time Forest Monitoring System

PubMed Central

Pratihast, Arun Kumar; DeVries, Ben; Avitabile, Valerio; de Bruin, Sytze; Herold, Martin; Bergsma, Aldo

2016-01-01

This paper describes an interactive web-based near real-time (NRT) forest monitoring system using four levels of geographic information services: 1) the acquisition of continuous data streams from satellite and community-based monitoring using mobile devices, 2) NRT forest disturbance detection based on satellite time-series, 3) presentation of forest disturbance data through a web-based application and social media and 4) interaction of the satellite based disturbance alerts with the end-user communities to enhance the collection of ground data. The system is developed using open source technologies and has been implemented together with local experts in the UNESCO Kafa Biosphere Reserve, Ethiopia. The results show that the system is able to provide easy access to information on forest change and considerably improves the collection and storage of ground observation by local experts. Social media leads to higher levels of user interaction and noticeably improves communication among stakeholders. Finally, an evaluation of the system confirms the usability of the system in Ethiopia. The implemented system can provide a foundation for an operational forest monitoring system at the national level for REDD+ MRV applications. PMID:27031694

THE JEFFERSON PARISH-LOUISIANA PROJECT - DELIVERING TIME RELEVANT WATER QUALITY INFORMATION TO YOUR COMMUNITY

EPA Science Inventory

The USEPA has developed a handbook to help state and local governmental officials implement near-real-time water quality monitoring and outreach programs with step-by-step instructions on how to: 1) Employ satellite and robotic water monitoring equipment, 2) collect, transfer, an...

Performance assessment of multi-GNSS real-time PPP over Iran

NASA Astrophysics Data System (ADS)

Abdi, Naser; Ardalan, Alireza A.; Karimi, Roohollah; Rezvani, Mohammad-Hadi

2017-06-01

With the advent of multi-GNSS constellations and thanks to providing the real-time precise products by IGS, multi-GNSS Real-Time PPP has been of special interest to the geodetic community. These products stream in the form of RTCM-SSR through NTRIP broadcaster. In this contribution, we aim at assessing the convergence time and positioning accuracy of Real-Time PPP over Iran by means of GPS, GPS + GLONASS, GPS + BeiDou, and GPS + GLONASS + BeiDou configurations. To this end, RINEX observations of six GNSS stations, within Iranian Permanent GNSS Network (IPGN), over consecutive sixteen days were processed via BKG NTRIP Client (BNC, v 2.12). In the processing steps, the IGS-MGEX broadcast ephemerides (BRDM, provided by TUM/DLR) and the pre-saved CLK93 broadcast corrections stream (provided by CNES) have been used as the satellites known information. The numerical results were compared against the station coordinates obtained from the double-difference solutions by Bernese GPS Software v 5.0. Accordingly, we have found that GPS + BeiDou combination can reduce the convergence time by 27%, 16% and 10% and improve the positioning accuracy by 22%, 18% and 2%, in the north, east and up components, respectively, as compared with the GPS PPP. Additionally, in comparison to the GPS + GLONASS results, GPS + GLONASS + BeiDou combination speeds up the convergence time by 9%, 8% and 9% and enhance the positioning accuracy by 8%, 5% and 6%, in the north, east and up components, respectively. Overall, thanks to the availability of the current BeiDou constellation observations, the considerable decrease in the convergence time on one hand, and the improvement in the positioning accuracy on the other, can verify the efficiency of utilizing multi-GNSS PPP for real-time applications over Iran.

Satellite-aided coastal zone monitoring and vessel traffic system

NASA Technical Reports Server (NTRS)

Baker, J. L.

1981-01-01

The development and demonstration of a coastal zone monitoring and vessel traffic system is described. This technique uses a LORAN-C navigational system and relays signals via the ATS-3 satellite to a computer driven color video display for real time control. Multi-use applications of the system to search and rescue operations, coastal zone management and marine safety are described. It is emphasized that among the advantages of the system are: its unlimited range; compatibility with existing navigation systems; and relatively inexpensive cost.

Real Time Volcanic Cloud Products and Predictions for Aviation Alerts

NASA Technical Reports Server (NTRS)

Krotkov, Nickolay A.; Habib, Shahid; da Silva, Arlindo; Hughes, Eric; Yang, Kai; Brentzel, Kelvin; Seftor, Colin; Li, Jason Y.; Schneider, David; Guffanti, Marianne;

A Comparison of MODIS and DOAS Sulfur Dioxide Measurements of the April 24, 2004 Eruption of Anatahan Volcano, Mariana Islands

NASA Astrophysics Data System (ADS)

Meier, V. L.; Scuderi, L.; Fischer, T.; Realmuto, V.; Hilton, D.

2006-12-01

Measurements of volcanic SO2 emissions provide insight into the processes working below a volcano, which can presage volcanic events. Being able to measure SO2 in near real-time is invaluable for the planning and response of hazard mitigation teams. Currently, there are several methods used to quantify the SO2 output of degassing volcanoes. Ground and aerial-based measurements using the differential optical absorption spectrometer (mini-DOAS) provide real-time estimates of SO2 output. Satellite-based measurements, which can provide similar estimates in near real-time, have increasingly been used as a tool for volcanic monitoring. Direct Broadcast (DB) real-time processing of remotely sensed data from NASA's Earth Observing System (EOS) satellites (MODIS Terra and Aqua) presents volcanologists with a range of spectral bands and processing options for the study of volcanic emissions. While the spatial resolution of MODIS is 1 km in the Very Near Infrared (VNIR) and Thermal Infrared (TIR), a high temporal resolution and a wide range of radiance measurements in 32 channels between VNIR and TIR combine to provide a versatile space borne platform to monitor SO2 emissions from volcanoes. An important question remaining to be answered is how well do MODIS SO2 estimates compare with DOAS estimates? In 2004 ground-based plume measurements were collected on April 24th and 25th at Anatahan volcano in the Mariana Islands using a mini-DOAS (Fischer and Hilton). SO2 measurements for these same dates have also been calculated using MODIS images and SO2 mapping software (Realmuto). A comparison of these different approaches to the measurement of SO2 for the same plume is presented. Differences in these observations are used to better quantify SO2 emissions, to assess the current mismatch between ground based and remotely sensed retrievals, and to develop an approach to continuously and accurately monitor volcanic activity from space in near real-time.

Effective Utilization of Satellite Observations for Assessing Transnational Impact of Disasters

NASA Astrophysics Data System (ADS)

Alozie, J. E.; Anuforom, A. C.

2014-12-01

General meteorological observations sources for the surface, upper air and outer space are conducted using different technological equipment and instruments that meet international standards prescribed and approved by the United Nations organizations such as the International Civil Aviation Organization (ICAO) and the World Meteorological Organization (WMO). Satellite weather observations are critical for effective monitoring of the developments, propagations and disseminations of cold clouds and their expected adverse weather conditions as they move across national and transnational boundaries. The Nigerian Meteorological Agency (NiMet) which is the national weather service provider for Nigeria, utilizes an array of satellite products obtained from mainly the European Meteorological Satellite (EUMETSAT) for its routine weather and climate monitoring and forecasts. Overtime, NiMet has used weather workstations such as MSG, SYNERGIE and now PUMA for accessing satellite products such as RGB, Infra-red, Water vapour and the Multi-sensor Precipitation Estimate (MPE) obtained at near real-time periods. The satellite imageries find extensive applications in the delivery of early warning of raising of severe weather conditions such as dust storm and dust haze during the harmattan season (November - February); and thunderstorm accompanied by severe lightning and destructive strong winds. The paper will showcase some special cases of the tracking of squall lines and issuance of weather alerts through the media. The good result is that there was limited damage to infrastructure and no loss of life from the flash floods caused by the heavy rainfall from the squally thunderstorm.

Interdisciplinary Modeling and Dynamics of Archipelago Straits

DTIC Science & Technology

2009-01-01

modeling, tidal modeling and multi-dynamics nested domains and non-hydrostatic modeling WORK COMPLETED Realistic Multiscale Simulations, Real-time...six state variables (chlorophyll, nitrate , ammonium, detritus, phytoplankton, and zooplankton) were needed to initialize simulations. Using biological...parameters from literature, climatology from World Ocean Atlas data for nitrate and chlorophyll profiles extracted from satellite data, a first

The combined use of the RST-FIRES algorithm and geostationary satellite data to timely detect fires

NASA Astrophysics Data System (ADS)

Filizzola, Carolina; Corrado, Rosita; Marchese, Francesco; Mazzeo, Giuseppe; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2017-04-01

Timely detection of fires may enable a rapid contrast action before they become uncontrolled and wipe out entire forests. Remote sensing, especially based on geostationary satellite data, can be successfully used to this aim. Differently from sensors onboard polar orbiting platforms, instruments on geostationary satellites guarantee a very high temporal resolution (from 30 to 2,5 minutes) which may be usefully employed to carry out a "continuous" monitoring over large areas as well as to timely detect fires at their early stages. Together with adequate satellite data, an appropriate fire detection algorithm should be used. Over the last years, many fire detection algorithms have been just adapted from polar to geostationary sensors and, consequently, the very high temporal resolution of geostationary sensors is not exploited at all in tests for fire identification. In addition, even when specifically designed for geostationary satellite sensors, fire detection algorithms are frequently based on fixed thresholds tests which are generally set up in the most conservative way to avoid false alarm proliferation. The result is a low algorithm sensitivity which generally means that only large and/or extremely intense events are detected. This work describes the Robust Satellite Techniques for FIRES detection and monitoring (RST-FIRES) which is a multi-temporal change-detection technique trying to overcome the above mentioned issues. Its performance in terms of reliability and sensitivity was verified using data acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the Meteosat Second Generation (MSG) geostationary platform. More than 20,000 SEVIRI images, collected during a four-year-collaboration with the Regional Civil Protection Departments and Local Authorities of two Italian regions, were used. About 950 near real-time ground and aerial checks of the RST-FIRES detections were performed. This study also demonstrates the added value of the RST-FIRES technique to detect starting/small fires and its sensitivity from 3 to 70 times higher than any other similar SEVIRI-based products.

An Optimized Method to Detect BDS Satellites’ Orbit Maneuvering and Anomalies in Real-Time

PubMed Central

Huang, Guanwen; Qin, Zhiwei; Zhang, Qin; Wang, Le; Yan, Xingyuan; Wang, Xiaolei

2018-01-01

The orbital maneuvers of Global Navigation Satellite System (GNSS) Constellations will decrease the performance and accuracy of positioning, navigation, and timing (PNT). Because satellites in the Chinese BeiDou Navigation Satellite System (BDS) are in Geostationary Orbit (GEO) and Inclined Geosynchronous Orbit (IGSO), maneuvers occur more frequently. Also, the precise start moment of the BDS satellites’ orbit maneuvering cannot be obtained by common users. This paper presented an improved real-time detecting method for BDS satellites’ orbit maneuvering and anomalies with higher timeliness and higher accuracy. The main contributions to this improvement are as follows: (1) instead of the previous two-steps method, a new one-step method with higher accuracy is proposed to determine the start moment and the pseudo random noise code (PRN) of the satellite orbit maneuvering in that time; (2) BDS Medium Earth Orbit (MEO) orbital maneuvers are firstly detected according to the proposed selection strategy for the stations; and (3) the classified non-maneuvering anomalies are detected by a new median robust method using the weak anomaly detection factor and the strong anomaly detection factor. The data from the Multi-GNSS Experiment (MGEX) in 2017 was used for experimental analysis. The experimental results and analysis showed that the start moment of orbital maneuvers and the period of non-maneuver anomalies can be determined more accurately in real-time. When orbital maneuvers and anomalies occur, the proposed method improved the data utilization for 91 and 95 min in 2017. PMID:29495638

Interactive Visualization of Near Real-Time and Production Global Precipitation Mission Data Online Using CesiumJS

NASA Astrophysics Data System (ADS)

Lammers, M.

2016-12-01

Advancements in the capabilities of JavaScript frameworks and web browsing technology make online visualization of large geospatial datasets viable. Commonly this is done using static image overlays, pre-rendered animations, or cumbersome geoservers. These methods can limit interactivity and/or place a large burden on server-side post-processing and storage of data. Geospatial data, and satellite data specifically, benefit from being visualized both on and above a three-dimensional surface. The open-source JavaScript framework CesiumJS, developed by Analytical Graphics, Inc., leverages the WebGL protocol to do just that. It has entered the void left by the abandonment of the Google Earth Web API, and it serves as a capable and well-maintained platform upon which data can be displayed. This paper will describe the technology behind the two primary products developed as part of the NASA Precipitation Processing System STORM website: GPM Near Real Time Viewer (GPMNRTView) and STORM Virtual Globe (STORM VG). GPMNRTView reads small post-processed CZML files derived from various Level 1 through 3 near real-time products. For swath-based products, several brightness temperature channels or precipitation-related variables are available for animating in virtual real-time as the satellite observed them on and above the Earth's surface. With grid-based products, only precipitation rates are available, but the grid points are visualized in such a way that they can be interactively examined to explore raw values. STORM VG reads values directly off the HDF5 files, converting the information into JSON on the fly. All data points both on and above the surface can be examined here as well. Both the raw values and, if relevant, elevations are displayed. Surface and above-ground precipitation rates from select Level 2 and 3 products are shown. Examples from both products will be shown, including visuals from high impact events observed by GPM constellation satellites.

Interactive Visualization of Near Real Time and Production Global Precipitation Measurement (GPM) Mission Data Online Using CesiumJS

NASA Technical Reports Server (NTRS)

Lammers, Matthew

2016-01-01

Advancements in the capabilities of JavaScript frameworks and web browsing technology make online visualization of large geospatial datasets viable. Commonly this is done using static image overlays, prerendered animations, or cumbersome geoservers. These methods can limit interactivity andor place a large burden on server-side post-processing and storage of data. Geospatial data, and satellite data specifically, benefit from being visualized both on and above a three-dimensional surface. The open-source JavaScript framework CesiumJS, developed by Analytical Graphics, Inc., leverages the WebGL protocol to do just that. It has entered the void left by the abandonment of the Google Earth Web API, and it serves as a capable and well-maintained platform upon which data can be displayed. This paper will describe the technology behind the two primary products developed as part of the NASA Precipitation Processing System STORM website: GPM Near Real Time Viewer (GPMNRTView) and STORM Virtual Globe (STORM VG). GPMNRTView reads small post-processed CZML files derived from various Level 1 through 3 near real-time products. For swath-based products, several brightness temperature channels or precipitation-related variables are available for animating in virtual real-time as the satellite-observed them on and above the Earths surface. With grid-based products, only precipitation rates are available, but the grid points are visualized in such a way that they can be interactively examined to explore raw values. STORM VG reads values directly off the HDF5 files, converting the information into JSON on the fly. All data points both on and above the surface can be examined here as well. Both the raw values and, if relevant, elevations are displayed. Surface and above-ground precipitation rates from select Level 2 and 3 products are shown. Examples from both products will be shown, including visuals from high impact events observed by GPM constellation satellites.

Development of IDEA product for GOES-R aerosol data

NASA Astrophysics Data System (ADS)

Zhang, Hai; Hoff, Raymond M.; Kondragunta, Shobha

2009-08-01

The NOAA GOES-R Advanced Baseline Imager (ABI) will have nearly the same capabilities as NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) to generate multi-wavelength retrievals of aerosol optical depth (AOD) with high temporal and spatial resolution, which can be used as a surrogate of surface particulate measurements such as PM2.5 (particulate matter with diameter less than 2.5 μm). To prepare for the launch of GOES-R and its application in the air quality forecasting, we have transferred and enhanced the Infusing satellite Data into Environmental Applications (IDEA) product from University of Wisconsin to NOAA NESDIS. IDEA was created through a NASA/EPA/NOAA cooperative effort. The enhanced IDEA product provides near-real-time imagery of AOD derived from multiple satellite sensors including MODIS Terra, MODIS Aqua, GOES EAST and GOES WEST imager. Air quality forecast guidance is produced through a trajectory model initiated at locations with high AOD retrievals and/or high aerosol index (AI) from OMI (Ozone Monitoring Instrument). The product is currently running at http://www.star.nesdis.noaa.gov/smcd/spb/aq/. The IDEA system will be tested using the GOES-R ABI proxy dataset, and will be ready to operate with GOES-R aerosol data when GOES-R is launched.

Easing the Discovery of NASA and International Near-Real-Time Data Using the Global Change Master Directory

NASA Astrophysics Data System (ADS)

Ritz, S.; Olsen, L. M.; Morahan, M.; Stevens, T.; Aleman, A.; Grebas, S. K.

2011-12-01

The Global Change Master Directory (GCMD) provides an extensive directory of descriptive and spatial information about data sets and data-related services, which are relevant to Earth science research. The directory's data discovery components include controlled keywords, free-text searches, and map/date searches. The GCMD portal for NASA's Land Atmosphere Near-real-time Capability for EOS (LANCE) data products leverages these discovery features by providing users a direct route to NASA's Near-Real-Time (NRT) collections. This portal offers direct access to collection entries by instrument name, informing users of the availability of data. After a relevant collection entry is found through the GCMD's search components, the "Get Data" URL within the entry directs the user to the desired data. Building on the importance of Near-Real-Time (NRT) data, the Committee on Earth Observation Satellites (CEOS) International Directory Network (IDN) is targeting an effort to identify NRT data set collections from the CEOS international members. The international collections will be advertised as the "CEOS IDN NRT" portal to assist users in rapidly discovering these products, which are potentially useful for their research or public response. [This portal is expected to be released in 2012.

On the combined use of high temporal resolution, optical satellite data for flood monitoring and mapping: a possible contribution from the RST approach

NASA Astrophysics Data System (ADS)

Faruolo, M.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

2009-04-01

Among natural disasters, floods are ones of those more common and devastating, often causing high environmental, economical and social costs. When a flooding event occurs, timely information about precise location, extent, dynamic evolution, etc., is highly required in order to effectively support civil protection activities aimed at managing the emergency. Satellite remote sensing may represent a supplementary information source, providing mapping and continuous monitoring of flooding extent as well as a quick damage assessment. Such purposes need frequently updated satellite images as well as suitable image processing techniques, able to identify flooded areas with reliability and timeliness. Recently, an innovative satellite data analysis approach (named RST, Robust Satellite Technique) has been applied to NOAA-AVHRR (Advanced Very High Resolution Radiometer) satellite data in order to dynamically map flooded areas. Thanks to a multi-temporal analysis of co-located satellite records and an automatic change detection scheme, such an approach allows to overcome major drawbacks related to the previously proposed methods (mostly not automatic and based on empirically chosen thresholds, often affected by false identifications). In this paper, RST approach has been for the first time applied to both AVHRR and EOS/MODIS (Moderate Resolution Imaging Spectroradiometer) data, in order to assess its potential - in flooded area mapping and monitoring - on different satellite packages characterized by different spectral and spatial resolutions. As a study case, the flooding event which hit the Europe in August 2002 has been selected. Preliminary results shown in this study seem to confirm the potential of such an approach in providing reliable and timely information, useful for near real time flood hazard assessment and monitoring, using both MODIS and AVHRR data. Moreover, the combined use of information coming from both satellite packages (easily achievable thanks to the intrinsic RST exportability on different sensors) significantly improves (from 6 to less than 3 hours) surface sampling rate, reducing the negative impact of cloud coverage, currently one of the main limit of this kind of satellite technology.

DEVELOPMENT OF IMPROVED TECHNIQUES FOR SATELLITE REMOTE SENSING OF CLOUDS AND RADIATION USING ARM DATA, FINAL REPORT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Minnis, Patrick

2013-06-28

During the period, March 1997 – February 2006, the Principal Investigator and his research team co-authored 47 peer-reviewed papers and presented, at least, 138 papers at conferences, meetings, and workshops that were supported either in whole or in part by this agreement. We developed a state-of-the-art satellite cloud processing system that generates cloud properties over the Atmospheric Radiation (ARM) surface sites and surrounding domains in near-real time and outputs the results on the world wide web in image and digital formats. When the products are quality controlled, they are sent to the ARM archive for further dissemination. These products andmore » raw satellite images can be accessed at http://cloudsgate2.larc.nasa.gov/cgi-bin/site/showdoc?docid=4&cmd=field-experiment-homepage&exp=ARM and are used by many in the ARM science community. The algorithms used in this system to generate cloud properties were validated and improved by the research conducted under this agreement. The team supported, at least, 11 ARM-related or supported field experiments by providing near-real time satellite imagery, cloud products, model results, and interactive analyses for mission planning, execution, and post-experiment scientific analyses. Comparisons of cloud properties derived from satellite, aircraft, and surface measurements were used to evaluate uncertainties in the cloud properties. Multiple-angle satellite retrievals were used to determine the influence of cloud structural and microphysical properties on the exiting radiation field.« less

Amateur-Professional Collaborations in the AAVSO

NASA Astrophysics Data System (ADS)

Hawkins, G.; Mattei, J. A.; Waagen, E. O.

2000-05-01

The AAVSO coordinates, collects, evaluates, and archives variable star observations made largely by amateur astronomers around the world, and publishes and disseminates these observations to researchers and educators worldwide. Its electronic database of nearly 10 million visual variable star observations contributed by 6,000 amateur astronomers in over 40 countries since 1911 is the world's largest and longest-running. The AAVSO has a long history of collaborations between its amateur astronomer observers and professional astronomers. Many of the over 275 requests received yearly from astronomers for AAVSO data and services result in collaborative projects - particularly in multiwavelength observations of variable stars using ground-based telescopes and/or satellites - to help schedule observing runs; provide sumultaneous optical coverage of observing targets and immediate notification of their activity during particular satellite observations; correlate multiwavelength data; and analyze long-term variable star behavior. Among the more dramatic collaborations AAVSO observers have participated in are numerous multi-satellite observing runs on specific variable stars triggered in response to real-time alerts to stellar activity from AAVSO observers; and the variable star observations made during the Astro-2 mission, in which real-time observations by AAVSO observers directed shuttle astronauts to observing targets, and resulted in seminal new information about the cataclysmic variable Z Camelopardalis. The AAVSO is embarking on an exciting new collaboration with Gamma-Ray astronomers at NASA/Marshall Space Flight Center. The AAVSO and the MSFC Gamma-Ray Burst Team have established a Gamma-Ray Burst Network, in which participating AAVSO observers will be alerted immediately via pagers and email to the detection of gamma-ray bursts and will use their own CCD-equipped telescopes to search for the optical counterpart. We gratefully acknowledge partial funding of this network by NASA. Contact the AAVSO at aavso@aavso.org or http://www.aavso.org.

From Wheatstone to Cameron and beyond: overview in 3-D and 4-D imaging technology

NASA Astrophysics Data System (ADS)

Gilbreath, G. Charmaine

2012-02-01

This paper reviews three-dimensional (3-D) and four-dimensional (4-D) imaging technology, from Wheatstone through today, with some prognostications for near future applications. This field is rich in variety, subject specialty, and applications. A major trend, multi-view stereoscopy, is moving the field forward to real-time wide-angle 3-D reconstruction as breakthroughs in parallel processing and multi-processor computers enable very fast processing. Real-time holography meets 4-D imaging reconstruction at the goal of achieving real-time, interactive, 3-D imaging. Applications to telesurgery and telemedicine as well as to the needs of the defense and intelligence communities are also discussed.

Teamwork Reasoning and Multi-Satellite Missions

NASA Technical Reports Server (NTRS)

Marsella, Stacy C.; Plaunt, Christian (Technical Monitor)

2002-01-01

NASA is rapidly moving towards the use of spatially distributed multiple satellites operating in near Earth orbit and Deep Space. Effective operation of such multi-satellite constellations raises many key research issues. In particular, the satellites will be required to cooperate with each other as a team that must achieve common objectives with a high degree of autonomy from ground based operations. The multi-agent research community has made considerable progress in investigating the challenges of realizing such teamwork. In this report, we discuss some of the teamwork issues that will be faced by multi-satellite operations. The basis of the discussion is a particular proposed mission, the Magnetospheric MultiScale mission to explore Earth's magnetosphere. We describe this mission and then consider how multi-agent technologies might be applied in the design and operation of these missions. We consider the potential benefits of these technologies as well as the research challenges that will be raised in applying them to NASA multi-satellite missions. We conclude with some recommendations for future work.

Applications of Satellite Observations to Aerosol Analyses and Forecasting using the NAAPS Model and the DataFed Distributed Data System

NASA Astrophysics Data System (ADS)

Husar, R. B.; Hoijarvi, K.; Westphal, D. L.; Scheffe, R.; Keating, T.; Frank, N.; Poirot, R.; DuBois, D. W.; Bleiweiss, M. P.; Eberhard, W. L.; Menon, R.; Sethi, V.; Deshpande, A.

2012-12-01

Near-real-time (NRT) aerosol characterization, forecasting and decision support is now possible through the availability of (1) surface-based monitoring of regional PM concentrations, (2) global-scale columnar aerosol observations through satellites; (3) an aerosol model (NAAPS) that is capable of assimilating NRT satellite observations; and (4) an emerging cyber infrastructure for processing and distribution of data and model results (DataFed) for a wide range of users. This report describes the evolving NRT aerosol analysis and forecasting system and its applications at Federal and State and other AQ Agencies and groups. Through use cases and persistent real-world applications in the US and abroad, the report will show how satellite observations along with surface data and models are combined to aid decision support for AQ management, science and informing the public. NAAPS is the U.S. Navy's global aerosol and visibility forecast model that generates operational six-day global-scale forecasts for sulfate, dust, sea salt, and smoke aerosol. Through NAVDAS-AOD, NAAPS operationally assimilates filtered and corrected MODIS MOD04 aerosol optical depths and uses satellite-derived FLAMBÉ smoke emissions. Washington University's federated data system, DataFed, consist of a (1) data server which mediates the access to AQ datasets from distributed providers (NASA, NOAA, EPA, etc.,); (2) an AQ Data Catalog for finding and accessing data; and (3) a set of application programs/tools for browsing, exploring, comparing, aggregating, fusing data, evaluating models and delivering outputs through interactive visualization. NAAPS and DataFed are components of the Global Earth Observation System of Systems (GEOSS). Satellite data support the detection of long-range transported wind-blown dust and biomass smoke aerosols on hemispheric scales. The AQ management and analyst communities use the satellite/model data through DataFed and other channels as evidence for Exceptional Events (EE) as defined by EPA; i.e., Sahara dust impact on Texas and Florida, local dusts events in the Southwestern U.S. and Canadian smoke events over the Northeastern U.S. Recent applications include the impact analysis of a major Saudi Arabian dust event on Mumbai, India air quality. The NAAPS model and the DataFed tools can visualize the dynamic AQ events as they are manifested through the different sensors. Satellite-derived aerosol observations assimilated into NAAPS provide estimates of daily emission rates for dust and biomass fire sources. Tuning and reconciliation of the observations, emissions and models constitutes a key and novel contribution yielding a convergence toward the true five-dimensional (X, Y, Z, T, Composition) characterization of the atmospheric aerosol data space. This observation-emission-model reconciliation effort is aided by model evaluation tools and supports the international HTAP program. The report will also discuss some of the challenges facing multi-disciplinary, multi-agency, multi-national applications of integrated observation-modeling system of systems that impede the incorporation of satellite observations into AQ management decision support systems.

Oil spill disasters detection and monitoring by optical satellite data

NASA Astrophysics Data System (ADS)

Livia Grimaldi, Caterina Sara; Coviello, Irina; Lacava, Teodosio; Pergola, Nicola; Tramutoli, Valerio

2010-05-01

Marine oil spill disasters may be related to natural hazards, when storms and hurricanes cause the sinking of tankers carrying crude or refined oil, as well as to human action, as illegal discharges, assessment errors (failures or collisions) or acts of warfare. Their consequence has a devastating effects on the marine and coastal environment. In order to reduce the environmental impact of such kind of hazard, giving to local authorities necessary information of pollution entity and evolution, timely detection and continuously updated information are fundamental. Satellite remote sensing can give a significant contribution in such a direction. Nowadays, SAR (Synthetic Aperture Radar) technology has been recognized as the most efficient for oil spill detection and description, thanks to the high spatial resolution and all-time/weather capability of the present operational sensors. Anyway, the actual SARs revisiting time does not allow a rapid detection and near real-time monitoring of these phenomena at global scale. The COSMO-Skymed Italian dual-mission (expected in the 2010) will overcome this limitation improving the temporal resolution until 12 hours by a SAR constellation of four satellites, but several open questions regarding costs and global delivery policy of such data, might prevent their use in an operational context. Passive optical sensors, on board meteorological satellites, thanks to their high temporal resolution (from a few hours to 15 minutes, depending on the characteristics of the platform/sensor), may represent, at this moment, a suitable SAR alternative/complement for oil spill detection and monitoring. Up to now, some techniques have been proposed for mapping known oil spill discharges monitoring using optical satellite data, on the other hand, reliable satellite methods for an automatic and timely detection of oil spill are still currently missing. Existing methods, in fact, can localize the presence of an oil spill only after an alert and require the presence of a qualified operator. Recently, an innovative technique for near real time oil spill detection and monitoring has been proposed. The technique is based on the general RST (Robust Satellite Technique) approach which exploits long-term multi-temporal satellite records in order to obtain a former characterization of the measured signal, in terms of expected value and natural variability, providing a further identification of signal anomalies by an automatic, unsupervised change detection step. Results obtained by using both AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) data in different geographic areas and observational conditions demonstrate excellent detection capabilities both in term of sensitivity (to the presence even of very thin/old oil films) and reliability (up to zero occurrence of false alarms) mainly due to the RST invariance regardless of local and environmental conditions. Moreover, the possibility to apply RST approach to both MODIS and AVHRR sensors may ensure an improved (up to 3 hours and less) frequency of TIR (Thermal Infrared) observations as well as an increased spatial accuracy of the description of oil spills (thanks to higher spatial resolution of MODIS visible channels). In this paper, results obtained applying the proposed methodology to events of different extension and in different geographic areas are shown and discussed.

SO2 plume height retrieval from UV satellite measurements in support to aviation control

NASA Astrophysics Data System (ADS)

van Gent, Jeroen; Brenot, Hugues; Lerot, Christophe; Theys, Nicolas; Van Roozendael, Michel

2014-05-01

The Support to Aviation Control Service (SACS), operated at our institute, uses multi-sensor UV-visible and infrared satellite measurements to provide near real-time information on volcanic ash and SO2 concentrations. In case of enhanced SO2 concentrations, notifications are send out to subscribing organisations and individuals, with details regarding the volcanic event. This information may be used by aviation control organisations to judge the risc to air traffic and provide possible alternative routing. One of the latest additions to the system is information on the altitude of SO2 plumes, based on UV measurements of the GOME-2 sensors on the platforms METOP-A and METOP-B. Further improvement of this system is ongoing. This poster shows examples of plume height retrieval from GOME-2 (METOP-A and -B) and OMI (EOS-AURA). Results are shown for a number of recent major volcanic eruptions, each with different characteristics. The applied technique to retrieve altitude information will be discussed, as well as the applicability, quality and limitations of the method.

Informing future NRT satellite distribution capabilities: Lessons learned from NASA's Land Atmosphere NRT capability for EOS (LANCE)

NASA Astrophysics Data System (ADS)

Davies, D.; Murphy, K. J.; Michael, K.

2013-12-01

NASA's Land Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE) provides data and imagery from Terra, Aqua and Aura satellites in less than 3 hours from satellite observation, to meet the needs of the near real-time (NRT) applications community. This article describes the architecture of the LANCE and outlines the modifications made to achieve the 3-hour latency requirement with a view to informing future NRT satellite distribution capabilities. It also describes how latency is determined. LANCE is a distributed system that builds on the existing EOS Data and Information System (EOSDIS) capabilities. To achieve the NRT latency requirement, many components of the EOS satellite operations, ground and science processing systems have been made more efficient without compromising the quality of science data processing. The EOS Data and Operations System (EDOS) processes the NRT stream with higher priority than the science data stream in order to minimize latency. In addition to expediting transfer times, the key difference between the NRT Level 0 products and those for standard science processing is the data used to determine the precise location and tilt of the satellite. Standard products use definitive geo-location (attitude and ephemeris) data provided daily, whereas NRT products use predicted geo-location provided by the instrument Global Positioning System (GPS) or approximation of navigational data (depending on platform). Level 0 data are processed in to higher-level products at designated Science Investigator-led Processing Systems (SIPS). The processes used by LANCE have been streamlined and adapted to work with datasets as soon as they are downlinked from satellites or transmitted from ground stations. Level 2 products that require ancillary data have modified production rules to relax the requirements for ancillary data so reducing processing times. Looking to the future, experience gained from LANCE can provide valuable lessons on satellite and ground system architectures and on how the delivery of NRT products from other NASA missions might be achieved.

Smap Soil Moisture Data Assimilation for the Continental United States and Eastern Africa

NASA Astrophysics Data System (ADS)

Blankenship, C. B.; Case, J.; Zavodsky, B.; Crosson, W. L.

2016-12-01

The NASA Short-Term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center manages near-real-time runs of the Noah Land Surface Model within the NASA Land Information System (LIS) over Continental U.S. (CONUS) and Eastern Africa domains. Soil moisture products from the CONUS model run are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. The baseline LIS configuration is the Noah model driven by atmospheric and combined radar/gauge precipitation analyses, and input satellite-derived real-time green vegetation fraction on a 3-km grid for the CONUS. This configuration is being enhanced by adding the assimilation of Level 2 Soil Moisture Active/Passive (SMAP) soil moisture retrievals in a parallel run beginning on 1 April 2015. Our implementation of SMAP assimilation includes a cumulative distribution function (CDF) matching approach that aggregates points with similar soil types. This method allows creation of robust CDFs with a short data record, and also permits the correction of local anomalies that may arise from poor forcing data (e.g., quality-control problems with rain gauges). Validation results using in situ soil monitoring networks in the CONUS are shown, with comparisons to the baseline SPoRT-LIS run. Initial results are also presented from a modeling run in eastern Africa, forced by Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data. Strategies for spatial downscaling and for dealing with effective depth of the retrieval product are also discussed.

Combining Satellite Measurements and Numerical Flood Prediction Models to Save Lives and Property from Flooding

NASA Astrophysics Data System (ADS)

Saleh, F.; Garambois, P. A.; Biancamaria, S.

2017-12-01

Floods are considered the major natural threats to human societies across all continents. Consequences of floods in highly populated areas are more dramatic with losses of human lives and substantial property damage. This risk is projected to increase with the effects of climate change, particularly sea-level rise, increasing storm frequencies and intensities and increasing population and economic assets in such urban watersheds. Despite the advances in computational resources and modeling techniques, significant gaps exist in predicting complex processes and accurately representing the initial state of the system. Improving flood prediction models and data assimilation chains through satellite has become an absolute priority to produce accurate flood forecasts with sufficient lead times. The overarching goal of this work is to assess the benefits of the Surface Water Ocean Topography SWOT satellite data from a flood prediction perspective. The near real time methodology is based on combining satellite data from a simulator that mimics the future SWOT data, numerical models, high resolution elevation data and real-time local measurement in the New York/New Jersey area.

A daily wetness index from satellite gravity for near-real time global monitoring of hydrological extremes

NASA Astrophysics Data System (ADS)

Gouweleeuw, Ben; Kvas, Andreas; Gruber, Christian; Mayer-Gürr, Torsten; Flechtner, Frank; Hasan, Mehedi; Güntner, Andreas

2017-04-01

Since April 2002, the Gravity Recovery and Climate Experiment (GRACE) satellite mission has been churning out water storage anomaly data, which has been shown to be a unique descriptor of large-scale hydrological extreme events. Nonetheless, efforts to assess the comprehensive information from GRACE on total water storage variations for near-real time flood or drought monitoring have been limited so far, primarily due to its coarse temporal (weekly to monthly) and spatial (> 150.000 km2) resolution and the latency of standard products of about 2 months,. Pending the status of the aging GRACE satellite mission, the Horizon 2020 funded EGSIEM (European Gravity Service for Improved Emergency Management) project is scheduled to launch a 6 month duration near-real time test run of GRACE gravity field data from April 2017 onward, which will provide daily gridded data with a latency of 5 days. This fast availability allows the monitoring of total water storage variations related to hydrological extreme events, as they occur, as opposed to a 'confirmation after occurrence', which is the current situation. This contribution proposes a global GRACE-derived gridded wetness indicator, expressed as a gravity anomaly in dimensionless units of standard deviation. Results of a retrospective evaluation (April 2002-December 2015) of the proposed index against databases of hydrological extremes will be presented. It is shown that signals for large extreme floods related to heavy/monsoonal rainfall are picked up really well in the Southern Hemisphere and lower Northern Hemisphere (Africa, S-America, Australia, S-Asia), while extreme floods in the Northern Hemisphere (Russia) related to snow melt are often not. The latter is possibly related to a lack of mass movement over longer distances, e.g. when melt water is not drained due to river ice blocking.

Using CYGNSS to Observe Convectively Driven Near-Surface Winds in Tropical Precipitation Systems During Madden-Julian Oscillation Events

NASA Technical Reports Server (NTRS)

Lang, Timothy J.; Li, Xuanli; Mecikalski, John; Hoover, Kacie; Castillo, Tyler; Chronis, Themis

2017-01-01

The Cyclone Global Navigation OKLMA 1411 UTC Satellite System (CYGNSS) is a multi-satellite constellation that launched 15 December 2016. The primary objective of CYGNSS is to use bistatic Global Positioning System (GPS) reflectometry to accurately measure near-surface wind speeds within the heavily raining inner core of tropical cyclones. CYGNSS also features rapid revisit times over a given region in the tropics - ranging from several minutes to a few hours, depending on the constellation geometry at that time. Despite the focus on tropical cyclones, the ability of CYGNSS to provide rapid updates of winds, unbiased by the presence of precipitation, has many other potential applications related to general tropical convection.

Compact SAR and Small Satellite Solutions for Earth Observation

NASA Astrophysics Data System (ADS)

LaRosa, M.; L'Abbate, M.

2016-12-01

Requirements for near and short term mission applications (Observation and Reconnaissance, SIGINT, Early Warning, Meteorology,..) are increasingly calling for spacecraft operational responsiveness, flexible configuration, lower cost satellite constellations and flying formations, to improve both the temporal performance of observation systems (revisit, response time) and the remote sensing techniques (distributed sensors, arrays, cooperative sensors). In answer to these users' needs, leading actors in Space Systems for EO are involved in development of Small and Microsatellites solutions. Thales Alenia Space (TAS) has started the "COMPACT-SAR" project to develop a SAR satellite characterized by low cost and reduced mass while providing, at the same time, high image quality in terms of resolution, swath size, and radiometric performance. Compact SAR will embark a X-band SAR based on a deployable reflector antenna fed by an active phased array feed. This concept allows high performance, providing capability of electronic beam steering both in azimuth and elevation planes, improving operational performance over a purely mechanically steered SAR system. Instrument provides both STRIPMAP and SPOTLIGHT modes, and thanks to very high gain antenna, can also provide a real maritime surveillance mode based on a patented Low PRF radar mode. Further developments are in progress considering missions based on Microsatellites technology, which can provide effective solutions for different user needs, such as Operational responsiveness, low cost constellations, distributed observation concept, flying formations, and can be conceived for applications in the field of Observation, Atmosphere sensing, Intelligence, Surveillance, Reconnaissance (ISR), Signal Intelligence. To satisfy these requirements, flexibility of small platforms is a key driver and especially new miniaturization technologies able to optimize the performance. An overview new micros-satellite (based on NIMBUS platform) and mission concepts is provided, such as passive SAR for multi-static imaging and tandem, Medium swath/medium resolution dual pol MICROSAR for in L-C-X band multi-application for maritime surveillance and land monitoring, applications for Space Debris monitoring, precision farming, Atmosphere sensing.

News at Nine: The value of near-real time data for reaching mass media

NASA Astrophysics Data System (ADS)

Allen, J.; Ward, K.; Simmon, R. B.; Carlowicz, M. J.; Scott, M.; Przyborski, P. D.; Voiland, A. P.

2012-12-01

NASA's Earth Observatory (EO) is an online publication featuring NASA Earth science news and images. Since its inception in 1999, the EO team has relied heavily on near-real time satellite data to publish imagery of breaking news events, such as volcanoes, floods, fires, and dust storms. Major news outlets (Associated Press, The Weather Channel, CNN, etc.) have regularly republished Earth Observatory imagery in their coverage of events. Because of the nature of modern 24-hour news cycle, media almost always want near-real time coverage; providing it depends heavily on rapid data turnaround, user-friendly data systems, and fast data access. We will discuss how we use near-real time data and provide examples of how data systems have been transformed in the past 13 years. We will offer some thoughts on best practices (from the view of a user) in expedited data systems and the positive effect of those practices on public awareness of our content.. Finally, we will share how we work with science teams to see the potential stories in their data and the value of providing the data in a timely fashionAcquired October 9, 2010, this natural-color image shows the toxic sludge spill from an alumina plant in southern Hungary.

Determining coordinates of the rotational pole using satellite data from four sites

NASA Astrophysics Data System (ADS)

Pisacane, V. L.; Dillon, S. C.

1981-02-01

The precision of the terrestrial coordinates of the rotational pole was determined from the satellite data using the Navy Navigation Satellite System (TRANSIT). Observations were made in Maine, Minnesota, California, and Hawaii; the data agreed with extrapolated and final coordinates from the Bureau International de l'Heure and final coordinates from the Doppler Polar Motion Service. The investigation indicates that low-cost and near-real-time estimates of the terrestrial coordinates of the pole are available as a by-product of the routine support required for the TRANSIT.

Web tools concerning performance analysis and planning support for solar energy plants starting from remotely sensed optical images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morelli, Marco, E-mail: marco.morelli1@unimi.it; Masini, Andrea, E-mail: andrea.masini@flyby.it; Ruffini, Fabrizio, E-mail: fabrizio.ruffini@i-em.eu

We present innovative web tools, developed also in the frame of the FP7 ENDORSE (ENergy DOwnstReam SErvices) project, for the performance analysis and the support in planning of solar energy plants (PV, CSP, CPV). These services are based on the combination between the detailed physical model of each part of the plants and the near real-time satellite remote sensing of incident solar irradiance. Starting from the solar Global Horizontal Irradiance (GHI) data provided by the Monitoring Atmospheric Composition and Climate (GMES-MACC) Core Service and based on the elaboration of Meteosat Second Generation (MSG) satellite optical imagery, the Global Tilted Irradiancemore » (GTI) or the Beam Normal Irradiance (BNI) incident on plant's solar PV panels (or solar receivers for CSP or CPV) is calculated. Combining these parameters with the model of the solar power plant, using also air temperature values, we can assess in near-real-time the daily evolution of the alternate current (AC) power produced by the plant. We are therefore able to compare this satellite-based AC power yield with the actually measured one and, consequently, to readily detect any possible malfunctions and to evaluate the performances of the plant (so-called “Controller” service). Besides, the same method can be applied to satellite-based averaged environmental data (solar irradiance and air temperature) in order to provide a Return on Investment analysis in support to the planning of new solar energy plants (so-called “Planner” service). This method has been successfully applied to three test solar plants (in North, Centre and South Italy respectively) and it has been validated by comparing satellite-based and in-situ measured hourly AC power data for several months in 2013 and 2014. The results show a good accuracy: the overall Normalized Bias (NB) is − 0.41%, the overall Normalized Mean Absolute Error (NMAE) is 4.90%, the Normalized Root Mean Square Error (NRMSE) is 7.66% and the overall Correlation Coefficient (CC) is 0.9538. The maximum value of the Normalized Absolute Error (NAE) is about 30% and occurs for time periods with highly variable meteorological conditions. - Highlights: • We developed an online service (Controller) dedicated to solar energy plants real-time monitoring • We developed an online service (Planner) that supports the planning of new solar energy plants • The services are based on the elaboration of satellite optical imagery in near real-time • The validation with respect to in-situ measured hourly AC power data for three test solar plants shows good accuracy • The maximum value of the Normalized Absolute Error is about 30% and occurs for highly variable meteorological conditions.« less

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Palilonda, Rabindra; Heck, Patrick W.; Spangenberg, Douglas A.; Doelling, David R.; Ayers, J. Kirk; Smith, William L., Jr.; Khaiyer, Mandana M.; Trepte, Qing Z.;

CEOS Ocean Variables Enabling Research and Applications for Geo (COVERAGE)

NASA Astrophysics Data System (ADS)

Tsontos, V. M.; Vazquez, J.; Zlotnicki, V.

2017-12-01

The CEOS Ocean Variables Enabling Research and Applications for GEO (COVERAGE) initiative seeks to facilitate joint utilization of different satellite data streams on ocean physics, better integrated with biological and in situ observations, including near real-time data streams in support of oceanographic and decision support applications for societal benefit. COVERAGE aligns with programmatic objectives of CEOS (the Committee on Earth Observation Satellites) and the missions of GEO-MBON (Marine Biodiversity Observation Network) and GEO-Blue Planet, which are to advance and exploit synergies among the many observational programs devoted to ocean and coastal waters. COVERAGE is conceived of as 3 year pilot project involving international collaboration. It focuses on implementing technologies, including cloud based solutions, to provide a data rich, web-based platform for integrated ocean data delivery and access: multi-parameter observations, easily discoverable and usable, organized by disciplines, available in near real-time, collocated to a common grid and including climatologies. These will be complemented by a set of value-added data services available via the COVERAGE portal including an advanced Web-based visualization interface, subsetting/extraction, data collocation/matchup and other relevant on demand processing capabilities. COVERAGE development will be organized around priority use cases and applications identified by GEO and agency partners. The initial phase will be to develop co-located 25km products from the four Ocean Virtual Constellations (VCs), Sea Surface Temperature, Sea Level, Ocean Color, and Sea Surface Winds. This aims to stimulate work among the ocean VCs while developing products and system functionality based on community recommendations. Such products as anomalies from a time mean, would build on the theme of applications with a relevance to CEOS/GEO mission and vision. Here we provide an overview of the COVERAGE initiative with an emphasis on international collaborative aspects entailed with the intent of soliciting community feedback as we develop and implement

Towards a Three-Dimensional Near-Real Time Cloud Product for Aviation Safety and Weather Diagnoses

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Palikonda, Rabindra; Spangeberg, Douglas; Nordeen, Michele L.; Yi, Yu-Hong; Ayers, J. Kirk

2004-01-01

Satellite data have long been used for determining the extent of cloud cover and for estimating the properties at the cloud tops. The derived properties can also be used to estimate aircraft icing potential to improve the safety of air traffic in the region. Currently, cloud properties and icing potential are derived in near-real time over the United States of America (USA) from the Geostationary Operational Environmental Satellite GOES) imagers at 75 W and 135 W. Traditionally, the results have been given in two dimensions because of the lack of knowledge about the vertical extent of clouds and the occurrence of overlapping clouds. Aircraft fly in a three-dimensional space and require vertical as well as horizontal information about clouds, their intensity, and their potential for icing. To improve the vertical component of the derived cloud and icing parameters, this paper explores various methods and datasets for filling in the three-dimensional space over the USA with cloud water.

Impact of orbit, clock and EOP errors in GNSS Precise Point Positioning

NASA Astrophysics Data System (ADS)

Hackman, C.

2012-12-01

Precise point positioning (PPP; [1]) has gained ever-increasing usage in GNSS carrier-phase positioning, navigation and timing (PNT) since its inception in the late 1990s. In this technique, high-precision satellite clocks, satellite ephemerides and earth-orientation parameters (EOPs) are applied as fixed input by the user in order to estimate receiver/location-specific quantities such as antenna coordinates, troposphere delay and receiver-clock corrections. This is in contrast to "network" solutions, in which (typically) less-precise satellite clocks, satellite ephemerides and EOPs are used as input, and in which these parameters are estimated simultaneously with the receiver/location-specific parameters. The primary reason for increased PPP application is that it offers most of the benefits of a network solution with a smaller computing cost. In addition, the software required to do PPP positioning can be simpler than that required for network solutions. Finally, PPP permits high-precision positioning of single or sparsely spaced receivers that may have few or no GNSS satellites in common view. A drawback of PPP is that the accuracy of the results depend directly on the accuracy of the supplied orbits, clocks and EOPs, since these parameters are not adjusted during the processing. In this study, we will examine the impact of orbit, EOP and satellite clock estimates on PPP solutions. Our primary focus will be the impact of these errors on station coordinates; however the study may be extended to error propagation into receiver-clock corrections and/or troposphere estimates if time permits. Study motivation: the United States Naval Observatory (USNO) began testing PPP processing using its own predicted orbits, clocks and EOPs in Summer 2012 [2]. The results of such processing could be useful for real- or near-real-time applications should they meet accuracy/precision requirements. Understanding how errors in satellite clocks, satellite orbits and EOPs propagate into PPP positioning and timing results allows researchers to focus their improvement efforts in areas most in need of attention. The initial study will be conducted using the simulation capabilities of Bernese GPS Software and extended to using real data if time permits. [1] J.F. Zumberge, M.B. Heflin, D.C. Jefferson, M.M. Watkins and F.H. Webb, Precise point positioning for the efficient and robust analysis of GPS data from large networks, J. Geophys. Res., 102(B3), 5005-5017, doi:10.1029/96JB03860, 1997. [2] C. Hackman, S.M. Byram, V.J. Slabinski and J.C. Tracey, Near-real-time and other high-precision GNSS-based orbit/clock/earth-orientation/troposphere parameters available from USNO, Proc. 2012 ION Joint Navigation Conference, 15 pp., in press, 2012.

Use of TV in space science activities - Some considerations. [onboard primary experimental data recording

NASA Technical Reports Server (NTRS)

Bannister, T. C.

1977-01-01

Advantages in the use of TV on board satellites as the primary data-recording system in a manned space laboratory when certain types of experiments are flown are indicated. Real-time or near-real-time validation, elimination of film weight, improved depth of field and low-light sensitivity, and better adaptability to computer and electronic processing of data are spelled out as advantages of TV over photographic techniques, say, in fluid dynamics experiments, and weightlessness studies.

Adapting CALIPSO Climate Measurements for Near Real Time Analyses and Forecasting

NASA Technical Reports Server (NTRS)

Vaughan, Mark A.; Trepte, Charles R.; Winker, David M.; Avery, Melody A.; Campbell, James; Hoff, Ray; Young, Stuart; Getzewich, Brian J.; Tackett, Jason L.; Kar, Jayanta

2011-01-01

The Cloud-Aerosol Lidar and Infrared Pathfinder satellite Observations (CALIPSO) mission was originally conceived and designed as a climate measurements mission, with considerable latency between data acquisition and the release of the level 1 and level 2 data products. However, the unique nature of the CALIPSO lidar backscatter profiles quickly led to the qualitative use of CALIPSO?s near real time (i.e., ? expedited?) lidar data imagery in several different forecasting applications. To enable quantitative use of their near real time analyses, the CALIPSO project recently expanded their expedited data catalog to include all of the standard level 1 and level 2 lidar data products. Also included is a new cloud cleared level 1.5 profile product developed for use by operational forecast centers for verification of aerosol predictions. This paper describes the architecture and content of the CALIPSO expedited data products. The fidelity and accuracy of the expedited products are assessed via comparisons to the standard CALIPSO data products.

Enhancements to NASA's Land Atmosphere Near real-time Capability for EOS (LANCE)

NASA Astrophysics Data System (ADS)

Michael, K.; Davies, D. K.; Schmaltz, J. E.; Boller, R. A.; Mauoka, E.; Ye, G.; Vermote, E.; Harrison, S.; Rinsland, P. L.; Protack, S.; Durbin, P. B.; Justice, C. O.

2016-12-01

NASA's Land, Atmosphere Near real-time Capability for EOS (LANCE) supports application users interested in monitoring a wide variety of natural and man-made phenomena. Near Real-Time (NRT) data and imagery from the AIRS, AMSR2, MISR, MLS, MODIS, OMI and VIIRS instruments are available much quicker than routine processing allows. Most data products are available within 3 hours from satellite observation. NRT imagery are generally available 3-5 hours after observation. This article describes LANCE and enhancements made to LANCE over the last year. These enhancements include: the addition of MISR L1 Georeferenced Radiance and L2 Cloud Motion Vector products, AMSR2 Unified L2B Half-Orbit 25 km EASE-Grid Surface Soil Moisture products and VIIRS VIIRS Day/Night Band, Land Surface Reflectance and Corrected Surface reflectance products. In addition, the selection of LANCE NRT imagery that can be interactively viewed through Worldview and the Global Imagery Browse Services (GIBS) has been expanded. LANCE is also working to ingest and process data from OMPS.

Use of satellite data in volcano monitoring

NASA Technical Reports Server (NTRS)

Mcclelland, Lindsay

1987-01-01

It is argued that Total Ozone Mapping Spectrometer (TOMS) data, especially data on sulfur dioxide detection in volcanic clouds, and weather satellite data complement each other. TOMS data is most useful for discovering previously unknown eruptions and indicating a minimum volume of SO sub 2 produced by a given eruption. Once an eruption has been reported, weather satellite data can be used to accurately monitor its progress. To be used effectively, these data need to be analyzed jointly and in real time. Toward this end, it is hoped that full and timely utilization can be made of existing TOMS data, a polar orbiting TOMS can be launched in the near future, and that TOMS type instruments can be included on future geostationary satellites.

Improved Orbit Determination and Forecasts with an Assimilative Tool for Satellite Drag Specification

NASA Astrophysics Data System (ADS)

Pilinski, M.; Crowley, G.; Sutton, E.; Codrescu, M.

2016-09-01

Much as aircraft are affected by the prevailing winds and weather conditions in which they fly, satellites are affected by the variability in density and motion of the near earth space environment. Drastic changes in the neutral density of the thermosphere, caused by geomagnetic storms or other phenomena, result in perturbations of LEO satellite motions through drag on the satellite surfaces. This can lead to difficulties in locating important satellites, temporarily losing track of satellites, and errors when predicting collisions in space. As the population of satellites in Earth orbit grows, higher space-weather prediction accuracy is required for critical missions, such as accurate catalog maintenance, collision avoidance for manned and unmanned space flight, reentry prediction, satellite lifetime prediction, defining on-board fuel requirements, and satellite attitude dynamics. We describe ongoing work to build a comprehensive nowcast and forecast system for specifying the neutral atmospheric state related to orbital drag conditions. The system outputs include neutral density, winds, temperature, composition, and the satellite drag derived from these parameters. This modeling tool is based on several state-of-the-art coupled models of the thermosphere-ionosphere as well as several empirical models running in real-time and uses assimilative techniques to produce a thermospheric nowcast. This software will also produce 72 hour predictions of the global thermosphere-ionosphere system using the nowcast as the initial condition and using near real-time and predicted space weather data and indices as the inputs. In this paper, we will review the driving requirements for our model, summarize the model design and assimilative architecture, and present preliminary validation results. Validation results will be presented in the context of satellite orbit errors and compared with several leading atmospheric models. As part of the analysis, we compare the drag observed by a variety of satellites which were not used as part of the assimilation-dataset and whose perigee altitudes span a range from 200 km to 700 km.

Characterization of precipitation features over CONUS derived from satellite, radar, and rain gauge datasets (2002-2012)

NASA Astrophysics Data System (ADS)

Prat, O. P.; Nelson, B. R.

2013-12-01

We use a suite of quantitative precipitation estimates (QPEs) derived from satellite, radar, surface observations, and models to derive precipitation characteristics over CONUS for the period 2002-2012. This comparison effort includes satellite multi-sensor datasets of TMPA 3B42, CMORPH, and PERSIANN. The satellite based QPEs are compared over the concurrent period with the NCEP Stage IV product, which is a near real time product providing precipitation data at the hourly temporal scale gridded at a nominal 4-km spatial resolution. In addition, remotely sensed precipitation datasets are compared with surface observations from the Global Historical Climatology Network (GHCN-Daily) and from the PRISM (Parameter-elevation Regressions on Independent Slopes Model), which provides gridded precipitation estimates that are used as a baseline for multi-sensor QPE products comparison. The comparisons are performed at the annual, seasonal, monthly, and daily scales with focus on selected river basins (Southeastern US, Pacific Northwest, Great Plains). While, unconditional annual rain rates present a satisfying agreement between all products, results suggest that satellite QPE datasets exhibit important biases in particular at higher rain rates (≥4 mm/day). Conversely, on seasonal scales differences between remotely sensed data and ground surface observations can be greater than 50% and up to 90% for low daily accumulation (≤1 mm/day) such as in the Western US (summer) and Central US (winter). The conditional analysis performed using different daily rainfall accumulation thresholds (from low rainfall intensity to intense precipitation) shows that while intense events measured at the ground are infrequent (around 2% for daily accumulation above 2 inches/day), remotely sensed products displayed differences from 20-50% and up to 90-100%. A discussion on the impact of differing spatial and temporal resolutions with respect to the datasets ability to capture extreme precipitation events is also provided. Furthermore, this work is part of a broader effort to evaluate long-term multi-sensor QPEs in the perspective of developing Climate Data Records (CDRs) for precipitation.

A multi-scale automatic observatory of soil moisture and temperature served for satellite product validation in Tibetan Plateau

NASA Astrophysics Data System (ADS)

Tang, S.; Dong, L.; Lu, P.; Zhou, K.; Wang, F.; Han, S.; Min, M.; Chen, L.; Xu, N.; Chen, J.; Zhao, P.; Li, B.; Wang, Y.

2016-12-01

Due to the lack of observing data which match the satellite pixel size, the inversion accuracy of satellite products in Tibetan Plateau(TP) is difficult to be evaluated. Hence, the in situ observations are necessary to support the calibration and validation activities. Under the support of the Third Tibetan Plateau Atmospheric Scientific Experiment (TIPEX-III) projec a multi-scale automatic observatory of soil moisture and temperature served for satellite product validation (TIPEX-III-SMTN) were established in Tibetan Plateau. The observatory consists of two regional scale networks, including the Naqu network and the Geji network. The Naqu network is located in the north of TP, and characterized by alpine grasslands. The Geji network is located in the west of TP, and characterized by marshes. Naqu network includes 33 stations, which are deployed in a 75KM*75KM region according to a pre-designed pattern. At Each station, soil moisture and temperature are measured by five sensors at five soil depths. One sensor is vertically inserted into 0 2 cm depth to measure the averaged near-surface soil moisture and temperature. The other four sensors are horizontally inserted at 5, 10, 20, and 30 cm depths, respectively. The data are recorded every 10 minutes. A wireless transmission system is applied to transmit the data in real time, and a dual power supply system is adopted to keep the continuity of the observation. The construction of Naqu network has been accomplished in August, 2015, and Geji network will be established before Oct., 2016. Observations acquired from TIPEX-III-SMTN can be used to validate satellite products with different spatial resolution, and TIPEX-III-SMTN can also be used as a complementary of the existing similar networks in this area, such as CTP-SMTMN (the multiscale Soil Moistureand Temperature Monitoring Network on the central TP) . Keywords: multi-scale soil moisture soil temperature, Tibetan Plateau Acknowledgments: This work was jointly supported by CMA Special Fund for Scientific Research in the Public Interest (Grant No. GYHY201406001, GYHY201206008-01), and Climate change special fund (QHBH2014)'

Near-real time orbit determination for the GPS, CHAMP, GRACE, TerraSAR-X, and TanDEM-X satellites

NASA Astrophysics Data System (ADS)

Michalak, Grzegorz; Koenig, Rolf

The GFZ German Research Centre for Geosciences developed a near-real time (NRT) orbit gen-eration system for GPS and Low Earth Orbiting (LEO) satellites to support radio occultation data processing for the CHAMP, GRACE, Terra-SAR-X and the upcoming TanDEM-X mis-sions and fast baseline determination for the TanDEM-X mission. Precise NRT orbits are being generated for the CHAMP and GRACE-A satellites since August 2006 and for TerraSAR-X since August 2007. For each LEO, the system consists of three independent chains delivering NRT orbits with different latencies and accuracies. The first chain generates in a preceding step NRT GPS orbits and clock biases and based thereon LEO orbits with delays of 30 minutes counted from the last measurement point to the time the orbit product is available. The orbit accuracies can be assessed via Satellite Laser Ranging (SLR) to 7 cm. The second chain is based on predicted GPS orbits from the International GNSS Service (IGS) but endowed with in-house estimated clock biases. This chain generates orbits with the same latency of 30 minutes but with better accuracies of 5 cm SLR RMS. The third chain, the least accurate but the fastest, is based on predicted IGS GPS orbits and clocks and delivers LEO orbits with latencies of 13 minutes and accuracies of 10 cm SLR RMS. The system design is such that it can easily be extended to cope with new satellites like TanDEM-X requiring precise and fast available orbits.

Land, Atmosphere Near Real-time Capability for EOS (LANCE) AMSR2 Data System

NASA Astrophysics Data System (ADS)

Smith, D. K.; Harrison, S.; Lin, H.; Flynn, S.; Nair, M.; Conover, H.; Graves, S. J.

2016-12-01

The Land, Atmosphere Near real-time Capability for EOS (LANCE) system was initiated to ensure the availability of NASA satellite data products to those partners who have grown to rely upon near real-time (NRT) data for their decision support systems. The LANCE Advanced Microwave Scanning Radiometer-EOS (AMSR-E) system was able to address the needs of the NRT community in areas such as weather prediction and forecasting, monitoring of natural hazards, disaster relief, agriculture, and homeland security for nearly one year before the instrument failed in 2011. The timely launch of Global Change Observation Mission -Water 1 (GCOM-W1) and the AMSR2 instrument by the Japanese Aerospace Exploration Agency (JAXA) in 2012 was very important to continue the time series of AMSR instruments. The LANCE element for AMSR2 was able to leverage the LANCE AMSR-E system architecture, using modified AMSR-E standard product algorithms in order to make preliminary data products available to NRT users before US AMSR2 standard product algorithms were available. This presentation will describe the five AMSR2 NRT product suites available from LANCE - Sea Ice, Snow, Rain/Ocean, and Soil Moisture. We will also discuss future plans for LANCE AMSR2.

Can Real-Time Data Also Be Climate Quality?

NASA Astrophysics Data System (ADS)

Brewer, M.; Wentz, F. J.

2015-12-01

GMI, AMSR-2 and WindSat herald a new era of highly accurate and timely microwave data products. Traditionally, there has been a large divide between real-time and re-analysis data products. What if these completely separate processing systems could be merged? Through advanced modeling and physically based algorithms, Remote Sensing Systems (RSS) has narrowed the gap between real-time and research-quality. Satellite microwave ocean products have proven useful for a wide array of timely Earth science applications. Through cloud SST capabilities have enormously benefited tropical cyclone forecasting and day to day fisheries management, to name a few. Oceanic wind vectors enhance operational safety of shipping and recreational boating. Atmospheric rivers are of import to many human endeavors, as are cloud cover and knowledge of precipitation events. Some activities benefit from both climate and real-time operational data used in conjunction. RSS has been consistently improving microwave Earth Science Data Records (ESDRs) for several decades, while making near real-time data publicly available for semi-operational use. These data streams have often been produced in 2 stages: near real-time, followed by research quality final files. Over the years, we have seen this time delay shrink from months or weeks to mere hours. As well, we have seen the quality of near real-time data improve to the point where the distinction starts to blur. We continue to work towards better and faster RFI filtering, adaptive algorithms and improved real-time validation statistics for earlier detection of problems. Can it be possible to produce climate quality data in real-time, and what would the advantages be? We will try to answer these questions…

Real time forest fire warning and forest fire risk zoning: a Vietnamese case study

NASA Astrophysics Data System (ADS)

Chu, T.; Pham, D.; Phung, T.; Ha, A.; Paschke, M.

2016-12-01

Forest fire occurs seriously in Vietnam and has been considered as one of the major causes of forest lost and degradation. Several studies of forest fire risk warning were conducted using Modified Nesterov Index (MNI) but remaining shortcomings and inaccurate predictions that needs to be urgently improved. In our study, several important topographic and social factors such as aspect, slope, elevation, distance to residential areas and road system were considered as "permanent" factors while meteorological data were updated hourly using near-real-time (NRT) remotely sensed data (i.e. MODIS Terra/Aqua and TRMM) for the prediction and warning of fire. Due to the limited number of weather stations in Vietnam, data from all active stations (i.e. 178) were used with the satellite data to calibrate and upscale meteorological variables. These data with finer resolution were then used to generate MNI. The only significant "permanent" factors were selected as input variables based on the correlation coefficients that computed from multi-variable regression among true fire-burning (collected from 1/2007) and its spatial characteristics. These coefficients also used to suggest appropriate weight for computing forest fire risk (FR) model. Forest fire risk model was calculated from the MNI and the selected factors using fuzzy regression models (FRMs) and GIS based multi-criteria analysis. By this approach, the FR was slightly modified from MNI by the integrated use of various factors in our fire warning and prediction model. Multifactor-based maps of forest fire risk zone were generated from classifying FR into three potential danger levels. Fire risk maps were displayed using webgis technology that is easy for managing data and extracting reports. Reported fire-burnings thereafter have been used as true values for validating the forest fire risk. Fire probability has strong relationship with potential danger levels (varied from 5.3% to 53.8%) indicating that the higher potential risk, the more chance of fire happen. By adding spatial factors to continuous daily updated remote sensing based meteo-data, results are valuable for both mapping forest fire risk zones in short and long-term and real time fire warning in Vietnam. Key words: Near-real-time, forest fire warning, fuzzy regression model, remote sensing.

Stationary orbits of satellites of disk galaxies

NASA Technical Reports Server (NTRS)

Polyachenko, Valerij L.

1990-01-01

The satellite of an S-galaxy will experience opposing dynamical-friction forces from the stars of the disk and the halo. If these forces are in balance, the satellite may travel in a stable, near-circular orbit whose radius, for a wide range of physical parameters, should be limited to a zone 1.2 to 1.4 times the disk radius, much as is observed. The idea is very simple. The dynamical friction acting on a small satellite, moving through a stellar galactic halo, makes this satellite slow down. On the other hand, a stellar disk, rotating faster than a satellite, makes it speed up. But the density distributions in radius for disk's and halo's stars in real flat galaxies are quite different (respectively, exponential and power-law). Moreover, the observational data show that the exponential profile for disk's surface density drops abruptly at some radius (r sub d). So it is natural to expect that a stationary orbit could be near the edge of a disk (where two effects are mutually compensated).

Early Warning Systems of natural disasters in the frame of EUNADICS-AV

NASA Astrophysics Data System (ADS)

Brenot, Hugues; Theys, Nicolas; Clarisse, Lieven; Kopp, Anna; Graf, Kaspar; Mona, Lucia; Coltelli, Mauro; Peltonen, Tuomas; Hirtl, Marcus; Virtanen, Timo; Nína Petersen, Guðrún

2017-04-01

Aviation is one of the most critical infrastructures of the 21st century. In Europe, safe flight operations, air traffic management and air traffic control are shared responsibilities of EUROCONTROL, national authorities, airlines and pilots. All stakeholders have one common goal, namely to warrant and maintain the safety of flight crews and passengers. Currently, however, there is a significant gap in the availability of real-time hazard measurement and monitoring information for airborne hazards. The main objective of the new Horizon 2020 project EUNADICS-AV (European Natural Airborne Disaster Information and Coordination System for Aviation; http://www.eunadics.eu) is to close this gap in data and information availability, enabling all stakeholders in the aviation system to obtain fast, coherent, and consistent information. Here we report on WP5 of EUNADICS-AV, the objective of which is to develop a prototype multi-hazard monitoring and early warning system. This task includes the development of a service for improved near real-time analyses (delay of a few hours maximum) of observations from satellite and ground-based platforms in order to detect ash and SO2 plumes (at the global scale), as well as desert sand dusts, fire plumes, and radioactive plumes.

Real-time new satellite product demonstration from microwave sensors and GOES-16 at NRL TC web

NASA Astrophysics Data System (ADS)

Cossuth, J.; Richardson, K.; Surratt, M. L.; Bankert, R.

2017-12-01

The Naval Research Laboratory (NRL) Tropical Cyclone (TC) satellite webpage (https://www.nrlmry.navy.mil/TC.html) provides demonstration analyses of storm imagery to benefit operational TC forecast centers around the world. With the availability of new spectral information provided by GOES-16 satellite data and recent research into improved visualization methods of microwave data, experimental imagery was operationally tested to visualize the structural changes of TCs during the 2017 hurricane season. This presentation provides an introduction into these innovative satellite analysis methods, NRL's next generation satellite analysis system (the Geolocated Information Processing System, GeoIPSTM), and demonstration the added value of additional spectral frequencies when monitoring storms in near-realtime.

A system concept for gradual deployment of geostationary lightsats

NASA Astrophysics Data System (ADS)

Peters, Graham C.; Garry, James R. C.

1993-10-01

Small satellites provide an attractive option for developing countries wishing to own and operate a satellite for the first time. It is proposed that space segment capacity could be built-up in response to increasing traffic requirements by launching small satellites at intervals into a single orbital slot to form a cluster. This paper, which results from an ESA study, reviews the various system aspects which must be considered and develops a suitable approach for multi-satellite deployment and collocation. Particular attention is paid to the system and payload configuration required to achieve effective mutual sparing between the satellites' payloads as the constellation is expanded. Mission and operational aspects are examined to obtain an acceptable risk of collisions between the satellites in a single orbit slot. The complexity and cost of operations are investigated to obtain the optimum size of satellite required to satisfy different demand requirements taken from real market scenarios.

Sensors and OBIA synergy for operational monitoring of surface water

NASA Astrophysics Data System (ADS)

Masson, Eric; Thenard, Lucas

2010-05-01

This contribution will focus on combining Object Based Image Analysis (i.e. OBIA with e-Cognition 8) and recent sensors (i.e. Spot 5 XS, Pan and ALOS Prism, Avnir2, Palsar) to address the technical feasibility for an operational monitoring of surface water. Three cases of river meandering (India), flood mapping (Nepal) and dam's seasonal water level monitoring (Morocco) using recent sensors will present various application of surface water monitoring. The operational aspect will be demonstrated either by sensor properties (i.e. spatial resolution and bandwidth), data acquisition properties (i.e. multi sensor, return period and near real-time acquisition) but also with OBIA algorithms (i.e. fusion of multi sensors / multi resolution data and batch processes). In the first case of river meandering (India) we will address multi sensor and multi date satellite acquisition to monitor the river bed mobility within a floodplain using an ALOS dataset. It will demonstrate the possibility of an operational monitoring system that helps the geomorphologist in the analysis of fluvial dynamic and sediment budget for high energy rivers. In the second case of flood mapping (Nepal) we will address near real time Palsar data acquisition at high spatial resolution to monitor and to map a flood extension. This ALOS sensor takes benefit both from SAR and L band properties (i.e. atmospheric transparency, day/night acquisition, low sensibility to surface wind). It's a real achievement compared to optical imagery or even other high resolution SAR properties (i.e. acquisition swath, bandwidth and data price). These advantages meet the operational needs set by crisis management of hydrological disasters but also for the implementation of flood risk management plans. The last case of dam surface water monitoring (Morocco) will address an important issue of water resource management in countries affected by water scarcity. In such countries water users have to cope with over exploitation, frequent drought period and now with foreseen climate change impacts. This third case will demonstrate the efficiency of SPOT 5 programming in synergy with OBIA methodology to assess the evolution of dam surface water within a complete water cycle (i.e. 2008-09). In all those three cases image segmentation and classification algorithms developed with e-Cognition 8 software allow an easy to use implementation of simple to highly sophisticate OBIA rulsets fully operational in batch processes. Finally this contribution foresees the new opportunity of integration of Worldview 2 multispectral imagery (i.e. 8 bands) including its "coastal" band that will also find an application in continental surface water bathymetry. Worldview 2 is a recently launch satellite (e.g. October 2009) that starts to collect earth observation data since January 2010. It is therefore a promising new remote sensing tool to develop operational hydrology in combination high resolution SAR imagery and OBIA methodology. This contribution will conclude on the strong potential for operationalisation in hydrology and water resources management that recent and future sensors and image analysis methodologies are offering to water management and decision makers.

Development of a multi-sensor based urban discharge forecasting system using remotely sensed data: A case study of extreme rainfall in South Korea

NASA Astrophysics Data System (ADS)

Yoon, Sunkwon; Jang, Sangmin; Park, Kyungwon

2017-04-01

Extreme weather due to changing climate is a main source of water-related disasters such as flooding and inundation and its damage will be accelerated somewhere in world wide. To prevent the water-related disasters and mitigate their damage in urban areas in future, we developed a multi-sensor based real-time discharge forecasting system using remotely sensed data such as radar and satellite. We used Communication, Ocean and Meteorological Satellite (COMS) and Korea Meteorological Agency (KMA) weather radar for quantitative precipitation estimation. The Automatic Weather System (AWS) and McGill Algorithm for Precipitation Nowcasting by Lagrangian Extrapolation (MAPLE) were used for verification of rainfall accuracy. The optimal Z-R relation was applied the Tropical Z-R relationship (Z=32R1.65), it has been confirmed that the accuracy is improved in the extreme rainfall events. In addition, the performance of blended multi-sensor combining rainfall was improved in 60mm/h rainfall and more strong heavy rainfall events. Moreover, we adjusted to forecast the urban discharge using Storm Water Management Model (SWMM). Several statistical methods have been used for assessment of model simulation between observed and simulated discharge. In terms of the correlation coefficient and r-squared discharge between observed and forecasted were highly correlated. Based on this study, we captured a possibility of real-time urban discharge forecasting system using remotely sensed data and its utilization for real-time flood warning. Acknowledgement This research was supported by a grant (13AWMP-B066744-01) from Advanced Water Management Research Program (AWMP) funded by Ministry of Land, Infrastructure and Transport (MOLIT) of Korean government.

Generation of real-time global ionospheric map based on the global GNSS stations with only a sparse distribution

NASA Astrophysics Data System (ADS)

Li, Zishen; Wang, Ningbo; Li, Min; Zhou, Kai; Yuan, Yunbin; Yuan, Hong

2017-04-01

The Earth's ionosphere is part of the atmosphere stretching from an altitude of about 50 km to more than 1000 km. When the Global Navigation Satellite System (GNSS) signal emitted from a satellite travels through the ionosphere before reaches a receiver on or near the Earth surface, the GNSS signal is significantly delayed by the ionosphere and this delay bas been considered as one of the major errors in the GNSS measurement. The real-time global ionospheric map calculated from the real-time data obtained by global stations is an essential method for mitigating the ionospheric delay for real-time positioning. The generation of an accurate global ionospheric map generally depends on the global stations with dense distribution; however, the number of global stations that can produce the real-time data is very limited at present, which results that the generation of global ionospheric map with a high accuracy is very different when only using the current stations with real-time data. In view of this, a new approach is proposed for calculating the real-time global ionospheric map only based on the current stations with real-time data. This new approach is developed on the basis of the post-processing and the one-day predicted global ionospheric map from our research group. The performance of the proposed approach is tested by the current global stations with the real-time data and the test results are also compared with the IGS-released final global ionospheric map products.

Ice Surface Temperature Variability in the Polar Regions and the Relationships to 2 Meter Air Temperatures

NASA Astrophysics Data System (ADS)

Hoyer, J.; Madsen, K. S.; Englyst, P. N.

2017-12-01

Determining the surface and near surface air temperature from models or observations in the Polar Regions is challenging due to the extreme conditions and the lack of in situ observations. The errors in near surface temperature products are typically larger than for other regions of the world, and the potential for using Earth Observations is large. As part of the EU project, EUSTACE, we have developed empirical models for the relationship between the satellite observed skin ice temperatures and 2m air temperatures. We use the Arctic and Antarctic Sea and sea ice Surface Temperatures from thermal Infrared satellite sensors (AASTI) reanalysis to estimate daily surface air temperature over land ice and sea ice for the Arctic and the Antarctic. Large efforts have been put into collecting and quality controlling in situ observations from various data portals and research projects. The reconstruction is independent of numerical weather prediction models and thus provides an important alternative to modelled air temperature estimates. The new surface air temperature data record has been validated against more than 58.000 independent in situ measurements for the four surface types: Arctic sea ice, Greenland ice sheet, Antarctic sea ice and Antarctic ice sheet. The average correlations are 92-97% and average root mean square errors are 3.1-3.6°C for the four surface types. The root mean square error includes the uncertainty of the in-situ measurement, which ranges from 0.5 to 2°C. A comparison with ERA-Interim shows a consistently better performance of the satellite based air temperatures than the ERA-Interim for the Greenland ice sheet, when compared against observations not used in any of the two estimates. This is encouraging and demonstrates the values of these products. In addition, the procedure presented here works on satellite observations that are available in near real time and this opens up for a near real time estimation of the surface air temperature over ice from satellites.

Satellite Data Product and Data Dissemination Updates for the SPoRT Sea Surface Temperature Composite Product

NASA Technical Reports Server (NTRS)

Zavodsky, Bradley; LaFontaine, Frank; Berndt, Emily; Meyer, Paul; Jedlovec, Gary

2017-01-01

The SPoRT SST composite is a reliable and robust high-resolution product generated twice per day in near real time. It incorporates highest quality data satellite data from infrared imagers and global analysis from NESDIS and UKMO. Recent updates to the product include the inclusion of VIIRS data to extend the life of the product beyond the MODIS era. It is used by a number of users in their DSS.

Towards a Cloud Computing Environment: Near Real-time Cloud Product Processing and Distribution for Next Generation Satellites

NASA Astrophysics Data System (ADS)

Nguyen, L.; Chee, T.; Minnis, P.; Palikonda, R.; Smith, W. L., Jr.; Spangenberg, D.

2016-12-01

The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) processes and derives near real-time (NRT) global cloud products from operational geostationary satellite imager datasets. These products are being used in NRT to improve forecast model, aircraft icing warnings, and support aircraft field campaigns. Next generation satellites, such as the Japanese Himawari-8 and the upcoming NOAA GOES-R, present challenges for NRT data processing and product dissemination due to the increase in temporal and spatial resolution. The volume of data is expected to increase to approximately 10 folds. This increase in data volume will require additional IT resources to keep up with the processing demands to satisfy NRT requirements. In addition, these resources are not readily available due to cost and other technical limitations. To anticipate and meet these computing resource requirements, we have employed a hybrid cloud computing environment to augment the generation of SatCORPS products. This paper will describe the workflow to ingest, process, and distribute SatCORPS products and the technologies used. Lessons learn from working on both AWS Clouds and GovCloud will be discussed: benefits, similarities, and differences that could impact decision to use cloud computing and storage. A detail cost analysis will be presented. In addition, future cloud utilization, parallelization, and architecture layout will be discussed for GOES-R.

Near real time/low latency data collection for climate warming manipulations and an elevated CO2 SPRUCE experiment

NASA Astrophysics Data System (ADS)

Krassovski, M.; Hanson, P. J.; Riggs, J. S.; Nettles, W. R., IV

2017-12-01

Climate change studies are one of the most important aspects of modern science and related experiments are getting bigger and more complex. One such experiment is the Spruce and Peatland Responses Under Climatic and Environmental Change experiment (SPRUCE, http://mnspruce.ornl.gov) conducted in in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. This manipulation experiment generates a lot of observational data and requires a reliable onsite data collection system, dependable methods to transfer data to a robust scientific facility, and real-time monitoring capabilities. This presentation shares our experience of establishing near real time/low latency data collection and monitoring system using satellite communication.

Potential Utility of the Real-Time TMPA-RT Precipitation Estimates in Streamflow Prediction

NASA Technical Reports Server (NTRS)

Su, Fengge; Gao, Huilin; Huffman, George J.; Lettenmaier, Dennis P.

2010-01-01

We investigate the potential utility of the real-time Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA-RT) data for streamflow prediction, both through direct comparisons of TMPA-RT estimates with a gridded gauge product, and through evaluation of streamflow simulations over four tributaries of La Plata Basin (LPB) in South America using the two precipitation products. Our assessments indicate that the relative accuracy and the hydrologic performance of TMPA-RT-based streamflow simulations generally improved after February 2005. The improvements in TMPA-RT since 2005 are closely related to upgrades in the TMPA-RT algorithm in early February, 2005 which include use of additional microwave sensors (AMSR-E and AMSU-B) and implementation of different calibration schemes. Our work suggests considerable potential for hydrologic prediction using purely satellite-derived precipitation estimates (no adjustments by in situ gauges) in parts of the globe where in situ observations are sparse.

The Waypoint Planning Tool: Real Time Flight Planning for Airborne Science

NASA Astrophysics Data System (ADS)

He, M.; Goodman, H. M.; Blakeslee, R.; Hall, J. M.

2010-12-01

NASA Earth science research utilizes both spaceborne and airborne real time observations in the planning and operations of its field campaigns. The coordination of air and space components is critical to achieve the goals and objectives and ensure the success of an experiment. Spaceborne imagery provides regular and continual coverage of the Earth and it is a significant component in all NASA field experiments. Real time visible and infrared geostationary images from GOES satellites and multi-spectral data from the many elements of the NASA suite of instruments aboard the TRMM, Terra, Aqua, Aura, and other NASA satellites have become norm. Similarly, the NASA Airborne Science Program draws upon a rich pool of instrumented aircraft. The NASA McDonnell Douglas DC-8, Lockheed P3 Orion, DeHavilland Twin Otter, King Air B200, Gulfstream-III are all staples of a NASA’s well-stocked, versatile hangar. A key component in many field campaigns is coordinating the aircraft with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions. Given the variables involved, developing a good flight plan that meets the objectives of the field experiment can be a challenging and time consuming task. Planning a research aircraft mission within the context of meeting the science objectives is complex task because it is much more than flying from point A to B. Flight plans typically consist of flying a series of transects or involve dynamic path changes when “chasing” a hurricane or forest fire. These aircraft flight plans are typically designed by the mission scientists then verified and implemented by the navigator or pilot. Flight planning can be an arduous task requiring frequent sanity checks by the flight crew. This requires real time situational awareness of the weather conditions that affect the aircraft track. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an interactive software tool, that enables scientists to develop their own flight plans (also known as waypoints) with point-and-click mouse capabilities on a digital map draped with real time satellite imagery. The Waypoint Planning Tool has further advanced to include satellite orbit predictions and seamlessly interfaces with the Real Time Mission Monitor which tracks the aircraft’s position when the planes are flying. This presentation will describe the capabilities and features of the Waypoint Planning Tool highlighting the real time aspect, interactive nature and the resultant benefits to the airborne science community.

The Waypoint Planning Tool: Real Time Flight Planning for Airborne Science

NASA Technical Reports Server (NTRS)

He, Yubin; Blakeslee, Richard; Goodman, Michael; Hall, John

2010-01-01

NASA Earth science research utilizes both spaceborne and airborne real time observations in the planning and operations of its field campaigns. The coordination of air and space components is critical to achieve the goals and objectives and ensure the success of an experiment. Spaceborne imagery provides regular and continual coverage of the Earth and it is a significant component in all NASA field experiments. Real time visible and infrared geostationary images from GOES satellites and multi-spectral data from the many elements of the NASA suite of instruments aboard the TRMM, Terra, Aqua, Aura, and other NASA satellites have become norm. Similarly, the NASA Airborne Science Program draws upon a rich pool of instrumented aircraft. The NASA McDonnell Douglas DC-8, Lockheed P3 Orion, DeHavilland Twin Otter, King Air B200, Gulfstream-III are all staples of a NASA's well-stocked, versatile hangar. A key component in many field campaigns is coordinating the aircraft with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions. Given the variables involved, developing a good flight plan that meets the objectives of the field experiment can be a challenging and time consuming task. Planning a research aircraft mission within the context of meeting the science objectives is complex task because it is much more than flying from point A to B. Flight plans typically consist of flying a series of transects or involve dynamic path changes when "chasing" a hurricane or forest fire. These aircraft flight plans are typically designed by the mission scientists then verified and implemented by the navigator or pilot. Flight planning can be an arduous task requiring frequent sanity checks by the flight crew. This requires real time situational awareness of the weather conditions that affect the aircraft track. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an interactive software tool, that enables scientists to develop their own flight plans (also known as waypoints) with point-and-click mouse capabilities on a digital map draped with real time satellite imagery. The Waypoint Planning Tool has further advanced to include satellite orbit predictions and seamlessly interfaces with the Real Time Mission Monitor which tracks the aircraft s position when the planes are flying. This presentation will describe the capabilities and features of the Waypoint Planning Tool highlighting the real time aspect, interactive nature and the resultant benefits to the airborne science community.

Use of real-time GNSS-RF data to characterize the swing movements of forestry equipment

Treesearch

Ryer M. Becker; Robert F. Keefe; Nathaniel M. Anderson

2017-01-01

The western United States faces significant forest management challenges after severe bark beetle infestations have led to substantial mortality. Minimizing costs is vital for increasing the feasibility of management operations in affected forests. Multi‐transmitter Global Navigation Satellite System (GNSS)‐radio frequencies (RF) technology has applications in the...

Real-Time Spaceborne Synthetic Aperture Radar Float-Point Imaging System Using Optimized Mapping Methodology and a Multi-Node Parallel Accelerating Technique

PubMed Central

Li, Bingyi; Chen, Liang; Yu, Wenyue; Xie, Yizhuang; Bian, Mingming; Zhang, Qingjun; Pang, Long

2018-01-01

With the development of satellite load technology and very large-scale integrated (VLSI) circuit technology, on-board real-time synthetic aperture radar (SAR) imaging systems have facilitated rapid response to disasters. A key goal of the on-board SAR imaging system design is to achieve high real-time processing performance under severe size, weight, and power consumption constraints. This paper presents a multi-node prototype system for real-time SAR imaging processing. We decompose the commonly used chirp scaling (CS) SAR imaging algorithm into two parts according to the computing features. The linearization and logic-memory optimum allocation methods are adopted to realize the nonlinear part in a reconfigurable structure, and the two-part bandwidth balance method is used to realize the linear part. Thus, float-point SAR imaging processing can be integrated into a single Field Programmable Gate Array (FPGA) chip instead of relying on distributed technologies. A single-processing node requires 10.6 s and consumes 17 W to focus on 25-km swath width, 5-m resolution stripmap SAR raw data with a granularity of 16,384 × 16,384. The design methodology of the multi-FPGA parallel accelerating system under the real-time principle is introduced. As a proof of concept, a prototype with four processing nodes and one master node is implemented using a Xilinx xc6vlx315t FPGA. The weight and volume of one single machine are 10 kg and 32 cm × 24 cm × 20 cm, respectively, and the power consumption is under 100 W. The real-time performance of the proposed design is demonstrated on Chinese Gaofen-3 stripmap continuous imaging. PMID:29495637

Utah State University Global Assimilation of Ionospheric Measurements Gauss-Markov Kalman filter model of the ionosphere: Model description and validation

NASA Astrophysics Data System (ADS)

Scherliess, L.; Schunk, R. W.; Sojka, J. J.; Thompson, D. C.; Zhu, L.

2006-11-01

The Utah State University Gauss-Markov Kalman Filter (GMKF) was developed as part of the Global Assimilation of Ionospheric Measurements (GAIM) program. The GMKF uses a physics-based model of the ionosphere and a Gauss-Markov Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) observations. The physics-based model is the Ionospheric Forecast Model (IFM), which accounts for five ion species and covers the E region, F region, and the topside from 90 to 1400 km altitude. Within the GMKF, the IFM derived ionospheric densities constitute a background density field on which perturbations are superimposed based on the available data and their errors. In the current configuration, the GMKF assimilates slant total electron content (TEC) from a variable number of global positioning satellite (GPS) ground sites, bottomside electron density (Ne) profiles from a variable number of ionosondes, in situ Ne from four Defense Meteorological Satellite Program (DMSP) satellites, and nighttime line-of-sight ultraviolet (UV) radiances measured by satellites. To test the GMKF for real-time operations and to validate its ionospheric density specifications, we have tested the model performance for a variety of geophysical conditions. During these model runs various combination of data types and data quantities were assimilated. To simulate real-time operations, the model ran continuously and automatically and produced three-dimensional global electron density distributions in 15 min increments. In this paper we will describe the Gauss-Markov Kalman filter model and present results of our validation study, with an emphasis on comparisons with independent observations.

Global Water Surface Dynamics: Toward a Near Real Time Monitoring Using Landsat and Sentinel Data

NASA Astrophysics Data System (ADS)

Pekel, J. F.; Belward, A.; Gorelick, N.

2017-12-01

Global surface water dynamics and its long-term changes have been documented at 30m spatial resolution using the entire multi-temporal orthorectified Landsat 5, 7 and 8 archive for the years 1984 to 2015. This validated dataset recorded the months and years when water was present, where occurrence changed and what form changes took (in terms of seasonality), documents inter-annual variability, and multi-annual trends. This information is freely available from the global surface water explorer https://global-surface-water.appspot.com. Here we extend this work (doi:10.1038/nature20584 ) by combining post 2015 Landsat 7 and 8 data with imagery from the Copernicus program's Sentinel 2a and b satellites. Using these data in combination improves the spatial resolution (from 30m to a nominal 10m) and temporal resolution (from 8 days to 4 days revisit time at the equator). The improved geographic and temporal completeness of the combined Landsat / Sentinel dataset also offers new opportunities for the identification and characterization of seasonally occurring waterbodies. These improvements are also being examined in the light of reporting progress against Agenda 2030's Sustainable Development Goal 6, especially the indicator used to measure 'change in the extent of water-related ecosystems over time'.

The Real-Time Monitoring Service Platform for Land Supervision Based on Cloud Integration

NASA Astrophysics Data System (ADS)

Sun, J.; Mao, M.; Xiang, H.; Wang, G.; Liang, Y.

2018-04-01

Remote sensing monitoring has become the important means for land and resources departments to strengthen supervision. Aiming at the problems of low monitoring frequency and poor data currency in current remote sensing monitoring, this paper researched and developed the cloud-integrated real-time monitoring service platform for land supervision which enhanced the monitoring frequency by acquiring the domestic satellite image data overall and accelerated the remote sensing image data processing efficiency by exploiting the intelligent dynamic processing technology of multi-source images. Through the pilot application in Jinan Bureau of State Land Supervision, it has been proved that the real-time monitoring technical method for land supervision is feasible. In addition, the functions of real-time monitoring and early warning are carried out on illegal land use, permanent basic farmland protection and boundary breakthrough in urban development. The application has achieved remarkable results.

Towards a Satellite-Based Near Real-Time Monitoring System for Water Quality; September 27th 2017

EPA Science Inventory

Declining water quality in inland and coastal systems has become, and will continue to be, a major environmental, social and economic problem as human populations increase, agricultural activities expand, and climate change effects on hydrological cycles and extreme events become...

77 FR 70139 - Submission for OMB Review; Comment Request

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-23

... species on the high seas in the Convention Area to carry and operate near real-time satellite-based... Commission as part of a vessel monitoring system (VMS) operated by the Commission (50 CFR 300.45). Under this...: National Oceanic and Atmospheric Administration (NOAA). Title: Vessel Monitoring System Requirements under...

Operational monitoring and forecasting of bathing water quality through exploiting satellite Earth observation and models: The AlgaRisk demonstration service

NASA Astrophysics Data System (ADS)

Shutler, J. D.; Warren, M. A.; Miller, P. I.; Barciela, R.; Mahdon, R.; Land, P. E.; Edwards, K.; Wither, A.; Jonas, P.; Murdoch, N.; Roast, S. D.; Clements, O.; Kurekin, A.

2015-04-01

Coastal zones and shelf-seas are important for tourism, commercial fishing and aquaculture. As a result the importance of good water quality within these regions to support life is recognised worldwide and a number of international directives for monitoring them now exist. This paper describes the AlgaRisk water quality monitoring demonstration service that was developed and operated for the UK Environment Agency in response to the microbiological monitoring needs within the revised European Union Bathing Waters Directive. The AlgaRisk approach used satellite Earth observation to provide a near-real time monitoring of microbiological water quality and a series of nested operational models (atmospheric and hydrodynamic-ecosystem) provided a forecast capability. For the period of the demonstration service (2008-2013) all monitoring and forecast datasets were processed in near-real time on a daily basis and disseminated through a dedicated web portal, with extracted data automatically emailed to agency staff. Near-real time data processing was achieved using a series of supercomputers and an Open Grid approach. The novel web portal and java-based viewer enabled users to visualise and interrogate current and historical data. The system description, the algorithms employed and example results focussing on a case study of an incidence of the harmful algal bloom Karenia mikimotoi are presented. Recommendations and the potential exploitation of web services for future water quality monitoring services are discussed.

Satellite-Based Assessment of Rainfall-Triggered Landslide Hazard for Situational Awareness

NASA Astrophysics Data System (ADS)

Kirschbaum, Dalia; Stanley, Thomas

2018-03-01

Determining the time, location, and severity of natural disaster impacts is fundamental to formulating mitigation strategies, appropriate and timely responses, and robust recovery plans. A Landslide Hazard Assessment for Situational Awareness (LHASA) model was developed to indicate potential landslide activity in near real-time. LHASA combines satellite-based precipitation estimates with a landslide susceptibility map derived from information on slope, geology, road networks, fault zones, and forest loss. Precipitation data from the Global Precipitation Measurement (GPM) mission are used to identify rainfall conditions from the past 7 days. When rainfall is considered to be extreme and susceptibility values are moderate to very high, a "nowcast" is issued to indicate the times and places where landslides are more probable. When LHASA nowcasts were evaluated with a Global Landslide Catalog, the probability of detection (POD) ranged from 8% to 60%, depending on the evaluation period, precipitation product used, and the size of the spatial and temporal window considered around each landslide point. Applications of the LHASA system are also discussed, including how LHASA is used to estimate long-term trends in potential landslide activity at a nearly global scale and how it can be used as a tool to support disaster risk assessment. LHASA is intended to provide situational awareness of landslide hazards in near real-time, providing a flexible, open-source framework that can be adapted to other spatial and temporal scales based on data availability.

4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications

NASA Technical Reports Server (NTRS)

Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.

2015-01-01

This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011) has the potential to provide valuable information about the near-surface soil moisture state for improving land surface modeling output.

The surface drifter program for real time and off-line validation of ocean forecasts and reanalyses

NASA Astrophysics Data System (ADS)

Hernandez, Fabrice; Regnier, Charly; Drévillon, Marie

2017-04-01

As part of the Global Ocean Observing System, the Global Drifter Program (GDP) is comprised of an array of about 1250 drifting buoys spread over the global ocean, that provide operational, near-real time surface velocity, sea surface temperature (SST) and sea level pressure observations. This information is used mainly used for numerical weather forecasting, research, and in-situ calibration/verification of satellite observations. Since 2013 the drifting buoy SST measurements are used for near real time assessment of global forecasting systems from Canada, France, UK, USA, Australia in the frame of the GODAE OceanView Intercomparison and Validation Task. For most of these operational systems, these data are not used for assimilation, and offer an independent observation assessment. This approach mimics the validation performed for SST satellite products. More recently, validation procedures have been proposed in order to assess the surface dynamics of Mercator Océan global and regional forecast and reanalyses. Velocities deduced from drifter trajectories are used in two ways. First, the Eulerian approach where buoy and ocean model velocity values are compared at the position of drifters. Then, from discrepancies, statistics are computed and provide an evaluation of the ocean model's surface dynamics reliability. Second, the Lagrangian approach, where drifting trajectories are simulated at each location of the real drifter trajectory using the ocean model velocity fields. Then, on daily basis, real and simulated drifter trajectories are compared by analyzing the spread after one day, two days etc…. The cumulated statistics on specific geographical boxes are evaluated in term of dispersion properties of the "real ocean" as captured by drifters, and those properties in the ocean model. This approach allows to better evaluate forecasting score for surface dispersion applications, like Search and Rescue, oil spill forecast, drift of other objects or contaminant, larvae dispersion etc… These Eulerian and Lagrangian validation approach can be applied for real time or offline assessment of ocean velocity products. In real time, the main limitation is our capability to detect drifter drogue's loss, causing erroneous assessment. Several methods, by comparison to wind entrainment effect or other velocity estimates like from satellite altimetry, are used. These Eulerian and Lagrangian surface velocity validation methods are planned to be adopted by the GODAE OceanView operational community in order to offer independent verification of surface current forecast.

The INTELSAT VI SSTDMA network diagnostic system

NASA Astrophysics Data System (ADS)

Tamboli, Satish P.; Zhu, Xiaobo; Wilkins, Kim N.; Gupta, Ramesh K.

The system-level design of an expert-system-based, near-real-time diagnostic system for INTELSAT VI satellite-switched time-division multiple access (SSTDMA) network is described. The challenges of INTELSAT VI diagnostics are discussed, along with alternative approaches for network diagnostics and the rationale for choosing a method based on burst unique-word detection. The focal point of the diagnostic system is the diagnostic processor, which resides in the central control and monitoring facility known as the INTELSAT Operations Center TDMA Facility (IOCTF). As real-time information such as burst unique-word detection data, reference terminal status data, and satellite telemetry alarm data are received at the IOCTF, the diagnostic processor continuously monitors the data streams. When a burst status change is detected, a 'snapshot' of the real-time data is forwarded to the expert system. Receipt of the change causes a set of rules to be invoked which associate the traffic pattern with a set of probable causes. A user-friendly interface allows a graphical view of the burst time plan and provides the ability to browse through the knowledge bases.

Real-time estimation of BDS/GPS high-rate satellite clock offsets using sequential least squares

NASA Astrophysics Data System (ADS)

Fu, Wenju; Yang, Yuanxi; Zhang, Qin; Huang, Guanwen

2018-07-01

The real-time precise satellite clock product is one of key prerequisites for real-time Precise Point Positioning (PPP). The accuracy of the 24-hour predicted satellite clock product with 15 min sampling interval and an update of 6 h provided by the International GNSS Service (IGS) is only 3 ns, which could not meet the needs of all real-time PPP applications. The real-time estimation of high-rate satellite clock offsets is an efficient method for improving the accuracy. In this paper, the sequential least squares method to estimate real-time satellite clock offsets with high sample rate is proposed to improve the computational speed by applying an optimized sparse matrix operation to compute the normal equation and using special measures to take full advantage of modern computer power. The method is first applied to BeiDou Navigation Satellite System (BDS) and provides real-time estimation with a 1 s sample rate. The results show that the amount of time taken to process a single epoch is about 0.12 s using 28 stations. The Standard Deviation (STD) and Root Mean Square (RMS) of the real-time estimated BDS satellite clock offsets are 0.17 ns and 0.44 ns respectively when compared to German Research Center for Geosciences (GFZ) final clock products. The positioning performance of the real-time estimated satellite clock offsets is evaluated. The RMSs of the real-time BDS kinematic PPP in east, north, and vertical components are 7.6 cm, 6.4 cm and 19.6 cm respectively. The method is also applied to Global Positioning System (GPS) with a 10 s sample rate and the computational time of most epochs is less than 1.5 s with 75 stations. The STD and RMS of the real-time estimated GPS satellite clocks are 0.11 ns and 0.27 ns, respectively. The accuracies of 5.6 cm, 2.6 cm and 7.9 cm in east, north, and vertical components are achieved for the real-time GPS kinematic PPP.

Efficiently Scheduling Multi-core Guest Virtual Machines on Multi-core Hosts in Network Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoginath, Srikanth B; Perumalla, Kalyan S

2011-01-01

Virtual machine (VM)-based simulation is a method used by network simulators to incorporate realistic application behaviors by executing actual VMs as high-fidelity surrogates for simulated end-hosts. A critical requirement in such a method is the simulation time-ordered scheduling and execution of the VMs. Prior approaches such as time dilation are less efficient due to the high degree of multiplexing possible when multiple multi-core VMs are simulated on multi-core host systems. We present a new simulation time-ordered scheduler to efficiently schedule multi-core VMs on multi-core real hosts, with a virtual clock realized on each virtual core. The distinguishing features of ourmore » approach are: (1) customizable granularity of the VM scheduling time unit on the simulation time axis, (2) ability to take arbitrary leaps in virtual time by VMs to maximize the utilization of host (real) cores when guest virtual cores idle, and (3) empirically determinable optimality in the tradeoff between total execution (real) time and time-ordering accuracy levels. Experiments show that it is possible to get nearly perfect time-ordered execution, with a slight cost in total run time, relative to optimized non-simulation VM schedulers. Interestingly, with our time-ordered scheduler, it is also possible to reduce the time-ordering error from over 50% of non-simulation scheduler to less than 1% realized by our scheduler, with almost the same run time efficiency as that of the highly efficient non-simulation VM schedulers.« less

Visualizing and Integrating AFSCN Utilization into a Common Operational Picture

NASA Astrophysics Data System (ADS)

Hays, B.; Carlile, A.; Mitchell, T.

The Department of Defense (DoD) and the 50th Space Network Operations Group Studies and Analysis branch (50th SCS/SCXI), located at Schriever AFB Colorado, face the unique challenge of forecasting the expected near term and future utilization of the Air Force Satellite Control Network (AFSCN). The forecasting timeframe covers the planned load from the current date to ten years out. The various satellite missions, satellite requirements, orbital regions, and ground architecture dynamics provide the model inputs and constraints that are used in generating the forecasted load. The AFSCN is the largest network the Air Force uses to control satellites worldwide. Each day, network personnel perform over 500 scheduled events-from satellite maneuvers to critical data downloads. The Forecasting Objective is to provide leadership with the insights necessary to manage the network today and tomorrow. For both today's needs and future needs, SCXI develops AFSCN utilization forecasts to optimize the ground system's coverage and capacity to meet user satellite requirements. SCXI also performs satellite program specific studies to determine network support feasibility. STK and STK Scheduler form the core of the tools used by SCXI. To establish this tool suite, we had to evaluate, evolve, and validate both the COTS products and our own developed code and processes. This began with calibrating the network model to emulate the real life scheduling environment of the AFSCN. Multiple STK Scheduler optimizing (de-confliction) algorithms, including Multi-Pass, Sequential, Random, and Neural, were evaluated and adjusted to determine applicability to the model and the accuracy of the prediction. Additionally, the scheduling Figure of Merit (FOM), which permits custom weighting of various parameters, was analyzed and tested to achieve the most accurate real life result. With the inherent capabilities of STK and the ability to wrap and automate output, SCXI is now able to visually communicate satellite loads in a manner never seen before in AFSCN management meetings. Scenarios such as regional antenna load stress, satellite missed opportunities, and the overall network "big picture" can be visually displayed in 3D versus the textual and line graph methods used for many years. This is the first step towards an integrated space awareness picture with an operational focus. SCXI is working on taking the visual forecast concept farther and begin fusing multiple sources of data to build a 50 SW Common Operating Picture (COP). The vision is to integrate more effective orbital determination processes, resource outages, current and forecasted satellite mission requirements, and future architectural changes into a real-time visual status to enable quick and responsive decisions. This COP would be utilized in a Wing Operations Center to provide up to the minute network status on where satellites are, which ground resources are in contact with them, and what resources are down. The ability to quickly absorb and process this data will enhance decision analysis and save valuable time in both day to day operations and wartime scenarios.

The Global Precipitation Measurement (GPM) Mission contributions to hydrology and societal applications

NASA Astrophysics Data System (ADS)

Kirschbaum, D.; Huffman, G. J.; Skofronick Jackson, G.

2016-12-01

Too much or too little rain can serve as a tipping point for triggering catastrophic flooding and landslides or widespread drought. Knowing when, where and how much rain is falling globally is vital to understanding how vulnerable areas may be more or less impacted by these disasters. The Global Precipitation Measurement (GPM) mission provides near real-time precipitation data worldwide that is used by a broad range of end users, from tropical cyclone forecasters to agricultural modelers to researchers evaluating the spread of diseases. The GPM constellation provides merged, multi-satellite data products at three latencies that are critical for research and societal applications around the world. This presentation will outline current capabilities in using accurate and timely information of precipitation to directly benefit society, including examples of end user applications within the tropical cyclone forecasting, disasters response, agricultural forecasting, and disease tracking communities, among others. The presentation will also introduce some of the new visualization and access tools developed by the GPM team.

Detection of volcanic eruptions from space by their sulfur dioxide clouds

NASA Technical Reports Server (NTRS)

Krueger, A. J.

1985-01-01

The capabilities of the total ozone mapping spectrometer (TOMS) on the Nimbus 7 satellite for tracking volcano plumes are assessed. TOMS was installed on the sun-synchronous polar orbiting satellite to measure spatial variations in the global total ozone field. Radiance absorption coefficients of the atmosphere for four near-UV wavelengths from 312.5-380.0 are measured. Data from the El Chichon eruption in March-April 1982 revealed that SO2 was an absorbing species at 312.5 and 317.5 nm. The near-UV absorption level differences between SO2 and O3 permit discriminating the atmospheric densities of each species. An examination of the data base generated by TOMS since 1978 showed the perceptible tracks of all known major eruptions in the 1978-1982 time period. A constellation of three of the polar orbiting TOMS would be sufficient to provide near-real time alerts of plumes to warn aircraft of the hazards.

On analytic modeling of lunar perturbations of artificial satellites of the earth

NASA Astrophysics Data System (ADS)

Lane, M. T.

1989-06-01

Two different procedures for analytically modeling the effects of the moon's direct gravitational force on artificial earth satellites are discussed from theoretical and numerical viewpoints. One is developed using classical series expansions of inclination and eccentricity for both the satellite and the moon, and the other employs the method of averaging. Both solutions are seen to have advantages, but it is shown that while the former is more accurate in special situations, the latter is quicker and more practical for the general orbit determination problem where observed data are used to correct the orbit in near real time.

A System for Monitoring and Forecasting Land Surface Phenology Using Time Series of JPSS VIIRS Observations and Its Applications

NASA Astrophysics Data System (ADS)

Zhang, X.; Yu, Y.; Liu, L.

2015-12-01

Land surface phenology quantifies seasonal dynamics of vegetation properties including the timing and magnitude of vegetation greenness from satellite observations. Over the last decade, historical time series of AVHRR and MODIS data has been used to characterize the seasonal and interannual variation in terrestrial ecosystems and their responses to a changing and variable climate. The Visible Infrared Imaging Radiometer Suite (VIIRS) instrument on board the operational JPSS satellites provides land surface observations in a timely fashion, which has the capability to monitor phenological development in near real time. This capability is particularly important for assisting agriculture, natural resource management, and land modeling for weather prediction systems. Here we introduce a system to monitor in real time and forecast in the short term phenological development based on daily VIIRS observations available with a one-day latency. The system integrates a climatological land surface phenology from long-term MODIS data and available VIIRS observations to simulate a set of potential temporal trajectories of greenness development at a given time and pixel. The greenness trajectories, which are qualified using daily two-band Enhanced Vegetation Index (EVI2), are applied to identify spring green leaf development and autumn color foliage status in real time and to predict the occurrence of future phenological events. This system currently monitors vegetation development across the North America every three days and makes prediction to 10 days ahead. We further introduce the applications of near real time spring green leaf and fall color foliage. Specifically, this system is used for tracing the crop progress across the United States, guiding the field observations in US National Phenology Network, servicing tourists for the observation of color fall foliage, and parameterizing seasonal surface physical conditions for numerical weather prediction models.

New Energetic Particle Data and Products from the GOES Program

NASA Astrophysics Data System (ADS)

Onsager, Terrance; Rodriguez, Juan

The NOAA Geostationary Operational Environmental Satellite (GOES) program has provided continuous, real-time measurements of the near-Earth space environment for decades. In addition to their scientific value, the GOES energetic particle measurements are the basis for a variety of space weather products and services, including the forecasting of elevated energetic particle levels, real-time knowledge of the satellite environment at geostationary orbit, and data to allow post-event analyses when satellite anomalies occur. The GOES satellites have traditionally provided measurements of high-energy electrons, protons, and alpha particles (100s of keV to 100s of MeV). Beginning with the launch of GOES-13 in 2006, the measurement capabilities were expanded to include medium-energy electrons and protons (10s to 100s of keV) with pitch angle resolution. The next generation of GOES satellites, starting with GOES-R in 2016, will include low-energy electrons and ions (10s of eV to 10s of keV) as well as energetic heavy ions. In this presentation, we will overview the GOES particle measurements available now and in the future and describe the space weather services and scientific investigations that these data support.

Hydrological similarity approach and rainfall satellite utilization for mini hydro power dam basic design (case study on the ungauged catchment at West Borneo, Indonesia)

NASA Astrophysics Data System (ADS)

Prakoso, W. G.; Murtilaksono, K.; Tarigan, S. D.; Purwanto, Y. J.

2018-05-01

An approach on flow duration and flood design estimation on the ungauged catchment with no rainfall and discharge data availability was been being develop with hydrological modelling including rainfall run off model implemented with watershed characteristic dataset. Near real time Rainfall data from multi satellite platform e.g. TRMM can be utilized for regionalization approach on the ungauged catchment. Watershed hydrologically similarity analysis were conducted including all of the major watershed in Borneo which was predicted to be similar with the Nanga Raun Watershed. It was found that a satisfactory hydrological model calibration could be achieved using catchment weighted time series of TRMM daily rainfall data, performed on nearby catchment deemed to be sufficiently similar to Nanga Raun catchment in hydrological terms. Based on this calibration, rainfall runoff parameters were then transferred to a model. Relatively reliable flow duration curve and extreme discharge value estimation were produced with reasonable several limitation. Further approach may be performed in order to deal with the primary limitations inherent in the hydrological and statistical analysis, especially to give prolongation to the availability of the rainfall and climate data with some novel approach like downscaling of global climate model.

From scientific understanding to operational utility: New concepts and tools for monitoring space weather effects on satellites

NASA Astrophysics Data System (ADS)

Green, J. C.; Rodriguez, J. V.; Denig, W. F.; Redmon, R. J.; Blake, J. B.; Mazur, J. E.; Fennell, J. F.; O'Brien, T. P.; Guild, T. B.; Claudepierre, S. G.; Singer, H. J.; Onsager, T. G.; Wilkinson, D. C.

2013-12-01

NOAA space weather sensors have monitored the near Earth space radiation environment for more than three decades providing one of the only long-term records of these energetic particles that can disable satellites and pose a threat to astronauts. These data have demonstrated their value for operations for decades, but they are also invaluable for scientific discovery. Here we describe the development of new NOAA tools for assessing radiation impacts to satellites and astronauts working in space. In particular, we discuss the new system implemented for processing and delivering near real time particle radiation data from the POES/MetOp satellites. We also describe the development of new radiation belt indices from the POES/MetOp data that capture significant global changes in the environment needed for operational decision making. Lastly, we investigate the physical processes responsible for dramatic changes of the inner proton belt region and the potential consequences these new belts may have for satellite operations.

Impacts of Satellite Orbit and Clock on Real-Time GPS Point and Relative Positioning.

PubMed

Shi, Junbo; Wang, Gaojing; Han, Xianquan; Guo, Jiming

2017-06-12

Satellite orbit and clock corrections are always treated as known quantities in GPS positioning models. Therefore, any error in the satellite orbit and clock products will probably cause significant consequences for GPS positioning, especially for real-time applications. Currently three types of satellite products have been made available for real-time positioning, including the broadcast ephemeris, the International GNSS Service (IGS) predicted ultra-rapid product, and the real-time product. In this study, these three predicted/real-time satellite orbit and clock products are first evaluated with respect to the post-mission IGS final product, which demonstrates cm to m level orbit accuracies and sub-ns to ns level clock accuracies. Impacts of real-time satellite orbit and clock products on GPS point and relative positioning are then investigated using the P3 and GAMIT software packages, respectively. Numerical results show that the real-time satellite clock corrections affect the point positioning more significantly than the orbit corrections. On the contrary, only the real-time orbit corrections impact the relative positioning. Compared with the positioning solution using the IGS final product with the nominal orbit accuracy of ~2.5 cm, the real-time broadcast ephemeris with ~2 m orbit accuracy provided <2 cm relative positioning error for baselines no longer than 216 km. As for the baselines ranging from 574 to 2982 km, the cm-dm level positioning error was identified for the relative positioning solution using the broadcast ephemeris. The real-time product could result in <5 mm relative positioning accuracy for baselines within 2982 km, slightly better than the predicted ultra-rapid product.

Multi-scale model of the ionosphere from the combination of modern space-geodetic satellite techniques - project status and first results

NASA Astrophysics Data System (ADS)

Schmidt, M.; Hugentobler, U.; Jakowski, N.; Dettmering, D.; Liang, W.; Limberger, M.; Wilken, V.; Gerzen, T.; Hoque, M.; Berdermann, J.

2012-04-01

Near real-time high resolution and high precision ionosphere models are needed for a large number of applications, e.g. in navigation, positioning, telecommunications or astronautics. Today these ionosphere models are mostly empirical, i.e., based purely on mathematical approaches. In the DFG project 'Multi-scale model of the ionosphere from the combination of modern space-geodetic satellite techniques (MuSIK)' the complex phenomena within the ionosphere are described vertically by combining the Chapman electron density profile with a plasmasphere layer. In order to consider the horizontal and temporal behaviour the fundamental target parameters of this physics-motivated approach are modelled by series expansions in terms of tensor products of localizing B-spline functions depending on longitude, latitude and time. For testing the procedure the model will be applied to an appropriate region in South America, which covers relevant ionospheric processes and phenomena such as the Equatorial Anomaly. The project connects the expertise of the three project partners, namely Deutsches Geodätisches Forschungsinstitut (DGFI) Munich, the Institute of Astronomical and Physical Geodesy (IAPG) of the Technical University Munich (TUM) and the German Aerospace Center (DLR), Neustrelitz. In this presentation we focus on the current status of the project. In the first year of the project we studied the behaviour of the ionosphere in the test region, we setup appropriate test periods covering high and low solar activity as well as winter and summer and started the data collection, analysis, pre-processing and archiving. We developed partly the mathematical-physical modelling approach and performed first computations based on simulated input data. Here we present information on the data coverage for the area and the time periods of our investigations and we outline challenges of the multi-dimensional mathematical-physical modelling approach. We show first results, discuss problems in modelling and possible solution strategies and finally, we address open questions.

The use of the AOA TTR-4P GPS receiver in operation at the BIPM for real-time restitution of GPS time

NASA Technical Reports Server (NTRS)

Thomas, Claudine

1994-01-01

The Global Positioning System is an outstanding tool for the dissemination of time. Using mono-channel C/A-code GPS time receivers, the restitution of GPS time through the satellite constellation presents a peak-to-peak discrepancy of several tens of nanoseconds without SA but may be as high as several hundreds of nanoseconds with SA. As a consequence, civil users are more and more interested in implementing hardware and software methods for efficient restitution of GPS time, especially in the framework of the project of a real-time prediction of UTC (UTCp) which could be available in the form of time differences (UTCp - GPS time). Previous work, for improving the real-time restitution of GPS time with SA, to the level obtained without SA, focused on the implementation of a Kalman filter based on past data and updated at each new observation. An alternative solution relies upon the statistical features of the noise brought about by SA; it has already been shown that the SA noise is efficiently reduced by averaging data from numerous satellites observed simultaneously over a sufficiently long time. This method was successfully applied to data from a GPS time receiver, model AOA TTR-4P, connected to the cesium clock kept at the BIPM. This device, a multi-channel, dual frequency, P-code GPS time receiver, is one of the first TTR-4P units in operation in a civil laboratory. Preliminary comparative studies of this new equipment with conventional GPS time receivers are described in this paper. The results of an experimental restitution of GPS time, obtained in June 1993, are also detailed: 3 to 6 satellites were observed simultaneously with a sample interval of 15 s, an efficient smoothing of SA noise was realized by averaging data on all observed satellites over more than 1 hour. When the GPS system is complete in 1994, 8 satellites will be observable continuously from anywhere in the world and the same level of uncertainty will be obtained using a shorter averaging time.

Near-Real-Time Earth Observation Data Supporting Wildfire Management

NASA Astrophysics Data System (ADS)

Ambrosia, V. G.; Zajkowski, T.; Quayle, B.

2013-12-01

During disaster events, the most critical element needed by responding personnel and management teams is situational intelligence / awareness. During rapidly-evolving events such as wildfires, the need for timely information is critical to save lives, property and resources. The wildfire management agencies in the US rely heavily on remote sensing information both from airborne platforms as well as from orbital assets. The ability to readily have information from those systems, not just data, is critical to effective control and damage mitigation. NASA has been collaborating with the USFS to mature and operationalize various asset-information capabilities to effect improved knowledge of fire-prone areas, monitor wildfire events in real-time, assess effectiveness of fire management strategies, and provide rapid, post-fire assessment for recovery operations. Specific examples of near-real-time remote sensing asset utility include daily MODIS data employed to assess fire potential / wildfire hazard areas, and national-scale hot-spot detection, airborne thermal sensor collected during wildfire events to effect management strategies, EO-1 ALI 'pointable' satellite sensor data to assess fire-retardant application effectiveness, and Landsat 8 and other sensor data to derive burn severity indices for post-fire remediation work. These cases of where near-real-time data is used operationally during the previous few fire seasons will be presented.

Marshall Installs Receiving Antenna for Next-Generation Weather Satellites

NASA Image and Video Library

2016-12-16

Technicians assemble a hefty segment of a new antenna system in this 30-second time-lapse video captured Dec. 16 at NASA's Marshall Space Flight Center. The high-performance ground station is designed to receive meteorological and space weather data from instruments flown on the National Oceanic and Atmospheric Administration's new, game-changing Geostationary Operational Environmental Satellite series. The six-meter dish antenna near Building 4316 expands the capacity of Marshall’s Earth Science Office to use real-time GOES observations for studies of Earth and to deliver new forecasting, warning and disaster response tools to partners around the world. (NASA/MSFC)

A framework to monitor activities of satellite data processing in real-time

NASA Astrophysics Data System (ADS)

Nguyen, M. D.; Kryukov, A. P.

2018-01-01

Space Monitoring Data Center (SMDC) of SINP MSU is one of the several centers in the world that collects data on the radiational conditions in near-Earth orbit from various Russian (Lomonosov, Electro-L1, Electro-L2, Meteor-M1, Meteor-M2, etc.) and foreign (GOES 13, GOES 15, ACE, SDO, etc.) satellites. The primary purposes of SMDC are: aggregating heterogeneous data from different sources; providing a unified interface for data retrieval, visualization, analysis, as well as development and testing new space weather models; and controlling the correctness and completeness of data. Space weather models rely on data provided by SMDC to produce forecasts. Therefore, monitoring the whole data processing cycle is crucial for further success in the modeling of physical processes in near-Earth orbit based on the collected data. To solve the problem described above, we have developed a framework called Live Monitor at SMDC. Live Monitor allows watching all stages and program components involved in each data processing cycle. All activities of each stage are logged by Live Monitor and shown in real-time on a web interface. When an error occurs, a notification message will be sent to satellite operators via email and the Telegram messenger service so that they could take measures in time. The Live Monitor’s API can be used to create a customized monitoring service with minimum coding.

NOAA Coral Reef Watch: Decision Support Tools for Coral Reef Managers

NASA Astrophysics Data System (ADS)

Rauenzahn, J.; Eakin, C.; Skirving, W. J.; Burgess, T.; Christensen, T.; Heron, S. F.; Li, J.; Liu, G.; Morgan, J.; Nim, C.; Parker, B. A.; Strong, A. E.

2010-12-01

A multitude of natural and anthropogenic stressors exert substantial influence on coral reef ecosystems and contribute to bleaching events, slower coral growth, infectious disease outbreaks, and mortality. Satellite-based observations can monitor, at a global scale, environmental conditions that influence both short-term and long-term coral reef ecosystem health. From research to operations, NOAA Coral Reef Watch (CRW) incorporates paleoclimatic, in situ, and satellite-based biogeophysical data to provide near-real-time and forecast information and tools to help managers, researchers, and other stakeholders interpret coral health and stress. CRW has developed an operational, near-real-time product suite that includes sea surface temperature (SST), SST time series data, SST anomaly charts, coral bleaching HotSpots, and Degree Heating Weeks (DHW). Bi-weekly global SST analyses are based on operational nighttime-only SST at 50-km resolution. CRW is working to develop high-resolution products to better address thermal stress on finer scales and is applying climate models to develop seasonal outlooks of coral bleaching. Automated Satellite Bleaching Alerts (SBAs), available at Virtual Stations worldwide, provide the only global early-warning system to notify managers of changing reef environmental conditions. Currently, CRW is collaborating with numerous domestic and international partners to develop new tools to address ocean acidification, infectious diseases of corals, combining light and temperature to detect coral photosystem stress, and other parameters.

Near Real-Time Use of Optical Remote Sensing and Synthetic Aperture Radar for Response to Central U.S. Flooding in Late April-Early May 2017

NASA Astrophysics Data System (ADS)

Bell, J. R.; Schultz, L. A.; Jones, M.; Molthan, A.; Arko, S. A.; Hogenson, K.; Meyer, F. J.

2017-12-01

In late April and early May 2017, heavy rainfall across Missouri led to extensive flooding along the Missouri and Mississippi River basins in the Central United States. Determining the extent of flooding is critical for response organizations to properly deploy personnel and other assets involved in preparedness, mitigation, response, and recovery efforts. The Federal Emergency Management Agency (FEMA) relies on geospatial flood extent data, among other data, to estimate the impacts to population and infrastructure in order to prepare and engage response activities in support of the affected states and communities. To assist FEMA in mapping flood extent in a near real-time, the NASA Earth Science Disasters Program coordinates a multi-NASA center response to provide satellite imagery and products to FEMA during major flood events to supplement their analysis tools and capabilities. Scientists at the NASA Short-term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center, who led this particular response, have been working with the Alaska Satellite Facility (ASF) at the University of Alaska Fairbanks to provide synthetic aperture radar (SAR) imagery and derived flood products to FEMA's geospatial response team in support of flooding events. Combined, these efforts helped to provide preliminary flood mapping to FEMA from a broad constellation of remote sensors. The presentation will describe the various products available throughout the response event, post-event collaborations examining these products in comparison to additional modeling and data collection by FEMA, training needs to improve product use, and more efficient methods for data delivery. Lessons learned will highlight opportunities for future work and improvement, and guide other ongoing efforts to develop collaborations that would also support other domestic emergency response activities, such as those led by the National Guard Bureau, which assists individual state Guard units.

The Promise and Challenges of High Rate GNSS for Environmental Monitoring and Response

NASA Astrophysics Data System (ADS)

LaBrecque, John

2017-04-01

The decadal vision Global Geodetic Observing System recognizes the potential of high rate real time GNSS for environmental monitoring. The GGOS initiated a program to advance GNSS real time high rate measurements to augment seismic and other sensor systems for earthquake and tsunami early warning. High rate multi-GNSS networks can provide ionospheric tomography for the detection and tracking of land, ocean and atmospheric gravity waves that can provide coastal warning of tsunamis induced by earthquakes, volcanic eruptions, severe weather and other catastrophic events. NASA has collaborated on a microsatellite constellation of GPS receivers to measure ocean surface roughness to improve severe storm tracking and a equatorial system of GPS occultation receivers to measure ionospheric and atmospheric dynamics. Systems such as these will be significantly enhanced by the availability of a four fold increase in GNSS satellite systems with new and enhanced signal structures and by the densification of regional multi-GNSS networks. These new GNSS capabilities will rely upon improved and cost effective communications infrastructure for a network of coordinated real time analysis centers with input to national warning systems. Most important, the implementation of these new real time GNSS capabilities will rely upon the broad international support for the sharing of real time GNSS much as is done in weather and seismic observing systems and as supported by the Committee of Experts on UN Global Geodetic Information Management (UNGGIM).

An automated mapping satellite system ( Mapsat).

USGS Publications Warehouse

Colvocoresses, A.P.

1982-01-01

The favorable environment of space permits a satellite to orbit the Earth with very high stability as long as no local perturbing forces are involved. Solid-state linear-array sensors have no moving parts and create no perturbing force on the satellite. Digital data from highly stabilized stereo linear arrays are amenable to simplified processing to produce both planimetric imagery and elevation data. A satellite imaging system, called Mapsat, including this concept has been proposed to produce data from which automated mapping in near real time can be accomplished. Image maps as large as 1:50 000 scale with contours as close as a 20-m interval may be produced from Mapsat data. -from Author

Multi-agent robotic systems and applications for satellite missions

NASA Astrophysics Data System (ADS)

Nunes, Miguel A.

A revolution in the space sector is happening. It is expected that in the next decade there will be more satellites launched than in the previous sixty years of space exploration. Major challenges are associated with this growth of space assets such as the autonomy and management of large groups of satellites, in particular with small satellites. There are two main objectives for this work. First, a flexible and distributed software architecture is presented to expand the possibilities of spacecraft autonomy and in particular autonomous motion in attitude and position. The approach taken is based on the concept of distributed software agents, also referred to as multi-agent robotic system. Agents are defined as software programs that are social, reactive and proactive to autonomously maximize the chances of achieving the set goals. Part of the work is to demonstrate that a multi-agent robotic system is a feasible approach for different problems of autonomy such as satellite attitude determination and control and autonomous rendezvous and docking. The second main objective is to develop a method to optimize multi-satellite configurations in space, also known as satellite constellations. This automated method generates new optimal mega-constellations designs for Earth observations and fast revisit times on large ground areas. The optimal satellite constellation can be used by researchers as the baseline for new missions. The first contribution of this work is the development of a new multi-agent robotic system for distributing the attitude determination and control subsystem for HiakaSat. The multi-agent robotic system is implemented and tested on the satellite hardware-in-the-loop testbed that simulates a representative space environment. The results show that the newly proposed system for this particular case achieves an equivalent control performance when compared to the monolithic implementation. In terms on computational efficiency it is found that the multi-agent robotic system has a consistent lower CPU load of 0.29 +/- 0.03 compared to 0.35 +/- 0.04 for the monolithic implementation, a 17.1 % reduction. The second contribution of this work is the development of a multi-agent robotic system for the autonomous rendezvous and docking of multiple spacecraft. To compute the maneuvers guidance, navigation and control algorithms are implemented as part of the multi-agent robotic system. The navigation and control functions are implemented using existing algorithms, but one important contribution of this section is the introduction of a new six degrees of freedom guidance method which is part of the guidance, navigation and control architecture. This new method is an explicit solution to the guidance problem, and is particularly useful for real time guidance for attitude and position, as opposed to typical guidance methods which are based on numerical solutions, and therefore are computationally intensive. A simulation scenario is run for docking four CubeSats deployed radially from a launch vehicle. Considering fully actuated CubeSats, the simulations show docking maneuvers that are successfully completed within 25 minutes which is approximately 30% of a full orbital period in low earth orbit. The final section investigates the problem of optimization of satellite constellations for fast revisit time, and introduces a new method to generate different constellation configurations that are evaluated with a genetic algorithm. Two case studies are presented. The first is the optimization of a constellation for rapid coverage of the oceans of the globe in 24 hours or less. Results show that for an 80 km sensor swath width 50 satellites are required to cover the oceans with a 24 hour revisit time. The second constellation configuration study focuses on the optimization for the rapid coverage of the North Atlantic Tracks for air traffic monitoring in 3 hours or less. The results show that for a fixed swath width of 160 km and for a 3 hour revisit time 52 satellites are required.

Robust satellite techniques for oil spill detection and monitoring

NASA Astrophysics Data System (ADS)

Casciello, D.; Pergola, N.; Tramutoli, V.

Discharge of oil into the sea is one of the most dangerous, among technological hazards, for the maritime environment. In the last years maritime transport and exploitation of marine resources continued to increase; as a result, tanker accidents are nowadays increasingly frequent, continuously menacing the maritime security and safety. Satellite remote sensing could contribute in multiple ways, in particular for what concerns early warning and real-time (or near real-time) monitoring. Several satellite techniques exist, mainly based on the use of SAR (Synthetic Aperture Radar) technology, which are able to recognise, with sufficient accuracy, oil spills discharged into the sea. Unfortunately, such methods cannot be profitably used for real-time detection, because of the low observational frequency assured by present satellite platforms carrying SAR sensors (the mean repetition rate is something like 30 days). On the other hand, potential of optical sensors aboard meteorological satellites, was not yet fully exploited and no reliable techniques have been developed until now for this purpose. Main limit of proposed techniques can be found in the ``fixed threshold'' approach which makes such techniques difficult to implement without operator supervision and, generally, without an independent information on the oil spill presence that could drive the choice of the best threshold. A different methodological approach (RAT, Robust AVHRR Techniques) proposed by Tramutoli (1998) and already successfully applied to several natural and environmental emergencies related to volcanic eruptions, forest fires and seismic activity. In this paper its extension to near real-time detection and monitoring of oil spills by means of NOAA-AVHRR (Advanced Very High Resolution Radiometer) records will be described. Briefly, RAT approach is an automatic change-detection scheme that considers a satellite image as a space-time process, described at each place (x,y) and time t, by the value of the satellite derived measurements V(x,y,t). Generally speaking an Absolute Local Index of Change of the Environment (ALICE) is computed and this index permits to identify signal anomalies, in the space-time domain, as deviations from a normal state preliminarily defined, for each image pixel, (e.g. in terms of time average and standard deviation) on the base only of satellite observations collected during several year in the past, in similar observational conditions (same time of the day, same month of the year). By this way local (i.e. specific for the place and the time of observation) instead than fixed thresholds are automatically set by RAT which permit to discriminate signal anomalies from those variations due to natural or observational condition variability. Using AVHRR observations in the Thermal (TIR) and Middle (MIR) Infrared region, such an approach has been applied to the extended oil spill event, occurred at the end of January 1991 in the Persian Gulf. Preliminary results will be analysed that confirm as the suggested technique is able to detect and monitoring oil spills also in the most difficult observational conditions. Automatic implementation, intrinsic exportability on whatever geographic zone and/or satellite package, high sensitivity also to low intensity signals (i.e. small or thin spills), no need for ancillary information (different form satellite data at hand), seem the most promising merits of the proposed technique. Although these results should be confirmed by further analyses on different events and extended also to other AVHRR spectral bands (VIS, NIR), this work surely encourages to continue the research in this field. Moreover, the complete independence of the RAT approach on the specific sensor and/or satellite system, will ensure its full exportability on the new generation of Earth observation satellite sensors (e.g. SEVIRI-Spinning Enhanced Visible and Infrared Imager onboard Meteosat Second generation satellite, with a repetition rate of 15 minutes and 12 spectral bands) which, thanks to their improved capabilities, could actually guarantee timely, reliable and accurate information.

Long-term changes in the Northwestern Atlantic and Mediterranean SST from 1982 to 2016: A contribution of the Operational Oceanography to the determination of the present day Climate

NASA Astrophysics Data System (ADS)

Artale, Vincenzo; Buongiorno Nardelli, Bruno; Marullo, Salvatore; Pisano, Andrea; Santoleri, Rosalia; Tronconi, Cristina

2017-04-01

Estimating long-term SST changes is crucial to evaluate global warming impact at regional scales. Here, we analyze the Mediterranean (MED) and the Northwestern Atlantic Box (NWA) SST changes over the last 34 years (1982 - 2016) by combining reprocessed (REP) and near-real-time (NRT) data. Actually, the Italian National Research Council (CNR) has recently produced daily (nighttime), 4 km resolution REP MED level 4 datasets (REP L4), also covering the adjacent Atlantic region, based on the latest Pathfinder v5.2 AVHRR dataset (1982-2012). These data represent the longest satellite MED SST L4 time series and are freely distributed through the European Copernicus Marine Environment Monitoring Service (CMEMS). However, as Pathfinder has not yet released an update of its product, the REP data end in 2012. To fill in the gap between 2013 and 2016, we investigated the possibility to extend the time series by using the Mediterranean near real time (NRT), multi-sensor L4 SST data at Ultra-High spatial Resolution (UHR) produced by CNR, which are distributed through CMEMS and now mirrored at GHRSST. Since this product is available since 2008, the consistency with the REP has been assessed. Combining the REP L4 data (1982-2012) and a bias-corrected version of the NRT L4 data (2013-2016), we built the SST time series and provided updated estimates of the MED and NWA SST trends. The analysis shows that The Atlantic Box and The Mediterranean Sea have similar trend behavior until 2008. Afterward the Mediterranean Sea SST continued to increase while the Atlantic Box persisted in its warming pause.

OCEANIDS: Autonomous Data Acquisition, Management and Distribution System

NASA Technical Reports Server (NTRS)

Bingham, Andrew; Rigor, Eric; Cervantes, Alex; Armstrong, Edward

2004-01-01

OCEANIDS is a clearinghouse for mission essential and near-real-time satellite data streams. This viewgraph presentation describes this mission, and includes the following topics: 1) OCEANIDS Motivation; 2) High-Level Architecture; 3) OCEANIDS Features; 4) OCEANIDS GUI: Nodes; 5) OCEANIDS GUI: Cluster; 6) Data Streams; 7) Statistics; and 8) GHRSST-PP.

The MyOcean Thematic Assembly Centres: Satellite and In-situ Observation Services in Review

NASA Astrophysics Data System (ADS)

Hackett, Bruce; Breivik, Lars-Anders; Larnicol, Gilles; Pouliquen, Sylvie; Santoleri, Rosalia; Roquet, Hervé; Stoffelen, Ad

2015-04-01

The MyOcean (2009-2012), MyOcean2 (2012-2014) and MyOcean Follow-On (October 2014 - March 2015) projects, respectively funded by the EU's 7th Framework Programme for Research (FP7 2007-2013) and HORIZON 2020 (EU Research and Innovation programme 2014-2020), have been designed to prepare and to lead the demonstration phases of the nascent European Copernicus Marine Environment Monitoring Service (CMS). The observational component of the MyOcean services is embodied in four Thematic Assembly Centres (TACs): Three provide satellite-based products for sea level (SL-TAC), for ocean colour (OC-TAC) and for surface temperature, winds and sea ice (OSI-TAC), while the fourth provides in-situ observations (INS-TAC). All the TAC production is developed from existing capabilities and there is close collaboration with related national and European data providers. Data products include near-real-time data and multi-year reprocessed datasets. Data formatting, dissemination methods and documentation follow uniform MyOcean standards for ease of use. The presentation will track the evolution of the TAC services through the MyOcean projects up to the opening of the CMS.

Proposal to evaluate the use of ERTS-1 imagery in mapping and managing soil and range resources in the Sand Hills region of Nebraska

NASA Technical Reports Server (NTRS)

Drew, J. V. (Principal Investigator)

1974-01-01

The author has identified the following significant results. Increase in radiance values is directly related to decrease in vegetative biomass, though not in a linear manner. Should the relationship hold true over an entire growing season, this would allow an extremely rapid evaluation of range condition. Computer access by remote terminal would allow production of this type of range condition evaluation in near real time, which is essential if grazing practice decisions are to be made based on satellite imagery acquisition. Negating the manipulation of photographic products appears to be the logical way to provide satellite imagery data to the user in near real time. There appears to be a direct linear relationship between radiance values of bands 4 and 5 and increase in total inorganic ions (6 ions) of lakes in the Sand hills region. Consistent ion concentration of lakes during the year could allow their radiance values to serve as a means of equating radiance values from image to image.

Remote-Sensing and Automated Water Resources Tracking: Near Real-Time Decision Support for Water Managers Facing Drought and Flood

NASA Astrophysics Data System (ADS)

Reiter, M. E.; Elliott, N.; Veloz, S.; Love, F.; Moody, D.; Hickey, C.; Fitzgibbon, M.; Reynolds, M.; Esralew, R.

2016-12-01

Innovative approaches for tracking the Earth's natural resources, especially water which is essential for all living things, are essential during a time of rapid environmental change. The Central Valley is a nexus for water resources in California, draining the Sacramento and San Joaquin River watersheds. The distribution of water throughout California and the Central Valley, while dynamic, is highly managed through an extensive regional network of canals, levees, and pumps. Water allocation and delivery is determined through a complex set of rules based on water contracts, historic priority, and other California water policies. Furthermore, urban centers, agriculture, and the environment throughout the state are already competing for water, particularly during drought. Competition for water is likely to intensify as California is projected to experience continued increases in demand due to population growth and more arid growing conditions, while also having reduced or modified water supply due to climate change. As a result, it is difficult to understand or predict how water will be used to fulfill wildlife and wetland conservation needs. A better understanding of the spatial distribution of water in near real-time can facilitate adaptation of water resource management to changing conditions on the landscape, both over the near- and long-term. The Landsat satellite mission delivers imagery every 16-days from nearly every place on the earth at a high spatial resolution. We have integrated remote sensing of satellite data, classification modeling, bioinformatics, optimization, and ecological analyses to develop an automated near real-time water resources tracking and decision-support system for the Central Valley of California. Our innovative system has applications for coordinated water management in the Central Valley to support people, places, and wildlife and is being used to understand the factors that drive variation in the distribution and abundance of water resources, particularly drought and flood, at multiple spatial and temporal scales.

PAU/GNSS-R: Implementation, Performance and First Results of a Real-Time Delay-Doppler Map Reflectometer Using Global Navigation Satellite System Signals

PubMed Central

Marchan-Hernandez, Juan Fernando; Camps, Adriano; Rodriguez-Alvarez, Nereida; Bosch-Lluis, Xavier; Ramos-Perez, Isaac; Valencia, Enric

2008-01-01

Signals from Global Navigation Satellite Systems (GNSS) were originally conceived for position and speed determination, but they can be used as signals of opportunity as well. The reflection process over a given surface modifies the properties of the scattered signal, and therefore, by processing the reflected signal, relevant geophysical data regarding the surface under study (land, sea, ice…) can be retrieved. In essence, a GNSS-R receiver is a multi-channel GNSS receiver that computes the received power from a given satellite at a number of different delay and Doppler bins of the incoming signal. The first approaches to build such a receiver consisted of sampling and storing the scattered signal for later post-processing. However, a real-time approach to the problem is desirable to obtain immediately useful geophysical variables and reduce the amount of data. The use of FPGA technology makes this possible, while at the same time the system can be easily reconfigured. The signal tracking and processing constraints made necessary to fully design several new blocks. The uniqueness of the implemented system described in this work is the capability to compute in real-time Delay-Doppler maps (DDMs) either for four simultaneous satellites or just one, but with a larger number of bins. The first tests have been conducted from a cliff over the sea and demonstrate the successful performance of the instrument to compute DDMs in real-time from the measured reflected GNSS/R signals. The processing of these measurements shall yield quantitative relationships between the sea state (mainly driven by the surface wind and the swell) and the overall DDM shape. The ultimate goal is to use the DDM shape to correct the sea state influence on the L-band brightness temperature to improve the retrieval of the sea surface salinity (SSS). PMID:27879862

A Real-Time California Coastal Ocean Nowcast/Forecast System: Skill Assessment, User Products, and Transition from Research to Operations

NASA Astrophysics Data System (ADS)

Farrara, J. D.; Chao, Y.; Chai, F.; Zhang, H.

2016-02-01

The real-time California coastal ocean nowcast/forecast system is described. The model is based on the Regional Ocean Modeling System (ROMS) and covers the entire California coastal ocean with a horizontal resolution of 3 km and 40 vertical layers. The atmospheric forcing is derived from the operational regional atmospheric model forecasts. The lateral boundary conditions are provided by the operational ocean model forecasts. A multi-scale 3-dimensional variational (3DVAR) data assimilation scheme is used to assimilate both in situ (e.g., vertical profiles of temperature and salinity) and remotely sensed data from both satellite (e.g., sea surface temperature and sea surface height) and land-based platforms (e.g., surface current). The performance of our nowcast/forecast system is evaluated in real-time by a number of metrics that are published as soon as they become available. User tools and products have been developed for both general users and super-users (e.g., NOAA Office of Response and Restoration and USCG). Recent results comparing the 3DVAR with the ensemble Kalman Filter (EnKF) using Data Assimilation Research Testbed (DART) will be presented. Preliminary results coupling the ROMS circulation model with a biogeochemistry/ecosystem model (i.e., CoSiNE) will also discussed. Cloud computing services (e.g., Microsoft, Google) are now being tested to increase the reliability and timeliness in order to be accepted as a truly operational system in the near future.

Estimation of corn yield using multi-temporal optical and radar satellite data and artificial neural networks

NASA Astrophysics Data System (ADS)

Fieuzal, R.; Marais Sicre, C.; Baup, F.

2017-05-01

The yield forecasting of corn constitutes a key issue in agricultural management, particularly in the context of demographic pressure and climate change. This study presents two methods to estimate yields using artificial neural networks: a diagnostic approach based on all the satellite data acquired throughout the agricultural season, and a real-time approach, where estimates are updated after each image was acquired in the microwave and optical domains (Formosat-2, Spot-4/5, TerraSAR-X, and Radarsat-2) throughout the crop cycle. The results are based on the Multispectral Crop Monitoring experimental campaign conducted by the CESBIO (Centre d'Études de la BIOsphère) laboratory in 2010 over an agricultural region in southwestern France. Among the tested sensor configurations (multi-frequency, multi-polarization or multi-source data), the best yield estimation performance (using the diagnostic approach) is obtained with reflectance acquired in the red wavelength region, with a coefficient of determination of 0.77 and an RMSE of 6.6 q ha-1. In the real-time approach the combination of red reflectance and CHH backscattering coefficients provides the best compromise between the accuracy and earliness of the yield estimate (more than 3 months before the harvest), with an R2 of 0.69 and an RMSE of 7.0 q ha-1 during the development of the central stem. The two best yield estimates are similar in most cases (for more than 80% of the monitored fields), and the differences are related to discrepancies in the crop growth cycle and/or the consequences of pests.

Numerical simulations of tropical cyclones with assimilation of satellite, radar and in-situ observations: lessons learned from recent field programs and real-time experimental forecasts

NASA Astrophysics Data System (ADS)

Pu, Z.; Zhang, L.

2010-12-01

The impact of data assimilation on the predictability of tropical cyclones is examined with the cases from recent field programs and real-time hurricane forecast experiments. Mesoscale numerical simulations are performed to simulate major typhoons during the T-PARC/TCS08 field campaign with the assimilation of satellite, radar and in-situ observations. Results confirmed that data assimilation has indeed resulted in improved numerical simulations of tropical cyclones. However, positive impacts from the satellite and radar data are strongly depend on the quality of these data. Specifically, it is found that the overall impacts of assimilating AIRS retrieved atmospheric temperature and moisture profiles on numerical simulations of tropical cyclones are very sensitive to the bias corrections of the data.For instance, the dry biases of moisture profiles can cause the decay of tropical cyclones in the numerical simulations.In addition, the quality of airborne Doppler radar data has strong influence on numerical simulations of tropical cyclones in terms of their track, intensity and precipitation structures. Outcomes from assimilating radar data with various quality thresholds suggest that a trade-off between the quality and area coverage of the radar data is necessary in the practice. Some of those experiences obtained from the field case studies are applied to the near-real time experimental hurricane forecasts during the 2010 hurricane season. Results and issues raised from the case studies and real-time experiments will be discussed.

Monitoring volcanic thermal activity by Robust Satellite Techniques: achievements and perspectives

NASA Astrophysics Data System (ADS)

Tramutoli, V.; Marchese, F.; Mazzeo, G.; Pergola, N.

2009-12-01

Satellite data have been increasingly used in last decades to study active volcanoes and to monitor thermal activity variation in space-time domain. Several satellite techniques and original methods have been developed and tested, devoted to hotspot detection and thermal monitoring. Among them, a multi-temporal approach, named RST (Robust Satellite Techniques), has shown high performances in detecting hotspots, with a low false positive rate under different observational and atmospheric conditions, providing also a potential toward low-level thermal anomalies which may announce incoming eruptions. As the RST scheme is intrinsically exportable on different geographic areas and satellite sensors, it has been applied and tested on a number of volcanoes and in different environmental conditions. This work presents major results and outcomes of studies carried out on Etna and Stromboli (Italy), Merapi (Java Indonesia), Asamayama (Japan), Jebel Al Tair (Yemen) by using different satellite systems and sensors (e.g. NOAA-AVHRR, EOS-MODIS, MSG-SEVIRI). Performances on hotspot detection, early warning and real-time monitoring, together with capabilities in possible thermal precursor identification, will be presented and discussed.

A Physical Validation Program for the GPM Mission

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2003-01-01

The GPM mission is currently planned for start in the late 2007 - early 2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycling. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. A major requirement before the retrieved rainfall information generated by the GPM mission can be used effectively by prognostic models to improve weather forecasts, hydrometeorological forecasts, and climate model reanalysis simulations is a capability to quantify the error characteristics of the retrievals. A solution for this problem has been upheld in past precipitation missions because of the lack of suitable error modeling systems incorporated into the validation programs and data distribution systems. An overview of how NASA intends to overcome this problem for the GPM mission using a physically-based error modeling approach within a multi-faceted validation program is described. The solution is to first identify specific user requirements and then determine the most stringent of these requirements that embodies all essential error characterization information needed by the entire user community. In the context of NASA s scientific agenda for the GPM mission, the most stringent user requirement is found within the data assimilation community. The fundamental theory of data assimilation vis-a-vis ingesting satellite precipitation information into the pre-forecast initializations is based on quantifying the conditional bias and precision errors of individual rain retrievals, and the space-time structure of the precision error (i.e., the spatial-temporal error covariance). By generating the hardware and software capability to produce this information in a near real-time fashion, and to couple the derived quantitative error properties to the actual retrieved rainrates, all key validation users can be satisfied. The talk will describe the essential components of the hardware and software systems needed to generate such near real-time error properties, as well as the various paradigm shifts needed within the validation community to produce a validation program relevant to the precipitation user community.

The use of remotely sensed data for operational fisheries oceanography

NASA Technical Reports Server (NTRS)

Fiuza, Armando F. G.

1992-01-01

Satellite remote sensing data are used under two contexts in fisheries: as a tool for fisheries research and as a means to provide operational support to fishing activities. Fishing operations need synoptic data provided timely; fisheries research needs that type of data and, also, good short-term climatologies. A description is given of several experiences conducted around the world which have employed or are using satellite data for operational fisheries problems. An overview is included of the Portuguese program for fisheries support using remotely sensed data provided by satellites and in situ observations conducted by fishermen. Environmental products useful for fisheries necessarily combine satellite and in situ data. The role of fishermen as a source of good, near-real-time in situ environmental data is stressed; so far, this role seems to have been largely overlooked.

Introducing Real-Time AVHRR-APT Satellite Imagery in the Classroom Environment

ERIC Educational Resources Information Center

Moxey, Lucas; Tucker, Compton; Sloan, Jim; Chadwick, John

2004-01-01

A low-cost (US$350) satellite receiving station was assembled and operated within a classroom environment in Gainesville (Florida) on October 2001 for acquiring satellite data directly from the Advanced Very High Resolution Radiometer (AVHRR) satellites. The simplicity of the satellite signal makes this source of real-time satellite data readily…

Predictive Habitat Use of California Sea Lions and Its Implications for Fisheries Management

NASA Astrophysics Data System (ADS)

Briscoe, D.

2016-02-01

Advancements in satellite telemetry and remotely-sensed oceanography have shown that species and the environment they utilize are highly dynamic in space and time. However, biophysical features often overlap with human use. For this reason, spatially-explicit management approaches may only provide a snapshot of protection for a highly mobile species throughout its range. As a migratory species, California sea lions (Zalophus californianus) utilize dynamic oceanographic features that overlap with the California swordfish fishery, and are subject to incidental catch. The development of near-real time tools can assist in management efforts to mitigate against human impacts, such as fisheries interactions and dynamic marine species. Here, we combine near-real time remotely-sensed satellite oceanography, animal tracking data, and Generalized Additive Mixed Models (GAMMs) to: a) determine suitable habitat for 75 female California sea lions throughout their range, b) forecast when and where these non-target interactions are likely to occur, and c) validate these models with observed data of such interactions. Model results can be used to provide resource management that are highly responsive to the movement of managed species, ocean users, and underlying ocean features.

Predictive Habitat Use of California Sea Lions and Its Implications for Fisheries Management

NASA Astrophysics Data System (ADS)

Briscoe, D.

2016-12-01

Advancements in satellite telemetry and remotely-sensed oceanography have shown that species and the environment they utilize are highly dynamic in space and time. However, biophysical features often overlap with human use. For this reason, spatially-explicit management approaches may only provide a snapshot of protection for a highly mobile species throughout its range. As a migratory species, California sea lions (Zalophus californianus) utilize dynamic oceanographic features that overlap with the California swordfish fishery, and are subject to incidental catch. The development of near-real time tools can assist in management efforts to mitigate against human impacts, such as fisheries interactions and dynamic marine species. Here, we combine near-real time remotely-sensed satellite oceanography, animal tracking data, and Generalized Additive Mixed Models (GAMMs) to: a) determine suitable habitat for 75 female California sea lions throughout their range, b) forecast when and where these non-target interactions are likely to occur, and c) validate these models with observed data of such interactions. Model results can be used to provide resource management that are highly responsive to the movement of managed species, ocean users, and underlying ocean features.

Timely detection and monitoring of oil leakage by satellite optical data.

NASA Astrophysics Data System (ADS)

Grimaldi, C. S. L.; Coviello, I.; Lacava, T.; Pergola, N.; Tramutoli, V.

2009-04-01

Sea oil pollution can derive from different sources. Accidental release of oil into the oceans caused by "human errors" (tankers collisions and/or shipwrecks) or natural hazards (hurricanes, landslides, earthquakes) have remarkable ecological impact on maritime and coastal environments. Katrina Hurricane, for example, hitting oil and gas infrastructures off USA coasts caused the destruction of more than 100 platforms and the release into the sea of more than 10,000 gallons of crude oil. In order to reduce the environmental impact of such kind of technological hazards, timely detection and continuously updated information are fundamental. Satellite remote sensing can give a significant contribution in such a direction. Nowadays, SAR (Synthetic Aperture Radar) technology has been recognized as the most efficient for oil spill detection and mapping, thanks to the high spatial resolution and all-time/weather capability of the present operational sensors. Anyway, due to their current revisiting cycles, SAR systems cannot be profitably used for a rapid detection and for a continuous and near real-time monitoring of these phenomena. Until COSMO-Skymed SAR constellation, that will be able to improve SAR observational frequency, will not be fully operational, passive optical sensors on board meteorological satellites, thanks to their high temporal resolution, may represent a suitable alternative for early detection and continuous monitoring of oil spills, provided that adequate and reliable data analysis techniques exist. Recently, an innovative technique for oil spill detection and monitoring, based on the general Robust Satellite Techniques (RST) approach, has been proposed. It exploits the multi-temporal analysis of optical data acquired by both AVHRR (Advanced Very High Resolution Radiometer) and MODIS (Moderate Resolution Imaging Spectroradiometer) sensors in order to detect, automatically and timely, the presence of oil spill over the sea surface, trying to minimize the "false-detections" possibly caused by spurious effects (e.g. clouds). In this paper, preliminary results obtained applying the proposed methodology to different test-cases are shown and discussed.

Near-real-time TOMS, telecommunications and meteorological support for the 1987 Airborne Antarctic Ozone Experiment

NASA Technical Reports Server (NTRS)

Ardanuy, P.; Victorine, J.; Sechrist, F.; Feiner, A.; Penn, L.

1988-01-01

The goal of the 1987 Airborne Antarctic Ozone Experiment was to improve the understanding of the mechanisms involved in the formation of the Antarctic ozone hole. Total ozone data taken by the Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) played a central role in the successful outcome of the experiment. During the experiment, the near-real-time TOMS total ozone observations were supplied within hours of real time to the operations center in Punta Arenas, Chile. The final report summarizes the role which Research and Data Systems (RDS) Corporation played in the support of the experiment. The RDS provided telecommunications to support the science and operations efforts for the Airborne Antarctic Ozone Experiment, and supplied near real-time weather information to ensure flight and crew safety; designed and installed the telecommunications network to link NASA-GSFC, the United Kingdom Meteorological Office (UKMO), Palmer Station, the European Center for Medium-Range Weather Forecasts (ECMWF) to the operation at Punta Arenas; engineered and installed stations and other stand-alone systems to collect data from designated low-orbiting polar satellites and beacons; provided analyses of Nimbus-7 TOMS data and backup data products to Punta Arenas; and provided synoptic meteorological data analysis and reduction.

Scheduling algorithm for data relay satellite optical communication based on artificial intelligent optimization

NASA Astrophysics Data System (ADS)

Zhao, Wei-hu; Zhao, Jing; Zhao, Shang-hong; Li, Yong-jun; Wang, Xiang; Dong, Yi; Dong, Chen

2013-08-01

Optical satellite communication with the advantages of broadband, large capacity and low power consuming broke the bottleneck of the traditional microwave satellite communication. The formation of the Space-based Information System with the technology of high performance optical inter-satellite communication and the realization of global seamless coverage and mobile terminal accessing are the necessary trend of the development of optical satellite communication. Considering the resources, missions and restraints of Data Relay Satellite Optical Communication System, a model of optical communication resources scheduling is established and a scheduling algorithm based on artificial intelligent optimization is put forwarded. According to the multi-relay-satellite, multi-user-satellite, multi-optical-antenna and multi-mission with several priority weights, the resources are scheduled reasonable by the operation: "Ascertain Current Mission Scheduling Time" and "Refresh Latter Mission Time-Window". The priority weight is considered as the parameter of the fitness function and the scheduling project is optimized by the Genetic Algorithm. The simulation scenarios including 3 relay satellites with 6 optical antennas, 12 user satellites and 30 missions, the simulation result reveals that the algorithm obtain satisfactory results in both efficiency and performance and resources scheduling model and the optimization algorithm are suitable in multi-relay-satellite, multi-user-satellite, and multi-optical-antenna recourses scheduling problem.

Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method

PubMed Central

Zhong, Xinke; Huo, Xing; Ren, Chao; Labed, Jelila; Li, Zhao-Liang

2016-01-01

Land Surface Temperature (LST) is a key parameter in climate systems. The methods for retrieving LST from hyperspectral thermal infrared data either require accurate atmospheric profile data or require thousands of continuous channels. We aim to retrieve LST for natural land surfaces from hyperspectral thermal infrared data using an adapted multi-channel method taking Land Surface Emissivity (LSE) properly into consideration. In the adapted method, LST can be retrieved by a linear function of 36 brightness temperatures at Top of Atmosphere (TOA) using channels where LSE has high values. We evaluated the adapted method using simulation data at nadir and satellite data near nadir. The Root Mean Square Error (RMSE) of the LST retrieved from the simulation data is 0.90 K. Compared with an LST product from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat, the error in the LST retrieved from the Infared Atmospheric Sounding Interferometer (IASI) is approximately 1.6 K. The adapted method can be used for the near-real-time production of an LST product and to provide the physical method to simultaneously retrieve atmospheric profiles, LST, and LSE with a first-guess LST value. The limitations of the adapted method are that it requires the minimum LSE in the spectral interval of 800–950 cm−1 larger than 0.95 and it has not been extended for off-nadir measurements. PMID:27187408

Real-Time Detection of Tsunami Ionospheric Disturbances with a Stand-Alone GNSS Receiver: An Integration of GPS and Galileo Systems

NASA Astrophysics Data System (ADS)

Savastano, Giorgio; Komjathy, Attila; Verkhoglyadova, Olga; Wei, Yong; Mazzoni, Augusto; Crespi, Mattia

2017-04-01

Tsunamis can produce gravity waves that propagate up to the ionosphere generating disturbed electron densities in the E and F regions. These ionospheric disturbances are studied in detail using ionospheric total electron content (TEC) measurements collected by continuously operating ground-based receivers from the Global Navigation Satellite Systems (GNSS). Here, we present results using a new approach, named VARION (Variometric Approach for Real-Time Ionosphere Observation), and for the first time, we estimate slant TEC (sTEC) variations in a real-time scenario from GPS and Galileo constellations. Specifically, we study the 2016 New Zealand tsunami event using GNSS receivers with multi-constellation tracking capabilities located in the Pacific region. We compare sTEC estimates obtained using GPS and Galileo constellations. The efficiency of the real-time sTEC estimation using the VARION algorithm has been demonstrated for the 2012 Haida Gwaii tsunami event. TEC variations induced by the tsunami event are computed using 56 GPS receivers in Hawai'i. We observe TEC perturbations with amplitudes up to 0.25 TEC units and traveling ionospheric disturbances moving away from the epicenter at a speed of about 316 m/s. We present comparisons with the real-time tsunami model MOST (Method of Splitting Tsunami) provided by the NOAA Center for Tsunami Research. We observe variations in TEC that correlate well in time and space with the propagating tsunami waves. We conclude that the integration of different satellite constellations is a crucial step forward to increasing the reliability of real-time tsunami detection systems using ground-based GNSS receivers as an augmentation to existing tsunami early warning systems.

Near real-time monitoring of UT1 with geodetic VLBI

NASA Astrophysics Data System (ADS)

Haas, R.; Hobiger, T.; Sekido, M.; Koyama, Y.; Kondo, T.; Takiguchi, H.; Kurihara, S.; Kokado, K.; Tanimoto, D.; Nozawa, K.; Wagner, J.; Ritakari, J.; Mujunen, A.; Uunila, M.

2011-07-01

Geodetic VLBI is unique among the geodetic space techniques since it provides a direct connection between the international terrestrial reference frame and the international celestial reference frame. The Earth rotation angle, usually expressed as UT1, can be determined directly from geodetic VLBI observations. Accurate information about the Earth rotation angle is necessary and important for navigation purposes, in particular for satellite missions and space navigation. A near real-time knowledge of UT1 with high accuracy is therefore highly desirable. During the last few years the advances in data transfer over high-speed optical fibre lines have made it possible to electronically send the observational data from a VLBI radio telescope on one side of the globe in real-time to a VLBI correlator on the other side of the globe. Thus, data of two telescopes on opposite sides of the Earth, forming a long east-west oriented baseline, can be correlated in near real-time. Furthermore, advances in automated processing of the correlation results have made it possible to derive the Earth rotation angle UT1 in near real-time. Since 2007, the VLBI research groups in Sweden, Finland and Japan collaborate to derive UT1 in near real-time. Several dedicated so-called ultra-rapid UT1-sessions with 1-2 hours duration were performed. It was shown that final UT1-results can be derived within a few minutes after the end of an observing session (Sekido et al., 2008; Matsuzaka et al., 2008). The quality of the UT1-results is on the same level as the so-called IERS rapid solutions, but with a much lower latency (Haas et al., 2010). Recently, the ultra-rapid approach has been applied to standard 24 hour long VLBI observing sessions that are organized by the International VLBI Service for Geodesy and Astrometry (IVS). The long east-west baseline between Onsala (Sweden) and Tsukuba (Japan) is used to derive UT1 with a sliding window approach already during the ongoing IVS-session. The data processing and analysis is performed with a fully automated analysis software (Hobiger et al., 2010). We present results from the ultra-rapid UT1-sessions, both, from dedicated one-baseline sessions, as well from 24-hour ultra-rapid sessions during standard IVS-experiments. The near real-time UT1 results are compared to corresponding post-processing results, and results from independent analyses and techniques. Refrences: Sekido et al. (2008) Ultra-rapid UT1 measurements by e-VLBI, Earth Planets and Space, Vol. 60, 865-870. Matsuzaka et al. (2008) Ultra Rapid UT1 Experiment with e-VLBI, In: Proc. 5th IVS General Meeting, 68-71. Haas R et al. (2010) Ultra-Rapid DUT1-Observations with E-VLBI. Artificial Satellites, 45, 75-79. Hobiger et al. (2010) Fully automated VLBI analysis with c5++ for ultra-rapid determination of UT1, Earth Planets Space.

COLUMBUS as Engineering Testbed for Communications and Multimedia Equipment

NASA Astrophysics Data System (ADS)

Bank, C.; Anspach von Broecker, G. O.; Kolloge, H.-G.; Richters, M.; Rauer, D.; Urban, G.; Canovai, G.; Oesterle, E.

2002-01-01

The paper presents ongoing activities to prepare COLUMBUS for communications and multimedia technology experiments. For this purpose, Astrium SI, Bremen, has studied several options how to best combine the given system architecture with flexible and state-of-the-art interface avionics and software. These activities have been conducted in coordination with, and partially under contract of, DLR and ESA/ESTEC. Moreover, Astrium SI has realized three testbeds for multimedia software and hardware testing under own funding. The experimental core avionics unit - about a half double rack - establishes the core of a new multi-user experiment facility for this type of investigation onboard COLUMBUS, which shall be available to all users of COLUMBUS. It allows for the connection of 2nd generation payload, that is payload requiring broadband data transfer and near-real-time access by the Principal Investigator on ground, to test highly interactive and near-realtime payload operation. The facility is also foreseen to test new equipment to provide the astronauts onboard the ISS/COLUMBUS with bi- directional hi-fi voice and video connectivity to ground, private voice coms and e-mail, and a multimedia workstation for ops training and recreation. Connection to an appropriate Wide Area Network (WAN) on Earth is possible. The facility will include a broadband data transmission front-end terminal, which is mounted externally on the COLUMBUS module. This Equipment provides high flexibility due to the complete transparent transmit and receive chains, the steerable multi-frequency antenna system and its own thermal and power control and distribution. The Equipment is monitored and controlled via the COLUMBUS internal facility. It combines several new hardware items, which are newly developed for the next generation of broadband communication satellites and operates in Ka -Band with the experimental ESA data relay satellite ARTEMIS. The equipment is also TDRSS compatible; the open loop antenna tracking system employing star sensors enables usability with any other GEO data relay satellite system. In order to be prepared for the upcoming telecom standards for ground distribution of spacecraft generated data, the interface avionics allows for testing ATM-based data formatting and routing. Three testbeds accompany these studies and designs: i)a cable-and-connector testbed measures the signal characteristics for data transfer of up to 200 Mbps through the ii)an avionics &embedded software testbed prepares for data formatting, routing, and storage in CCSDS and ATM; iii)a software testbed tests newly developed S/W man-machine interfaces and simulates bandwidth limitations, on- This makes COLUMBUS a true technology testbed for a variety of engineering topics: - application of terrestrial standard data formats for broadband, near-real-time applications in space - qualification &test of off-the-shelf multimedia equipment in manned spacecraft - secure data transmission in flexible VPNs - in-orbit demonstration of advanced data transmission technology - elaboration of efficient crew and ground operations and training procedures - evaluation of personalized displays (S/W HFI) for long-duration space missions

Automatic analysis of stereoscopic satellite image pairs for determination of cloud-top height and structure

NASA Technical Reports Server (NTRS)

Hasler, A. F.; Strong, J.; Woodward, R. H.; Pierce, H.

1991-01-01

Results are presented on an automatic stereo analysis of cloud-top heights from nearly simultaneous satellite image pairs from the GOES and NOAA satellites, using a massively parallel processor computer. Comparisons of computer-derived height fields and manually analyzed fields show that the automatic analysis technique shows promise for performing routine stereo analysis in a real-time environment, providing a useful forecasting tool by augmenting observational data sets of severe thunderstorms and hurricanes. Simulations using synthetic stereo data show that it is possible to automatically resolve small-scale features such as 4000-m-diam clouds to about 1500 m in the vertical.

A Multi-Baseline 12 GHz Atmospheric Phase Interferometer with One Micron Path Length Sensitivity

NASA Astrophysics Data System (ADS)

Kimberk, Robert S.; Hunter, Todd R.; Leiker, Patrick S.; Blundell, Raymond; Nystrom, George U.; Petitpas, Glen R.; Test, John; Wilson, Robert W.; Yamaguchi, Paul; Young, Kenneth H.

2012-12-01

We have constructed a five station 12 GHz atmospheric phase interferometer (API) for the Submillimeter Array (SMA) located near the summit of Mauna Kea, Hawaii. Operating at the base of unoccupied SMA antenna pads, each station employs a commercial low noise mixing block coupled to a 0.7 m off-axis satellite dish which receives a broadband, white noise-like signal from a geostationary satellite. The signals are processed by an analog correlator to produce the phase delays between all pairs of stations with projected baselines ranging from 33-261 m. Each baseline's amplitude and phase is measured continuously at a rate of 8 kHz, processed, averaged and output at 10 Hz. Further signal processing and data reduction is accomplished with a Linux computer, including the removal of the diurnal motion of the target satellite. The placement of the stations below ground level with an environmental shield combined with the use of low temperature coefficient, buried fiber optic cables provides excellent system stability. The sensitivity in terms of rms path length is 1.3 microns which corresponds to phase deviations of about 1° of phase at the highest operating frequency of the SMA. The two primary data products are: (1) standard deviations of observed phase over various time scales, and (2) phase structure functions. These real-time statistical data measured by the API in the direction of the satellite provide an estimate of the phase front distortion experienced by the concurrent SMA astronomical observations. The API data also play an important role, along with the local opacity measurements and weather predictions, in helping to plan the scheduling of science observations on the telescope.

Multi-Decadal Variation of Aerosols: Sources, Transport, and Climate Effects

NASA Technical Reports Server (NTRS)

Chin, Mian; Diehl, Thomas; Bian, Huisheng; Streets, David

2008-01-01

We present a global model study of multi-decadal changes of atmospheric aerosols and their climate effects using a global chemistry transport model along with the near-term to longterm data records. We focus on a 27-year time period of satellite era from 1980 to 2006, during which a suite of aerosol data from satellite observations, ground-based measurements, and intensive field experiments have become available. We will use the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, which involves a time-varying, comprehensive global emission dataset that we put together in our previous investigations and will be improved/extended in this project. This global emission dataset includes emissions of aerosols and their precursors from fuel combustion, biomass burning, volcanic eruptions, and other sources from 1980 to the present. Using the model and satellite data, we will analyze (1) the long-term global and regional aerosol trends and their relationship to the changes of aerosol and precursor emissions from anthropogenic and natural sources, (2) the intercontinental source-receptor relationships controlled by emission, transport pathway, and climate variability.

Data Latency Characteristics Observed Through Diverse Communication Links by the EarthScope USArray Transportable Array

NASA Astrophysics Data System (ADS)

Vernon, F. L.; Eakins, J. A.; Busby, R.

2008-12-01

The USArray Transportable Array has deployed over 600 stations in aggregate over the past four years. All stations communicate in near-real time using ip protocols over a variety of communication links including satellite, cell phone, and DSL. Several different communication providers have been used for each type of communication links. In addition, data are being acquired from several regional networks either directly from a data server or after passing through the IRIS DMC BUD system. We will present results about the latency of data arriving at the UCSD Array Network Facility where the real time data are acquired. Under normal operating conditions the median data latency is several seconds. We will also examine the data return rates through the near-real time systems. In addition we will examine the statistics of over 36,000 events which have automatic event locations and associations. We evaluate the timeliness of these results in the context of seismic early warning systems.

A MODIS-based automated flood monitoring system for southeast asia

NASA Astrophysics Data System (ADS)

Ahamed, A.; Bolten, J. D.

2017-09-01

Flood disasters in Southeast Asia result in significant loss of life and economic damage. Remote sensing information systems designed to spatially and temporally monitor floods can help governments and international agencies formulate effective disaster response strategies during a flood and ultimately alleviate impacts to population, infrastructure, and agriculture. Recent destructive flood events in the Lower Mekong River Basin occurred in 2000, 2011, 2013, and 2016 (http://ffw.mrcmekong.org/historical_rec.htm, April 24, 2017). The large spatial distribution of flooded areas and lack of proper gauge data in the region makes accurate monitoring and assessment of impacts of floods difficult. Here, we discuss the utility of applying satellite-based Earth observations for improving flood inundation monitoring over the flood-prone Lower Mekong River Basin. We present a methodology for determining near real-time surface water extent associated with current and historic flood events by training surface water classifiers from 8-day, 250-m Moderate-resolution Imaging Spectroradiometer (MODIS) data spanning the length of the MODIS satellite record. The Normalized Difference Vegetation Index (NDVI) signature of permanent water bodies (MOD44W; Carroll et al., 2009) is used to train surface water classifiers which are applied to a time period of interest. From this, an operational nowcast flood detection component is produced using twice daily imagery acquired at 3-h latency which performs image compositing routines to minimize cloud cover. Case studies and accuracy assessments against radar-based observations for historic flood events are presented. The customizable system has been transferred to regional organizations and near real-time derived surface water products are made available through a web interface platform. Results highlight the potential of near real-time observation and impact assessment systems to serve as effective decision support tools for governments, international agencies, and disaster responders.

SciSpark: Highly Interactive and Scalable Model Evaluation and Climate Metrics

NASA Astrophysics Data System (ADS)

Wilson, B. D.; Mattmann, C. A.; Waliser, D. E.; Kim, J.; Loikith, P.; Lee, H.; McGibbney, L. J.; Whitehall, K. D.

2014-12-01

Remote sensing data and climate model output are multi-dimensional arrays of massive sizes locked away in heterogeneous file formats (HDF5/4, NetCDF 3/4) and metadata models (HDF-EOS, CF) making it difficult to perform multi-stage, iterative science processing since each stage requires writing and reading data to and from disk. We are developing a lightning fast Big Data technology called SciSpark based on ApacheTM Spark. Spark implements the map-reduce paradigm for parallel computing on a cluster, but emphasizes in-memory computation, "spilling" to disk only as needed, and so outperforms the disk-based ApacheTM Hadoop by 100x in memory and by 10x on disk, and makes iterative algorithms feasible. SciSpark will enable scalable model evaluation by executing large-scale comparisons of A-Train satellite observations to model grids on a cluster of 100 to 1000 compute nodes. This 2nd generation capability for NASA's Regional Climate Model Evaluation System (RCMES) will compute simple climate metrics at interactive speeds, and extend to quite sophisticated iterative algorithms such as machine-learning (ML) based clustering of temperature PDFs, and even graph-based algorithms for searching for Mesocale Convective Complexes. The goals of SciSpark are to: (1) Decrease the time to compute comparison statistics and plots from minutes to seconds; (2) Allow for interactive exploration of time-series properties over seasons and years; (3) Decrease the time for satellite data ingestion into RCMES to hours; (4) Allow for Level-2 comparisons with higher-order statistics or PDF's in minutes to hours; and (5) Move RCMES into a near real time decision-making platform. We will report on: the architecture and design of SciSpark, our efforts to integrate climate science algorithms in Python and Scala, parallel ingest and partitioning (sharding) of A-Train satellite observations from HDF files and model grids from netCDF files, first parallel runs to compute comparison statistics and PDF's, and first metrics quantifying parallel speedups and memory & disk usage.

Use of Remote Sensing Data to Enhance the National Weather Service (NWS) Storm Damage Toolkit

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Molthan, Andrew; White, Kris; Burks, Jason; Stellman, Keith; Smith, Matthew

2012-01-01

SPoRT is improving the use of near real-time satellite data in response to severe weather events and other diasters. Supported through NASA s Applied Sciences Program. Planned interagency collaboration to support NOAA s Damage Assessment Toolkit, with spinoff opportunities to support other entities such as USGS and FEMA.

On the Impact of Multi-GNSS Observations on Real-Time Precise Point Positioning Zenith Total Delay Estimates

NASA Astrophysics Data System (ADS)

Ding, Wenwu; Teferle, Norman; Kaźmierski, Kamil; Laurichesse, Denis; Yuan, Yunbin

2017-04-01

Observations from multiple Global Navigation Satellite System (GNSS) can improve the performance of real-time (RT) GNSS meteorology, in particular of the Zenith Total Delay (ZTD) estimates. RT ZTD estimates in combination with derived precipitable water vapour estimates can be used for weather now-casting and the tracking of severe weather events. While a number of published literature has already highlighted this positive development, in this study we describe an operational RT system for extracting ZTD using a modified version of the PPP-wizard (with PPP denoting Precise Point Positioning). Multi-GNSS, including GPS, GLONASS and Galileo, observation streams are processed using a RT PPP strategy based on RT satellite orbit and clock products from the Centre National d'Etudes Spatiales (CNES). A continuous experiment for 30 days was conducted, in which the RT observation streams of 20 globally distributed stations were processed. The initialization time and accuracy of the RT troposphere products using single and/or multi-system observations were evaluated. The effect of RT PPP ambiguity resolution was also evaluated. The results revealed that the RT troposphere products based on single system observations can fulfill the requirements of the meteorological application in now-casting systems. We noted that the GPS-only solution is better than the GLONASS-only solution in both initialization and accuracy. While the ZTD performance can be improved by applying RT PPP ambiguity resolution, the inclusion of observations from multiple GNSS has a more profound effect. Specifically, we saw that the ambiguity resolution is more effective in improving the accuracy, whereas the initialization process can be better accelerated by multi-GNSS observations. Combining all systems, RT troposphere products with an average accuracy of about 8 mm in ZTD were achieved after an initialization process of approximately 9 minutes, which supports the application of multi-GNSS observations and ambiguity resolution for RT meteorological applications.

Real-time on-board orbit determination with DORIS

NASA Technical Reports Server (NTRS)

Berthias, J.-P.; Jayles, C.; Pradines, D.

1993-01-01

A spaceborne orbit determination system is being developed by the French Space Agency (CNES) for the SPOT 4 satellite. It processes DORIS measurements to produce an orbit with an accuracy of about 50O meters rms. In order to evaluate the reliability of the software, it was combined with the MERCATOR man/machine interface and used to process the TOPEX/Poseidon DORIS data in near real time during the validation phase of the instrument, at JPL and at CNES. This paper gives an overview of the orbit determination system and presents the results of the TOPEX/Poseidon experiment.

Real-Time Estimation of Volcanic ASH/SO2 Cloud Height from Combined Uv/ir Satellite Observations and Numerical Modeling

NASA Astrophysics Data System (ADS)

Vicente, Gilberto A.

An efficient iterative method has been developed to estimate the vertical profile of SO2 and ash clouds from volcanic eruptions by comparing near real-time satellite observations with numerical modeling outputs. The approach uses UV based SO2 concentration and IR based ash cloud images, the volcanic ash transport model PUFF and wind speed, height and directional information to find the best match between the simulated and the observed displays. The method is computationally fast and is being implemented for operational use at the NOAA Volcanic Ash Advisory Centers (VAACs) in Washington, DC, USA, to support the Federal Aviation Administration (FAA) effort to detect, track and measure volcanic ash cloud heights for air traffic safety and management. The presentation will show the methodology, results, statistical analysis and SO2 and Aerosol Index input products derived from the Ozone Monitoring Instrument (OMI) onboard the NASA EOS/Aura research satellite and from the Global Ozone Monitoring Experiment-2 (GOME-2) instrument in the MetOp-A. The volcanic ash products are derived from AVHRR instruments in the NOAA POES-16, 17, 18, 19 as well as MetOp-A. The presentation will also show how a VAAC volcanic ash analyst interacts with the system providing initial condition inputs such as location and time of the volcanic eruption, followed by the automatic real-time tracking of all the satellite data available, subsequent activation of the iterative approach and the data/product delivery process in numerical and graphical format for operational applications.

Feasibility of NASA TT&C via Commercial Satellite Services

NASA Technical Reports Server (NTRS)

Mitchell, Carl W.; Weiss, Roland

1997-01-01

This report presents the results of a study to identify impact and driving requirements by implementing commercial satellite communications service into traditional National Aeronautics and Space Administration (NASA) space-ground communications. The NASA communication system is used to relay spacecraft and instrument commands, telemetry and science data. NASA's goal is to lower the cost of operation and increase the flexibility of spacecraft operations. Use of a commercial network offers the opportunity to contact a spacecraft on a nearly "on-demand" basis with ordinary phone calls to enable real time interaction with science events.

Applications of satellite data relay to problems of field seismology

NASA Technical Reports Server (NTRS)

Webster, W. J., Jr.; Miller, W. H.; Whitley, R.; Allenby, R. J.; Dennison, R. T.

1980-01-01

A seismic signal processor was developed and tested for use with the NOAA-GOES satellite data collection system. Performance tests on recorded, as well as real time, short period signals indicate that the event recognition technique used is nearly perfect in its rejection of cultural signals and that data can be acquired in many swarm situations with the use of solid state buffer memories. Detailed circuit diagrams are provided. The design of a complete field data collection platform is discussed and the employment of data collection platforms in seismic network is reviewed.

The Purpose of the Sensor Web

NASA Technical Reports Server (NTRS)

Schoeberl, Mark R.

2004-01-01

The Sensor Web concept emerged as the number of Earth Science Satellites began to increase in the recent years. The idea, part of a vision for the future of earth science, was that the sensor systems would be linked in an active way to provide improved forecast capability. This means that a system that is nearly autonomous would need to be developed to allow the satellites to re-target and deploy assets for particular phenomena or provide on board processing for real time data. This talk will describe several elements of the sensor web.

Assessment of the availability of the tracking and data relay satellite system for LANDSAT missions

NASA Technical Reports Server (NTRS)

1982-01-01

The telecommunications availability that can realistically be provided by the tracking and data relay satellite system (TDRSS) for LANDSAT D type missions. Although the assessment focusses on the telecommunications requirements of the near Earth orbit missions of the 1985 - 1989 time frame, it emphasizes LANDSAT D and its competing demand for wideband, real-time RF link services from TDRSS. Limitations in availability of communications services are identified, including systematic TDRSS restrictions, conflicting telecommunication requirements and loading problems of all users (missions) which are to be supported by TDRSS. Several telecommunications alternatives for LANDSAT D utilization independent of TDRSS services are discussed.

A case of timely satellite image acquisitions in support of coastal emergency environmental response management

USGS Publications Warehouse

Ramsey, Elijah W.; Werle, Dirk; Lu, Zhong; Rangoonwala, Amina; Suzuoki, Yukihiro

2009-01-01

The synergistic application of optical and radar satellite imagery improves emergency response and advance coastal monitoring from the realm of “opportunistic” to that of “strategic.” As illustrated by the Hurricane Ike example, synthetic aperture radar imaging capabilities are clearly applicable for emergency response operations, but they are also relevant to emergency environmental management. Integrated with optical monitoring, the nearly real-time availability of synthetic aperture radar provides superior consistency in status and trends monitoring and enhanced information concerning causal forces of change that are critical to coastal resource sustainability, including flooding extent, depth, and frequency.

Space Radiation Monitoring Center at SINP MSU

NASA Astrophysics Data System (ADS)

Kalegaev, Vladimir; Barinova, Wera; Barinov, Oleg; Bobrovnikov, Sergey; Dolenko, Sergey; Mukhametdinova, Ludmila; Myagkova, Irina; Nguen, Minh; Panasyuk, Mikhail; Shiroky, Vladimir; Shugay, Julia

2015-04-01

Data on energetic particle fluxes from Russian satellites have been collected in Space monitoring data center at Moscow State University in the near real-time mode. Web-portal http://smdc.sinp.msu.ru/ provides operational information on radiation state of the near-Earth space. Operational data are coming from space missions ELECTRO-L1, Meteor-M2. High-resolution data on energetic electron fluxes from MSU's satellite VERNOV with RELEC instrumentation on board are also available. Specific tools allow the visual representation of the satellite orbit in 3D space simultaneously with particle fluxes variations. Concurrent operational data coming from other spacecraft (ACE, GOES, SDO) and from the Earth's surface (geomagnetic indices) are used to represent geomagnetic and radiation state of near-Earth environment. Internet portal http://swx.sinp.msu.ru provides access to the actual data characterizing the level of solar activity, geomagnetic and radiation conditions in heliosphere and the Earth's magnetosphere in the real-time mode. Operational forecasting services automatically generate alerts on particle fluxes enhancements above the threshold values, both for SEP and relativistic electrons, using data from LEO and GEO orbits. The models of space environment working in autonomous mode are used to generalize the information obtained from different missions for the whole magnetosphere. On-line applications created on the base of these models provide short-term forecasting for SEP particles and relativistic electron fluxes at GEO and LEO, Dst and Kp indices online forecasting up to 1.5 hours ahead. Velocities of high-speed streams in solar wind on the Earth orbit are estimated with advance time of 3-4 days. Visualization system provides representation of experimental and modeling data in 2D and 3D.

Tropical Tropospheric Ozone: A Multi-Satellite View From TOMS and Other Instruments

NASA Technical Reports Server (NTRS)

Thompson, Anne M.; Hudson, Robert D.; Guo, Hua; Witte, Jacquelyn C.; Kucsera, Tom L.; Seybold, Matthew G.; Einaudi, Franco (Technical Monitor)

2000-01-01

New tropospheric ozone and aerosol products from the TOMS (Total Ozone Mapping Spectrometer) satellite instrument can resolve episodic pollution events in the tropics and interannual and seasonal variability. Modified-residual (MR) Nimbus 7 tropical tropospheric ozone (TTO), two maps/month (1979-1992, 1-deg latitude by 2-deg longitude) within the region in which total ozone displays a tropical wave-one pattern (maximum 20S to 20N), are available in digital form at http://metosrv2.umd.edu/tropo. Also available are preliminary 1996-1999 MR-TTO maps based on real-time Earth-Probe (EP)/TOMS observations. Examples of applications are given.

Online tools for uncovering data quality issues in satellite-based global precipitation products

NASA Astrophysics Data System (ADS)

Liu, Z.; Heo, G.

2015-12-01

Accurate and timely available global precipitation products are important to many applications such as flood forecasting, hydrological modeling, vector-borne disease research, crop yield estimates, etc. However, data quality issues such as biases and uncertainties are common in satellite-based precipitation products and it is important to understand these issues in applications. In recent years, algorithms using multi-satellites and multi-sensors for satellite-based precipitation estimates have become popular, such as the TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA) and the latest Integrated Multi-satellitE Retrievals for GPM (IMERG). Studies show that data quality issues for multi-satellite and multi-sensor products can vary with space and time and can be difficult to summarize. Online tools can provide customized results for a given area of interest, allowing customized investigation or comparison on several precipitation products. Because downloading data and software is not required, online tools can facilitate precipitation product evaluation and comparison. In this presentation, we will present online tools to uncover data quality issues in satellite-based global precipitation products. Examples will be presented as well.

Real-time estimation of ionospheric delay using GPS measurements

NASA Astrophysics Data System (ADS)

Lin, Lao-Sheng

1997-12-01

When radio waves such as the GPS signals propagate through the ionosphere, they experience an extra time delay. The ionospheric delay can be eliminated (to the first order) through a linear combination of L1 and L2 observations from dual-frequency GPS receivers. Taking advantage of this dispersive principle, one or more dual- frequency GPS receivers can be used to determine a model of the ionospheric delay across a region of interest and, if implemented in real-time, can support single-frequency GPS positioning and navigation applications. The research objectives of this thesis were: (1) to develop algorithms to obtain accurate absolute Total Electron Content (TEC) estimates from dual-frequency GPS observables, and (2) to develop an algorithm to improve the accuracy of real-time ionosphere modelling. In order to fulfil these objectives, four algorithms have been proposed in this thesis. A 'multi-day multipath template technique' is proposed to mitigate the pseudo-range multipath effects at static GPS reference stations. This technique is based on the assumption that the multipath disturbance at a static station will be constant if the physical environment remains unchanged from day to day. The multipath template, either single-day or multi-day, can be generated from the previous days' GPS data. A 'real-time failure detection and repair algorithm' is proposed to detect and repair the GPS carrier phase 'failures', such as the occurrence of cycle slips. The proposed algorithm uses two procedures: (1) application of a statistical test on the state difference estimated from robust and conventional Kalman filters in order to detect and identify the carrier phase failure, and (2) application of a Kalman filter algorithm to repair the 'identified carrier phase failure'. A 'L1/L2 differential delay estimation algorithm' is proposed to estimate GPS satellite transmitter and receiver L1/L2 differential delays. This algorithm, based on the single-site modelling technique, is able to estimate the sum of the satellite and receiver L1/L2 differential delay for each tracked GPS satellite. A 'UNSW grid-based algorithm' is proposed to improve the accuracy of real-time ionosphere modelling. The proposed algorithm is similar to the conventional grid-based algorithm. However, two modifications were made to the algorithm: (1) an 'exponential function' is adopted as the weighting function, and (2) the 'grid-based ionosphere model' estimated from the previous day is used to predict the ionospheric delay ratios between the grid point and reference points. (Abstract shortened by UMI.)

Oceanic Weather Decision Support for Unmanned Global Hawk Science Missions into Hurricanes with Tailored Satellite Derived Products

NASA Astrophysics Data System (ADS)

Feltz, Wayne; Griffin, Sarah; Velden, Christopher; Zipser, Ed; Cecil, Daniel; Braun, Scott

2017-04-01

The purpose of this presentation is to identify in-flight hazards to high-altitude aircraft, namely the Global Hawk. The Global Hawk was used during Septembers 2012-2016 as part of two NASA funded Hurricane Sentinel-3 field campaigns to over-fly hurricanes in the Atlantic Ocean. This talk identifies the cause of severe turbulence experienced over Hurricane Emily (2005) and how a combination of NOAA funded GOES-R algorithm derived cloud top heights/tropical overshooting tops using GOES-13/SEVIRI imager radiances, and lightning information are used to identify areas of potential turbulence for near real-time navigation decision support. Several examples will demonstrate how the Global Hawk pilots remotely received and used real-time satellite derived cloud and lightning detection information to keep the aircraft safely above clouds and avoid regions of potential turbulence.

A multidisciplinary and multi-sensor assessment of continuous degassing at Turrialba volcano, Costa Rica; insights and their application to hazard management

NASA Astrophysics Data System (ADS)

van Manen, S. M.; Tortini, R.; Burson, B.; Carn, S. A.

2013-12-01

Turrialba is an active stratovolcano located in the Central Cordillera of Costa Rica with an elevation of 3,340 m. Located just 35 km northeast of Costa Rica's capital city San Jose it looms over Costa Rica's Central Valley, the social and economic hub of the country. After more than 100 years of quiescence Turrialba resumed activity in 1996, marked by progressive increases in degassing and seismic activity with gas emissions becoming continuous in 2007. Intermittent phreatic explosions accompanied by ash emissions that have reached the capital have been occurring since 2010. The activity has resulted in the evacuation of two villages, closure of the National Park that comprises the summit region of the volcano and devastation of the local ecosystem. In this work we present a multi-disciplinary and multi-sensor assessment of the persistent degassing and its impacts on the local ecosystem. Combining a variety of high temporal and high spatial resolution satellite-based time series with ground-based measurements of ambient gas concentrations, element deposition and surveys of species richness, enables a comprehensive assessment of SO2 emissions and changes in vegetation. Satellite-based time-series were obtained from Landsat TM and ETM+, Terra ASTER and MODIS, Aqua MODIS, EO-1 and Aura OMI, with some of the data dating back to 2000. Preliminary results show exposure to the volcanic plume results in high soil acidity and significant uptake of certain heavy metals (e.g. Cd, Co, Cu, Hg and Pb) by vegetation, in contrast other elements such as Ba, Ca and Sr are leached from the soil as a result of the acid deposition. These factors are likely to be responsible for decreased species richness and physiological damage observed downwind of Turrialba. Ambient SO2 concentrations that exceed WHO guideline values have been recorded, which has potentially important consequences for human health in the area. Analyzing and relating the remote observations to conditions and impacts on the ground provides an increased understanding of volcanic degassing, its impacts in terms of the long-term vegetation response and how satellite-based monitoring can be used to inform hazard management strategies related to land use, agricultural productivity and human health in near-real time.

Utilizing Satellite-derived Precipitation Products in Hydrometeorological Applications

NASA Astrophysics Data System (ADS)

Liu, Z.; Ostrenga, D.; Teng, W. L.; Kempler, S. J.; Huffman, G. J.

2012-12-01

Each year droughts and floods happen around the world and can cause severe property damages and human casualties. Accurate measurement and forecast are important for preparedness and mitigation efforts. Through multi-satellite blended techniques, significant progress has been made over the past decade in satellite-based precipitation product development, such as, products' spatial and temporal resolutions as well as timely availability. These new products are widely used in various research and applications. In particular, the TRMM Multi-satellite Precipitation Analysis (TMPA) products archived and distributed by the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) provide 3-hourly, daily and monthly near-global (50° N - 50° S) precipitation datasets for research and applications. Two versions of TMPA products are available, research (3B42, 3B43, rain gauge adjusted) and near-real-time (3B42RT). At GES DISC, we have developed precipitation data services to support hydrometeorological applications in order to maximize the TRMM mission's societal benefits. In this presentation, we will present examples of utilizing TMPA precipitation products in hydrometeorological applications including: 1) monitoring global floods and droughts; 2) providing data services to support the USDA Crop Explorer; 3) support hurricane monitoring activities and research; and 4) retrospective analog year analyses to improve USDA's world agricultural supply and demand estimates. We will also present precipitation data services that can be used to support hydrometeorological applications including: 1) User friendly TRMM Online Visualization and Analysis System (TOVAS; URL: http://disc2.nascom.nasa.gov/Giovanni/tovas/); 2) Mirador (http://mirador.gsfc.nasa.gov/), a simplified interface for searching, browsing, and ordering Earth science data at GES DISC; 3) Simple Subset Wizard (http://disc.sci.gsfc.nasa.gov/SSW/ ) for data subsetting and format conversion; 4) Data via OPeNDAP (http://disc.sci.gsfc.nasa.gov/services/opendap/) that can be used for remote access to individual variables within datasets in a form usable by many tools, such as IDV, McIDAS-V, Panoply, Ferret and GrADS; 4) GrADS-DODS Data Server or GDS (http://disc2.nascom.nasa.gov/dods/); 5) The Open Geospatial Consortium (OGC) Web Map Service (WMS) (http://disc.sci.gsfc.nasa.gov/services/wxs_ogc.shtml) that allows the use of data and enables clients to build customized maps with data coming from a different network; and 6) Providing NASA gridded hydrological data access through CUAHSI HIS (Consortium of Universities for the Advancement of Hydrologic Science, Inc. - Hydrologic Information Systems).

GEO Optical Data Association with Concurrent Metric and Photometric Information

NASA Astrophysics Data System (ADS)

Dao, P.; Monet, D.

Data association in a congested area of the GEO belt with occasional visits by non-resident objects can be treated as a Multi-Target-Tracking (MTT) problem. For a stationary sensor surveilling the GEO belt, geosynchronous and near GEO objects are not completely motionless in the earth-fixed frame and can be observed as moving targets. In some clusters, metric or positional information is insufficiently accurate or up-to-date to associate the measurements. In the presence of measurements with uncertain origin, star tracks (residuals) and other sensor artifacts, heuristic techniques based on hard decision assignment do not perform adequately. In the MMT community, Bar-Shalom [2009 Bar-Shalom] was first in introducing the use of measurements to update the state of the target of interest in the tracking filter, e.g. Kalman filter. Following Bar-Shalom’s idea, we use the Probabilistic Data Association Filter (PDAF) but to make use of all information obtainable in the measurement of three-axis-stabilized GEO satellites, we combine photometric with metric measurements to update the filter. Therefore, our technique Concurrent Spatio- Temporal and Brightness (COSTB) has the stand-alone ability of associating a track with its identity –for resident objects. That is possible because the light curve of a stabilized GEO satellite changes minimally from night to night. We exercised COSTB on camera cadence data to associate measurements, correct mistags and detect non-residents in a simulated near real time cadence. Data on GEO clusters were used.

Applications of neural network methods to the processing of earth observation satellite data.

PubMed

Loyola, Diego G

2006-03-01

The new generation of earth observation satellites carries advanced sensors that will gather very precise data for studying the Earth system and global climate. This paper shows that neural network methods can be successfully used for solving forward and inverse remote sensing problems, providing both accurate and fast solutions. Two examples of multi-neural network systems for the determination of cloud properties and for the retrieval of total columns of ozone using satellite data are presented. The developed algorithms based on multi-neural network are currently being used for the operational processing of European atmospheric satellite sensors and will play a key role in related satellite missions planed for the near future.

Near Real Time Processing Chain for Suomi NPP Satellite Data

NASA Astrophysics Data System (ADS)

Monsorno, Roberto; Cuozzo, Giovanni; Costa, Armin; Mateescu, Gabriel; Ventura, Bartolomeo; Zebisch, Marc

2014-05-01

Since 2009, the EURAC satellite receiving station, located at Corno del Renon, in a free obstacle site at 2260 m a.s.l., has been acquiring data from Aqua and Terra NASA satellites equipped with Moderate Resolution Imaging Spectroradiometer (MODIS) sensors. The experience gained with this local ground segmenthas given the opportunity of adapting and modifying the processing chain for MODIS data to the Suomi NPP, the natural successor to Terra and Aqua satellites. The processing chain, initially implemented by mean of a proprietary system supplied by Seaspace and Advanced Computer System, was further developed by EURAC's Institute for Applied Remote Sensing engineers. Several algorithms have been developed using MODIS and Visible Infrared Imaging Radiometer Suite (VIIRS) data to produce Snow Cover, Particulate Matter estimation and Meteo maps. These products are implemented on a common processor structure based on the use of configuration files and a generic processor. Data and products have then automatically delivered to the customers such as the Autonomous Province of Bolzano-Civil Protection office. For the processing phase we defined two goals: i) the adaptation and implementation of the products already available for MODIS (and possibly new ones) to VIIRS, that is one of the sensors onboard Suomi NPP; ii) the use of an open source processing chain in order to process NPP data in Near Real Time, exploiting the knowledge we acquired on parallel computing. In order to achieve the second goal, the S-NPP data received and ingested are sent as input to RT-STPS (Real-time Software Telemetry Processing System) software developed by the NASA Direct Readout Laboratory 1 (DRL) that gives as output RDR files (Raw Data Record) for VIIRS, ATMS (Advanced Technology Micorwave Sounder) and CrIS (Cross-track Infrared Sounder)sensors. RDR are then transferred to a server equipped with CSPP2 (Community Satellite Processing Package) software developed by the University of Wisconsin. CSPP subdivides the input file in granules, making possible the use of parallel computing, and produces SDR (Science Data Record) and some EDR (Environmental Data Record) products. The integration with the EDRs not yet available with CSPP is realized with the use of SPAs (Science Processing Algorithm) stand-alone version by DRL. The important result of this system consists in the possibility of processing data acquired by the EURAC antenna with open source software and delivering the SDRs, EDRs and higher level products developed internally by EURAC in near real time using a Data Exchange Server. By means of the parallelized CSPP, SDR data are currently available after about 7 minutes since the production of RDR, while we are currently implementing a strategy to get the best possible processing time for the EDRs products that are in principle not parallelizable. 1. http://directreadout.sci.gsfc.nasa.gov/ 2. http://cimss.ssec.wisc.edu/cspp/

A seamless global hydrological monitoring and forecasting system for water resources assessment and hydrological hazard early warning

NASA Astrophysics Data System (ADS)

Sheffield, Justin; He, Xiaogang; Wood, Eric; Pan, Ming; Wanders, Niko; Zhan, Wang; Peng, Liqing

2017-04-01

Sustainable management of water resources and mitigation of the impacts of hydrological hazards are becoming ever more important at large scales because of inter-basin, inter-country and inter-continental connections in water dependent sectors. These include water resources management, food production, and energy production, whose needs must be weighed against the water needs of ecosystems and preservation of water resources for future generations. The strains on these connections are likely to increase with climate change and increasing demand from burgeoning populations and rapid development, with potential for conflict over water. At the same time, network connections may provide opportunities to alleviate pressures on water availability through more efficient use of resources such as trade in water dependent goods. A key constraint on understanding, monitoring and identifying solutions to increasing competition for water resources and hazard risk is the availability of hydrological data for monitoring and forecasting water resources and hazards. We present a global online system that provides continuous and consistent water products across time scales, from the historic instrumental period, to real-time monitoring, short-term and seasonal forecasts, and climate change projections. The system is intended to provide data and tools for analysis of historic hydrological variability and trends, water resources assessment, monitoring of evolving hazards and forecasts for early warning, and climate change scale projections of changes in water availability and extreme events. The system is particular useful for scientists and stakeholders interested in regions with less available in-situ data, and where forecasts have the potential to help decision making. The system is built on a database of high-resolution climate data from 1950 to present that merges available observational records with bias-corrected reanalysis and satellite data, which then drives a coupled land surface model-flood inundation model to produce hydrological variables and indices at daily, 0.25-degree resolution, globally. The system is updated in near real-time (< 2 days) using satellite precipitation and weather model data, and produces forecasts at short-term (out to 7 days) based on the Global Forecast System (GFS) and seasonal (up to 6 months) based on U.S. National Multi-Model Ensemble (NMME) seasonal forecasts. Climate change projections are based on bias-corrected and downscaled CMIP5 climate data that is used to force the hydrological model. Example products from the system include real-time and forecast drought indices for precipitation, soil moisture, and streamflow, and flood magnitude and extent indices. The model outputs are complemented by satellite based products and indices based on satellite data for vegetation health (MODIS NDVI) and soil moisture (SMAP). We show examples of the validation of the system at regional scales, including how local information can significantly improve predictions, and examples of how the system can be used to understand large-scale water resource issues, and in real-world contexts for early warning, decision making and planning.

Monitoring Land Based Sources of Pollution over Coral Reefs using VIIRS Ocean Color Products

NASA Astrophysics Data System (ADS)

Geiger, E.; Strong, A. E.; Eakin, C. M.; Wang, M.; Hernandez, W. J.; Cardona Maldonado, M. A.; De La Cour, J. L.; Liu, G.; Tirak, K.; Heron, S. F.; Skirving, W. J.; Armstrong, R.; Warner, R. A.

2016-02-01

NOAA's Coral Reef Watch (CRW) program and the NESDIS Ocean Color Team are developing new products to monitor land based sources of pollution (LBSP) over coral reef ecosystems using the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the S-NPP satellite. LBSP are a major threat to corals that can cause disease and mortality, disrupt critical ecological reef functions, and impede growth, reproduction, and larval settlement, among other impacts. From VIIRS, near-real-time satellite products of Chlorophyll-a, Kd(490), and sea surface temperature are being developed for three U.S. Coral Reef Task Force priority watershed sites - Ka'anapali (West Maui, Hawai'i), Faga'alu (American Samoa), and Guánica Bay (Puerto Rico). Background climatological levels of these parameters are being developed to construct anomaly products. Time-series data are being generated to monitor changes in water quality in near-real-time and provide information on historical variations, especially following significant rain events. A pilot calibration/validation field study of the VIIRS-based ocean color products is underway in Puerto Rico; we plan to expand this validation effort to the other two watersheds. Working with local resource managers, we have identified a focal area for product development and validation for each watershed and its associated local reefs. This poster will present preliminary results and identify a path forward to ensure marine resource managers understand and correctly use the new ocean color products, and to help NOAA CRW refine its satellite products to maximize their benefit to coral reef management. NOAA - National Oceanic and Atmospheric Administration NESDIS - NOAA/National Environmental Satellite, Data, and Information Service S-NPP - Suomi National Polar-orbiting Partnership

Quantifying Cyanobacteria and High Biomass Bloms from Satellite to Support Environmental Management and Public Use of U.S. Lakes and Estuaries

NASA Astrophysics Data System (ADS)

Tomlinson, Michelle C.; Stumpf, Richard P.; Dupuy, Danielle; Wynne, Timothy T.; Briggs, Travis

2015-12-01

Algal blooms of high biomass and cyanobacteria are on the rise, occurring both nationally and internationally. These blooms can foul beaches, clog water intakes, produce toxins that contaminate drinking water, and pose a threat to human and domestic animal health. A quantitative tool can aid in the management needs to respond to these issues. These blooms can affect many lakes within a state management district, pointing to the need for a synoptic and timely assessment. The 300 m Medium Resolution Imaging Spectrometer (MERIS) satellite imagery provided by the European Space Agency from 2002 to 2012 has led to advances in our ability to monitor these systems. Algorithms specific to quantifying high biomass blooms have been developed for use by state managers through a comparison of field radiometry, water quality and cell enumeration measurements, and remotely-sensed satellite data. These algorithms are designed to detect blooms even with atmospheric interference and suspended sediments. Initial evaluations were conducted for Florida lakes and the St. Johns River, Florida, USA and showed that cyanobacteria blooms, especially of Microcystis, can be identified and their biomass can be estimated (as chlorophyll concentration and other metrics). Forecasts and monitoring have been demonstrated for Lake Erie and for Florida. A multi-agency (NASA, EPA, NOAA, and USGS) project, “Cyanobacteria Assessment Network (CyAN)” intends to apply these methods to Sentinel-3 data in near real-time on a U.S. national scale, in order to support state management agencies in protecting public health and the environment.

MODIS Near real-time (NRT) data for fire applications

NASA Astrophysics Data System (ADS)

Wong, M.; Davies, D.; Ilavajhala, S.; Molinario, G.; Justice, C.; Latham, J.; Martucci, A.; Murphy, K. J.

2011-12-01

This paper describes the lessons learned from the development of the Fire Information for Resource Management System (FIRMS) prototype and its transition to an operational system, the Global Fire Information Management System (GFIMS), at the United Nations Food and Agriculture Organization (FAO) in August 2010. These systems provide active fire data from the MODIS sensor, on board NASA's Terra and Aqua Earth Observing Satellites, to users at no cost, in near-real time and in easy-to-use formats. The FIRMS prototype evolved from simply providing daily active fire text files via FTP, to include services such as providing fire data in various data formats, an interactive WebGIS allowing users to view and query the data and an email alert service enabling users to receive emails of near real-time fire data of their chosen area of interest. FIRMS was designed to remove obstacles to the uptake and use of fire data by addressing issues often associated with satellite data: cost, timeliness of delivery, limited data formats and the need for technical expertise to process and analyze the data. We also illustrate how the MODIS active fire data are routinely used for firefighting and conservation monitoring. We present results from a user survey, completed by approximately 345 people from 65 countries, and provide case studies highlighting how the provision of MODIS active fire data have made an impact on conservation and firefighting, especially in remote areas where it is difficult to have on-the-ground surveillance. We highlight the gaps in current capabilities, both with users and the data. A major obstacle still for some users is having low or no internet connectivity and a possible solution is through the use of cell phone technologies such as SMS text messaging of fire locations and information. GFIMS, and its precursor, FIRMS, were developed by the University of Maryland with funding from NASA's Applied Sciences Program. With GFIMS established at FAO as an operational system, FIRMS will become part of NASA's Land Atmosphere Near-real-time Capability for EOS (LANCE), to continue to meet NASA data-user needs.

InSAR data for monitoring land subsidence: time to think big

NASA Astrophysics Data System (ADS)

Ferretti, A.; Colombo, D.; Fumagalli, A.; Novali, F.; Rucci, A.

2015-11-01

Satellite interferometric synthetic aperture radar (InSAR) data have proven effective and valuable in the analysis of urban subsidence phenomena based on multi-temporal radar images. Results obtained by processing data acquired by different radar sensors, have shown the potential of InSAR and highlighted the key points for an operational use of this technology, namely: (1) regular acquisition over large areas of interferometric data stacks; (2) use of advanced processing algorithms, capable of estimating and removing atmospheric disturbances; (3) access to significant processing power for a regular update of the information over large areas. In this paper, we show how the operational potential of InSAR has been realized thanks to the recent advances in InSAR processing algorithms, the advent of cloud computing and the launch of new satellite platforms, specifically designed for InSAR analyses (e.g. Sentinel-1a operated by the ESA and ALOS2 operated by JAXA). The processing of thousands of SAR scenes to cover an entire nation has been performed successfully in Italy in a project financed by the Italian Ministry of the Environment. The challenge for the future is to pass from the historical analysis of SAR scenes already acquired in digital archives to a near real-time monitoring program where up to date deformation data are routinely provided to final users and decision makers.

Assimilation of Real-Time Satellite And Human Sensor Networks for Modeling Natural Disasters

NASA Astrophysics Data System (ADS)

Aulov, O.; Halem, M.; Lary, D. J.

2011-12-01

We describe the development of underlying technologies needed to address the merging of a web of real time satellite sensor Web (SSW) and Human Sensor Web (HSW) needed to augment the US response to extreme events. As an initial prototyping step and use case scenario, we consider the development of two major system tools that can be transitioned from research to the responding operational agency for mitigating coastal oil spills. These tools consist of the capture of Situation Aware (SA) Social Media (SM) Data, and assimilation of the processed information into forecasting models to provide incident decision managers with interactive virtual spatial temporal animations superimposed with probabilistic data estimates. The system methodologies are equally applicable to the wider class of extreme events such as plume dispersions from volcanoes or massive fires, major floods, hurricane impacts, radioactive isotope dispersions from nuclear accidents, etc. A successful feasibility demonstration of this technology has been shown in the case of the Deepwater Horizon Oil Spill where Human Sensor Networks have been combined with a geophysical model to perform parameter assessments. Flickr images of beached oil were mined from the spill area, geolocated and timestamped and converted into geophysical data. This data was incorporated into General NOAA Operational Modeling Environment (GNOME), a Lagrangian forecast model that uses near real-time surface winds, ocean currents, and satellite shape profiles of oil to generate a forecast of plume movement. As a result, improved estimates of diffusive coefficients and rates of oil spill were determined. Current approaches for providing satellite derived oil distributions are collected from a satellite sensor web of operational and research sensors from many countries, and a manual analysis is performed by NESDIS. A real time SA HSW processing system based on geolocated SM data from sources such as Twitter, Flickr, YouTube etc., greatly supplements the current operational practice of sending out teams of humans to gather samples of tarballs reaching coastal locations. We show that ensemble Kalman filter assimilation of the combination of SM data with model forecast background data fields can minimize the false positive cases of satellite observations alone. Our future framework consists of two parts, a real time SA HSW processing system and an on-demand SSW processing system. HSW processing system uses a geolocated SM data to provide observations of coastal oil contact. SSW system is composed of selected instruments from NASA EOS, NPP and available Decadal Survey mission satellites along with other in situ data to form a real time regional oil spill observing system. We will automate the NESDIS manual process of providing oil spill maps by using Self Organizing Feature Map (SOFM) algorithm. We use the LETKF scheme for assimilating the satellite sensor web and HSW observations into the GNOME model to reduce the uncertainty of the observations. We intend to infuse these developments in an SOA implementation for execution of event driven model forecast assimilation cycles in a dedicated HPC cloud.

Monitoring of pipeline ruptures by means of a Robust Satellite Technique (RST)

NASA Astrophysics Data System (ADS)

Filizzola, C.; Baldassarre, G.; Corrado, R.; Mazzeo, G.; Marchese, F.; Paciello, R.; Pergola, N.; Tramutoli, V.

2009-04-01

Pipeline ruptures have deep economic and ecologic consequences so that pipeline networks represent critical infrastructures to be carefully monitored particularly in areas which are frequently affected by natural disasters like earthquakes, hurricanes, landslide, etc. In order to minimize damages, the detection of harmful events along pipelines should be as rapid as possible and, at the same time, what is detected should be an actual incident and not a false alarm. In this work, a Robust Satellite Technique (RST), already applied to the prevision and NRT (Near Real Time) monitoring of major natural and environmental hazards (such as seismically active areas, volcanic activity, hydrological risk, forest fires and oil spills) has been employed to automatically identify, from satellite, anomalous Thermal Infrared (TIR) transients related to explosions of oil/gas pipelines. In this context, the combination of the RST approach with high temporal resolution, offered by geostationary satellites, seems to assure both a reliable and timely detection of such events. The potentials of the technique (applied to MSG-SEVIRI data) were tested over Iraq, a region which is sadly known for the numerous (mainly manmade) accidents to pipelines, in order to have a simulation of the effects (such as fires or explosions near or directly involving a pipeline facility) due to natural disasters.

Using optimal interpolation to assimilate surface measurements and satellite AOD for ozone and PM2.5: A case study for July 2011.

PubMed

Tang, Youhua; Chai, Tianfeng; Pan, Li; Lee, Pius; Tong, Daniel; Kim, Hyun-Cheol; Chen, Weiwei

2015-10-01

We employed an optimal interpolation (OI) method to assimilate AIRNow ozone/PM2.5 and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth (AOD) data into the Community Multi-scale Air Quality (CMAQ) model to improve the ozone and total aerosol concentration for the CMAQ simulation over the contiguous United States (CONUS). AIRNow data assimilation was applied to the boundary layer, and MODIS AOD data were used to adjust total column aerosol. Four OI cases were designed to examine the effects of uncertainty setting and assimilation time; two of these cases used uncertainties that varied in time and location, or "dynamic uncertainties." More frequent assimilation and higher model uncertainties pushed the modeled results closer to the observation. Our comparison over a 24-hr period showed that ozone and PM2.5 mean biases could be reduced from 2.54 ppbV to 1.06 ppbV and from -7.14 µg/m³ to -0.11 µg/m³, respectively, over CONUS, while their correlations were also improved. Comparison to DISCOVER-AQ 2011 aircraft measurement showed that surface ozone assimilation applied to the CMAQ simulation improves regional low-altitude (below 2 km) ozone simulation. This paper described an application of using optimal interpolation method to improve the model's ozone and PM2.5 estimation using surface measurement and satellite AOD. It highlights the usage of the operational AIRNow data set, which is available in near real time, and the MODIS AOD. With a similar method, we can also use other satellite products, such as the latest VIIRS products, to improve PM2.5 prediction.

Airborne net-centric multi-INT sensor control, display, fusion, and exploitation systems

NASA Astrophysics Data System (ADS)

Linne von Berg, Dale C.; Lee, John N.; Kruer, Melvin R.; Duncan, Michael D.; Olchowski, Fred M.; Allman, Eric; Howard, Grant

2004-08-01

The NRL Optical Sciences Division has initiated a multi-year effort to develop and demonstrate an airborne net-centric suite of multi-intelligence (multi-INT) sensors and exploitation systems for real-time target detection and targeting product dissemination. The goal of this Net-centric Multi-Intelligence Fusion Targeting Initiative (NCMIFTI) is to develop an airborne real-time intelligence gathering and targeting system that can be used to detect concealed, camouflaged, and mobile targets. The multi-INT sensor suite will include high-resolution visible/infrared (EO/IR) dual-band cameras, hyperspectral imaging (HSI) sensors in the visible-to-near infrared, short-wave and long-wave infrared (VNIR/SWIR/LWIR) bands, Synthetic Aperture Radar (SAR), electronics intelligence sensors (ELINT), and off-board networked sensors. Other sensors are also being considered for inclusion in the suite to address unique target detection needs. Integrating a suite of multi-INT sensors on a single platform should optimize real-time fusion of the on-board sensor streams, thereby improving the detection probability and reducing the false alarms that occur in reconnaissance systems that use single-sensor types on separate platforms, or that use independent target detection algorithms on multiple sensors. In addition to the integration and fusion of the multi-INT sensors, the effort is establishing an open-systems net-centric architecture that will provide a modular "plug and play" capability for additional sensors and system components and provide distributed connectivity to multiple sites for remote system control and exploitation.

Assessment of a demonstration project to supply near real-time sea ice information to end users

NASA Astrophysics Data System (ADS)

Blackford, C.; Howes, Sally; Whitelaw, Alan S.; Laxon, S.; Mantripp, D.

1994-12-01

Sea ice maps are required by a diverse range of users for scientific research and operational activities. Satellite remote sensing provides opportunities for monitoring and producing sea ice maps at a range of scales, in near real time. During March 1994 ESYS Limited and the University College London Mullard Space Science Laboratory (MSSL) operated a sea ice demonstration project to supply near real time sea ice maps in the southern ocean. The sea ice information was derived from a number of data sources: DMSP SSM/I data; ERS-1 SAR and Radar Altimeter fast delivery data; NOAA AVHRR data; and PoSAT-1 imagery. The maps were supplied to three users, two involved in yacht races in the southern ocean and a ship on an oceanographic research cruise in the waters of the Princess Elizabeth Trough region of Antarctica. The demonstration was successful, supplying the users with sea ice information which they had previously not received and combining data from various sources to produce sea ice maps. The demonstration also developed operational skills within ESYS and enabled the transfer of knowledge from MSSL to ESYS.

Africa-Wide Monitoring of Small Surface Water Bodies Using Multisource Satellite Data: A Monitoring System for FEWS NET

NASA Astrophysics Data System (ADS)

Velpuri, N. M.; Senay, G. B.; Rowland, J.; Budde, M. E.; Verdin, J. P.

2015-12-01

Continental Africa has the largest volume of water stored in wetlands, large lakes, reservoirs and rivers, yet it suffers with problems such as water availability and access. Furthermore, African countries are amongst the most vulnerable to the impact of natural hazards such as droughts and floods. With climate change intensifying the hydrologic cycle and altering the distribution and frequency of rainfall, the problem of water availability and access is bound to increase. The U.S Geological Survey Famine Early Warning Systems Network (FEWS NET), funded by the U.S. Agency for International Development, has initiated a large-scale project to monitor small to medium surface water bodies in Africa. Under this project, multi-source satellite data and hydrologic modeling techniques are integrated to monitor these water bodies in Africa. First, small water bodies are mapped using satellite data such as Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Landsat, and high resolution Google Earth imagery. Stream networks and watersheds for each water body are identified using Shuttle Radar Topography Mission (SRTM) digital elevation data. Finally, a hydrologic modeling approach that uses satellite-derived precipitation estimates and evapotranspiration data calculated from global data assimilation system climate parameters is applied to model water levels. This approach has been implemented to monitor nearly 300 small water bodies located in 10 countries in sub-Saharan Africa. Validation of modeled scaled depths with field-installed gauge data in East Africa demonstrated the ability of the model to capture both the spatial patterns and seasonal variations. Modeled scaled estimates captured up to 60% of the observed gauge variability with an average RMSE of 22%. Current and historic data (since 2001) on relative water level, precipitation, and evapotranspiration for each water body is made available in near real time. The water point monitoring network will be further expanded to cover other pastoral regions of sub-Saharan Africa. This project provides timely information on water availability that supports FEWS NET monitoring activities in Africa. Information on water availability produced in this study would further increase the resilience of local communities to floods and droughts.

Near-Real Time Monitoring of TEC Over Japan at NICT (RWC Tokyo OF ISES)

NASA Astrophysics Data System (ADS)

Miyake, W.; Jin, H.

2010-05-01

The world wide use of global navigation satellite systems such as GPS offers unique opportunities for a permanent monitoring of the total electron content (TEC) of the ionosphere. We have developed a system of the rapid derivation of TEC from GEONET (a dense GPS receiver network in Japan). In addition to a previous plot of TEC temporal variation over Japan, we have recently developed a near-real-time two-dimensional TEC map and have used it for the daily operation of Space Weather Forecast Center at NICT (Regional Warning Center Tokyo of International Space Environment Service). The TEC map can be used to continuously monitor the ionospheric disturbances over Japan, including spatial and temporal development of ionospheric storms, large-amplitude traveling ionospheric disturbances, and plasma bubbles intruding over Japan, with high time resolution. The development of the real-time monitoring system of TEC enables us to monitor large ionospheric disturbances, ranging from global- to small-scale disturbances, expected in the next solar maximum. The plot and maps are open to the public and are available on http://wdc.nict.go.jp/IONO/index_E.html.

Satellite clock corrections estimation to accomplish real time ppp: experiments for brazilian real time network

NASA Astrophysics Data System (ADS)

Marques, Haroldo; Monico, João; Aquino, Marcio; Melo, Weyller

2014-05-01

The real time PPP method requires the availability of real time precise orbits and satellites clocks corrections. Currently, it is possible to apply the solutions of clocks and orbits available by BKG within the context of IGS Pilot project or by using the operational predicted IGU ephemeris. The accuracy of the satellite position available in the IGU is enough for several applications requiring good quality. However, the satellites clocks corrections do not provide enough accuracy (3 ns ~ 0.9 m) to accomplish real time PPP with the same level of accuracy. Therefore, for real time PPP application it is necessary to further research and develop appropriated methodologies for estimating the satellite clock corrections in real time with better accuracy. Currently, it is possible to apply the real time solutions of clocks and orbits available by Federal Agency for Cartography and Geodesy (BKG) within the context of IGS Pilot project. The BKG corrections are disseminated by a new proposed format of the RTCM 3.x and can be applied in the broadcasted orbits and clocks. Some investigations have been proposed for the estimation of the satellite clock corrections using GNSS code and phase observable at the double difference level between satellites and epochs (MERVAT, DOUSA, 2007). Another possibility consists of applying a Kalman Filter in the PPP network mode (HAUSCHILD, 2010) and it is also possible the integration of both methods, using network PPP and observables at double difference level in specific time intervals (ZHANG; LI; GUO, 2010). For this work the methodology adopted consists in the estimation of the satellite clock corrections based on the data adjustment in the PPP mode, but for a network of GNSS stations. The clock solution can be solved by using two types of observables: code smoothed by carrier phase or undifferenced code together with carrier phase. In the former, we estimate receiver clock error; satellite clock correction and troposphere, considering that the phase ambiguities are eliminated when applying differences between consecutive epochs. However, when using undifferenced code and phase, the ambiguities may be estimated together with receiver clock errors, satellite clock corrections and troposphere parameters. In both strategies it is also possible to correct the troposphere delay from a Numerical Weather Forecast Model instead of estimating it. The prediction of the satellite clock correction can be performed using a straight line or a second degree polynomial using the time series of the estimated satellites clocks. To estimate satellite clock correction and to accomplish real time PPP two pieces of software have been developed, respectively, "RT_PPP" and "RT_SAT_CLOCK". The system (RT_PPP) is able to process GNSS code and phase data using precise ephemeris and precise satellites clocks corrections together with several corrections required for PPP. In the software RT_SAT_CLOCK we apply a Kalman filter algorithm to estimate satellite clock correction in the network PPP mode. In this case, all PPP corrections must be applied for each station. The experiments were generated in real time and post-processed mode (simulating real time) considering data from the Brazilian continuous GPS network and also from the IGS network in a global satellite clock solution. We have used IGU ephemeris for satellite position and estimated the satellite clock corrections, performing the updates as soon as new ephemeris files were available. Experiments were accomplished in order to assess the accuracy of the estimated clocks when using the Brazilian Numerical Weather Forecast Model (BNWFM) from CPTEC/INPE and also using the ZTD from European Centre for Medium-Range Weather Forecasts (ECMWF) together with Vienna Mapping Function VMF or estimating troposphere with clocks and ambiguities in the Kalman Filter. The daily precision of the estimated satellite clock corrections reached the order of 0.15 nanoseconds. The clocks were applied in the Real Time PPP for Brazilian network stations and also for flight test of the Brazilian airplanes and the results show that it is possible to accomplish real time PPP in the static and kinematic modes with accuracy of the order of 10 to 20 cm, respectively.

Downscaling hydrodynamics features to depict causes of major productivity of Sicilian-Maltese area and implications for resource management.

PubMed

Capodici, Fulvio; Ciraolo, Giuseppe; Cosoli, Simone; Maltese, Antonino; Mangano, M Cristina; Sarà, Gianluca

2018-07-01

Chlorophyll-a (CHL-a) and sea surface temperature (SST) are generally accepted as proxies for water quality. They can be easily retrieved in a quasi-near real time mode through satellite remote sensing and, as such, they provide an overview of the water quality on a synoptic scale in open waters. Their distributions evolve in space and time in response to local and remote forcing, such as winds and currents, which however have much finer temporal and spatial scales than those resolvable by satellites in spite of recent advances in satellite remote-sensing techniques. Satellite data are often characterized by a moderate temporal resolution to adequately catch the actual sub-grid physical processes. Conventional pointwise measurements can resolve high-frequency motions such as tides or high-frequency wind-driven currents, however they are inadequate to resolve their spatial variability over wide areas. We show in this paper that a combined use of near-surface currents, available through High-Frequency (HF) radars, and satellite data (e.g., TERRA and AQUA/MODIS), can properly resolve the main oceanographic features in both coastal and open-sea regions, particularly at the coastal boundaries where satellite imageries fail, and are complementary tools to interpret ocean productivity and resource management in the Sicily Channel. Copyright © 2018. Published by Elsevier B.V.

Multi-GNSS PPP-RTK: From Large- to Small-Scale Networks

PubMed Central

Nadarajah, Nandakumaran; Wang, Kan; Choudhury, Mazher

2018-01-01

Precise point positioning (PPP) and its integer ambiguity resolution-enabled variant, PPP-RTK (real-time kinematic), can benefit enormously from the integration of multiple global navigation satellite systems (GNSS). In such a multi-GNSS landscape, the positioning convergence time is expected to be reduced considerably as compared to the one obtained by a single-GNSS setup. It is therefore the goal of the present contribution to provide numerical insights into the role taken by the multi-GNSS integration in delivering fast and high-precision positioning solutions (sub-decimeter and centimeter levels) using PPP-RTK. To that end, we employ the Curtin PPP-RTK platform and process data-sets of GPS, BeiDou Navigation Satellite System (BDS) and Galileo in stand-alone and combined forms. The data-sets are collected by various receiver types, ranging from high-end multi-frequency geodetic receivers to low-cost single-frequency mass-market receivers. The corresponding stations form a large-scale (Australia-wide) network as well as a small-scale network with inter-station distances less than 30 km. In case of the Australia-wide GPS-only ambiguity-float setup, 90% of the horizontal positioning errors (kinematic mode) are shown to become less than five centimeters after 103 min. The stated required time is reduced to 66 min for the corresponding GPS + BDS + Galieo setup. The time is further reduced to 15 min by applying single-receiver ambiguity resolution. The outcomes are supported by the positioning results of the small-scale network. PMID:29614040

Multi-GNSS PPP-RTK: From Large- to Small-Scale Networks.

PubMed

Nadarajah, Nandakumaran; Khodabandeh, Amir; Wang, Kan; Choudhury, Mazher; Teunissen, Peter J G

2018-04-03

Precise point positioning (PPP) and its integer ambiguity resolution-enabled variant, PPP-RTK (real-time kinematic), can benefit enormously from the integration of multiple global navigation satellite systems (GNSS). In such a multi-GNSS landscape, the positioning convergence time is expected to be reduced considerably as compared to the one obtained by a single-GNSS setup. It is therefore the goal of the present contribution to provide numerical insights into the role taken by the multi-GNSS integration in delivering fast and high-precision positioning solutions (sub-decimeter and centimeter levels) using PPP-RTK. To that end, we employ the Curtin PPP-RTK platform and process data-sets of GPS, BeiDou Navigation Satellite System (BDS) and Galileo in stand-alone and combined forms. The data-sets are collected by various receiver types, ranging from high-end multi-frequency geodetic receivers to low-cost single-frequency mass-market receivers. The corresponding stations form a large-scale (Australia-wide) network as well as a small-scale network with inter-station distances less than 30 km. In case of the Australia-wide GPS-only ambiguity-float setup, 90% of the horizontal positioning errors (kinematic mode) are shown to become less than five centimeters after 103 min. The stated required time is reduced to 66 min for the corresponding GPS + BDS + Galieo setup. The time is further reduced to 15 min by applying single-receiver ambiguity resolution. The outcomes are supported by the positioning results of the small-scale network.

Advancing satellite operations with intelligent graphical monitoring systems

NASA Technical Reports Server (NTRS)

Hughes, Peter M.; Shirah, Gregory W.; Luczak, Edward C.

1993-01-01

For nearly twenty-five years, spacecraft missions have been operated in essentially the same manner: human operators monitor displays filled with alphanumeric text watching for limit violations or other indicators that signal a problem. The task is performed predominately by humans. Only in recent years have graphical user interfaces and expert systems been accepted within the control center environment to help reduce operator workloads. Unfortunately, the development of these systems is often time consuming and costly. At the NASA Goddard Space Flight Center (GSFC), a new domain specific expert system development tool called the Generic Spacecraft Analyst Assistant (GenSAA) has been developed. Through the use of a highly graphical user interface and point-and-click operation, GenSAA facilitates the rapid, 'programming-free' construction of intelligent graphical monitoring systems to serve as real-time, fault-isolation assistants for spacecraft analysts. Although specifically developed to support real-time satellite monitoring, GenSAA can support the development of intelligent graphical monitoring systems in a variety of space and commercial applications.

Full-Physics Inverse Learning Machine for Satellite Remote Sensing Retrievals

NASA Astrophysics Data System (ADS)

Loyola, D. G.

2017-12-01

The satellite remote sensing retrievals are usually ill-posed inverse problems that are typically solved by finding a state vector that minimizes the residual between simulated data and real measurements. The classical inversion methods are very time-consuming as they require iterative calls to complex radiative-transfer forward models to simulate radiances and Jacobians, and subsequent inversion of relatively large matrices. In this work we present a novel and extremely fast algorithm for solving inverse problems called full-physics inverse learning machine (FP-ILM). The FP-ILM algorithm consists of a training phase in which machine learning techniques are used to derive an inversion operator based on synthetic data generated using a radiative transfer model (which expresses the "full-physics" component) and the smart sampling technique, and an operational phase in which the inversion operator is applied to real measurements. FP-ILM has been successfully applied to the retrieval of the SO2 plume height during volcanic eruptions and to the retrieval of ozone profile shapes from UV/VIS satellite sensors. Furthermore, FP-ILM will be used for the near-real-time processing of the upcoming generation of European Sentinel sensors with their unprecedented spectral and spatial resolution and associated large increases in the amount of data.

Measurement of Thunderstorm Cloud-Top Parameters Using High-Frequency Satellite Imagery

DTIC Science & Technology

1978-01-01

short wave was present well to the south of this system approximately 2000 ka west of Baja California. Two distinct flow patterns were present, one...view can be observed in near real time whereas radar observations, although excellent for local purposes, involve substantial errors when composited...on a large scale. The time delay in such large scale compositing is critical when attempting to monitor convective cloud systems for a potential

Tactical Satellite 3

DTIC Science & Technology

2008-08-01

identified for static experiments , target arrays have been designed and ground truth systems are already in place. Participation in field ...key objectives are rapid launch and on-orbit checkout, theater commanding, and near -real time theater data integration. It will also feature a rapid...Organisation (DSTO) plan to participate in TacSat-3 experiments . 1. INTRODUCTION In future conflicts, military space forces will likely face

Near real-time wildfire mapping using spatially-refined satellite data: The rim fire case study

Treesearch

Patricia Oliva; Wilfrid Schroeder

2015-01-01

Fire incident teams depend on accurate fire diagnostics and predictive data to guide daily positioning and tactics of fire crews. Currently, the U.S. Department of Agriculture - Forest Service National Infrared Operations (NIROPs) nighttime airborne data provides daily information about the fire front and total fire affected area of priority fires to the incident teams...

Natural disasters online

NASA Astrophysics Data System (ADS)

Showstack, Randy

Wildfires, severe storms, floods, volcanic eruptions, and major air pollution events are types of major natural hazards that NASA will track on a new Web site unveiled on 16 January. The site, part of the agency's Earth Observatory, will track these hazards in near-real time with imagery acquired from NASA's Earth Science Enterprise and Earth Observing System satellite missions, along with related descriptive information.

Applications for Near-Real Time Satellite Cloud and Radiation Products

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Palikonda, Rabindra; Chee, Thad L.; Bedka, Kristopher M.; Smith, W.; Ayers, Jeffrey K.; Benjamin, Stanley; Chang, F.-L.; Nguyen, Louis; Norris, Peter;

Research of real-time communication software

NASA Astrophysics Data System (ADS)

Li, Maotang; Guo, Jingbo; Liu, Yuzhong; Li, Jiahong

2003-11-01

Real-time communication has been playing an increasingly important role in our work, life and ocean monitor. With the rapid progress of computer and communication technique as well as the miniaturization of communication system, it is needed to develop the adaptable and reliable real-time communication software in the ocean monitor system. This paper involves the real-time communication software research based on the point-to-point satellite intercommunication system. The object-oriented design method is adopted, which can transmit and receive video data and audio data as well as engineering data by satellite channel. In the real-time communication software, some software modules are developed, which can realize the point-to-point satellite intercommunication in the ocean monitor system. There are three advantages for the real-time communication software. One is that the real-time communication software increases the reliability of the point-to-point satellite intercommunication system working. Second is that some optional parameters are intercalated, which greatly increases the flexibility of the system working. Third is that some hardware is substituted by the real-time communication software, which not only decrease the expense of the system and promotes the miniaturization of communication system, but also aggrandizes the agility of the system.

USGS Provision of Near Real Time Remotely Sensed Imagery for Emergency Response

NASA Astrophysics Data System (ADS)

Jones, B. K.

2014-12-01

The use of remotely sensed imagery in the aftermath of a disaster can have an important impact on the effectiveness of the response for many types of disasters such as floods, earthquakes, volcanic eruptions, landslides, and other natural or human-induced disasters. Ideally, responders in areas that are commonly affected by disasters would have access to archived remote sensing imagery plus the ability to easily obtain the new post event data products. The cost of obtaining and storing the data and the lack of trained professionals who can process the data into a mapping product oftentimes prevent this from happening. USGS Emergency Operations provides remote sensing and geospatial support to emergency managers by providing access to satellite images from numerous domestic and international space agencies including those affiliated with the International Charter Space and Major Disasters and their space-based assets and by hosting and distributing thousands of near real time event related images and map products through the Hazards Data Distribution System (HDDS). These data may include digital elevation models, hydrographic models, base satellite images, vector data layers such as roads, aerial photographs, and other pre and post disaster data. These layers are incorporated into a Web-based browser and data delivery service, the Hazards Data Distribution System (HDDS). The HDDS can be made accessible either to the general public or to specific response agencies. The HDDS concept anticipates customer requirements and provides rapid delivery of data and services. This presentation will provide an overview of remotely sensed imagery that is currently available to support emergency response operations and examples of products that have been created for past events that have provided near real time situational awareness for responding agencies.

The improved broadband Real-Time Seismic Network in Romania

NASA Astrophysics Data System (ADS)

Neagoe, C.; Ionescu, C.

2009-04-01

Starting with 2002 the National Institute for Earth Physics (NIEP) has developed its real-time digital seismic network. This network consists of 96 seismic stations of which 48 broad band and short period stations and two seismic arrays are transmitted in real-time. The real time seismic stations are equipped with Quanterra Q330 and K2 digitizers, broadband seismometers (STS2, CMG40T, CMG 3ESP, CMG3T) and strong motions sensors Kinemetrics episensors (+/- 2g). SeedLink and AntelopeTM (installed on MARMOT) program packages are used for real-time (RT) data acquisition and exchange. The communication from digital seismic stations to the National Data Center in Bucharest is assured by 5 providers (GPRS, VPN, satellite communication, radio lease line and internet), which will assure the back-up communications lines. The processing centre runs BRTT's AntelopeTM 4.10 data acquisition and processing software on 2 workstations for real-time processing and post processing. The Antelope Real-Time System is also providing automatic event detection, arrival picking, event location and magnitude calculation. It provides graphical display and reporting within near-real-time after a local or regional event occurred. Also at the data center was implemented a system to collect macroseismic information using the internet on which macro seismic intensity maps are generated. In the near future at the data center will be install Seiscomp 3 data acquisition processing software on a workstation. The software will run in parallel with Antelope software as a back-up. The present network will be expanded in the near future. In the first half of 2009 NIEP will install 8 additional broad band stations in Romanian territory, which also will be transmitted to the data center in real time. The Romanian Seismic Network is permanently exchanging real -time waveform data with IRIS, ORFEUS and different European countries through internet. In Romania, magnitude and location of an earthquake are now available within a few minutes after the earthquake occurred. One of the greatest challenges in the near future is to provide shaking intensity maps and other ground motion parameters, within 5 minutes post-event, on the Internet and GIS-based format in order to improve emergency response, public information, preparedness and hazard mitigation

Steps Towards an Operational Service Using Near Real-Time Altimeter Data

NASA Astrophysics Data System (ADS)

Ash, E. R.

2006-07-01

Thanks largely to modern computing power, numerical forecasts of w inds and waves over the oceans ar e ev er improving, offering greater accuracy and finer resolution in time and sp ace. Howev er, it is recognized that met-ocean models still have difficulty in accurately forecasting sever e w eather conditions, conditions that cause the most damag e and difficulty in mar itime operations. Ther efore a key requir emen t is to provid e improved information on sever e conditions. No individual measur emen t or prediction system is perfect. Offshore buoys provide a continuous long-ter m record of wind and wave conditions, but only at a limited numb er of sites. Satellite data offer all-weath er global cov erage, but with relatively infrequen t samp ling. Forecasts rely on imperf ect numerical schemes and the ab ility to manage a vast quantity of input data. Therefore the best system is one that integr ates information from all available sources, taking advantage of the benef its that each can offer. We report on an initiative supported by the European Space Agen cy (ESA) which investig ated how satellite data could be used to enhan ce systems to provide Near Real Time mon itor ing of met-ocean conditions.

Using RAQMS Chemical Transport Model, Aircraft In-situ and Satellite Data to Verify Ground-based Biomass Burning Emissions from the Extreme Fire Event in Boreal Alaska 2004

NASA Astrophysics Data System (ADS)

Soja, A. J.; Pierce, R. B.; Al-Saadi, J. A.; Alvarado, E.; Sandberg, D. V.; Ottmar, R. D.; Kittaka, C.; McMillian, W. W.; Sachse, G. W.; Warner, J. X.; Szykman, J. J.

2006-12-01

Current climate change scenarios are predicted to result in increased biomass burning, particularly in boreal regions. Biomass burning events feedback to the climate system by altering albedo (affecting the energy balance) and by direct and indirect fire emissions. Additionally, fire emissions influence air quality and human health downwind of burning. Biomass burning emission estimates are difficult to quantify in near-real-time and accurate estimates are useful for large-scale chemical transport models, which could be used to warn the public of potential health risks and for climate modeling. In this talk, we describe a methodology to quantify emissions, validate those emission estimates, transport the emissions and verify the resultant CO plume 100's of kilometers from the fire events using aircraft in-situ and satellite data. First, we developed carbon consumption estimates that are specifically designed for near-real-time use in conjunction with satellite-derived fire data for regional- to global-chemical transport models. Large-scale carbon consumption estimates are derived for 10 ecozones across North America and each zone contains 3 classes of severity. The estimates range is from a low severity 3.11 t C ha-1 estimate from the Western Taiga Shield to a high severity 59.83 t C ha-1 estimate from the Boreal Cordillera. These estimates are validated using extensive supplementary ground-based Alaskan data. Then, the RAQMS chemical transport model ingests these data and transports CO from the Alaskan 2004 fires across North America, where results are compared with in-situ flight CO data measured during INTEX-A and satellite-based CO data (AIRS and MOPITT). Ground-based CO is 6 to 14 times greater than the typically modeled fire climatology. RAQMS often overestimates CO in the biomass plumes in comparison to satellite- derived CO data and we suspect this may be due to the satellite instruments low sensitivity to planetary boundary layer CO, which is prevalent in the near field plumes, and also the assumption of high-severity fires throughout the burning season. RAQMS underestimates biomass CO in comparison to in-situ CO data (146 out of 148 ascents and descents), and we suspect this may be due to RAQMS difficulty in defining narrow fire plumes due to the 1.4° x 1.4° resolution.

Day 1 for the Integrated Multi-Satellite Retrievals for GPM (IMERG) Data Sets

NASA Astrophysics Data System (ADS)

Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K. L.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

2014-12-01

The Integrated Multi-satellitE Retrievals for GPM (IMERG) is designed to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG was developed to use GPM Core Observatory data as a reference for the international constellation of satellites of opportunity that constitute the GPM virtual constellation. Computationally, IMERG is a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design, development, testing, and current status. IMERG provides 0.1°x0.1° half-hourly data, and will be run at multiple times, providing successively more accurate estimates: 4 hours, 8 hours, and 2 months after observation time. In Day 1 the spatial extent is 60°N-S, for the period March 2014 to the present. In subsequent reprocessing the data will extend to fully global, covering the period 1998 to the present. Both the set of input data set retrievals and the IMERG system are substantially different than those used in previous U.S. products. The input passive microwave data are all being produced with GPROF2014, which is substantially upgraded compared to previous versions. For the first time, this includes microwave sounders. Accordingly, there is a strong need to carefully check the initial test data sets for performance. IMERG output will be illustrated using pre-operational test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. Finally, we will summarize the expected release of various output products, and the subsequent reprocessing sequence.

The Snow Data System at NASA JPL

NASA Astrophysics Data System (ADS)

Laidlaw, R.; Painter, T. H.; Mattmann, C. A.; Ramirez, P.; Bormann, K.; Brodzik, M. J.; Burgess, A. B.; Rittger, K.; Goodale, C. E.; Joyce, M.; McGibbney, L. J.; Zimdars, P.

2014-12-01

NASA JPL's Snow Data System has a data-processing pipeline powered by Apache OODT, an open source software tool. The pipeline has been running for several years and has successfully generated a significant amount of cryosphere data, including MODIS-based products such as MODSCAG, MODDRFS and MODICE, with historical and near-real time windows and covering regions such as the Artic, Western US, Alaska, Central Europe, Asia, South America, Australia and New Zealand. The team continues to improve the pipeline, using monitoring tools such as Ganglia to give an overview of operations, and improving fault-tolerance with automated recovery scripts. Several alternative adaptations of the Snow Covered Area and Grain size (SCAG) algorithm are being investigated. These include using VIIRS and Landsat TM/ETM+ satellite data as inputs. Parallel computing techniques are being considered for core SCAG processing, such as using the PyCUDA Python API to utilize multi-core GPU architectures. An experimental version of MODSCAG is also being developed for the Google Earth Engine platform, a cloud-based service.

Multicore-based 3D-DWT video encoder

NASA Astrophysics Data System (ADS)

Galiano, Vicente; López-Granado, Otoniel; Malumbres, Manuel P.; Migallón, Hector

2013-12-01

Three-dimensional wavelet transform (3D-DWT) encoders are good candidates for applications like professional video editing, video surveillance, multi-spectral satellite imaging, etc. where a frame must be reconstructed as quickly as possible. In this paper, we present a new 3D-DWT video encoder based on a fast run-length coding engine. Furthermore, we present several multicore optimizations to speed-up the 3D-DWT computation. An exhaustive evaluation of the proposed encoder (3D-GOP-RL) has been performed, and we have compared the evaluation results with other video encoders in terms of rate/distortion (R/D), coding/decoding delay, and memory consumption. Results show that the proposed encoder obtains good R/D results for high-resolution video sequences with nearly in-place computation using only the memory needed to store a group of pictures. After applying the multicore optimization strategies over the 3D DWT, the proposed encoder is able to compress a full high-definition video sequence in real-time.

Development of HWIL Testing Capabilities for Satellite Target Emulation at AEDC

NASA Astrophysics Data System (ADS)

Lowry, H.; Crider, D.; Burns, J.; Thompson, R.; Goldsmith, G., II; Sholes, W.

Programs involved in Space Situational Awareness (SSA) need the capability to test satellite sensors in a Hardware-in-the-Loop (HWIL) environment. Testing in a ground system avoids the significant cost of on-orbit test targets and the resulting issues such as debris mitigation, and in-space testing implications. The space sensor test facilities at AEDC consist of cryo-vacuum chambers that have been developed to project simulated targets to air-borne, space-borne, and ballistic platforms. The 7V chamber performs calibration and characterization of surveillance and seeker systems, as well as some mission simulation. The 10V chamber is being upgraded to provide real-time target simulation during the detection, acquisition, discrimination, and terminal phases of a seeker mission. The objective of the Satellite Emulation project is to upgrade this existing capability to support the ability to discern and track other satellites and orbital debris in a HWIL capability. It would provide a baseline for realistic testing of satellite surveillance sensors, which would be operated in a controlled environment. Many sensor functions could be tested, including scene recognition and maneuvering control software, using real interceptor hardware and software. Statistically significant and repeatable datasets produced by the satellite emulation system can be acquired during such test and saved for further analysis. In addition, the robustness of the discrimination and tracking algorithms can be investigated by a parametric analysis using slightly different scenarios; this will be used to determine critical points where a sensor system might fail. The radiometric characteristics of satellites are expected to be similar to the targets and decoys that make up a typical interceptor mission scenario, since they are near ambient temperature. Their spectral reflectivity, emissivity, and shape must also be considered, but the projection systems employed in the 7V and 10V chambers should be capable of providing the simulation of satellites as well. There may also be a need for greater radiometric intensity or shorter time response. An appropriate satellite model is integral to the scene generation process to meet the requirements of SSA programs. The Kinetic Kill Vehicle Hardware-in-the-Loop Simulator (KHILS) facility and the Guided Weapons Evaluation Facility (GWEF), both at Eglin Air Force Base, FL are assisting in developing the scene projection hardware, based on their significant test experience using resistive emitter arrays to test interceptors in a real-time environment. Army Aviation and Missile Research & Development Command (AMRDEC) will develop the Scene Generation System for the real-time mission simulation.

Merging Satellite Optical Sensors and Radar Altimetry for Daily River Discharge Estimation

NASA Astrophysics Data System (ADS)

Tarpanelli, A.; Santi, E. S.; Tourian, M. J.; Filippucci, P.; Amarnath, G.; Brocca, L.; Benveniste, J.

2017-12-01

River discharge is a fundamental physical variable of the hydrological cycle and notwithstanding its importance the monitoring of the flow in many parts of the Earth is still an open issue. Satellite sensors have great potential in offering new ways to monitor river discharge, because they guarantees regular, uniform and global measurements for long period thanks to the large number of satellites launched during the last twenty-five years. The multi-mission approach has been becoming a useful tool to integrate measurements and intensify the number of samples in space and time. In this study, we investigated the possibility to merge data from optical, i.e. Near InfraRed bands (from MODIS, MERIS, Landsat, and OLCI) and altimetry data (from Topex-Poseidon, Envisat/RA-2, Jason-2, SARAL/AltiKa and CryoSat-2) for estimating daily river discharge in Nigeria and Italy. The merging procedure is carried out by using artificial neural networks. Regarding the optical sensors, results are more affected by the temporal resolution than the spatial resolution. Landsat fails in the estimation of extreme events missing most of the peak values because of the long revisit time (14-16 days). Better performances are obtained with the Near InfraRed bands from MODIS and MERIS that give similar results in river discharge estimation. Finally, the multi-mission approach involving also radar altimetry data is found to be the most reliable tool to estimate river discharge in medium to large rivers.

Global and Regional Real-time Systems for Flood and Drought Monitoring and Prediction

NASA Astrophysics Data System (ADS)

Hong, Y.; Gourley, J. J.; Xue, X.; Flamig, Z.

2015-12-01

A Hydrometeorological Extreme Mapping and Prediction System (HyXtreme-MaP), initially built upon the Coupled Routing and Excess STorage (CREST) distributed hydrological model, is driven by real-time quasi-global TRMM/GPM satellites and by the US Multi-Radar Multi-Sensor (MRMS) radar network with dual-polarimetric upgrade to simulate streamflow, actual ET, soil moisture and other hydrologic variables at 1/8th degree resolution quasi-globally (http://eos.ou.edu) and at 250-meter 2.5-mintue resolution over the Continental United States (CONUS: http://flash.ou.edu).­ Multifaceted and collaborative by-design, this end-to-end research framework aims to not only integrate data, models, and applications but also brings people together (i.e., NOAA, NASA, University researchers, and end-users). This presentation will review the progresses, challenges and opportunities of such HyXTREME-MaP System used to monitor global floods and droughts, and also to predict flash floods over the CONUS.

A Challenging Trio in Space 'Routine' Operations of the Swarm Satellite Constellation

NASA Astrophysics Data System (ADS)

Diekmann, Frank-Jurgen; Clerigo, Ignacio; Albini, Giuseppe; Maleville, Laurent; Neto, Alessandro; Patterson, David; Nino, Ana Piris; Sieg, Detlef

2016-08-01

Swarm is the first ESA Earth Observation Mission with three satellites flying in a semi-controlled constellation. The trio is operated from ESA's satellite control centre ESOC in Darmstadt, Germany. The Swarm Flight Operations Segment consists of the typical elements of a satellite control system at ESOC, but had to be carefully tailored for this innovative mission. The main challenge was the multi-satellite system of Swarm, which necessitated the development of a Mission Control System with a multi-domain functionality, both in hardware and software and covering real-time and backup domains. This was driven by the need for extreme flexibility for constellation operations and parallel activities.The three months of commissioning in 2014 were characterized by a very tight and dynamically changing schedule of activities. All operational issues could be solved during that time, including the challenging orbit acquisition phase to achieve the final constellation.Although the formal spacecraft commissioning phase was concluded in spring 2014, the investigations for some payload instruments continue even today. The Electrical Field Instruments are for instance still being tested in order to characterize and improve science data quality. Various test phases also became necessary for the Accelerometers on the Swarm satellites. In order to improve the performance of the GPS Receivers for better scientific exploitation and to minimize the failures due to loss of synchronization, a number of parameter changes were commanded via on-board patches.Finally, to minimize the impact on operations, a new strategy had to be implemented to handle single/multi bit errors in the on-board mass Memories, defining when to ignore and when to restore the memory via a re-initialisation.The poster presentation summarizes the Swarm specific ground segment elements of the FOS and explains some of the extended payload commissioning operations, turning Swarm into a most demanding and challenging mission for the Flight Control Team at ESOC.

Combined Global Navigation Satellite Systems in the Space Service Volume

NASA Technical Reports Server (NTRS)

Force, Dale A.; Miller, James J.

2015-01-01

Besides providing position, navigation, and timing (PNT) services to traditional terrestrial and airborne users, GPS is also being increasingly used as a tool to enable precision orbit determination, precise time synchronization, real-time spacecraft navigation, and three-axis attitude control of Earth orbiting satellites. With additional Global Navigation Satellite System (GNSS) constellations being replenished and coming into service (GLONASS, Beidou, and Galileo), it will become possible to benefit from greater signal availability and robustness by using evolving multi-constellation receivers. The paper, "GPS in the Space Service Volume," presented at the ION GNSS 19th International Technical Meeting in 2006 (Ref. 1), defined the Space Service Volume, and analyzed the performance of GPS out to seventy thousand kilometers. This paper will report a similar analysis of the signal coverage of GPS in the space domain; however, the analyses will also consider signal coverage from each of the additional GNSS constellations noted earlier to specifically demonstrate the expected benefits to be derived from using GPS in conjunction with other foreign systems. The Space Service Volume is formally defined as the volume of space between three thousand kilometers altitude and geosynchronous altitude circa 36,000 km, as compared with the Terrestrial Service Volume between 3,000 km and the surface of the Earth. In the Terrestrial Service Volume, GNSS performance is the same as on or near the Earth's surface due to satellite vehicle availability and geometry similarities. The core GPS system has thereby established signal requirements for the Space Service Volume as part of technical Capability Development Documentation (CDD) that specifies system performance. Besides the technical discussion, we also present diplomatic efforts to extend the GPS Space Service Volume concept to other PNT service providers in an effort to assure that all space users will benefit from the enhanced interoperability of GNSS services in the space domain. A separate paper presented at the conference covers the individual GNSS performance parameters for respective Space Service Volumes.

Current Saturation Avoidance with Real-Time Control using DPCS

NASA Astrophysics Data System (ADS)

Ferrara, M.; Hutchinson, I.; Wolfe, S.; Stillerman, J.; Fredian, T.

2008-11-01

Tokamak ohmic-transformer and equilibrium-field coils need to be able to operate near their maximum current capabilities. However if they reach their upper limit during high-performance discharges or in the presence of a strong off-normal event, shape control is compromised, and instability, even plasma disruptions can result. On Alcator C-Mod we designed and tested an anti-saturation routine which detects the impending saturation of OH and EF currents and interpolates to a neighboring safe equilibrium in real-time. The routine was implemented with a multi-processor, multi-time-scale control scheme, which is based on a master process and multiple asynchronous slave processes. The scheme is general and can be used for any computationally-intensive algorithm. USDoE award DE- FC02-99ER545512.

Near real-time qualitative monitoring of lake water chlorophyll globally using GoogleEarth Engine

NASA Astrophysics Data System (ADS)

Zlinszky, András; Supan, Peter; Koma, Zsófia

2017-04-01

Monitoring ocean chlorophyll and suspended sediment has been made possible using optical satellite imaging, and has contributed immensely to our understanding of the Earth and its climate. However, lake water quality monitoring has limitations due to the optical complexity of shallow, sediment- and organic matter-laden waters. Meanwhile, timely and detailed information on basic lake water quality parameters would be essential for sustainable management of inland waters. Satellite-based remote sensing can deliver area-covering, high resolution maps of basic lake water quality parameters, but scientific application of these datasets for lake monitoring has been hindered by limitations to calibration and accuracy evaluation, and therefore access to such data has been the privilege of scientific users. Nevertheless, since for many inland waters satellite imaging is the only source of monitoring data, we believe it is urgent to make map products of chlorophyll and suspended sediment concentrations available to a wide range of users. Even if absolute accuracy can not be validated, patterns, processes and qualitative information delivered by such datasets in near-real time can act as an early warning system, raise awareness to water quality processes and serve education, in addition to complementing local monitoring activities. By making these datasets openly available on the internet through an easy to use framework, dialogue between stakeholders, management and governance authorities can be facilitated. We use GoogleEarthEngine to access and process archive and current satellite data. GoogleEarth Engine is a development and visualization framework that provides access to satellite datasets and processing capacity for analysis at the Petabyte scale. Based on earlier investigations, we chose the fluorescence line height index to represent water chlorophyll concentration. This index relies on the chlorophyll fluorescence peak at 680 nm, and has been tested for open ocean but also inland lake situations for MODIS and MERIS satellite sensor data. In addition to being relatively robust and less sensitive to atmospheric influence, this algorithm is also very simple, being based on the height of the 680 nm peak above the linear interpolation of the two neighbouring bands. However, not all satellite datasets suitable for FLH are catalogued for GoogleEarth Engine. In the current testing phase, Landsat 7, Landsat 8 (30 m resolution), and Sentinel 2 (20 m) are being tested. Landsat 7 has suitable band configuration, but has a strip error due to a sensor problem. Landsat 8 and Sentinel 2 lack a single spectral optimal for FLH. Sentinel 3 would be an optimal data source and has shown good performace during small-scale initial tests, but is not distributed globally for GoogleEarth Engine. In addition to FLH data from these satellites, our system delivers cloud and ice masking, qualitative suspended sediment data (based on the band closest to 600 nm) and true colour images, all within an easy-to-use Google Maps background. This allows on-demand understanding and interpretation of water quality patterns and processes in near real time. While the system is still under development, we believe it could significantly contribute to lake water quality management and monitoring worldwide.

Characterizing Global Flood Wave Travel Times to Optimize the Utility of Near Real-Time Satellite Remote Sensing Products

NASA Astrophysics Data System (ADS)

Allen, G. H.; David, C. H.; Andreadis, K. M.; Emery, C. M.; Famiglietti, J. S.

2017-12-01

Earth observing satellites provide valuable near real-time (NRT) information about flood occurrence and magnitude worldwide. This NRT information can be used in early flood warning systems and other flood management applications to save lives and mitigate flood damage. However, these NRT products are only useful to early flood warning systems if they are quickly made available, with sufficient time for flood mitigation actions to be implemented. More specifically, NRT data latency, or the time period between the satellite observation and when the user has access to the information, must be less than the time it takes a flood to travel from the flood observation location to a given downstream point of interest. Yet the paradigm that "lower latency is always better" may not necessarily hold true in river systems due to tradeoffs between data latency and data quality. Further, the existence of statistical breaks in the global distribution of flood wave travel time (i.e. a jagged statistical distribution) would represent preferable latencies for river-observation NRT remote sensing products. Here we present a global analysis of flood wave velocity (i.e. flow celerity) and travel time. We apply a simple kinematic wave model to a global hydrography dataset and calculate flow wave celerity and travel time during bankfull flow conditions. Bankfull flow corresponds to the condition of maximum celerity and thus we present the "worst-case scenario" minimum flow wave travel time. We conduct a similar analysis with respect to the time it takes flood waves to reach the next downstream city, as well as the next downstream reservoir. Finally, we conduct these same analyses, but with regards to the technical capabilities of the planned Surface Water and Ocean Topography (SWOT) satellite mission, which is anticipated to provide waterbody elevation and extent measurements at an unprecedented spatial and temporal resolution. We validate these results with discharge records from paired USGS gauge stations located along a diverse collection of river reaches. These results provide a scientific rationale for optimizing the utility of existing and future NRT river-observation products.

Mapping Historic Gypsy Moth Defoliation with MODIS Satellite Data: Implications for Forest Threat Early Warning System

NASA Technical Reports Server (NTRS)

Spurce, Joseph P.; Hargrove, William; Ryan, Robert E.; Smooth, James C.; Prados, Don; McKellip, Rodney; Sader, Steven A.; Gasser, Jerry; May, George

2008-01-01

This viewgraph presentation reviews a project, the goal of which is to study the potential of MODIS data for monitoring historic gypsy moth defoliation. A NASA/USDA Forest Service (USFS) partnership was formed to perform the study. NASA is helping USFS to implement satellite data products into its emerging Forest Threat Early Warning System. The latter system is being developed by the USFS Eastern and Western Forest Threat Assessment Centers. The USFS Forest Threat Centers want to use MODIS time series data for regional monitoring of forest damage (e.g., defoliation) preferably in near real time. The study's methodology is described, and the results of the study are shown.

Multi-Level Wild Land Fire Fighting Management Support System for an Optimized Guidance of Ground and Air Forces

NASA Astrophysics Data System (ADS)

Almer, Alexander; Schnabel, Thomas; Perko, Roland; Raggam, Johann; Köfler, Armin; Feischl, Richard

2016-04-01

Climate change will lead to a dramatic increase in damage from forest fires in Europe by the end of this century. In the Mediterranean region, the average annual area affected by forest fires has quadrupled since the 1960s (WWF, 2012). The number of forest fires is also on the increase in Central and Northern Europe. The Austrian forest fire database shows a total of 584 fires for the period 2012 to 2014, while even large areas of Sweden were hit by forest fires in August 2014, which were brought under control only after two weeks of intense fire-fighting efforts supported by European civil protection modules. Based on these facts, the improvements in forest fire control are a major international issue in the quest to protect human lives and resources as well as to reduce the negative environmental impact of these fires to a minimum. Within this paper the development of a multi-functional airborne management support system within the frame of the Austrian national safety and security research programme (KIRAS) is described. The main goal of the developments is to assist crisis management tasks of civil emergency teams and armed forces in disaster management by providing multi spectral, near real-time airborne image data products. As time, flexibility and reliability as well as objective information are crucial aspects in emergency management, the used components are tailored to meet these requirements. An airborne multi-functional management support system was developed as part of the national funded project AIRWATCH, which enables real-time monitoring of natural disasters based on optical and thermal images. Airborne image acquisition, a broadband line of sight downlink and near real-time processing solutions allow the generation of an up-to-date geo-referenced situation map. Furthermore, this paper presents ongoing developments for innovative extensions and research activities designed to optimize command operations in national and international fire-fighting missions. The ongoing development focuses on the following topics: (1) Development of a multi-level management solution to coordinate and guide different airborne and terrestrial deployed firefighting modules as well as related data processing and data distribution activities. (2) Further, a targeted control of the thermal sensor based on a rotating mirror system to extend the "area performance" (covered area per hour) in time critical situations for the monitoring requirements during forest fire events. (3) Novel computer vision methods for analysis of thermal sensor signatures, which allow an automatic classification of different forest fire types and situations. (4) A module for simulation-based decision support for planning and evaluation of resource usage and the effectiveness of performed fire-fighting measures. (5) Integration of wearable systems to assist ground teams in rescue operations as well as a mobile information system into innovative command and fire-fighting vehicles. In addition, the paper gives an outlook on future perspectives including a first concept for the integration of the near real-time multilevel forest fire fighting management system into an "EU Civil Protection Team" to support the EU civil protection modules and the Emergency Response Coordination Centre in Brussels. Keywords: Airborne sensing, multi sensor imaging, near real-time fire monitoring, simulation-based decision support, forest firefighting management, firefighting impact analysis.

Advances in air quality prediction with the use of integrated systems

NASA Astrophysics Data System (ADS)

Dragani, R.; Benedetti, A.; Engelen, R. J.; Peuch, V. H.

2017-12-01

Recent years have seen the rise of global operational atmospheric composition forecasting systems for several applications including climate monitoring, provision of boundary conditions for regional air quality forecasting, energy sector applications, to mention a few. Typically, global forecasts are provided in the medium-range up to five days ahead and are initialized with an analysis based on satellite data. In this work we present the latest advances in data assimilation using the ECMWF's 4D-Var system extended to atmospheric composition which is currently operational under the Copernicus Atmosphere Monitoring Service of the European Commission. The service is based on acquisition of all relevant data available in near-real-time, the processing of these datasets in the assimilation and the subsequent dissemination of global forecasts at ECMWF. The global forecasts are used by the CAMS regional models as boundary conditions for the European forecasts based on a multi-model ensemble. The global forecasts are also used to provide boundary conditions for other parts of the world (e.g., China) and are freely available to all interested entities. Some of the regional models also perform assimilation of satellite and ground-based observations. All products are assessed, validated and made publicly available on https://atmosphere.copernicus.eu/.

Multi-Decadal Change of Atmospheric Aerosols and Their Effect on Surface Radiation

NASA Technical Reports Server (NTRS)

Chin, Mian; Diehl, Thomas; Tan, Qian; Wild, Martin; Qian, Yun; Yu, Hongbin; Bian, Huisheng; Wang, Weiguo

2012-01-01

We present an investigation on multi-decadal changes of atmospheric aerosols and their effects on surface radiation using a global chemistry transport model along with the near-term to long-term data records. We focus on a 28-year time period of satellite era from 1980 to 2007, during which a suite of aerosol data from satellite observations and ground-based remote sensing and in-situ measurements have become available. We analyze the long-term global and regional aerosol optical depth and concentration trends and their relationship to the changes of emissions" and assess the role aerosols play in the multi-decadal change of solar radiation reaching the surface (known as "dimming" or "brightening") at different regions of the world, including the major anthropogenic source regions (North America, Europe, Asia) that have been experiencing considerable changes of emissions, dust and biomass burning regions that have large interannual variabilities, downwind regions that are directly affected by the changes in the source area, and remote regions that are considered to representing "background" conditions.

Simultaneous all-sky and multi-satellite observations of auroral breakup and magnetic reconnection

NASA Astrophysics Data System (ADS)

Kawashima, T.; Ieda, A.; Machida, S.; Nishimura, Y.; Miura, T.

2017-12-01

A substorm is a large-scale disturbance including auroral breakup in the ionosphere and magnetic reconnection in the magnetotail. Two predominant models of the substorm time history have been proposed: the near-Earth neutral line (NENL) model and the current disruption model. The former is of outside-in type with tailward propagation of the disturbance, whereas the latter is of inside-out type with earthward propagation of the disturbance. To determine such time histories of such substorms using aurora all-sky and magnetotail multi-satellite observations, the National Aeronautics and Space Administration (NASA) is conducting a mission named the "Time History of Events and Macroscale Interactions during Substorms (THEMIS)". The time history of a substorm is expected to be best clarified when satellites are aligned along the tail axis. A substorm occurred under such a satellite distribution on 0743:42 UT February 27, 2009, and we investigated the auroral breakup and fast plasma flows produced by the magnetic reconnection in this substorm. The THEMIS satellites observed that a northward magnetic field variation propagated earthward. Because this earthward propagation is consistent with the NENL model, observation of a substorm onset after the magnetic reconnection was expected. However, the substorm onset was observed in the all-sky images before the magnetic reconnection, as noted in a previous study. In this study, we report that another earthward fast plasma flow occurred before the substorm onset, indicating that another magnetic reconnection occurred before the substorm onset. In addition, we confirm that the above mentioned post-onset magnetic reconnection occurred simultaneously with auroral poleward expansion, within a 1-min period. These results support the NENL model and further suggest that the two-step development of magnetic reconnection is a key component of the substorm time history.

Real Time Space Weather Support for Chandra X-ray Observatory Operations

NASA Technical Reports Server (NTRS)

O'Dell, Stephen L.; Miller, J. Scott; Minow, Joseph I.; Wolk, Scott J.; Aldcroft, Thomas L.; Spitzbart, Bradley D.; Swartz, Douglas A.

2012-01-01

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ("soft", 100-500 keV) protons as Chandra passed through the Earth s radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth's magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (less than 1 MeV) flux in Chandra s high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) satellite at L1, with real-time data provided by NOAA's Space Weather Prediction Center. This presentation will discuss radiation mitigation against proton damage, including models and real-time data sources used to protect the ACIS detector system.

Real Time Space Weather Support for Chandra X-Ray Observatory Operations

NASA Technical Reports Server (NTRS)

O'Dell, Stephen L.; Minow, Joseph I.; Miller, J. Scott; Wolk, Scott J.; Aldcroft, Thomas L.; Spitzbart, Bradley D.; Swartz. Douglas A.

2012-01-01

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ( soft , 100 500 keV) protons as Chandra passed through the Earth s radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth s magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (< 1 MeV) flux in Chandra s high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) satellite at L1, with real-time data provided by NOAA s Space Weather Prediction Center. This presentation describes the radiation mitigation strategies to minimize the proton damage in the ACIS CCD detectors and the importance of real-time data sources that are used to protect the ACIS detector system from space weather events.

Real Time Space Weather Support for Chandra X-ray Observatory Operations

NASA Astrophysics Data System (ADS)

O'Dell, S. L.; Miller, S.; Minow, J. I.; Wolk, S.; Aldcroft, T. L.; Spitzbart, B. D.; Swartz, D. A.

2012-12-01

NASA launched the Chandra X-ray Observatory in July 1999. Soon after first light in August 1999, however, degradation in the energy resolution and charge transfer efficiency of the Advanced CCD Imaging Spectrometer (ACIS) x-ray detectors was observed. The source of the degradation was quickly identified as radiation damage in the charge-transfer channel of the front-illuminated CCDs, by weakly penetrating ("soft", 100-500 keV) protons as Chandra passed through the Earth's radiation belts and ring currents. As soft protons were not considered a risk to spacecraft health before launch, the only on-board radiation monitoring system is the Electron, Proton, and Helium Instrument (EPHIN) which was included on Chandra with the primary purpose of monitoring energetic solar particle events. Further damage to the ACIS detector has been successfully mitigated through a combination of careful mission planning, autonomous on-board radiation protection, and manual intervention based upon real-time monitoring of the soft-proton environment. The AE-8 and AP-8 trapped radiation models and Chandra Radiation Models are used to schedule science operations in regions of low proton flux. EPHIN has been used as the primary autonomous in-situ radiation trigger; but, it is not sensitive to the soft protons that damage the front-illuminated CCDs. Monitoring of near-real-time space weather data sources provides critical information on the proton environment outside the Earth's magnetosphere due to solar proton events and other phenomena. The operations team uses data from the Geostationary Operational Environmental Satellites (GOES) to provide near-real-time monitoring of the proton environment; however, these data do not give a representative measure of the soft-proton (< 1 MeV) flux in Chandra's high elliptical orbit. The only source of relevant measurements of sub-MeV protons is the Electron, Proton, and Alpha Monitor (EPAM) aboard the Advanced Composition Explorer (ACE) satellite at L1, with real-time data provided by NOAA's Space Weather Prediction Center. This presentation will discuss radiation mitigation against proton damage, including models and real-time data sources used to protect the ACIS detector system.

Real-time Integration of Biological, Optical and Physical Oceanographic Data from Multiple Vessels and Nearshore Sites using a Wireless Network

DTIC Science & Technology

1997-09-30

field experiments in Puget Sound . Each research vessel will use multi- sensor profiling instrument packages which obtain high-resolution physical...field deployment of the wireless network is planned for May-July, 1998, at Orcas Island, WA. IMPACT We expect that wireless communication systems will...East Sound project to be a first step toward continental shelf and open ocean deployments with the next generation of wireless and satellite

High accuracy satellite drag model (HASDM)

NASA Astrophysics Data System (ADS)

Storz, M.; Bowman, B.; Branson, J.

The dominant error source in the force models used to predict low perigee satellite trajectories is atmospheric drag. Errors in operational thermospheric density models cause significant errors in predicted satellite positions, since these models do not account for dynamic changes in atmospheric drag for orbit predictions. The Air Force Space Battlelab's High Accuracy Satellite Drag Model (HASDM) estimates and predicts (out three days) a dynamically varying high-resolution density field. HASDM includes the Dynamic Calibration Atmosphere (DCA) algorithm that solves for the phases and amplitudes of the diurnal, semidiurnal and terdiurnal variations of thermospheric density near real-time from the observed drag effects on a set of Low Earth Orbit (LEO) calibration satellites. The density correction is expressed as a function of latitude, local solar time and altitude. In HASDM, a time series prediction filter relates the extreme ultraviolet (EUV) energy index E10.7 and the geomagnetic storm index a p to the DCA density correction parameters. The E10.7 index is generated by the SOLAR2000 model, the first full spectrum model of solar irradiance. The estimated and predicted density fields will be used operationally to significantly improve the accuracy of predicted trajectories for all low perigee satellites.

High accuracy satellite drag model (HASDM)

NASA Astrophysics Data System (ADS)

Storz, Mark F.; Bowman, Bruce R.; Branson, Major James I.; Casali, Stephen J.; Tobiska, W. Kent

The dominant error source in force models used to predict low-perigee satellite trajectories is atmospheric drag. Errors in operational thermospheric density models cause significant errors in predicted satellite positions, since these models do not account for dynamic changes in atmospheric drag for orbit predictions. The Air Force Space Battlelab's High Accuracy Satellite Drag Model (HASDM) estimates and predicts (out three days) a dynamically varying global density field. HASDM includes the Dynamic Calibration Atmosphere (DCA) algorithm that solves for the phases and amplitudes of the diurnal and semidiurnal variations of thermospheric density near real-time from the observed drag effects on a set of Low Earth Orbit (LEO) calibration satellites. The density correction is expressed as a function of latitude, local solar time and altitude. In HASDM, a time series prediction filter relates the extreme ultraviolet (EUV) energy index E10.7 and the geomagnetic storm index ap, to the DCA density correction parameters. The E10.7 index is generated by the SOLAR2000 model, the first full spectrum model of solar irradiance. The estimated and predicted density fields will be used operationally to significantly improve the accuracy of predicted trajectories for all low-perigee satellites.

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time

PubMed Central

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-01-01

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90–94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7–5.6% per millisecond, with most satellites acquired successfully. PMID:29495301

Low Computational Signal Acquisition for GNSS Receivers Using a Resampling Strategy and Variable Circular Correlation Time.

PubMed

Zhang, Yeqing; Wang, Meiling; Li, Yafeng

2018-02-24

For the objective of essentially decreasing computational complexity and time consumption of signal acquisition, this paper explores a resampling strategy and variable circular correlation time strategy specific to broadband multi-frequency GNSS receivers. In broadband GNSS receivers, the resampling strategy is established to work on conventional acquisition algorithms by resampling the main lobe of received broadband signals with a much lower frequency. Variable circular correlation time is designed to adapt to different signal strength conditions and thereby increase the operation flexibility of GNSS signal acquisition. The acquisition threshold is defined as the ratio of the highest and second highest correlation results in the search space of carrier frequency and code phase. Moreover, computational complexity of signal acquisition is formulated by amounts of multiplication and summation operations in the acquisition process. Comparative experiments and performance analysis are conducted on four sets of real GPS L2C signals with different sampling frequencies. The results indicate that the resampling strategy can effectively decrease computation and time cost by nearly 90-94% with just slight loss of acquisition sensitivity. With circular correlation time varying from 10 ms to 20 ms, the time cost of signal acquisition has increased by about 2.7-5.6% per millisecond, with most satellites acquired successfully.

Science Discoveries Enabled by Hosting Optical Imagers on Commercial Satellite Constellations

NASA Astrophysics Data System (ADS)

Erlandson, R. E.; Kelly, M. A.; Hibbitts, C.; Kumar, C.; Dyrud, L. P.

2012-12-01

The advent of commercial space activities that utilize large space-based constellations provide a new and cost effective opportunity to acquire multi-point observations. Previously, a custom designed space-based constellation, while technically feasible, would require a substantial monetary investment. However, commercial industry has now been entertaining the concept of hosting payloads on their space-based constellations resulting in low-cost access to space. Examples, include the low Earth orbit Iridium Next constellation as well as communication satellites in geostationary. In some of these constellations data distribution can be provided in real time, a feature relevant to applications in the areas of space weather and disaster monitoring. From the perspective of new scientific discoveries enabled by low cost access to space, the cost and thus value proposition is dramatically changed. For example, a constellation of sixty-six satellites (Iridium Next), hosting a single band or multi-spectral imager can now provide observations of the aurora with a spatial resolution of a few hundred meters at all local times and in both hemispheres simultaneously. Remote sensing of clouds is another example where it is now possible to acquire global imagery at resolutions between 100-1000m. Finally, land use imagery is another example where one can use either imaging or spectrographic imagers to solve a multitude of problems. In this work, we will discuss measurement architectures and the multi-disciplinary scientific discoveries that are enable by large space based constellations.

Real-Time Continuous Response Spectra Exceedance Calculation

NASA Astrophysics Data System (ADS)

Vernon, Frank; Harvey, Danny; Lindquist, Kent; Franke, Mathias

2017-04-01

A novel approach is presented for near real-time earthquake alarms for critical structures at distributed locations using real-time estimation of response spectra obtained from near free-field motions. Influential studies dating back to the 1980s identified spectral response acceleration as a key ground motion characteristic that correlates well with observed damage in structures. Thus, monitoring and reporting on exceedance of spectra-based thresholds are useful tools for assessing the potential for damage to facilities or multi-structure campuses based on input ground motions only. With as little as one strong-motion station per site, this scalable approach can provide rapid alarms on the damage status of remote towns, critical infrastructure (e.g., hospitals, schools) and points of interests (e.g., bridges) for a very large number of locations enabling better rapid decision making during critical and difficult immediate post-earthquake response actions. Real-time calculation of PSA exceedance and alarm dissemination are enabled with Bighorn, a module included in the Antelope software package that combines real-time spectral monitoring and alarm capabilities with a robust built-in web display server. Examples of response spectra from several M 5 events recorded by the ANZA seismic network in southern California will be presented.

System for near real-time crustal deformation monitoring

NASA Technical Reports Server (NTRS)

Macdoran, P. F. (Inventor)

1979-01-01

A system is described for use in detecting earth crustal deformation using an RF interferometer technique for such purposes as earthquake predictive research and eventual operational predictions. A lunar based RF transmission or transmissions from earth orbiting satellites are received at two locations on Earth, and a precise time dependent phase measurement is made of the RF signal as received at the two locations to determine two or three spatial parameters of the antenna relative positions. The received data are precisely time tagged and land-line routed to a central station for real-time phase comparison and analysis. By monitoring the antenna relative positions over an extended period of months or years, crustal deformation of the Earth can be detected.

Near Real Time Integration of Satellite and Radar Data for Probabilistic Nearcasting of Severe Weather

NASA Astrophysics Data System (ADS)

Pilone, D.; Quinn, P.; Mitchell, A. E.; Baynes, K.; Shum, D.

2014-12-01

This talk introduces the audience to some of the very real challenges associated with visualizing data from disparate data sources as encountered during the development of real world applications. In addition to the fundamental challenges of dealing with the data and imagery, this talk discusses usability problems encountered while trying to provide interactive and user-friendly visualization tools. At the end of this talk the audience will be aware of some of the pitfalls of data visualization along with tools and techniques to help mitigate them. There are many sources of variable resolution visualizations of science data available to application developers including NASA's Global Imagery Browse Services (GIBS), however integrating and leveraging visualizations in modern applications faces a number of challenges, including: - Varying visualized Earth "tile sizes" resulting in challenges merging disparate sources - Multiple visualization frameworks and toolkits with varying strengths and weaknesses - Global composite imagery vs. imagery matching EOSDIS granule distribution - Challenges visualizing geographically overlapping data with different temporal bounds - User interaction with overlapping or collocated data - Complex data boundaries and shapes combined with multi-orbit data and polar projections - Discovering the availability of visualizations and the specific parameters, color palettes, and configurations used to produce them In addition to discussing the challenges and approaches involved in visualizing disparate data, we will discuss solutions and components we'll be making available as open source to encourage reuse and accelerate application development.

15 Years of Terra, 14 Years of Application Usage

NASA Astrophysics Data System (ADS)

Schmaltz, J. E.; Alarcon, C.; Boller, R. A.; Cechini, M. F.; Davies, D.; Fu, G.; Gunnoe, T.; Hall, J. R.; Huang, T.; Ilavajhala, S.; Jackson, M.; King, J.; McGann, M.; Murphy, K. J.; Roberts, J. T.; Thompson, C. K.; Ye, G.

2014-12-01

The instruments onboard the Terra spacecraft were designed for long-term Earth science research but not long after launch it became apparent that this data and imagery could be made available in near real-time for applications users. During the year 2000 fire season in the western United States, the US Forest Service approached NASA with a request to expedite MODIS fire detections. The Rapid Response system was created to generate fire detections as well as true color imagery in both swath and geo-referenced formats. This imagery was used by a wide variety of applications, such as NASA's AERONET program, the USDA Foreign Agricultural Service, Antarctic resupply shipping, flood mapping for relief agencies, Deepwater Horizon monitoring, volcanic ash monitoring, as well as print, televised, and Internet media. From 2004, the University of Maryland's Web Fire Mapper helped distribute fire detection information in a variety of formats. However, the applications community expressed the need for near-real time access to the underlying data. This requirement led to the development of the Land Atmosphere Near real-time Capability for EOS (Earth Observing System) (LANCE) in 2009. To achieve the latency requirements, many components of the EOS satellite operations, ground and science processing systems had to be made more efficient. In addition, products that require ancillary data were modified to use alternate inputs. Forty Terra MODIS data products are currently available from LANCE. LANCE also includes data from other instruments including AIRS, AMSR-E, MLS, and OMI. To help near-real time users navigate this large data offering, a new imagery service was begun in 2011 - Global Imagery Browse Services (GIBS). This service provides very responsive viewing using the Web Map Tile Service protocol. These programs will continue to support and expand the use of Terra data for near-real time applications well into the future.

Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

PubMed

Wei, Yawei; Venayagamoorthy, Ganesh Kumar

2017-09-01

To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

ISKANDARnet IOMOS: Near real-time equatorial space weather monitoring and alert system in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Musa, Tajul Ariffin; Leong, Shien Kwun; Abdullah, Khairul Anuar; Othman, Rusli

2012-11-01

This work proposes ISKANDARnet Ionospheric Outburst MOnitoring and alert System (IOMOS), along with Ionospheric Outburst Index (IOX) to develop an operational near real-time space weather service for Malaysia. The IOMOS is based on Global Positioning System (GPS) Network-based Real-Time Kinematic (NRTK) concept which is by nature for atmospheric (ionosphere and troposphere) modeling within the network coverage. The elegance of this solution lies in the fact that IOMOS utilize differential ionospheric residual from network of GPS baselines which incur no additional cost for operation. Users will be informed about the ionospheric perturbation through Short Message Service (SMS), email or Twitter®. This approach will ultimately beneficial for the navigation and satellite positioning communities, particularly during the coming Solar Cycle 24. In addition, a combination of local and global GPS network has been employed to study the equatorial ionosphere geomorphology and climatology in the Malaysian sector. Equatorial Total Electron Content (TEC) over Malaysia shows semi-annual, annual, and seasonal variations with maximum values appearing during equinoctial months and minimum during solstices months. The TEC value during vernal equinox is about 21% higher than autumnal equinox, and December solstice exceeds that at the June solstice by around 14%. It is also found that semi-annual variation is present at all levels of solar activity, whereas June solstice predominates December solstice during high solar activity for annual and seasonal variations. In near future, a near real-time TEC derivation system will be developed to support equatorial ionosphere modeling to enhance space weather service for Malaysia.

A Survey of Geosynchronous Satellite Glints

NASA Astrophysics Data System (ADS)

Vrba, F.; Hutter, D.; Shankland, P.; Armstrong, J.; Schmitt, H.; Hindsley, R.; Divittorio, M.; Benson, J.

Artificial satellites have characteristic diffuse reflected-light signatures as they are illuminated at varying phase angles by the Sun and are viewed at differing orientations by an observer. At times of favorable alignment between the satellite, observer and Sun, specular reflection off of relatively flat surfaces, such as solar panels, can cause brief increases in reflected light of several hundred times that of the nominal diffuse signature. Such events are commonly referred to as "glints". In the case of geosynchronous satellites, favorable glint alignments are due to changes in the Sun-Vehicle-Observer angle which are primarily due to the apparent motion of the Sun as the observer-satellite vector remains nearly stationary. These occur near in time to the vernal and autumnal equinoxes. While the most favorable geosynchronous satellite glint alignments are precluded by the fact that the satellites are at that time most likely to be in Earth shadow, observations of several glints have been reported in the literature. While such studies note the peak brightnesses, durations, and phase angles of individual glints, to our knowledge, no extended study of geosynchronous glint characteristics exists. Beginning with the autumnal equinox glint season of 2007 we have built on our earlier studies using the U.S. Naval Observatory, Flagstaff Station 40-inch Ritchey telescope to provide near-real-time astrometric and photometric information for use by the Navy Prototype Optical Interferometer (NPOI) team in its efforts to obtain interferometric fringes of geosynchronous satellites during a glint episode. The combined observations culminated in successful fringe measurements of DirecTV-9S during the vernal equinox 2008 and 2009 seasons (see Armstrong, et al. 2009, this conference). For our 40-inch telescope observations we used an LN2-cooled 2048x2048 CCD with standard R-band and H-alpha photometric filters, covering an area of the sky of approximately 22x22 arcmin with each integration. Observations typically were initiated well before a predicted potential glint and continued through the glint occurrence (if any) for our secondary goal of estimating peak glint brightnesses. As we were using photometric equipment, took care to obtain photometric calibrations, and were fortunate to have observed on several photometric nights, we have calibrated, time-resolved observations of numerous glint episodes, dominated by the GE2/GE4/DTV4S/DTV9S constellation. In particular, we will discuss systematic differences between glints from different satellites, comparison of glints from the same satellite during different epochs, and the time evolution of glints from DirecTV-9S during the 2009 vernal equinox observing season.

Visualization of multi-INT fusion data using Java Viewer (JVIEW)

NASA Astrophysics Data System (ADS)

Blasch, Erik; Aved, Alex; Nagy, James; Scott, Stephen

2014-05-01

Visualization is important for multi-intelligence fusion and we demonstrate issues for presenting physics-derived (i.e., hard) and human-derived (i.e., soft) fusion results. Physics-derived solutions (e.g., imagery) typically involve sensor measurements that are objective, while human-derived (e.g., text) typically involve language processing. Both results can be geographically displayed for user-machine fusion. Attributes of an effective and efficient display are not well understood, so we demonstrate issues and results for filtering, correlation, and association of data for users - be they operators or analysts. Operators require near-real time solutions while analysts have the opportunities of non-real time solutions for forensic analysis. In a use case, we demonstrate examples using the JVIEW concept that has been applied to piloting, space situation awareness, and cyber analysis. Using the open-source JVIEW software, we showcase a big data solution for multi-intelligence fusion application for context-enhanced information fusion.

Fast data reconstructed method of Fourier transform imaging spectrometer based on multi-core CPU

NASA Astrophysics Data System (ADS)

Yu, Chunchao; Du, Debiao; Xia, Zongze; Song, Li; Zheng, Weijian; Yan, Min; Lei, Zhenggang

2017-10-01

Imaging spectrometer can gain two-dimensional space image and one-dimensional spectrum at the same time, which shows high utility in color and spectral measurements, the true color image synthesis, military reconnaissance and so on. In order to realize the fast reconstructed processing of the Fourier transform imaging spectrometer data, the paper designed the optimization reconstructed algorithm with OpenMP parallel calculating technology, which was further used for the optimization process for the HyperSpectral Imager of `HJ-1' Chinese satellite. The results show that the method based on multi-core parallel computing technology can control the multi-core CPU hardware resources competently and significantly enhance the calculation of the spectrum reconstruction processing efficiency. If the technology is applied to more cores workstation in parallel computing, it will be possible to complete Fourier transform imaging spectrometer real-time data processing with a single computer.

Daytime Sky Brightness Characterization for Persistent GEO SSA

NASA Astrophysics Data System (ADS)

Thomas, G.; Cobb, R. G.

Space Situational Awareness (SSA) is fundamental to operating in space. SSA for collision avoidance ensures safety of flight for both government and commercial spacecraft through persistent monitoring. A worldwide network of optical and radar sensors gather satellite ephemeris data from the nighttime sky. Current practice for daytime satellite tracking is limited exclusively to radar as the brightening daytime sky prevents the use of visible-band optical sensors. Radar coverage is not pervasive and results in significant daytime coverage gaps in SSA. To mitigate these gaps, optical telescopes equipped with sensors in the near-infrared band (0.75-0.9m) may be used. The diminished intensity of the background sky radiance in the near-infrared band may allow for daylight tracking further into the twilight hours. To determine the performance of a near-infrared sensor for daylight custody, the sky background radiance must first be characterized spectrally as a function of wavelength. Using a physics-based atmospheric model with access to near-real time weather, we developed a generalized model for the apparent sky brightness of the Geostationary satellite belt. The model results are then compared to measured data collected from Dayton, OH through various look and Sun angles for model validation and spectral sky radiance quantification in the visible and near-infrared bands.

Real-Time Tracking of the Extreme Rainfall of Hurricanes Harvey, Irma, and Maria using UCI CHRS's iRain System

NASA Astrophysics Data System (ADS)

Shearer, E. J.; Nguyen, P.; Ombadi, M.; Palacios, T.; Huynh, P.; Furman, D.; Tran, H.; Braithwaite, D.; Hsu, K. L.; Sorooshian, S.; Logan, W. S.

2017-12-01

During the 2017 hurricane season, three major hurricanes-Harvey, Irma, and Maria-devastated the Atlantic coast of the US and the Caribbean Islands. Harvey set the record for the rainiest storm in continental US history, Irma was the longest-lived powerful hurricane ever observed, and Maria was the costliest storm in Puerto Rican history. The recorded maximum precipitation totals for these storms were 65, 16, and 20 inches respectively. These events provided the Center for Hydrometeorology and Remote Sensing (CHRS) an opportunity to test its global real-time satellite precipitation observation system, iRain, for extreme storm events. The iRain system has been under development through a collaboration between CHRS at the University of California, Irvine (UCI) and UNESCO's International Hydrological Program (IHP). iRain provides near real-time high resolution (0.04°, approx. 4km) global (60°N - 60°S) satellite precipitation data estimated by the PERSIANN-Cloud Classification System (PERSIANN-CCS) algorithm developed by the scientists at CHRS. The user-interactive and web-accessible iRain system allows users to visualize and download real-time global satellite precipitation estimates and track the development and path of the current 50 largest storms globally from data generated by the PERSIANN-CCS algorithm. iRain continuously proves to be an effective tool for measuring real-time precipitation amounts of extreme storms-especially in locations that do not have extensive rain gauge or radar coverage. Such areas include large portions of the world's oceans and over continents such as Africa and Asia. CHRS also created a mobile app version of the system named "iRain UCI", available for iOS and Android devices. During these storms, real-time rainfall data generated by PERSIANN-CCS was consistently comparable to radar and rain gauge data. This presentation evaluates iRain's efficiency as a tool for extreme precipitation monitoring and provides an evaluation of the PERSIANN-CCS real-time rainfall estimates during Hurricanes Harvey, Irma, and Maria in relation to radar and rain gauge data using continuous (correlation, root mean square error, and bias) and categorical (POD and FAR) indices. These results present the relative skill of PERSIANN-CCS real-time data to radar and rain gauge data.

Quantitative assessment of urban wetland dynamics using high spatial resolution satellite imagery between 2000 and 2013.

PubMed

Hu, Tangao; Liu, Jiahong; Zheng, Gang; Li, Yao; Xie, Bin

2018-05-09

Accurate and timely information describing urban wetland resources and their changes over time, especially in rapidly urbanizing areas, is becoming more important. We applied an object-based image analysis and nearest neighbour classifier to map and monitor changes in land use/cover using multi-temporal high spatial resolution satellite imagery in an urban wetland area (Hangzhou Xixi Wetland) from 2000, 2005, 2007, 2009 and 2013. The overall eight-class classification accuracies averaged 84.47% for the five years. The maps showed that between 2000 and 2013 the amount of non-wetland (urban) area increased by approximately 100%. Herbaceous (32.22%), forest (29.57%) and pond (23.85%) are the main land-cover types that changed to non-wetland, followed by cropland (6.97%), marsh (4.04%) and river (3.35%). In addition, the maps of change patterns showed that urban wetland loss is mainly distributed west and southeast of the study area due to real estate development, and the greatest loss of urban wetlands occurred from 2007 to 2013. The results demonstrate the advantages of using multi-temporal high spatial resolution satellite imagery to provide an accurate, economical means to map and analyse changes in land use/cover over time and the ability to use the results as inputs to urban wetland management and policy decisions.

Ash Emissions and Risk Management in the Pacific Ocean

NASA Astrophysics Data System (ADS)

Steensen, T. S.; Webley, P. W.; Stuefer, M.

2012-12-01

Located in the 'Ring of Fire', regions and communities around the Pacific Ocean often face volcanic eruptions and subsequent ash emissions. Volcanic ash clouds pose a significant risk to aviation, especially in the highly-frequented flight corridors around active volcano zones like Indonesia or Eastern Russia and the Alaskan Aleutian Islands. To mitigate and manage such events, a detailed quantitative analysis using a range of scientific measurements, including satellite data and Volcanic Ash Transport and Dispersion (VATD) model results, needs to be conducted in real-time. For the case study of the Sarychev Peak eruption in Russia's Kurile Islands during 2009, we compare ash loading and dispersion from Weather Research and Forecast model with online Chemistry (WRF-Chem) results with satellite data of the eruption. These parameters are needed for the real-time management of volcanic crises to outline no-fly zones and to predict the areas that the ash is most likely to reach in the near future. In the early stages after the eruption, an international group with representatives from the Kamchatkan and Sachalin Volcanic Eruption Response Teams (KVERT, SVERT), the National Aeronautics and Space Administration (NASA), and the Alaska Volcano Observatory (AVO) published early research on the geological and geophysical characteristics of the eruption and the behavior of the resulting ash clouds. The study presented here is a follow-up project aimed to implement VATD model results and satellite data retrospectively to demonstrate the possibilities to develop this approach in real-time for future eruptions. Our research finds that, although meteorological cloud coverage is high in those geographical regions and, consequently, these clouds can cover most of the ash clouds and as such prevent satellites from detecting it, both approaches compare well and supplement each other to reduce the risk of volcanic eruptions. We carry out spatial extent and absolute quantitative comparisons and analyze the sensitivity of model inputs, such as eruption rate and vertical particle size distributions. Our analysis shows that comparisons between real-time satellite observations and VATD model simulations is a complex and difficult process and we present several methods that could be used to reduce the hazards and be useful in any risk assessments.

ERP Estimation using a Kalman Filter in VLBI

NASA Astrophysics Data System (ADS)

Karbon, M.; Soja, B.; Nilsson, T.; Heinkelmann, R.; Liu, L.; Lu, C.; Mora-Diaz, J. A.; Raposo-Pulido, V.; Xu, M.; Schuh, H.

2014-12-01

Geodetic Very Long Baseline Interferometry (VLBI) is one of the primary space geodetic techniques, providing the full set of Earth Orientation Parameters (EOP), and it is unique for observing long term Universal Time (UT1). For applications such as satellite-based navigation and positioning, accurate and continuous ERP obtained in near real-time are essential. They also allow the precise tracking of interplanetary spacecraft. One of the goals of VGOS (VLBI Global Observing System) is to provide such near real-time ERP. With the launch of this next generation VLBI system, the International VLBI Service for Geodesy and Astrometry (IVS) increased its efforts not only to reach 1 mm accuracy on a global scale but also to reduce the time span between the collection of VLBI observations and the availability of the final results substantially. Project VLBI-ART contributes to these objectives by implementing an elaborate Kalman filter, which represents a perfect tool for analyzing VLBI data in quasi real-time. The goal is to implement it in the GFZ version of the Vienna VLBI Software (VieVS) as a completely automated tool, i.e., with no need for human interaction. Here we present the methodology and first results of Kalman filtered EOP from VLBI data.

Automated flood extent identification using WorldView imagery for the insurance industry

NASA Astrophysics Data System (ADS)

Geller, Christina

2017-10-01

Flooding is the most common and costly natural disaster around the world, causing the loss of human life and billions in economic and insured losses each year. In 2016, pluvial and fluvial floods caused an estimated 5.69 billion USD in losses worldwide with the most severe events occurring in Germany, France, China, and the United States. While catastrophe modeling has begun to help bridge the knowledge gap about the risk of fluvial flooding, understanding the extent of a flood - pluvial and fluvial - in near real-time allows insurance companies around the world to quantify the loss of property that their clients face during a flooding event and proactively respond. To develop this real-time, global analysis of flooded areas and the associated losses, a new methodology utilizing optical multi-spectral imagery from DigitalGlobe (DGI) WorldView satellite suite is proposed for the extraction of pluvial and fluvial flood extents. This methodology involves identifying flooded areas visible to the sensor, filling in the gaps left by the built environment (i.e. buildings, trees) with a nearest neighbor calculation, and comparing the footprint against an Industry Exposure Database (IE) to calculate a loss estimate. Full-automation of the methodology allows production of flood extents and associated losses anywhere around the world as required. The methodology has been tested and proven effective for the 2016 flood in Louisiana, USA.

Informatic infrastructure for Climatological and Oceanographic data based on THREDDS technology in a Grid environment

NASA Astrophysics Data System (ADS)

Tronconi, C.; Forneris, V.; Santoleri, R.

2009-04-01

CNR-ISAC-GOS is responsible for the Mediterranean Sea satellite operational system in the framework of MOON Patnership. This Observing System acquires satellite data and produces Near Real Time, Delayed Time and Re-analysis of Ocean Colour and Sea Surface Temperature products covering the Mediterranean and the Black Seas and regional basins. In the framework of several projects (MERSEA, PRIMI, Adricosm Star, SeaDataNet, MyOcean, ECOOP), GOS is producing Climatological/Satellite datasets based on optimal interpolation and specific Regional algorithm for chlorophyll, updated in Near Real Time and in Delayed mode. GOS has built • an informatic infrastructure data repository and delivery based on THREDDS technology The datasets are generated in NETCDF format, compliant with both the CF convention and the international satellite-oceanographic specification, as prescribed by GHRSST (for SST). All data produced, are made available to the users through a THREDDS server catalog. • A LAS has been installed in order to exploit the potential of NETCDF data and the OPENDAP URL. It provides flexible access to geo-referenced scientific data • a Grid Environment based on Globus Technologies (GT4) connecting more than one Institute; in particular exploiting CNR and ESA clusters makes possible to reprocess 12 years of Chlorophyll data in less than one month.(estimated processing time on a single core PC: 9months). In the poster we will give an overview of: • the features of the THREDDS catalogs, pointing out the powerful characteristics of this new middleware that has replaced the "old" OPENDAP Server; • the importance of adopting a common format (as NETCDF) for data exchange; • the tools (e.g. LAS) connected with THREDDS and NETCDF format use. • the Grid infrastructure on ISAC We will present also specific basin-scale High Resolution products and Ultra High Resolution regional/coastal products available on these catalogs.

Tracking, sensing and predicting flood wave propagation using nomadic satellite communication systems and hydrodynamic models

NASA Astrophysics Data System (ADS)

Hostache, R.; Matgen, P.; Giustarini, L.; Tailliez, C.; Iffly, J.-F.

2011-11-01

The main objective of this study is to contribute to the development and the improvement of flood forecasting systems. Since hydrometric stations are often poorly distributed for monitoring the propagation of extreme flood waves, the study aims at evaluating the hydrometric value of the Global Navigation Satellite System (GNSS). Integrated with satellite telecommunication systems, drifting or anchored floaters equipped with navigation systems such as GPS and Galileo, enable the quasi-continuous measurement and near real-time transmission of water level and flow velocity data, from virtually any point in the world. The presented study investigates the effect of assimilating GNSS-derived water level and flow velocity measurements into hydraulic models in order to reduce the associated predictive uncertainty.

A seismic signal processor suitable for use with the NOAA/GOES satellite data collection system

NASA Technical Reports Server (NTRS)

Webster, W. J., Jr.; Miller, W. H.; Whitley, R.; Allenby, R. J.; Dennison, R. T.

1981-01-01

Because of the high data-rate requirements, a practical system capable of collecting seismic information in the field and relaying it, via satellite, to a central collection point is not yet available. A seismic signal processor has been developed and tested for use with the NOAA/GOES satellite data collection system. Performance tests on recorded, as well as real time, short period signals indicate that the event recognition technique used is nearly perfect in its rejection of environmental noise and other non-seismic signals and that, with the use of solid state buffer memories, data can be acquired in many swarm situations. The design of a complete field data collection platform is discussed based on the prototype evaluation.

Using Landsat satellite data to support pesticide exposure assessment in California

USGS Publications Warehouse

Maxwell, Susan K.; Airola, Matthew; Nuckols, John R.

2010-01-01

We found the combination of Landsat 5 and 7 image data would clearly benefit pesticide exposure assessment in this region by 1) providing information on crop field conditions at or near the time when pesticides are applied, and 2) providing information for validating the CDWR map. The Landsat image time-series was useful for identifying idle, single-, and multi-cropped fields. Landsat data will be limited during the winter months due to cloud cover, and for years prior to the Landsat 7 launch (1999) when only one satellite was operational at any given time. We suggest additional research to determine the feasibility of integrating CDWR land use maps and Landsat data to derive crop maps in locations and time periods where maps are not available, which will allow for substantial improvements to chemical exposure estimation.

Operational Derivation of Surface Albedo and Down-Welling Short-Wave Radiation in the Satellite Application Facility for Land Surface Analysis

NASA Astrophysics Data System (ADS)

Geiger, B.; Carrer, D.; Meurey, C.; Roujean, J.-L.

2006-08-01

The Satellite Application Facility for Land Surface Anal- ysis hosted by the Portuguese Meteorological Institute in Lisbon generates and distributes value added satellite products for numerical weather prediction and environ- mental applications in near-real time. Within the project consortium M´et´eo-France is responsible for the land sur- face albedo and down-welling short-wave radiation flux products. Since the beginning of the year 2005 Meteosat Second Generation data are routinely processed by the Land-SAF operational system. In general the validation studies carried out so far show a good consistency with in-situ observations or equivalent products derived from other satellites. After one year of operations a summary of the product characteristics and performances is given. Key words: Surface Albedo; Down-welling Radiation; Land-SAF.

Real-time monitoring and warning for natural hazards can provide real-time benefits

NASA Astrophysics Data System (ADS)

Showstack, Randy

Downhill from a golf driving range on Maryland's Interstate 70 highway near the city of Frederick, U.S. Geological Survey (USGS) hydrologic technicians Richard Saffer and Robert Pentz strode along a short path and over a steel walkway for a site visit to a concrete gage house near the Monocacy River.Gage house #01643000 sits on top of a stilling well that reaches about 8.5 m above the normal flow stage of the river. Inside the house are floats to lower down the well shaft, a hand pump, pipes leading into the river, and other basic technology befitting a structure built in 1929. But the station also is equipped with a modern data collecting platform, an antenna link to transmit data to geostationary operations environmental satellites (GOES), a modem connection, and other high-tech tools of the trade.

GNSS Radio Occultation Observations as a data source for Ionospheric Assimilation: COSMIC-1 & COSMIC-2

NASA Astrophysics Data System (ADS)

Yue, X.; Schreiner, W. S.; Kuo, Y. H.

2014-12-01

Since the pioneer GPS/MET mission, low Earth orbit (LEO) based global navigation satellite system (GNSS) Radio Occultation (RO) technique has been a powerful technique in ionosphere monitoring. After that, many LEO satellites were launched with RO payload, include: CHAMP , GRACE, SAC-C/D, COSMIC, C/NOFS, Metop-A/B, TerraSAR-X/TanDEM-X, and etc. COSMIC was the first constellation of satellites dedicated primarily to RO and delivering RO data in near real time. Currently in UCAR CDAAC, we process most of these missions' RO data for the community. Due to the success of COSMIC mission, a follow on mission called COSMIC-2 will be launched in 2016 and 2018, respectively. The COSMIC-2 RO data will be 4-6 times of COSMIC due to the doubled satellite and GNSS signals. In this paper we will describe: (1) Data process and quality in UCAR/CDAAC; (2) Ionospheric data assimilation results based on COSMIC data; (3) OSSE study for COSMIC-2.

Automated Historical and Real-Time Cyclone Discovery With Multimodal Remote Satellite Measurements

NASA Astrophysics Data System (ADS)

Ho, S.; Talukder, A.; Liu, T.; Tang, W.; Bingham, A.

2008-12-01

Existing cyclone detection and tracking solutions involve extensive manual analysis of modeled-data and field campaign data by teams of experts. We have developed a novel automated global cyclone detection and tracking system by assimilating and sharing information from multiple remote satellites. This unprecedented solution of combining multiple remote satellite measurements in an autonomous manner allows leveraging off the strengths of each individual satellite. Use of multiple satellite data sources also results in significantly improved temporal tracking accuracy for cyclones. Our solution involves an automated feature extraction and machine learning technique based on an ensemble classifier and Kalman filter for cyclone detection and tracking from multiple heterogeneous satellite data sources. Our feature-based methodology that focuses on automated cyclone discovery is fundamentally different from, and actually complements, the well-known Dvorak technique for cyclone intensity estimation (that often relies on manual detection of cyclonic regions) from field and remote data. Our solution currently employs the QuikSCAT wind measurement and the merged level 3 TRMM precipitation data for automated cyclone discovery. Assimilation of other types of remote measurements is ongoing and planned in the near future. Experimental results of our automated solution on historical cyclone datasets demonstrate the superior performance of our automated approach compared to previous work. Performance of our detection solution compares favorably against the list of cyclones occurring in North Atlantic Ocean for the 2005 calendar year reported by the National Hurricane Center (NHC) in our initial analysis. We have also demonstrated the robustness of our cyclone tracking methodology in other regions over the world by using multiple heterogeneous satellite data for detection and tracking of three arbitrary historical cyclones in other regions. Our cyclone detection and tracking methodology can be applied to (i) historical data to support Earth scientists in climate modeling, cyclonic-climate interactions, and obtain a better understanding of the cause and effects of cyclone (e.g. cyclo-genesis), and (ii) automatic cyclone discovery in near real-time using streaming satellite to support and improve the planning of global cyclone field campaigns. Additional satellite data from GOES and other orbiting satellites can be easily assimilated and integrated into our automated cyclone detection and tracking module to improve the temporal tracking accuracy of cyclones down to ½ hr and reduce the incidence of false alarms.

Real-time Monitoring of 2017 Hurricanes and Typhoons with Lightning

NASA Astrophysics Data System (ADS)

Solorzano, N. N.; Thomas, J. N.; Bracy, C.; Holzworth, R. H., II

2017-12-01

The 2017 Atlantic season had the highest number of major hurricanes since 2005. To tackle the demand of real-time tropical cyclone (TC) monitoring, our group has developed a unique "storm-following" satellite and ground-based lightning product known as WWLLN-TC (World Wide Lightning Location Network - Tropical Cyclones; http://wwlln.net/storms/). In the present study, we explore this tool and other datasets, combining lightning and microwave data to quantify areas of intense convection in 2017 TCs Harvey, Hato, Irma, Maria, Nate, Ophelia and others. For each storm, the temporal distribution of discharges outside and within the inner core is compared to the changes in TC intensity. The intensification processes, monitored in near real-time by WWLLN-TC, are quantified in terms of pressure and/or wind speed changes. A peak in lightning activity is often observed in the inner core of TCs before and during rapid weakening, such as in Hurricanes Irma and Maria and Typhoon Hato. The microwave frequencies investigated include the 37 to 183 GHz channels of the satellite sensors DMSP/SSMIS and GPM/GMI. We reconstruct brightness temperatures from lightning data, providing more detailed pictures of the evolution of TCs at moments when satellite passes are missing or incomplete. This study also compares lightning activity in the inner core with convective and environmental parameters. Examples of environmental parameters discussed are sea surface temperature, wind shear, and sea surface height anomalies. We conclude by considering possible implications of WWLLN-TC on forecasts of rapid intensity change and rainfall.

Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria

NASA Astrophysics Data System (ADS)

O, Sungmin; Foelsche, Ulrich; Kirchengast, Gottfried; Fuchsberger, Juergen; Tan, Jackson; Petersen, Walter A.

2017-12-01

The Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) products provide quasi-global (60° N-60° S) precipitation estimates, beginning March 2014, from the combined use of passive microwave (PMW) and infrared (IR) satellites comprising the GPM constellation. The IMERG products are available in the form of near-real-time data, i.e., IMERG Early and Late, and in the form of post-real-time research data, i.e., IMERG Final, after monthly rain gauge analysis is received and taken into account. In this study, IMERG version 3 Early, Late, and Final (IMERG-E,IMERG-L, and IMERG-F) half-hourly rainfall estimates are compared with gauge-based gridded rainfall data from the WegenerNet Feldbach region (WEGN) high-density climate station network in southeastern Austria. The comparison is conducted over two IMERG 0.1° × 0.1° grid cells, entirely covered by 40 and 39 WEGN stations each, using data from the extended summer season (April-October) for the first two years of the GPM mission. The entire data are divided into two rainfall intensity ranges (low and high) and two seasons (warm and hot), and we evaluate the performance of IMERG, using both statistical and graphical methods. Results show that IMERG-F rainfall estimates are in the best overall agreement with the WEGN data, followed by IMERG-L and IMERG-E estimates, particularly for the hot season. We also illustrate, through rainfall event cases, how insufficient PMW sources and errors in motion vectors can lead to wide discrepancies in the IMERG estimates. Finally, by applying the method of Villarini and Krajewski (2007), we find that IMERG-F half-hourly rainfall estimates can be regarded as a 25 min gauge accumulation, with an offset of +40 min relative to its nominal time.

Version 4 IMERG: Investigating Runs and High Latitudes

NASA Astrophysics Data System (ADS)

Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K. L.; Joyce, R.; Kidd, C.; Nelkin, E. J.; Sorooshian, S.; Tan, J.; Xie, P.

2016-12-01

The Integrated Multi-satellitE Retrievals for GPM (IMERG) merged precipitation product is being computed by the U.S. Global Precipitation Measurement mission (GPM) science team, based on intercalibrated estimates from the international constellation of precipitation-relevant satellites and other data. Recently, GPM upgraded the precipitation retrieval algorithms applied to individual sensors, and following that, IMERG was upgraded to Version 4. These data sets are computed at the half hour, 0.1° x 0.1° resolution over the latitude belt 60°N-S. Various latency requirements for different users are accommodated by computing IMERG in three "Runs" - Early, Late, and Final (5 hours, 15 hours, and 2.5 months after observation time, respectively). The near-real-time Early and Late Runs and the research-quality Final Run incorporate increasing amounts of data; examples will highlight the contribution that additional data make for each Run. From Early to Late, the addition of backward propagated data in the Late allows temporally weighted interpolation of forward and backward propagated precipitation, rather than the forward-only extrapolation in the Early. From Late to Final, the major addition is the direct use of monthly precipitation gauge analysis (the Global Precipitation Climatology Centre's Monitoring Analysis), which mitigates the satellite biases over land for the Early and Late. In addition, the new capabilities of the input algorithms at higher latitudes will be discussed, both during the snow season and the summer rain season. These inputs have a dominant role in determining the utility of IMERG in all seasons. Rainfall over non-frozen surface is reasonably well represented, while precipitation over frozen surfaces is still a topic of active research.

ARMOR3D: A 3D multi-observations T,S,U,V product of the ocean

NASA Astrophysics Data System (ADS)

Verbrugge, Nathalie; Mulet, Sandrine; Guinehut, Stéphanie; Buongiorno-Nardelli, Bruno

2017-04-01

To have a synoptic view of the 3D ocean to pursue oceanic studies, an observed gridded product can be often useful instead of using raw observations which can be irregularly distributed in space and time as the in situ profiles for instance or which offer only a surface view of the ocean as satellite data. The originality of the ARMOR3D observation based product is to take advantage of the strengths of these 2 types of data by combining satellite SLA, SST, SSS datasets with in situ T, S vertical profiles in order to build a global 3D weekly temperature, salinity and geostrophic velocities fields at a spatial 1/4° resolution. The mesoscale content of the satellite data and the vertical sampling of the in situ profiles are complementary in this statistical approach. ARMOR3D is part of the CMEMS project through the GLO-OBS component. A full reprocessing from 1993 to 2016 and near-real-time fields from 1/1/2014 to present are available through the CMEMS web portal. The range of applications of this product is wide: OSE studies have been already conducted to evaluate the ARGO network and in 2017, OSE and OSSE will be performed in the western Tropical Pacific as part of the TPOS2020 project (Tropical Pacific Observing System for 2020 Pacific). The product is useful also to study mesoscale eddies characteristics as well as links with the biogeochemical processes. For example, in 2015, ARMOR3D fields have been used as inputs of a micronekton model within the framework of the ESA OSMOSIS Project. Furthermore, ARMOR3D also contributes to the annual CMEMS Ocean State Report.

Precise Point Positioning Using Triple GNSS Constellations in Various Modes

PubMed Central

Afifi, Akram; El-Rabbany, Ahmed

2016-01-01

This paper introduces a new dual-frequency precise point positioning (PPP) model, which combines the observations from three different global navigation satellite system (GNSS) constellations, namely GPS, Galileo, and BeiDou. Combining measurements from different GNSS systems introduces additional biases, including inter-system bias and hardware delays, which require rigorous modelling. Our model is based on the un-differenced and between-satellite single-difference (BSSD) linear combinations. BSSD linear combination cancels out some receiver-related biases, including receiver clock error and non-zero initial phase bias of the receiver oscillator. Forming the BSSD linear combination requires a reference satellite, which can be selected from any of the GPS, Galileo, and BeiDou systems. In this paper three BSSD scenarios are tested; each considers a reference satellite from a different GNSS constellation. Natural Resources Canada’s GPSPace PPP software is modified to enable a combined GPS, Galileo, and BeiDou PPP solution and to handle the newly introduced biases. A total of four data sets collected at four different IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) network are used to correct the GPS, Galileo, and BeiDou measurements in the post-processing PPP mode. A real-time PPP solution is also obtained, which is referred to as RT-PPP in the sequel, through the use of the IGS real-time service (RTS) for satellite orbit and clock corrections. However, only GPS and Galileo observations are used for the RT-PPP solution, as the RTS-IGS satellite products are not presently available for BeiDou system. All post-processed and real-time PPP solutions are compared with the traditional un-differenced GPS-only counterparts. It is shown that combining the GPS, Galileo, and BeiDou observations in the post-processing mode improves the PPP convergence time by 25% compared with the GPS-only counterpart, regardless of the linear combination used. The use of BSSD linear combination improves the precision of the estimated positioning parameters by about 25% in comparison with the GPS-only PPP solution. Additionally, the solution convergence time is reduced to 10 minutes for the BSSD model, which represents about 50% reduction, in comparison with the GPS-only PPP solution. The GNSS RT-PPP solution, on the other hand, shows a similar convergence time and precision to the GPS-only counterpart. PMID:27240376

Precise Point Positioning Using Triple GNSS Constellations in Various Modes.

PubMed

Afifi, Akram; El-Rabbany, Ahmed

2016-05-28

This paper introduces a new dual-frequency precise point positioning (PPP) model, which combines the observations from three different global navigation satellite system (GNSS) constellations, namely GPS, Galileo, and BeiDou. Combining measurements from different GNSS systems introduces additional biases, including inter-system bias and hardware delays, which require rigorous modelling. Our model is based on the un-differenced and between-satellite single-difference (BSSD) linear combinations. BSSD linear combination cancels out some receiver-related biases, including receiver clock error and non-zero initial phase bias of the receiver oscillator. Forming the BSSD linear combination requires a reference satellite, which can be selected from any of the GPS, Galileo, and BeiDou systems. In this paper three BSSD scenarios are tested; each considers a reference satellite from a different GNSS constellation. Natural Resources Canada's GPSPace PPP software is modified to enable a combined GPS, Galileo, and BeiDou PPP solution and to handle the newly introduced biases. A total of four data sets collected at four different IGS stations are processed to verify the developed PPP model. Precise satellite orbit and clock products from the International GNSS Service Multi-GNSS Experiment (IGS-MGEX) network are used to correct the GPS, Galileo, and BeiDou measurements in the post-processing PPP mode. A real-time PPP solution is also obtained, which is referred to as RT-PPP in the sequel, through the use of the IGS real-time service (RTS) for satellite orbit and clock corrections. However, only GPS and Galileo observations are used for the RT-PPP solution, as the RTS-IGS satellite products are not presently available for BeiDou system. All post-processed and real-time PPP solutions are compared with the traditional un-differenced GPS-only counterparts. It is shown that combining the GPS, Galileo, and BeiDou observations in the post-processing mode improves the PPP convergence time by 25% compared with the GPS-only counterpart, regardless of the linear combination used. The use of BSSD linear combination improves the precision of the estimated positioning parameters by about 25% in comparison with the GPS-only PPP solution. Additionally, the solution convergence time is reduced to 10 minutes for the BSSD model, which represents about 50% reduction, in comparison with the GPS-only PPP solution. The GNSS RT-PPP solution, on the other hand, shows a similar convergence time and precision to the GPS-only counterpart.

SSALTO/DUACS: Faster data delivery for operational oceanography and GMES

NASA Astrophysics Data System (ADS)

Dorandeu, J.; Dibarboure, G.; Larnicol, G.; Picot, N.

2008-12-01

This paper describes the DUACS multi-mission system, and its most relevant improvements and changes. Initiated 10 years ago with an EC project, DUACS is now a part of the CNES multi-mission ground segment SSALTO, and the backbone of the Sea Level Thematic Assembly Centre (SL-TAC) of the GMES Marine Core Service. Near Real Time (NRT): Daily Operational Products DUACS-NRT provides GODAE, climate forecasting centres, the MyOcean EU FP7 project, and real time oceanographic research (e.g.: in-situ campaigns) with directly useable, high quality near real time altimeter data. Regional products (European Shelves, Mediterranean Sea, and Black Sea) are delivered to operational projects. Commercial applications are also developed for the fishery and offshore drilling industries. All DUACS near real time products are generated and distributed on a daily basis to reduce the NRT delay, and to smooth the operational procedures of NRT users. DUACS features a systematic quality control of the input data, the system itself, and its products with detailed reports put online twice per week. The system also carries out on-the-fly editing and reprocessing of erroneous datasets, as well as a long term monitoring of NRT data it has used, to quickly detect anomalies, drifts and discontinuities in incoming altimeter data. Delayed Time (DT): A consistent data set from built upon all altimeters The second generation of DUACS-DT products is composed of global data sets of along track and gridded Sea Level Anomaly, Absolute Dynamic Topography, and geostrophic currents, but also of regional-specific products (higher resolution, optimized parameters). DUACS reprocessed all past altimeter data: Jason-1, T/P, ENVISAT, GFO, ERS1/2 and GEOSAT. These delayed time products are regularly updated when new Level2 data are released and fully validated. The system operationally integrates the state-of-the-art corrections, models and references recommended by the altimeter community, as well as the best Cal/Val and cross-calibration and merging algorithms. Ongoing Improvements to secure multi-mission products Adding Jason-2 to the system is arguably the most important improvement on DUACS in 2008. Additionally, the effort to improve the quality of DUACS combined data and the robustness of the NRT system are ongoing with the release of Key Performance Indicators on the system, and Ocean Indicators for a near real time ocean monitoring. Last year, preliminary studies were carried out to merge into the high-accuracy NRT system, innovative information of lower quality altimeter data flows such as OSDR / FDGDR / OGDR (real time data delivered in a few hours as opposed to 2 or 3 days for classical NRT data), as well as CryoSat data. These offline studies and experimental NRT productions will be integrated to the system in order to guarantee sustainability and quality in the operational DUACS framework.

Applications of Experimental Suomi-NPP VIIRS Flood Inundation Maps in Operational Flood Forecasting

NASA Astrophysics Data System (ADS)

Deweese, M. M.

2017-12-01

Flooding is the most costly natural disaster across the globe. In 2016 flooding caused more fatalities than any other natural disaster in the United States. The U.S. National Weather Service (NWS) is mandated to forecast rivers for the protection of life and property and the enhancement of the national economy. Since 2014, the NWS North Central River Forecast Center has utilized experimental near real time flood mapping products from the JPSS Suomi-NPP VIIRS satellite. These products have been demonstrated to provide reliable and high value information for forecasters in ice jam and snowmelt flooding in data sparse regions of the northern plains. In addition, they have proved valuable in rainfall induced flooding within the upper Mississippi River basin. Aerial photography and ground observations have validated the accuracy of the products. Examples are provided from numerous flooding events to demonstrate the operational application of this satellite derived information as a remotely sensed observational data source and it's utility in real time flood forecasting.

A 3D THz image processing methodology for a fully integrated, semi-automatic and near real-time operational system

NASA Astrophysics Data System (ADS)

Brook, A.; Cristofani, E.; Vandewal, M.; Matheis, C.; Jonuscheit, J.; Beigang, R.

2012-05-01

The present study proposes a fully integrated, semi-automatic and near real-time mode-operated image processing methodology developed for Frequency-Modulated Continuous-Wave (FMCW) THz images with the center frequencies around: 100 GHz and 300 GHz. The quality control of aeronautics composite multi-layered materials and structures using Non-Destructive Testing is the main focus of this work. Image processing is applied on the 3-D images to extract useful information. The data is processed by extracting areas of interest. The detected areas are subjected to image analysis for more particular investigation managed by a spatial model. Finally, the post-processing stage examines and evaluates the spatial accuracy of the extracted information.

Evaluation of the Potential of NASA Multi-satellite Precipitation Analysis in Global Landslide Hazard Assessment

NASA Technical Reports Server (NTRS)

Hong, Yang; Adler, Robert F.; Huffman, George J.

2007-01-01

Landslides are one of the most widespread natural hazards on Earth, responsible for thousands of deaths and billions of dollars in property damage every year. In the U.S. alone landslides occur in every state, causing an estimated $2 billion in damage and 25- 50 deaths each year. Annual average loss of life from landslide hazards in Japan is 170. The situation is much worse in developing countries and remote mountainous regions due to lack of financial resources and inadequate disaster management ability. Recently, a landslide buried an entire village on the Philippines Island of Leyte on Feb 17,2006, with at least 1800 reported deaths and only 3 houses left standing of the original 300. Intense storms with high-intensity , long-duration rainfall have great potential to trigger rapidly moving landslides, resulting in casualties and property damage across the world. In recent years, through the availability of remotely sensed datasets, it has become possible to conduct global-scale landslide hazard assessment. This paper evaluates the potential of the real-time NASA TRMM-based Multi-satellite Precipitation Analysis (TMPA) system to advance our understanding of and predictive ability for rainfall-triggered landslides. Early results show that the landslide occurrences are closely associated with the spatial patterns and temporal distribution of rainfall characteristics. Particularly, the number of landslide occurrences and the relative importance of rainfall in triggering landslides rely on the influence of rainfall attributes [e.g. rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms). TMPA precipitation data are available in both real-time and post-real-time versions, which are useful to assess the location and timing of rainfall-triggered landslide hazards by monitoring landslide-prone areas while receiving heavy rainfall. For the purpose of identifying rainfall-triggered landslides, an empirical global rainfall intensity-duration threshold is developed by examining a number of landslide occurrences and their corresponding TMPA precipitation characteristics across the world. These early results , in combination with TRMM real-time precipitation estimation system, may form a starting point for developing an operational early warning system for rainfall-triggered landslides around the globe.

Temporal and modal characterization of DoD source air toxic ...

EPA Pesticide Factsheets

This project tested three, real-/near real-time monitoring techniques to develop air toxic emission factors for Department of Defense (DoD) platform sources. These techniques included: resonance enhanced multi photon ionization time of flight mass spectrometry (REMPI-TOFMS) for organic air toxics, laser induced breakdown spectroscopy (LIBS) for metallic air toxics, and optical remote sensing (ORS) methods for measurement of criteria pollutants and other hazardous air pollutants (HAPs). Conventional emission measurements were used for verification of the real-time monitoring results. The REMPI-TOFMS system was demonstrated on the following: --a United States U.S. Marine Corps (USMC) diesel generator, --a U.S. Air Force auxiliary power unit (APU), --the waste combustor at the Portsmouth Naval Shipyard, during a multi-monitor environmental technology verification (ETV) test for dioxin monitoring systems, --two dynamometer-driven high mobility multi-purpose wheeled vehicles (HMMWVs), --an idling Abrams battle tank, --a Bradley infantry fighting vehicle (IFV), and --an F-15 and multiple F-22 U.S. Air Force aircraft engines. LIBS was tested and applied solely to the U.S. Marine Corps diesel generator. The high detection limits of LIBS for toxic metals limited its usefulness as a real time analyzer for most DoD sources. ORS was tested only on the APU with satisfactory results for non-condensable combustion products (carbon monoxide [CO], carbon dioxide

Near Real Time website for IASI observations of atmospheric anomalies

NASA Astrophysics Data System (ADS)

Hayer, Catherine; Grainger, Don; Marsh, Kevin; Carboni, Elisa; Ventress, Lucy; Smith, Andrew

2014-05-01

Rapid analysis of satellite observations of the state of the atmosphere and the contaminant levels within it can be used for pollution monitoring, forest fire detection and volcanic activity monitoring. There are numerous operational satellite instruments for which this is possible. The IASI instruments, currently flying on board the MetOp-A and MetOp-B satellite platforms, are used to produce Near Real Time (NRT) data using analysis algorithms developed by Oxford University. The data is then displayed on a website within 3 hours of measurement. This allows for the semi-continuous monitoring of the state of the atmosphere over most of the globe, both in daylight and at night. Global coverage is achieved 4 times per day, which is a significant advantage over most of the alternatives, either geostationary, giving limited spatial coverage, or UV instruments which are only able to observe during the daylight side of the orbit. The website includes flags for atmospheric contaminants detectable by IASI, including dust, biomass burning-derived species and volcanic ash and SO2. In the near future, the website will be developed to also include a quantitative estimate of the mass loading of SO2 contained within any volcanic cloud. Emissions of volcanic products, such as ash and SO2, are useful indicators of a change in the activity level of a volcano. Since many volcanoes are only monitored by remote sensing methods, such as satellite instruments, this can be the only such indicator available. These emissions are also dangerous to passing aircraft, causing damage to external surfaces of the plane and to the engines, sometimes leading to failure. Evacuation of regions surrounding volcanoes, and cessation or diversion of air traffic around actively erupting volcanoes is costly and highly disruptive but is sometimes required. Up to date information is of critical importance as to when to make these sensitive decisions. An archive of data will be available to allow for easy comparison with previous related events, such as large dust storms, forest fires or volcanic eruptions over the whole of the IASI lifetime. The website is being developed in conjunction with the Centre for Environmental Data Archival (CEDA).

Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia

NASA Astrophysics Data System (ADS)

Brocca, Luca; Pellarin, Thierry; Crow, Wade T.; Ciabatta, Luca; Massari, Christian; Ryu, Dongryeol; Su, Chun-Hsu; Rüdiger, Christoph; Kerr, Yann

2016-10-01

Remote sensing of soil moisture has reached a level of maturity and accuracy for which the retrieved products can be used to improve hydrological and meteorological applications. In this study, the soil moisture product from the Soil Moisture and Ocean Salinity (SMOS) satellite is used for improving satellite rainfall estimates obtained from the Tropical Rainfall Measuring Mission multisatellite precipitation analysis product (TMPA) using three different "bottom up" techniques: SM2RAIN, Soil Moisture Analysis Rainfall Tool, and Antecedent Precipitation Index Modification. The implementation of these techniques aims at improving the well-known "top down" rainfall estimate derived from TMPA products (version 7) available in near real time. Ground observations provided by the Australian Water Availability Project are considered as a separate validation data set. The three algorithms are calibrated against the gauge-corrected TMPA reanalysis product, 3B42, and used for adjusting the TMPA real-time product, 3B42RT, using SMOS soil moisture data. The study area covers the entire Australian continent, and the analysis period ranges from January 2010 to November 2013. Results show that all the SMOS-based rainfall products improve the performance of 3B42RT, even at daily time scale (differently from previous investigations). The major improvements are obtained in terms of estimation of accumulated rainfall with a reduction of the root-mean-square error of more than 25%. Also, in terms of temporal dynamic (correlation) and rainfall detection (categorical scores) the SMOS-based products provide slightly better results with respect to 3B42RT, even though the relative performance between the methods is not always the same. The strengths and weaknesses of each algorithm and the spatial variability of their performances are identified in order to indicate the ways forward for this promising research activity. Results show that the integration of bottom up and top down approaches has the potential to improve the quality of near-real-time rainfall estimates from remote sensing in the near future.

Spatial and radiometric characterization of multi-spectrum satellite images through multi-fractal analysis

NASA Astrophysics Data System (ADS)

Alonso, Carmelo; Tarquis, Ana M.; Zúñiga, Ignacio; Benito, Rosa M.

2017-03-01

Several studies have shown that vegetation indexes can be used to estimate root zone soil moisture. Earth surface images, obtained by high-resolution satellites, presently give a lot of information on these indexes, based on the data of several wavelengths. Because of the potential capacity for systematic observations at various scales, remote sensing technology extends the possible data archives from the present time to several decades back. Because of this advantage, enormous efforts have been made by researchers and application specialists to delineate vegetation indexes from local scale to global scale by applying remote sensing imagery. In this work, four band images have been considered, which are involved in these vegetation indexes, and were taken by satellites Ikonos-2 and Landsat-7 of the same geographic location, to study the effect of both spatial (pixel size) and radiometric (number of bits coding the image) resolution on these wavelength bands as well as two vegetation indexes: the Normalized Difference Vegetation Index (NDVI) and the Enhanced Vegetation Index (EVI). In order to do so, a multi-fractal analysis of these multi-spectral images was applied in each of these bands and the two indexes derived. The results showed that spatial resolution has a similar scaling effect in the four bands, but radiometric resolution has a larger influence in blue and green bands than in red and near-infrared bands. The NDVI showed a higher sensitivity to the radiometric resolution than EVI. Both were equally affected by the spatial resolution. From both factors, the spatial resolution has a major impact in the multi-fractal spectrum for all the bands and the vegetation indexes. This information should be taken in to account when vegetation indexes based on different satellite sensors are obtained.

Real-time visual communication to aid disaster recovery in a multi-segment hybrid wireless networking system

NASA Astrophysics Data System (ADS)

Al Hadhrami, Tawfik; Wang, Qi; Grecos, Christos

2012-06-01

When natural disasters or other large-scale incidents occur, obtaining accurate and timely information on the developing situation is vital to effective disaster recovery operations. High-quality video streams and high-resolution images, if available in real time, would provide an invaluable source of current situation reports to the incident management team. Meanwhile, a disaster often causes significant damage to the communications infrastructure. Therefore, another essential requirement for disaster management is the ability to rapidly deploy a flexible incident area communication network. Such a network would facilitate the transmission of real-time video streams and still images from the disrupted area to remote command and control locations. In this paper, a comprehensive end-to-end video/image transmission system between an incident area and a remote control centre is proposed and implemented, and its performance is experimentally investigated. In this study a hybrid multi-segment communication network is designed that seamlessly integrates terrestrial wireless mesh networks (WMNs), distributed wireless visual sensor networks, an airborne platform with video camera balloons, and a Digital Video Broadcasting- Satellite (DVB-S) system. By carefully integrating all of these rapidly deployable, interworking and collaborative networking technologies, we can fully exploit the joint benefits provided by WMNs, WSNs, balloon camera networks and DVB-S for real-time video streaming and image delivery in emergency situations among the disaster hit area, the remote control centre and the rescue teams in the field. The whole proposed system is implemented in a proven simulator. Through extensive simulations, the real-time visual communication performance of this integrated system has been numerically evaluated, towards a more in-depth understanding in supporting high-quality visual communications in such a demanding context.

Real-Time and Post-Processed Orbit Determination and Positioning

NASA Technical Reports Server (NTRS)

Harvey, Nathaniel E. (Inventor); Lu, Wenwen (Inventor); Miller, Mark A. (Inventor); Bar-Sever, Yoaz E. (Inventor); Miller, Kevin J. (Inventor); Romans, Larry J. (Inventor); Dorsey, Angela R. (Inventor); Sibthorpe, Anthony J. (Inventor); Weiss, Jan P. (Inventor); Bertiger, William I. (Inventor);

Real-Time and Post-Processed Orbit Determination and Positioning

NASA Technical Reports Server (NTRS)

Bar-Sever, Yoaz E. (Inventor); Romans, Larry J. (Inventor); Weiss, Jan P. (Inventor); Gross, Jason (Inventor); Harvey, Nathaniel E. (Inventor); Lu, Wenwen (Inventor); Dorsey, Angela R. (Inventor); Miller, Mark A. (Inventor); Sibthorpe, Anthony J. (Inventor); Bertiger, William I. (Inventor);

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Maintaining Balance: The Increasing Role of Energy Storage for Renewable Integration

DOE PAGES

Stenclik, Derek; Denholm, Paul; Chalamala, Babu

2017-10-17

For nearly a century, global power systems have focused on three key functions: to generate, transmit, and distribute electricity as a real-time commodity. Physics requires that electricity generation always be in real-time balance with load, despite variability in load on timescales ranging from sub-second disturbances to multi-year trends. With the increasing role of variable generation from wind and solar, retirements of fossil fuel-based generation, and a changing consumer demand profile, grid operators are using new methods to maintain this balance.

Real-Time Tropospheric Product Establishment and Accuracy Assessment in China

NASA Astrophysics Data System (ADS)

Chen, M.; Guo, J.; Wu, J.; Song, W.; Zhang, D.

2018-04-01

Tropospheric delay has always been an important issue in Global Navigation Satellite System (GNSS) processing. Empirical tropospheric delay models are difficult to simulate complex and volatile atmospheric environments, resulting in poor accuracy of the empirical model and difficulty in meeting precise positioning demand. In recent years, some scholars proposed to establish real-time tropospheric product by using real-time or near-real-time GNSS observations in a small region, and achieved some good results. This paper uses real-time observing data of 210 Chinese national GNSS reference stations to estimate the tropospheric delay, and establishes ZWD grid model in the country wide. In order to analyze the influence of tropospheric grid product on wide-area real-time PPP, this paper compares the method of taking ZWD grid product as a constraint with the model correction method. The results show that the ZWD grid product estimated based on the national reference stations can improve PPP accuracy and convergence speed. The accuracy in the north (N), east (E) and up (U) direction increase by 31.8 %,15.6 % and 38.3 %, respectively. As with the convergence speed, the accuracy of U direction experiences the most improvement.

Real-Time Precise Point Positioning (RTPPP) with raw observations and its application in real-time regional ionospheric VTEC modeling

NASA Astrophysics Data System (ADS)

Liu, Teng; Zhang, Baocheng; Yuan, Yunbin; Li, Min

2018-01-01

Precise Point Positioning (PPP) is an absolute positioning technology mainly used in post data processing. With the continuously increasing demand for real-time high-precision applications in positioning, timing, retrieval of atmospheric parameters, etc., Real-Time PPP (RTPPP) and its applications have drawn more and more research attention in recent years. This study focuses on the models, algorithms and ionospheric applications of RTPPP on the basis of raw observations, in which high-precision slant ionospheric delays are estimated among others in real time. For this purpose, a robust processing strategy for multi-station RTPPP with raw observations has been proposed and realized, in which real-time data streams and State-Space-Representative (SSR) satellite orbit and clock corrections are used. With the RTPPP-derived slant ionospheric delays from a regional network, a real-time regional ionospheric Vertical Total Electron Content (VTEC) modeling method is proposed based on Adjusted Spherical Harmonic Functions and a Moving-Window Filter. SSR satellite orbit and clock corrections from different IGS analysis centers are evaluated. Ten globally distributed real-time stations are used to evaluate the positioning performances of the proposed RTPPP algorithms in both static and kinematic modes. RMS values of positioning errors in static/kinematic mode are 5.2/15.5, 4.7/17.4 and 12.8/46.6 mm, for north, east and up components, respectively. Real-time slant ionospheric delays from RTPPP are compared with those from the traditional Carrier-to-Code Leveling (CCL) method, in terms of function model, formal precision and between-receiver differences of short baseline. Results show that slant ionospheric delays from RTPPP are more precise and have a much better convergence performance than those from the CCL method in real-time processing. 30 real-time stations from the Asia-Pacific Reference Frame network are used to model the ionospheric VTECs over Australia in real time, with slant ionospheric delays from both RTPPP and CCL methods for comparison. RMS of the VTEC differences between RTPPP/CCL method and CODE final products is 0.91/1.09 TECU, and RMS of the VTEC differences between RTPPP and CCL methods is 0.67 TECU. Slant Total Electron Contents retrieved from different VTEC models are also validated with epoch-differenced Geometry-Free combinations of dual-frequency phase observations, and mean RMS values are 2.14, 2.33 and 2.07 TECU for RTPPP method, CCL method and CODE final products, respectively. This shows the superiority of RTPPP-derived slant ionospheric delays in real-time ionospheric VTEC modeling.

Geostationary Lightning Mapper for GOES-R

NASA Technical Reports Server (NTRS)

Goodman, Steven; Blakeslee, Richard; Koshak, William

2007-01-01

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR optical detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. The mission objectives for the GLM are to 1) provide continuous, full-disk lightning measurements for storm warning and Nowcasting, 2) provide early warning of tornadic activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 11 year data record of global lightning activity. Instrument formulation studies begun in January 2006 will be completed in March 2007, with implementation expected to begin in September 2007. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite, airborne science missions (e.g., African Monsoon Multi-disciplinary Analysis, AMMA), and regional test beds (e.g, Lightning Mapping Arrays) are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data now being provided to selected forecast offices will lead to improved understanding of the application of these data in the severe storm warning process and accelerate the development of the pre-launch algorithms and Nowcasting applications. Proxy data combined with MODIS and Meteosat Second Generation SEVERI observations will also lead to new applications (e.g., multi-sensor precipitation algorithms blending the GLM with the Advanced Baseline Imager, convective cloud initiation and identification, early warnings of lightning threat, storm tracking, and data assimilation).

NASA's global differential GPS system and the TDRSS augmentation service for satellites

NASA Technical Reports Server (NTRS)

Bar-Sever, Yoaz; Young, Larry; Stocklin, Frank; Rush, John

2004-01-01

NASA is planning to launch a new service for Earth satellites providing them with precise GPS differential corrections and other ancillary information enabling decimeter level orbit determination accuracy, and nanosecond time-transfer accuracy, onboard, in real-time. The TDRSS Augmentation Service for Satellites (TASS) will broadcast its message on the S-band multiple access channel of NASA's Tracking and Data Relay Satellite System (TDRSS). The satellite's phase array antenna has been configured to provide a wide beam, extending coverage up to 1000 km altitude over the poles. Global coverage will be ensured with broadcast from three or more TDRSS satellites. The GPS differential corrections are provided by the NASA Global Differential GPS (GDGPS) System, developed and operated by NASA's Jet Propulsion Laboratory. The GDGPS System employs a global ground network of more than 70 GPS receivers to monitor the GPS constellation in real time. The system provides real-time estimates of the GPS satellite states, as well as many other real-time products such as differential corrections, global ionospheric maps, and integrity monitoring. The unique multiply redundant architecture of the GDGPS System ensures very high reliability, with 99.999% demonstrated since the inception of the system in Early 2000. The estimated real time GPS orbit and clock states provided by the GDGPS system are accurate to better than 20 cm 3D RMS, and have been demonstrated to support sub-decimeter real time positioning and orbit determination for a variety of terrestrial, airborne, and spaceborne applications. In addition to the GPS differential corrections, TASS will provide real-time Earth orientation and solar flux information that enable precise onboard knowledge of the Earth-fixed position of the spacecraft, and precise orbit prediction and planning capabilities. TASS will also provide 5 seconds alarms for GPS integrity failures based on the unique GPS integrity monitoring service of the GDGPS System.

NASA Remote Sensing Technologies for Improved Integrated Water Resources Management

NASA Astrophysics Data System (ADS)

Toll, D. L.; Doorn, B.; Searby, N. D.; Entin, J. K.; Lee, C. M.

2014-12-01

This presentation will emphasize NASA's water research, applications, and capacity building activities using satellites and models to contribute to water issues including water availability, transboundary water, flooding and droughts for improved Integrated Water Resources Management (IWRM). NASA's free and open exchange of Earth data observations and products helps engage and improve integrated observation networks and enables national and multi-national regional water cycle research and applications that are especially useful in data sparse regions of most developing countries. NASA satellite and modeling products provide a huge volume of valuable data extending back over 50 years across a broad range of spatial (local to global) and temporal (hourly to decadal) scales and include many products that are available in near real time (see earthdata.nasa.gov). To further accomplish these objectives NASA works to actively partner with public and private groups (e.g. federal agencies, universities, NGO's, and industry) in the U.S. and international community to ensure the broadest use of its satellites and related information and products and to collaborate with regional end users who know the regions and their needs best. Key objectives of this talk will highlight NASA's Water Resources and Capacity Building Programs with their objective to discover and demonstrate innovative uses and practical benefits of NASA's advanced system technologies for improved water management in national and international applications. The event will help demonstrate the strong partnering and the use of satellite data to provide synoptic and repetitive spatial coverage helping water managers' deal with complex issues. The presentation will also demonstrate how NASA is a major contributor to water tasks and activities in GEOSS (Global Earth Observing System of Systems) and GEO (Group on Earth Observations).

AstroSat: From Inception to Realization and Launch

NASA Astrophysics Data System (ADS)

Agrawal, P. C.

2017-06-01

The origin of the idea of AstroSat multi wavelength satellite mission and how it evolved over the next 15 years from a concept to the successful development of instruments for giving concrete shape to this mission, is recounted in this article. AstroSat is the outcome of intense deliberations in the Indian astronomy community leading to a consensus for a multi wavelength Observatory having broad spectral coverage over five decades in energy covering near-UV, far-UV, soft X-ray and hard X-ray bands. The multi wavelength observation capability of AstroSat with a suite of 4 co-aligned instruments and an X-ray sky monitor on a single satellite platform, imparts a unique character to this mission. AstroSat owes its realization to the collaborative efforts of the various ISRO centres, several Indian institutions, and a few institutions abroad which developed the 5 instruments and various sub systems of the satellite. AstroSat was launched on September 28, 2015 from India in a near equatorial 650 km circular orbit. The instruments are by and large working as planned and in the past 14 months more than 200 X-ray and UV sources have been studied with it. The important characteristics of AstroSat satellite and scientific instruments will be highlighted.

Multiple continuous coverage of the earth based on multi-satellite systems with linear structure

NASA Astrophysics Data System (ADS)

Saulskiy, V. K.

2009-04-01

A new and wider definition is given to multi-satellite systems with linear structure (SLS), and efficiency of their application to multiple continuous coverage of the Earth is substantiated. Owing to this widening, SLS have incorporated already well-recognized “polar systems” by L. Rider and W.S. Adams, “kinematically regular systems” by G.V. Mozhaev, and “delta-systems” by J.G. Walker, as well as “near-polar systems” by Yu.P. Ulybyshev, and some other satellite constellations unknown before. A universal method of SLS optimization is presented, valid for any values of coverage multiplicity and the number of satellites in a system. The method uses the criterion of minimum radius of a circle seen from a satellite on the surface of the globe. Among the best SLS found in this way there are both systems representing the well-known classes mentioned above and new orbit constellations of satellites.

Performance evaluation of latest integrated multi-satellite retrievals for Global Precipitation Measurement (IMERG) over the northern highlands of Pakistan

NASA Astrophysics Data System (ADS)

Anjum, Muhammad Naveed; Ding, Yongjian; Shangguan, Donghui; Ahmad, Ijaz; Ijaz, Muhammad Wajid; Farid, Hafiz Umar; Yagoub, Yousif Elnour; Zaman, Muhammad; Adnan, Muhammad

2018-06-01

Recently, the Global Precipitation Measurement (GPM) mission has released the Integrated Multi-satellite Retrievals for GPM (IMERG) at a fine spatial (0.1° × 0.1°) and temporal (half hourly) resolutions. A comprehensive evaluation of this newly launched precipitation product is very important for satellite-based precipitation data users as well as for algorithm developers. The objective of this study was to provide a preliminary and timely performance evaluation of the IMERG product over the northern high lands of Pakistan. For comparison reference, the real-time and post real-time Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) products were also evaluated parallel to the IMERG. All of the selected precipitation products were evaluated at annual, monthly, seasonal and daily time scales using reference gauges data from April 2014 to December 2016. The results showed that: (1) the precipitation estimates from IMERG, 3B42V7 and 3B42RT products correlated well with the reference gauges observations at monthly time scale (CC = 0.93, 0.91, 0.88, respectively), whereas moderately at the daily time scale (CC = 0.67, 0.61, and 0.58, respectively); (2) Compared to the 3B42V7 and 3B42RT, the precipitation estimates from IMERG were more reliable in all seasons particularly in the winter season with lowest relative bias (2.61%) and highest CC (0.87); (3) IMERG showed a clear superiority over 3B42V7 and 3B42RT products in order to capture spatial distribution of precipitation over the northern Pakistan; (4) Relative to the 3B42V7 and 3B42RT, daily precipitation estimates from IMEREG showed lowest relative bias (9.20% vs. 21.40% and 26.10%, respectively) and RMSE (2.05 mm/day vs. 2.49 mm/day and 2.88 mm/day, respectively); and (5) Light precipitation events (0-1 mm/day) were usually overestimated by all said satellite-based precipitation products. In contrast moderate (1-20 mm/day) to heavy (>20 mm/day) precipitation events were underestimated by both TMPA products while IMERG was found capable to detect moderate to heavy precipitation events more precisely. Overall, the performance of IMERG was better than that of TMPA products. This preliminary evaluation of new generation of satellite-based precipitation estimates might be a useful feedback for sensor and algorithm developers as well as data users.

Commanding and Controlling Satellite Clusters (IEEE Intelligent Systems, November/December 2000)

DTIC Science & Technology

2000-01-01

real - time operating system , a message-passing OS well suited for distributed...ground Flight processors ObjectAgent RTOS SCL RTOS RDMS Space command language Real - time operating system Rational database management system TS-21 RDMS...engineer with Princeton Satellite Systems. She is working with others to develop ObjectAgent software to run on the OSE Real Time Operating System .

Earth Science System of the Future: Observing, Processing, and Delivering Data Products Directly to Users

NASA Technical Reports Server (NTRS)

Crisp, David; Komar, George (Technical Monitor)

2001-01-01

Advancement of our predictive capabilities will require new scientific knowledge, improvement of our modeling capabilities, and new observation strategies to generate the complex data sets needed by coupled modeling networks. New observation strategies must support remote sensing from a variety of vantage points and will include "sensorwebs" of small satellites in low Earth orbit, large aperture sensors in Geostationary orbits, and sentinel satellites at L1 and L2 to provide day/night views of the entire globe. Onboard data processing and high speed computing and communications will enable near real-time tailoring and delivery of information products (i.e., predictions) directly to users.

Performance of a low data rate speech codec for land-mobile satellite communications

NASA Technical Reports Server (NTRS)

Gersho, Allen; Jedrey, Thomas C.

1990-01-01

In an effort to foster the development of new technologies for the emerging land mobile satellite communications services, JPL funded two development contracts in 1984: one to the Univ. of Calif., Santa Barbara and the other to the Georgia Inst. of Technology, to develop algorithms and real time hardware for near toll quality speech compression at 4800 bits per second. Both universities have developed and delivered speech codecs to JPL, and the UCSB codec was extensively tested by JPL in a variety of experimental setups. The basic UCSB speech codec algorithms and the test results of the various experiments performed with this codec are presented.

Utilizing new GNSS capabilities for exploring Geospace

NASA Astrophysics Data System (ADS)

Coster, A. J.

2015-12-01

In 2000 the density of GPS receivers across the continental United States increased to the point that strictly data-driven regional maps of total electron content (TEC) could be constructed. These data-driven maps allowed the TEC to be monitored throughout the course of geomagnetic storms and to observe the progression of traveling ionospheric disturbances. This allowed studies of the development of storm enhanced density plumes in both hemispheres and of the dynamic changes in the equatorial TEC following stratospheric warming events. Currently, GPS TEC maps have become recognized as one of the premier tools to monitor coupling of atmospheric regions from both below and above the ionosphere. The number of available scientific dual-frequency receivers across the globe now exceeds 3000. However this number is anticipated to increase rapidly in part due to the numerous arrays being fielded for commercial applications such as precision farming and highway surveying. In addition, there will be a rapid increase in the number of GNSS signals available in the near future. Besides GPS, the European Union is building a system named GALILEO, which will consist of a 30-satellite constellation. The Russians have a system based on a 24-satellite constellation named GLONASS. The Chinese are developing a system called Beidou, which means "stars of the Big Dipper". The Beidou system will consist of 35 satellites. By 2023, there will be more than 160 GNSS satellites and 400 signals. Multi-constellation, multi-band GNSS will be a major enabler for space weather studies. This talk will focus on the potential of using the multiple new GNSS signals and the new higher density receiver arrays for measurements of plasma drift, detailed studies of traveling ionospheric disturbances (TIDS) and expanded studies of atmospheric coupling. We will conclude by describing the tremendous potential of merging GNSS observations with observations collected by arrays of low-cost, low-power, and small form factor ionosondes. In the future, we predict that new ionosonde and GNSS receiver networks will enable unprecedented mesoscale real-time tomographic observations of the ionosphere.

Assessment of the Utility of the Advanced Himawari Imager to Detect Active Fire Over Australia

NASA Astrophysics Data System (ADS)

Hally, B.; Wallace, L.; Reinke, K.; Jones, S.

2016-06-01

Wildfire detection and attribution is an issue of importance due to the socio-economic impact of fires in Australia. Early detection of fires allows emergency response agencies to make informed decisions in order to minimise loss of life and protect strategic resources in threatened areas. Until recently, the ability of land management authorities to accurately assess fire through satellite observations of Australia was limited to those made by polar orbiting satellites. The launch of the Japan Meteorological Agency (JMA) Himawari-8 satellite, with the 16-band Advanced Himawari Imager (AHI-8) onboard, in October 2014 presents a significant opportunity to improve the timeliness of satellite fire detection across Australia. The near real-time availability of images, at a ten minute frequency, may also provide contextual information (background temperature) leading to improvements in the assessment of fire characteristics. This paper investigates the application of the high frequency observation data supplied by this sensor for fire detection and attribution. As AHI-8 is a new sensor we have performed an analysis of the noise characteristics of the two spectral bands used for fire attribution across various land use types which occur in Australia. Using this information we have adapted existing algorithms, based upon least squares error minimisation and Kalman filtering, which utilise high frequency observations of surface temperature to detect and attribute fire. The fire detection and attribution information provided by these algorithms is then compared to existing satellite based fire products as well as in-situ information provided by land management agencies. These comparisons were made Australia-wide for an entire fire season - including many significant fire events (wildfires and prescribed burns). Preliminary detection results suggest that these methods for fire detection perform comparably to existing fire products and fire incident reporting from relevant fire authorities but with the advantage of being near-real time. Issues remain for detection due to cloud and smoke obscuration, along with validation of the attribution of fire characteristics using these algorithms.

An Introduction to the Global Space-based Inter-Calibration System from a EUMETSAT Perspective

NASA Astrophysics Data System (ADS)

Wagner, S. C.; Hewison, T.; Roebeling, R. A.; Koenig, M.; Schulz, J.; Miu, P.

2012-04-01

The Global Space-based Inter-Calibration System (GSICS) (Goldberg and al. 2011) is an international collaborative effort which aims to monitor, improve and harmonize the quality of observations from operational weather and environmental satellites of the Global Observing System (GOS). GSICS aims at ensuring consistent accuracy among space-based observations worldwide for climate monitoring, weather forecasting, and environmental applications. This is achieved through a comprehensive calibration strategy, which involves monitoring instrument performances, operational inter-calibration of satellite instruments, tying the measurements to absolute references and standards, and recalibration of archived data. A major part of this strategy involves direct comparison of collocated observations from pairs of satellite instruments, which are used to systematically generate calibration functions to compare and correct the calibration of monitored instruments to references. These GSICS Corrections are needed for accurately integrating data from multiple observing systems into both near real-time and re-analysis products, applications and services. This paper gives more insight into the activities carried out by EUMETSAT as a GSICS Processing and Research Centre. Currently these are closely bound to the in-house development and operational implementation of calibration methods for solar and thermal band channels of geostationary and polar-orbiting satellites. They include inter-calibration corrections for Meteosat imagers using reference instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) on-board the Aqua satellite for solar band channels, the Infrared Atmospheric Sounding Interferometer (IASI) on-board Metop-A and, for historic archive data, the High-resolution InfraRed Sounder (HIRS). Additionally, bias monitoring is routinely performed, allowing users to visualise the calibration accuracy of the instruments in near real-time. These activities are based on principles and protocols defined by the GSICS Research Working Group and Data Management Working Group, which require assessment of the calibration uncertainties to ensure the traceability to community references.

Early assessment of Integrated Multi-satellite Retrievals for Global Precipitation Measurement over China

NASA Astrophysics Data System (ADS)

Guo, Hao; Chen, Sheng; Bao, Anming; Behrangi, Ali; Hong, Yang; Ndayisaba, Felix; Hu, Junjun; Stepanian, Phillip M.

2016-07-01

Two post-real time precipitation products from the Integrated Multi-satellite Retrievals for Global Precipitation Measurement Mission (IMERG) are systematically evaluated over China with China daily Precipitation Analysis Product (CPAP) as reference. The IMERG products include the gauge-corrected IMERG product (IMERG_Cal) and the version of IMERG without direct gauge correction (IMERG_Uncal). The post-research TRMM Multisatellite Precipitation Analysis version 7 (TMPA-3B42V7) is also evaluated concurrently with IMERG for better perspective. In order to be consistent with CPAP, the evaluation and comparison of selected products are performed at 0.25° and daily resolutions from 12 March 2014 through 28 February 2015. The results show that: Both IMERG and 3B42V7 show similar performances. Compared to IMERG_Uncal, IMERG_Cal shows significant improvement in overall and conditional bias and in the correlation coefficient. Both IMERG_Cal and IMERG_Uncal perform relatively poor in winter and over-detect slight precipitation events in northwestern China. As an early validation of the GPM-era IMERG products that inherit the TRMM-era global satellite precipitation products, these findings will provide useful feedbacks and insights for algorithm developers and data users over China and beyond.

JPL Genesis and Rapid Intensification Processes (GRIP) Portal

NASA Technical Reports Server (NTRS)

Knosp, Brian W.; Li, P. Peggy; Vu, Quoc A.; Turk, Francis J.; Shen, Tsae-Pyng J.; Hristova-Veleva, Svetla M.; Licata, Stephen J.; Poulsen, William L.

2012-01-01

Satellite observations can play a very important role in airborne field campaigns, since they provide a comprehensive description of the environment that is essential for the experiment design, flight planning, and post-experiment scientific data analysis. In the past, it has been difficult to fully utilize data from multiple NASA satellites due to the large data volume, the complexity of accessing NASA s data in near-real-time (NRT), as well as the lack of software tools to interact with multi-sensor information. The JPL GRIP Portal is a Web portal that serves a comprehensive set of NRT observation data sets from NASA and NOAA satellites describing the atmospheric and oceanic environments related to the genesis and intensification of the tropical storms in the North Atlantic Ocean. Together with the model forecast data from four major global atmospheric models, this portal provides a useful tool for the scientists and forecasters in planning and monitoring the NASA GRIP field campaign during the 2010 Atlantic Ocean hurricane season. This portal uses the Google Earth plug-in to visualize various types of data sets, such as 2D maps, wind vectors, streamlines, 3D data sets presented at series of vertical cross-sections or pointwise vertical profiles, and hurricane best tracks and forecast tracks. Additionally, it allows users to overlap multiple data sets, change the opacity of each image layer, generate animations on the fly with selected data sets, and compare the observation data with the model forecast using two independent calendars. The portal also provides the capability to identify the geographic location of any point of interest. In addition to supporting the airborne mission planning, the NRT data and portal will serve as a very rich source of information during the post-field campaign analysis stage of the airborne experiment. By including a diverse set of satellite observations and model forecasts, it provides a good spatial and temporal context for the high-resolution, but limited in space and time, airborne observations.

Utilizing multi-sensor fire detections to map fires in the United States

USGS Publications Warehouse

Howard, Stephen M.; Picotte, Joshua J.; Coan, Michael

2014-01-01

In 2006, the Monitoring Trends in Burn Severity (MTBS) project began a cooperative effort between the US Forest Service (USFS) and the U.S.Geological Survey (USGS) to map and assess burn severity all large fires that have occurred in the United States since 1984. Using Landsat imagery, MTBS is mandated to map wildfire and prescribed fire that meet specific size criteria: greater than 1000 acres in the west and 500 acres in the east, regardless of ownership. Relying mostly on federal and state fire occurrence records, over 15,300 individual fires have been mapped. While mapping recorded fires, an additional 2,700 “unknown” or undocumented fires were discovered and assessed. It has become apparent that there are perhaps thousands of undocumented fires in the US that are yet to be mapped. Fire occurrence records alone are inadequate if MTBS is to provide a comprehensive accounting of fire across the US. Additionally, the sheer number of fires to assess has overwhelmed current manual procedures. To address these problems, the National Aeronautics and Space Administration (NASA) Applied Sciences Program is helping to fund the efforts of the USGS and its MTBS partners (USFS, National Park Service) to develop, and implement a system to automatically identify fires using satellite data. In near real time, USGS will combine active fire satellite detections from MODIS, AVHRR and GOES satellites with Landsat acquisitions. Newly acquired Landsat imagery will be routinely scanned to identify freshly burned area pixels, derive an initial perimeter and tag the burned area with the satellite date and time of detection. Landsat imagery from the early archive will be scanned to identify undocumented fires. Additional automated fire assessment processes will be developed. The USGS will develop these processes using open source software packages in order to provide freely available tools to local land managers providing them with the capability to assess fires at the local level.

Utilizing Multi-Sensor Fire Detections to Map Fires in the United States

NASA Astrophysics Data System (ADS)

Howard, S. M.; Picotte, J. J.; Coan, M. J.

2014-11-01

In 2006, the Monitoring Trends in Burn Severity (MTBS) project began a cooperative effort between the US Forest Service (USFS) and the U.S.Geological Survey (USGS) to map and assess burn severity all large fires that have occurred in the United States since 1984. Using Landsat imagery, MTBS is mandated to map wildfire and prescribed fire that meet specific size criteria: greater than 1000 acres in the west and 500 acres in the east, regardless of ownership. Relying mostly on federal and state fire occurrence records, over 15,300 individual fires have been mapped. While mapping recorded fires, an additional 2,700 "unknown" or undocumented fires were discovered and assessed. It has become apparent that there are perhaps thousands of undocumented fires in the US that are yet to be mapped. Fire occurrence records alone are inadequate if MTBS is to provide a comprehensive accounting of fire across the US. Additionally, the sheer number of fires to assess has overwhelmed current manual procedures. To address these problems, the National Aeronautics and Space Administration (NASA) Applied Sciences Program is helping to fund the efforts of the USGS and its MTBS partners (USFS, National Park Service) to develop, and implement a system to automatically identify fires using satellite data. In near real time, USGS will combine active fire satellite detections from MODIS, AVHRR and GOES satellites with Landsat acquisitions. Newly acquired Landsat imagery will be routinely scanned to identify freshly burned area pixels, derive an initial perimeter and tag the burned area with the satellite date and time of detection. Landsat imagery from the early archive will be scanned to identify undocumented fires. Additional automated fire assessment processes will be developed. The USGS will develop these processes using open source software packages in order to provide freely available tools to local land managers providing them with the capability to assess fires at the local level.

Monitoring Rainfall by Combining Ground-based Observed Precipitation and PERSIANN Satellite Product (Case Study Area: Lake Urmia Basin)

NASA Astrophysics Data System (ADS)

Abrishamchi, A.; Mirshahi, A.

2015-12-01

The global coverage, quick access, and appropriate spatial-temporal resolution of satellite precipitation data renders the data appropriate for hydrologic studies, especially in regions with no sufficient rain-gauge network. On the other hand, satellite precipitation products may have major errors. The present study aims at reduction of estimation error of the PERSIANN satellite precipitation product. Bayesian logic employed to develop a statistical relationship between historical ground-based and satellite precipitation data. This relationship can then be used to reduce satellite precipitation product error in near real time, when there is no ground-based precipitation observation. The method was evaluated in the Lake Urmia basin with a monthly time scale; November to May of 2000- 2008 for the purpose of model development and two years of 2009 and 2010 for the validation of the established relationships. Moreover, Kriging interpolation method was employed to estimate the average rainfall in the basin. Furthermore, to downscale the satellite precipitation product from 0.25o to 0.05o, data-location downscaling algorithm was used. In 76 percent of months, the final product, compared with the satellite precipitation, had less error during the validation period. Additionally, its performance was marginally better than adjusted PERSIANN product.

Near real-time estimation of burned area using VIIRS 375 m active fire product

NASA Astrophysics Data System (ADS)

Oliva, P.; Schroeder, W.

2016-12-01

Every year, more than 300 million hectares of land burn globally, causing significant ecological and economic consequences, and associated climatological effects as a result of fire emissions. In recent decades, burned area estimates generated from satellite data have provided systematic global information for ecological analysis of fire impacts, climate and carbon cycle models, and fire regimes studies, among many others. However, there is still need of near real-time burned area estimations in order to assess the impacts of fire and estimate smoke and emissions. The enhanced characteristics of the Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m channels on board the Suomi National Polar-orbiting Partnesship (S-NPP) make possible the use of near real-time active fire detection data for burned area estimation. In this study, consecutive VIIRS 375 m active fire detections were aggregated to produce the VIIRS 375 m burned area (BA) estimation over ten ecologically diverse study areas. The accuracy of the BA estimations was assessed by comparison with Landsat-8 supervised burned area classification. The performance of the VIIRS 375 m BA estimates was dependent on the ecosystem characteristics and fire behavior. Higher accuracy was observed in forested areas characterized by large long-duration fires, while grasslands, savannas and agricultural areas showed the highest omission and commission errors. Complementing those analyses, we performed the burned area estimation of the largest fires in Oregon and Washington states during 2015 and the Fort McMurray fire in Canada 2016. The results showed good agreement with NIROPs airborne fire perimeters proving that the VIIRS 375 m BA estimations can be used for near real-time assessments of fire effects.

Utilizing NASA Earth Observations to Enhance Flood Impact Products and Mitigation in the Lower Mekong Water Basin

NASA Astrophysics Data System (ADS)

Doyle, C.; Gao, M.; Spruce, J.; Bolten, J. D.; Weber, S.

2014-12-01

This presentation discusses results of a project to develop a near real time flood monitoring capability for the Lower Mekong Water Basin (LMB), the largest river basin in Southeast Asia and home to more than sixty million people. The region has seen rapid population growth and socio-economic development, fueling unsustainable deforestation, agricultural expansion, and stream-flow regulation. The basin supports substantial rice farming and other agrarian activities, which heavily depend upon seasonal flooding. But, floods due to typhoons and other severe weather events can result in disasters that cost millions of dollars and cause hardships to millions of people. This study uses near real time and historical Aqua and Terra MODIS 250-m resolution Normalized Difference Vegetation Index (NDVI) products to map flood and drought impact within the LMB. In doing so, NDVI change products are derived by comparing from NDVI during the wet season to a baseline NDVI from the dry season. The method records flood events, which cause drastic decreases in NDVI compared to non-flooded conditions. NDVI change product computation was automated for updating a near real-time system, as part of the Committee on Earth Observing Satellites Disaster Risk Management Observation Strategy. The system is a web-based 'Flood Dashboard that will showcase MODIS flood monitoring products, along with other flood mapping and weather data products. This flood dashboard enables end-users to view and assess a variety of geospatial data to monitor floods and flood impacts in near real-time, as well provides a platform for further data aggregation for flood prediction modeling and post-event assessment.

New Near-Real Time Monitoring of the Ionosphere over Europe Available On-line

NASA Astrophysics Data System (ADS)

Chevalier, J. M.; Bergeot, N.; Bruyninx, C.; Pottiaux, E.; Aerts, W.; Baire, Q.; Legrand, J.; Defraigne, P.

2012-04-01

With the beginning of the 24th Solar cycle, the increased Solar activity requires having a close eye on the ionosphere for better understanding Space Weather physics and its effects on radio communications. In that frame, near-real time ionospheric models over Europe are now routinely generated at the Royal Observatory of Belgium (ROB). These models are made available to the public through new interactive web pages at the web site of the GNSS team (www.gnss.be) and the Solar Influences Data Analysis Center (www.sidc.be) of ROB. The models are ionospheric Vertical Total Electron Content (VTEC) maps estimated every 15 minutes on a 0.5°x0.5° grid. They use the high-rate GPS observations of the real-time stations in the EUREF Permanent Network (EPN) provided by the ROB NTRIP broadcaster. The maps are published on the ROB web site with a latency of 7-15 minutes with respect to the last GPS measurement included in the 15-minute observation files. In a first step, this paper presents the processing strategy used to generate the VTEC maps: input data, parameter estimation, data cleaning and interpolation method. In addition, the tools developed to further exploit the product are introduced, e.g. on-demand animated VTEC maps. In a second step, the VTEC maps are compared with external ionospheric products and models such as Global Ionospheric Maps and IRI 2011. These new near-real time VTEC maps will allow any user within the geographical scope of the maps to estimate in near-real time the ionospheric delay induced along the signal of any observed satellite. In the future, the web site will continuously be updated in response to evolving user needs. This paper opens doors to discussions with the user community to target their needs.

Real-time data and communications services of NCAR's Earth Observing Laboratory

NASA Astrophysics Data System (ADS)

Webster, C. J.; Daniels, M.; Stossmeister, G.

2011-12-01

Near real-time information is critical for mission management of atmospheric observing systems. Advances in satellite communications and Internet distribution have allowed the Earth Observing Laboratory (EOL) of NCAR to provide data, information and imagery to the scientists during evolving weather situations. Real-time data are necessary for updating interactive displays that show products from forecast models and many disparate observation systems (e.g. satellite, soundings, surface radars and aircraft in-situ observations). At the same time, network-based collaborative tools such as chat and web conferencing facilitate interactive participation between remote groups of scientists, engineers, operations centers and the observing platforms. In the recent PREDICT deployment of the NSF/NCAR GV research aircraft, dropsondes were released from the aircraft at 45,000 ft over a 1000 km x 1000 km area to give profiles of pressure, temperature, humidity and wind below the aircraft. Real-time data from the sondes was collected by the aircraft and relayed by satcom into the Global Telecommunications System (GTS) and assimilated into forecast models. The model forecast results were then fed back into ground-based and airborne displays (along with a multitude of observations) for enhanced decision-making and mission guidance. This environment of streaming data in real-time also allows more experts to look at data and compare it with other measurements. One particular benefit is that it alerts instrument operators on the ground and in the air to instrument problems, which can then be addressed very rapidly. The resulting communications and collaborations infrastructure results in unprecedented improvements to our data quality and rapid targeting of mission resources to important weather events. Using several examples, this presentation will provide an overview of current tools and processes in use at EOL, and future needs will be discussed.

Real Time, On Line Crop Monitoring and Analysis with Near Global Landsat-class Mosaics

NASA Astrophysics Data System (ADS)

Varlyguin, D.; Hulina, S.; Crutchfield, J.; Reynolds, C. A.; Frantz, R.

2015-12-01

The presentation will discuss the current status of GDA technology for operational, automated generation of 10-30 meter near global mosaics of Landsat-class data for visualization, monitoring, and analysis. Current version of the mosaic combines Landsat 8 and Landsat 7. Sentinel-2A imagery will be added once it is operationally available. The mosaics are surface reflectance calibrated and are analysis ready. They offer full spatial resolution and all multi-spectral bands of the source imagery. Each mosaic covers all major agricultural regions of the world and 16 day time window. 2014-most current dates are supported. The mosaics are updated in real-time, as soon as GDA downloads Landsat imagery, calibrates it to the surface reflectances, and generates data gap masks (all typically under 10 minutes for a Landsat scene). The technology eliminates the complex, multi-step, hands-on process of data preparation and provides imagery ready for repetitive, field-to-country analysis of crop conditions, progress, acreages, yield, and production. The mosaics can be used for real-time, on-line interactive mapping and time series drilling via GeoSynergy webGIS platform. The imagery is of great value for improved, persistent monitoring of global croplands and for the operational in-season analysis and mapping of crops across the globe in USDA FAS purview as mandated by the US government. The presentation will overview operational processing of Landsat-class mosaics in support of USDA FAS efforts and will look into 2015 and beyond.

A sensor architecture for real-time, in situ measurement of overlake evaporation on the Laurentian Great Lakes

NASA Astrophysics Data System (ADS)

Kerkez, B.; Fries, K. J.; Gronewold, A.; Lenters, J. D.

2014-12-01

While overlake evaporation is a major component of the Great Lakes' water balance, our scientific understanding of the climatic drivers of evaporation and its effects on water levels is significantly impeded by limited data. Existing measurement methods, such as eddy covariance, are not easily implemented in offshore applications. As such, there are only a handful of sites making direct, overlake measurements of evaporation on the entire Great Lakes, where the lake surface area comprises nearly one third of the entire basin. Long-term forecasts of water levels are thus very uncertain, particularly relating to climatic forcing, which is known to be a major driver of evaporation. We present a novel sensor architecture which is deployed on buoys, both tethered and drifting, to provide real-time measurements of overlake evaporation across the Great Lakes. Our system is comprised of a hierarchy of low-power, cost-effective sensor nodes, which carry out on-board computations to estimate evaporation in real-time. An ultra-low power microcontroller samples a suite of sensors to compute evaporation based on the Bowen ratio energy budget approach. The readings are then transmitted via satellite modules to a cloud-based server infrastructure for real-time updated scientific analysis and forecasting. Initial assessment of our new satellite drifter platform indicates robust field performance, validating its use in ongoing efforts to deploy a large-scale evaporation observation network across the Great Lakes basin.

Assessment of Evolving TRMM-Based Real-Time Precipitation Estimation Methods and Their Impacts on Hydrologic Prediction in a High-Latitude Basin

NASA Technical Reports Server (NTRS)

Yong, Bin; Hong, Yang; Ren, Li-Liang; Gourley, Jonathan; Huffman, George J.; Chen, Xi; Wang, Wen; Khan, Sadiq I.

2013-01-01

The real-time availability of satellite-derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time estimates (TMPA-RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA-RT estimates over its three major evolving periods were evaluated and inter-compared at daily, monthly and seasonal scales in the high-latitude Laohahe basin in China. Assessment results show that the performance of TMPA-RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA-RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest dataset of TMPA-RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA-RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.

An improved procedure for the validation of satellite-based precipitation estimates

NASA Astrophysics Data System (ADS)

Tang, Ling; Tian, Yudong; Yan, Fang; Habib, Emad

2015-09-01

The objective of this study is to propose and test a new procedure to improve the validation of remote-sensing, high-resolution precipitation estimates. Our recent studies show that many conventional validation measures do not accurately capture the unique error characteristics in precipitation estimates to better inform both data producers and users. The proposed new validation procedure has two steps: 1) an error decomposition approach to separate the total retrieval error into three independent components: hit error, false precipitation and missed precipitation; and 2) the hit error is further analyzed based on a multiplicative error model. In the multiplicative error model, the error features are captured by three model parameters. In this way, the multiplicative error model separates systematic and random errors, leading to more accurate quantification of the uncertainties. The proposed procedure is used to quantitatively evaluate the recent two versions (Version 6 and 7) of TRMM's Multi-sensor Precipitation Analysis (TMPA) real-time and research product suite (3B42 and 3B42RT) for seven years (2005-2011) over the continental United States (CONUS). The gauge-based National Centers for Environmental Prediction (NCEP) Climate Prediction Center (CPC) near-real-time daily precipitation analysis is used as the reference. In addition, the radar-based NCEP Stage IV precipitation data are also model-fitted to verify the effectiveness of the multiplicative error model. The results show that winter total bias is dominated by the missed precipitation over the west coastal areas and the Rocky Mountains, and the false precipitation over large areas in Midwest. The summer total bias is largely coming from the hit bias in Central US. Meanwhile, the new version (V7) tends to produce more rainfall in the higher rain rates, which moderates the significant underestimation exhibited in the previous V6 products. Moreover, the error analysis from the multiplicative error model provides a clear and concise picture of the systematic and random errors, with both versions of 3B42RT have higher errors in varying degrees than their research (post-real-time) counterparts. The new V7 algorithm shows obvious improvements in reducing random errors in both winter and summer seasons, compared to its predecessors V6. Stage IV, as expected, surpasses the satellite-based datasets in all the metrics over CONUS. Based on the results, we recommend the new procedure be adopted for routine validation of satellite-based precipitation datasets, and we expect the procedure will work effectively for higher resolution data to be produced in the Global Precipitation Measurement (GPM) era.

JPSS Proving Ground Activities with NASA's Short-term Prediction Research and Transition (SPoRT) Center

NASA Astrophysics Data System (ADS)

Schultz, L. A.; Smith, M. R.; Fuell, K.; Stano, G. T.; LeRoy, A.; Berndt, E.

2015-12-01

Instruments aboard the Joint Polar Satellite System (JPSS) series of satellites will provide imagery and other data sets relevant to operational weather forecasts. To prepare current and future weather forecasters in application of these data sets, Proving Ground activities have been established that demonstrate future JPSS capabilities through use of similar sensors aboard NASA's Terra and Aqua satellites, and the S-NPP mission. As part of these efforts, NASA's Short-term Prediction Research and Transition (SPoRT) Center in Huntsville, Alabama partners with near real-time providers of S-NPP products (e.g., NASA, UW/CIMSS, UAF/GINA, etc.) to demonstrate future capabilities of JPSS. This includes training materials and product distribution of multi-spectral false color composites of the visible, near-infrared, and infrared bands of MODIS and VIIRS. These are designed to highlight phenomena of interest to help forecasters digest the multispectral data provided by the VIIRS sensor. In addition, forecasters have been trained on the use of the VIIRS day-night band, which provides imagery of moonlit clouds, surface, and lights emitted by human activities. Hyperspectral information from the S-NPP/CrIS instrument provides thermodynamic profiles that aid in the detection of extremely cold air aloft, helping to map specific aviation hazards at high latitudes. Hyperspectral data also support the estimation of ozone concentration, which can highlight the presence of much drier stratospheric air, and map its interaction with mid-latitude or tropical cyclones to improve predictions of their strengthening or decay. Proving Ground activities are reviewed, including training materials and methods that have been provided to forecasters, and forecaster feedback on these products that has been acquired through formal, detailed assessment of their applicability to a given forecast threat or task. Future opportunities for collaborations around the delivery of training are proposed, along with other applications of multispectral data and derived, more quantitative products.

A Remotely Sensed Global Terrestrial Drought Severity Index

NASA Astrophysics Data System (ADS)

Mu, Q.; Zhao, M.; Kimball, J. S.; McDowell, N. G.; Running, S. W.

2012-12-01

Regional drought and flooding from extreme climatic events are increasing in frequency and severity, with significant adverse eco-social impacts. Detecting and monitoring drought at regional to global scales remains challenging, despite the availability of various drought indices and widespread availability of potentially synergistic global satellite observational records. We developed a method to generate a near-real-time remotely sensed Drought Severity Index (DSI) to monitor and detect drought globally at 1-km spatial resolution and regular 8-day, monthly and annual frequencies. The new DSI integrates and exploits information from current operational satellite based terrestrial evapotranspiration (ET) and Vegetation greenness Index (NDVI) products, which are sensitive to vegetation water stress. Specifically, our approach determines the annual DSI departure from its normal (2000-2011) using the remotely sensed ratio of ET to potential ET (PET) and NDVI. The DSI results were derived globally and captured documented major regional droughts over the last decade, including severe events in Europe (2003), the Amazon (2005 and 2010), and Russia (2010). The DSI corresponded favorably (r=0.43) with the precipitation based Palmer Drought Severity Index (PDSI), while both indices captured similar wetting and drying patterns. The DSI was also correlated with satellite based vegetation net primary production (NPP) records, indicating that the combined use of these products may be useful for assessing water supply and ecosystem interactions, including drought impacts on crop yields and forest productivity. The remotely-sensed global terrestrial DSI enhances capabilities for near-real-time drought monitoring to assist decision makers in regional drought assessment and mitigation efforts, and without many of the constraints of more traditional drought monitoring methods.

An Evaluation of Spacecraft Pointing Requirements for Optically Linked Satellite Systems

NASA Astrophysics Data System (ADS)

Gunter, B. C.; Dahl, T.

2017-12-01

Free space optical (laser) communications can offer certain advantages for many remote sensing applications, due primarily to the high data rates (Gb/s) and energy efficiences possible from such systems. An orbiting network of crosslinked satellites could potentially relay imagery and other high-volume data at near real-time intervals. To achieve this would require satellites actively tracking one or more satellites, as well as ground terminals. The narrow laser beam width utilized by the transmitting satellites pose technical challenges due to the higher pointing accuracy required for effective signal transmission, in particular if small satellites are involved. To better understand what it would take to realize such a small-satellite laser communication network, this study investigates the pointing requirements needed to support optical data links. A general method for characterizing pointing tolerance, angle rates and accelerations for line of site vectors is devised and applied to various case studies. Comparisons with state-of-the-art small satellite attitude control systems are also made to assess what is possible using current technology. The results help refine the trade space for designs for optically linked networks from the hardware aboard each satellite to the design of the satellite constellation itself.

Monitoring Snow and Land Ice Using Satellite data in the GMES Project CryoLand

NASA Astrophysics Data System (ADS)

Bippus, Gabriele; Nagler, Thomas

2013-04-01

The main objectives of the project "CryoLand - GMES Service Snow and Land Ice" are to develop, implement and validate services for snow, glaciers and lake and river ice products as a Downstream Service within the Global Monitoring for Environment and Security (GMES) program of the European Commission. CryoLand exploits Earth Observation data from current optical and microwave sensors and of the upcoming GMES Sentinel satellite family. The project prepares also the basis for the cryospheric component of the GMES Land Monitoring services. The CryoLand project team consists of 10 partner organisations from Austria, Finland, Norway, Sweden, Switzerland and Romania and is funded by the 7th Framework Program of the European Commission. The CryoLand baseline products for snow include fractional snow extent from optical satellite data, the extent of melting snow from SAR data, and coarse resolution snow water equivalent maps from passive microwave data. Experimental products include maps of snow surface wetness and temperature. The products range from large scale coverage at medium resolution to regional products with high resolution, in order to address a wide user community. Medium resolution optical data (e.g. MODIS, in the near future Sentinel-3) and SAR (ENVISAT ASAR, in the near future Sentinel-1) are the main sources of EO data for generating large scale products in near real time. For generation of regional products high resolution satellite data are used. Glacier products are based on high resolution optical (e.g. SPOT-5, in the near future Sentinel-2) and SAR (TerraSAR-X, in the near future Sentinel-1) data and include glacier outlines, mapping of glacier facies, glacier lakes and ice velocity. The glacier products are generated on users demand. Current test areas are located in the Alps, Norway, Greenland and the Himalayan Mountains. The lake and river ice products include ice extent and its temporal changes and snow extent on ice. The algorithms for these products are in development. One major task of CryoLand is the performance assessment of the products, which is carried out in different environments, climate zones and land cover types, selected jointly with users. Accuracy assessment is done for test areas using in-situ data and very high resolution satellite data. This presentation gives an overview on the processing lines and demonstration products for snow, glacier and lake ice parameters including examples of the product accuracy assessment. An important point of the CryoLand project is the use of advanced information technology, which is applied to process and distribute snow and land ice products in near real time.

1/32° real-time global ocean prediction and value-added over 1/16° resolution

NASA Astrophysics Data System (ADS)

Shriver, J. F.; Hurlburt, H. E.; Smedstad, O. M.; Wallcraft, A. J.; Rhodes, R. C.

2007-03-01

A 1/32° global ocean nowcast/forecast system has been developed by the Naval Research Laboratory at the Stennis Space Center. It started running at the Naval Oceanographic Office in near real-time on 1 Nov. 2003 and has been running daily in real-time since 1 Mar. 2005. It became an operational system on 6 March 2006, replacing the existing 1/16° system which ceased operation on 12 March 2006. Both systems use the NRL Layered Ocean Model (NLOM) with assimilation of sea surface height from satellite altimeters and sea surface temperature from multi-channel satellite infrared radiometers. Real-time and archived results are available online at http://www.ocean.nrlssc.navy.mil/global_nlom. The 1/32° system has improvements over the earlier system that can be grouped into two categories: (1) better resolution and representation of dynamical processes and (2) design modifications. The design modifications are the result of accrued knowledge since the development of the earlier 1/16° system. The improved horizontal resolution of the 1/32° system has significant dynamical benefits which increase the ability of the model to accurately nowcast and skillfully forecast. At the finer resolution, current pathways and their transports become more accurate, the sea surface height (SSH) variability increases and becomes more realistic and even the global ocean circulation experiences some changes (including inter-basin exchange). These improvements make the 1/32° system a better dynamical interpolator of assimilated satellite altimeter track data, using a one-day model forecast as the first guess. The result is quantitatively more accurate nowcasts, as is illustrated by several model-data comparisons. Based on comparisons with ocean color imagery in the northwestern Arabian Sea and the Gulf of Oman, the 1/32° system has even demonstrated the ability to map small eddies, 25-75 km in diameter, with 70% reliability and a median eddy center location error of 22.5 km, a surprising and unanticipated result from assimilation of altimeter track data. For all of the eddies (50% small eddies), the reliability was 80% and the median eddy center location error was 29 km. The 1/32° system also exhibits improved forecast skill in relation to the 1/16° system. This is due to ( a) a more accurate initial condition for the forecast and ( b) better resolution and representation of critical dynamical processes (such as upper ocean - topographic coupling via mesoscale flow instabilities) which allow the model to more accurately evolve these features in time while running in forecast mode (forecast atmospheric forcing for the first 5 days, then gradually reverting toward climatology for the remainder of the 30-day forecast period). At 1/32° resolution, forecast SSH generally compares better with unassimilated observations and the anomaly correlation of the forecast SSH exceeds that from persistence by a larger amount than found in the 1/16° system.

Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX

USDA-ARS?s Scientific Manuscript database

Real-time rainfall accumulation estimates at the global scale is useful for many applications. However, the real-time versions of satellite-based rainfall products are known to contain errors relative to real rainfall observed in situ. Recent studies have demonstrated how information about rainfall ...

Investigation of Pearl River data collection system

NASA Technical Reports Server (NTRS)

1976-01-01

The reliability of employing NASA developed remote sensing for in situ near real time monitoring of water quality in the Pearl River is evaluated. The placement, operation and maintenance of a number of NASA developed data collection platforms (DCP's) on the Pearl River are described. The reception, processing, and retransmission of water quality data from an ERTS satellite to the Mississippi Air and Water Pollution Control Commission (MAWPCC) via computer linkup are assessed.

The Joint Milli-Arcsecond Pathfinder Survey (J-MAPS) Mission: Application for Space Situational Awareness

DTIC Science & Technology

2008-09-01

One implication of this is that the instrument can physically resolve satellites at smaller separations than current and existing optical SSA assets...with the potential for 24/7 taskability and near-real time capability. By optimizing an instrument to perform position measurement rather than...sensors. The J-MAPS baseline also includes a novel filter-grating wheel, of interest in the area of non- resolved object characterization. We discuss the

Estimating Integrated Water Vapor (IWV) regional map distribution using METEOSAT satellite data and GPS Zenith Wet Delay (ZWD)

NASA Astrophysics Data System (ADS)

Reuveni, Y.; Leontiev, A.

2016-12-01

Using GPS satellites signals, we can study atmospheric processes and coupling mechanisms, which can help us understand the physical conditions in the upper atmosphere that might lead or act as proxies for severe weather events such as extreme storms and flooding. GPS signals received by geodetic stations on the ground are multi-purpose and can also provide estimates of tropospheric zenith delays, which can be converted into mm-accuracy Precipitable Water Vapor (PWV) using collocated pressure and temperature measurements on the ground. Here, we present the use of Israel's geodetic GPS receivers network for extracting tropospheric zenith path delays combined with near Real Time (RT) METEOSAT-10 Water Vapor (WV) and surface temperature pixel intensity values (7.3 and 12.1 channels, respectively) in order to obtain absolute IWV (kg/m2) or PWV (mm) map distribution. The results show good agreement between the absolute values obtained from our triangulation strategy based solely on GPS Zenith Total Delays (ZTD) and METEOSAT-10 surface temperature data compared with available radiosonde Precipitable IWV/PWV absolute values. The presented strategy can provide unprecedented temporal and special IWV/PWV distribution, which is needed as part of the accurate and comprehensive initial conditions pro­vided by upper-air observation systems at temporal and spatial resolutions consistent with the models assimilating them.

Nature and Intensity of the 22-23 April 2015 Eruptions of Volcán Calbuco, Chile, from Satellite, Lightning, and Field Observations

NASA Astrophysics Data System (ADS)

Van Eaton, A. R.; Amigo, A.; Bertin, D.; Mastin, L. G.; Giacosa, R.; Behnke, S. A.

2015-12-01

On 22 April 2015, Calbuco Volcano in southern Chile erupted for the first time in 43 years. The two primary phases of eruption, separated by a few hours, produced pyroclastic density currents, lahars, and spectacular vertical eruption columns that rose into the stratosphere. Clear weather conditions allowed the populated areas of Puerto Montt and Puerto Varas full view of the lightning-rich eruption, which was rapidly shared through social media. A wealth of remote-sensing data was also publically available in near real-time. We used this information to assess the eruption behavior by combining satellite-based umbrella growth rates, and the location and frequency of volcanic lightning. Umbrella expansion rates from GOES-13 satellite retrievals correspond to eruption rates of about 4x106 kg s-1 for the first eruptive phase and 6x106 kg s-1 for the second phase, following the approach of Pouget et al. (2013, JVGR, 258, 100-112). The location and timing of lightning flashes were obtained from the World Wide Lightning Location Network (WWLLN) Global Volcanic Lightning Monitor, which is updated approximately every minute (Ewert et al., 2010, Fall AGU Abstract AE31A-04). Interestingly, the onset of detected flashes was delayed by ~30 min after the start of each eruptive phase. Lighting provided a useful proxy for the waxing or waning intensity of the eruption, and helped identify the end of significant ash emissions. Using the 1-D volcanic plume model Plumeria, we have also simulated the vertical distribution of ash and ice in the plumes to examine potential causes of the extraordinary amount of volcanic lightning (1,094 flashes detected). Our analysis provides information on eruption timing, duration, and mass flow rate, which are necessary for ash dispersal modeling within hours of eruption. Results are also consistent with the field-based measurements of total erupted volume. We suggest that the combination of satellite-detected umbrella expansion rates with lightning data may provide a useful approach to constrain near real-time inputs for ash dispersal models and hazard warnings.

Introduction to SNPP/VIIRS Flood Mapping Software Version 1.0

NASA Astrophysics Data System (ADS)

Li, S.; Sun, D.; Goldberg, M.; Sjoberg, W.; Santek, D.; Hoffman, J.

2017-12-01

Near real-time satellite-derived flood maps are invaluable to river forecasters and decision-makers for disaster monitoring and relief efforts. With support from the JPSS (Joint Polar Satellite System) Proving Ground and Risk Reduction (PGRR) Program, flood detection software has been developed using Suomi-NPP/VIIRS (Suomi National Polar-orbiting Partnership/Visible Infrared Imaging Radiometer Suite) imagery to automatically generate near real-time flood maps for National Weather Service (NWS) River Forecast Centers (RFC) in the USA. The software, which is called VIIRS NOAA GMU Flood Version 1.0 (hereafter referred to as VNG Flood V1.0), consists of a series of algorithms that include water detection, cloud shadow removal, terrain shadow removal, minor flood detection, water fraction retrieval, and floodwater determination. The software is designed for flood detection in any land region between 80°S and 80°N, and it has been running routinely with direct broadcast SNPP/VIIRS data at the Space Science and Engineering Center at the University of Wisconsin-Madison (UW/SSEC) and the Geographic Information Network of Alaska at the University of Alaska-Fairbanks (UAF/GINA) since 2014. Near real-time flood maps are distributed via the Unidata Local Data Manager (LDM), reviewed by river forecasters in AWIPS-II (the second generation of the Advanced Weather Interactive Processing System) and applied in flood operations. Initial feedback from operational forecasters on the product accuracy and performance has been largely positive. The software capability has also been extended to areas outside of the USA via a case-driven mode to detect major floods all over the world. Offline validation efforts include the visual inspection of over 10,000 VIIRS false-color composite images, an inter-comparison with MODIS automatic flood products and a quantitative evaluation using Landsat imagery. The steady performance from the 3-year routine process and the promising validation results indicate that VNG Flood V1.0 has a high feasibility for flood detection at the product level.

Effect of general relativity on a near-Earth satellite in the geocentric and barycentric reference frames

NASA Technical Reports Server (NTRS)

Ries, J. C.; Huang, C.; Watkins, M. M.

1988-01-01

Whether one uses a solar-system barycentric frame or a geocentric frame when including the general theory of relativity in orbit determinations for near-Earth satellites, the results should be equivalent to some limiting accuracy. The purpose of this paper is to clarify the effects of relativity in each frame and to demonstrate their equivalence through the analysis of real laser-tracking data. A correction to the conventional barycentric equations of motion is shown to be required.

FP7 GLOWASIS - A new collaborative project aimed at pre-validation of a GMES Global Water Scarcity Information Service

NASA Astrophysics Data System (ADS)

Westerhoff, R.; Levizzani, V.; Pappenberger, F.; de Roo, A.; Lange, R. D.; Wagner, W.; Bierkens, M. F.; Ceran, M.; Weerts, A.; Sinclair, S.; Miguez-Macho, G.; Langius, E.; Glowasis Team

2011-12-01

The main objective of the project GLOWASIS is to pre-validate a GMES Global Service for Water Scarcity Information. It will be set up as a one-stop-shop portal for water scarcity information, in which focus is put on: - monitoring data from satellites and in-situ sensors; - improving forecasting models with improved monitoring data; - linking statistical water data in forecasting; - promotion of GMES Services and European satellites. In European and global pilots on the scale of river catchments it combines hydrological models with in-situ and satellite derived water cycle information, as well as government ruled statistical water demand data. By linking water demand and supply in three pilot studies with existing platforms (European Drought Observatory and PCR-GLOBWB) for medium- and long-term forecasting in Europe, Africa and worldwide, GLOWASIS' information contributes both in near-real time reporting for emerging drought events as well as in provision of climate change time series. By combining complex water cycle variables, governmental issues and economic relations with respect to water demand, GLOWASIS will aim for the needed streamlining of the wide variety of important water scarcity information. More awareness for the complexity of the water scarcity problem will be created and additional capabilities of satellite-measured water cycle parameters can be promoted. The service uses data from GMES Core Services LMCS Geoland2 and Marine Core Service MyOcean (land use, soil moisture, soil sealing, sea level), in-situ data from GEWEX' initiatives (i.e. International Soil Moisture network), agricultural and industrial water use and demand (statistical - AQUASTAT, SEEAW and modelled) and additional water-cycle information from existing global satellite services. In-depth interviews with a.o. EEA and the Australian Bureau of Meteorology are taking place. GLOWASIS will aim for an open source and open-standard information portal on water scarcity and use of modern media (forums, Twitter, etc). Infrastructure of the GLOWASIS portal is set up for dissemination and inclusion of current and future innovative and integrated multi-purpose products for research & operational applications with open standards. The project has started in January 2011 and the duration is 24 months.

Systematical estimation of GPM-based global satellite mapping of precipitation products over China

NASA Astrophysics Data System (ADS)

Zhao, Haigen; Yang, Bogang; Yang, Shengtian; Huang, Yingchun; Dong, Guotao; Bai, Juan; Wang, Zhiwei

2018-03-01

As the Global Precipitation Measurement (GPM) Core Observatory satellite continues its mission, new version 6 products for Global Satellite Mapping of Precipitation (GSMaP) have been released. However, few studies have systematically evaluated the GSMaP products over mainland China. This study quantitatively evaluated three GPM-based GSMaP version 6 precipitation products for China and eight subregions referring to the Chinese daily Precipitation Analysis Product (CPAP). The GSMaP products included near-real-time (GSMaP_NRT), microwave-infrared reanalyzed (GSMaP_MVK), and gauge-adjusted (GSMaP_Gau) data. Additionally, the gauge-adjusted Integrated Multi-Satellite Retrievals for Global Precipitation Measurement Mission (IMERG_Gau) was also assessed and compared with GSMaP_Gau. The analyses of the selected daily products were carried out at spatiotemporal resolutions of 1/4° for the period of March 2014 to December 2015 in consideration of the resolution of CPAP and the consistency of the coverage periods of the satellite products. The results indicated that GSMaP_MVK and GSMaP_NRT performed comparably and underdetected light rainfall events (< 5 mm/day) in the northwest and northeast of China. All the statistical metrics of GSMaP_MVK were slightly improved compared with GSMaP_NRT in spring, autumn, and winter, whereas GSMaP_NRT demonstrated superior Pearson linear correlation coefficient (CC), fractional standard error (FSE), and root-mean-square error (RMSE) metrics during the summer. Compared with GSMaP_NRT and GSMaP_MVK, GSMaP_Gau possessed significantly improved metrics over mainland China and the eight subregions and performed better in terms of CC, RMSE, and FSE but underestimated precipitation to a greater degree than IMERG_Gau. As a quantitative assessment of the GPM-era GSMaP products, these validation results will supply helpful references for both end users and algorithm developers. However, the study findings need to be confirmed over a longer future study period when the longer-period IMERG retrospectively-processed data are available.

Towards an Effective Decision Support System for Merapi Volcano (Yogyakarta Region, Indonesia)

NASA Astrophysics Data System (ADS)

Setijadji, L. D.

2011-12-01

The 2010 explosive eruption of Merapi has raised questions on how to develop a near real-time decision support system of multi volcanic hazards (e.g., ash plumes, pyroclastic flow and lahar floods) in populated volcanic terrains such as Yogyakarta region in Indonesia. Despite Merapi has been the most monitored volcano in the nation for a long time, the 2010 eruption behaviors have told us how dynamic a volcano is, and we have to anticipate for any scenarios. The Centre of Volcanology and Geo-hazards Mitigation (PVMBG) has long learned from the well-known Merapi-style eruption (i.e. typically starts with formation of lava dome and is followed by dome-collapse pyroclastic flows) to produce a long-established robust monitoring and prediction system for Merapi. However, the complex magmatic-volcanic system within volcano has proven that Merapi erupted violently in 2010 without a lava dome phase. The existing monitoring instruments which were mainly ground-based geophysical tools were destroyed and in large extent there were times during the crisis that no monitoring system was available in producing near real-time data input. Satellite images data could probably support this mission, but they were not part of existing monitoring systems of PVMBG. Partly as results of this failure, the 2010 eruption took large number of victims (reported loss of life 324) and as much as 320,000 citizens were displaced. The 2010 experience told us that we have to be ready with different styles of eruptions and that the current monitoring system needs to be supported by a reliable decision support system that allow scientists and decision makers to evaluate different scenarios quickly during the crisis, utilizing huge data sets from different instrumentations and platforms. For that purpose we initiated a research which is aimed to study the use of multi data sources such as satellite images and their integration within a Geographic Information System as key elements for a monitoring system during a volcanic eruption crisis and the following events, especially lahar hazards, using the case study of Merapi volcano. Remote sensing is still one of the most cost-effective tools, however the presence of so many different types of Earth Observation (EO) platforms and data make it difficult to select the most appropriate one, especially when we face a limited budget. Data are probably available within several institutions, but so far there is no strong coordination among governmental organizations who deal with geo-hazards. We are still on the progress to evaluate all possible sources of data, their platforms and formats, and building a scenario to use them within an integrative decision support system. We will test and improve the system when we now deal with the lahar flood hazards of Merapi that will likely to be the main hazard threat for people living surrounding Merapi for the next several years.

A New Model for Real-Time Regional Vertical Total Electron Content and Differential Code Bias Estimation Using IGS Real-Time Service (IGS-RTS) Products

NASA Astrophysics Data System (ADS)

Abdelazeem, Mohamed; Çelik, Rahmi N.; El-Rabbany, Ahmed

2016-04-01

The international global navigation satellite system (GNSS) real-time service (IGS-RTS) products have been used extensively for real-time precise point positioning and ionosphere modeling applications. In this study, we develop a regional model for real-time vertical total electron content (RT-VTEC) and differential code bias (RT-DCB) estimation over Europe using the IGS-RTS satellite orbit and clock products. The developed model has a spatial and temporal resolution of 1°×1° and 15 minutes, respectively. GPS observations from a regional network consisting of 60 IGS and EUREF reference stations are processed in the zero-difference mode using the Bernese-5.2 software package in order to extract the geometry-free linear combination of the smoothed code observations. The spherical harmonic expansion function is used to model the VTEC, the receiver and the satellite DCBs. To validate the proposed model, the RT-VTEC values are computed and compared with the final IGS-global ionospheric map (IGS-GIM) counterparts in three successive days under high solar activity including one of an extreme geomagnetic activity. The real-time satellite DCBs are also estimated and compared with the IGS-GIM counterparts. Moreover, the real-time receiver DCB for six IGS stations are obtained and compared with the IGS-GIM counterparts. The examined stations are located in different latitudes with different receiver types. The findings reveal that the estimated RT-VTEC values show agreement with the IGS-GIM counterparts with root mean-square-errors (RMSEs) values less than 2 TEC units. In addition, RMSEs of both the satellites and receivers DCBs are less than 0.85 ns and 0.65 ns, respectively in comparison with the IGS-GIM.

LANDSAT digital data processing: A near real-time application. [Gulf of Mexico

NASA Technical Reports Server (NTRS)

Barker, J. L.; Bohn, C.; Stuart, L.; Hill, J.

1975-01-01

An application of rapid generation of classed digital images from LANDSAT-1 was demonstrated and its feasibility evaluated by NASA in conjunction with the Environmental Protection Agency (EPA), Texas A and M University (TAMU), and the Cousteau Society. The primary purpose was to show that satellite data could be processed and transmitted to the Calypso, which was used as a research vessel, in time for use in directing it to specific locations of possible plankton upwellings, sediment, or other anomalies in the coastal water areas along the Gulf of Mexico.

DSCOVR Satellite Deploy & Light Test

NASA Image and Video Library

2014-11-24

Workers deploy the solar arrays on NOAA’s Deep Space Climate Observatory spacecraft, or DSCOVR, in the Building 1 high bay at the Astrotech payload processing facility in Titusville, Florida, near Kennedy Space Center. DSCOVR is a partnership between NOAA, NASA and the U.S. Air Force. DSCOVR will maintain the nation's real-time solar wind monitoring capabilities which are critical to the accuracy and lead time of NOAA's space weather alerts and forecasts. Launch is targeted for early 2015 aboard a SpaceX Falcon 9 v 1.1 launch vehicle from Cape Canaveral Air Force Station, Florida.

DSCOVR Satellite Deploy & Light Test

NASA Image and Video Library

2014-11-24

The solar arrays on NOAA’s Deep Space Climate Observatory spacecraft, or DSCOVR, are unfurled in the Building 1 high bay at the Astrotech payload processing facility in Titusville, Florida, near Kennedy Space Center. DSCOVR is a partnership between NOAA, NASA and the U.S. Air Force. DSCOVR will maintain the nation's real-time solar wind monitoring capabilities which are critical to the accuracy and lead time of NOAA's space weather alerts and forecasts. Launch is targeted for early 2015 aboard a SpaceX Falcon 9 v 1.1 launch vehicle from Cape Canaveral Air Force Station, Florida.

Canadian Astronautics Limited's SARSAT ground stations

NASA Technical Reports Server (NTRS)

Taylor, J. D.; Renner, R. C.

1984-01-01

The SARSAT Local User Terminal (LUT) is described. The RF receiving subsystem is based on a conventional 3 m dish antenna mounted on an elevation-over-azimuth pedestal to permit tracking of the low altitude, near polar satellites. Only program tracking is used since orbit parameters and time must always be known precisely for use in position location. Operation of the LUT is split into real-time mode during which Doppler data are generated and stored, and post-pass during which data are sorted and position located. Location accuracy is to within 20 km.

Pilot Weather Advisor System

NASA Technical Reports Server (NTRS)

Lindamood, Glenn; Martzaklis, Konstantinos Gus; Hoffler, Keith; Hill, Damon; Mehrotra, Sudhir C.; White, E. Richard; Fisher, Bruce D.; Crabill, Norman L.; Tucholski, Allen D.

2006-01-01

The Pilot Weather Advisor (PWA) system is an automated satellite radio-broadcasting system that provides nearly real-time weather data to pilots of aircraft in flight anywhere in the continental United States. The system was designed to enhance safety in two distinct ways: First, the automated receipt of information would relieve the pilot of the time-consuming and distracting task of obtaining weather information via voice communication with ground stations. Second, the presentation of the information would be centered around a map format, thereby making the spatial and temporal relationships in the surrounding weather situation much easier to understand

Using Multispectral False Color Imaging to Characterize Tropical Cyclone Structure and Environment

NASA Astrophysics Data System (ADS)

Cossuth, J.; Bankert, R.; Richardson, K.; Surratt, M. L.

2016-12-01

The Naval Research Laboratory's (NRL) tropical cyclone (TC) web page (http://www.nrlmry.navy.mil/TC.html) has provided nearly two decades of near real-time access to TC-centric images and products by TC forecasters and enthusiasts around the world. Particularly, microwave imager and sounder information that is featured on this site provides crucial internal storm structure information by allowing users to perceive hydrometeor structure, providing key details beyond cloud top information provided by visible and infrared channels. Towards improving TC analysis techniques and helping advance the utility of the NRL TC webpage resource, new research efforts are presented. This work demonstrates results as well as the methodology used to develop new automated, objective satellite-based TC structure and intensity guidance and enhanced data fusion imagery products that aim to bolster and streamline TC forecast operations. This presentation focuses on the creation and interpretation of false color RGB composite imagery that leverages the different emissive and scattering properties of atmospheric ice, liquid, and vapor water as well as ocean surface roughness as seen by microwave radiometers. Specifically, a combination of near-realtime data and a standardized digital database of global TCs in microwave imagery from 1987-2012 is employed as a climatology of TC structures. The broad range of TC structures, from pinhole eyes through multiple eyewall configurations, is characterized as resolved by passive microwave sensors. The extraction of these characteristic features from historical data also lends itself to statistical analysis. For example, histograms of brightness temperature distributions allows a rigorous examination of how structural features are conveyed in image products, allowing a better representation of colors and breakpoints as they relate to physical features. Such climatological work also suggests steps to better inform the near-real time application of upcoming satellite datasets to TC analyses.

Derivation of a New Smoke Emissions Inventory using Remote Sensing, and Its Implications for Near Real-Time Air Quality Applications

NASA Technical Reports Server (NTRS)

Ellison, Luke; Ichoku, Charles

2012-01-01

A new emissions inventory of particulate matter (PM) is being derived mainly from remote sensing data using fire radiative power (FRP) and aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, as well as wind data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis dataset, which spans the satellite era. This product is generated using a coefficient of emission, C(sub e), that has been produced on a 1x1 degree global grid such that, when it is multiplied with satellite measurements of FRP or its time-integrated equivalent fire radiative energy (FRE) retrieved over a given area and time period, the corresponding PM emissions are estimated. This methodology of using C(sub e) to derive PM emissions is relatively new and advantageous for near real-time air quality applications compared to current methods based on post-fire burned area that may not provide emissions in a timely manner. Furthermore, by using FRP to characterize a fire s output, it will represent better accuracy than the use of raw fire pixel counts, since fires in individual pixels can differ in size and strength by orders of magnitude, resulting in similar differences in emission rates. Here we will show examples of this effect and how this new emission inventory can properly account for the differing emission rates from fires of varying strengths. We also describe the characteristics of the new emissions inventory, and propose the process chain of incorporating it into models for air quality applications.

GLAS Spacecraft Pointing Study

NASA Technical Reports Server (NTRS)

Born, George H.; Gold, Kenn; Ondrey, Michael; Kubitschek, Dan; Axelrad, Penina; Komjathy, Attila

1998-01-01

Science requirements for the GLAS mission demand that the laser altimeter be pointed to within 50 m of the location of the previous repeat ground track. The satellite will be flown in a repeat orbit of 182 days. Operationally, the required pointing information will be determined on the ground using the nominal ground track, to which pointing is desired, and the current propagated orbit of the satellite as inputs to the roll computation algorithm developed by CCAR. The roll profile will be used to generate a set of fit coefficients which can be uploaded on a daily basis and used by the on-board attitude control system. In addition, an algorithm has been developed for computation of the associated command quaternions which will be necessary when pointing at targets of opportunity. It may be desirable in the future to perform the roll calculation in an autonomous real-time mode on-board the spacecraft. GPS can provide near real-time tracking of the satellite, and the nominal ground track can be stored in the on-board computer. It will be necessary to choose the spacing of this nominal ground track to meet storage requirements in the on-board environment. Several methods for generating the roll profile from a sparse reference ground track are presented.

Quantitative retrieval of aerosol optical thickness from FY-2 VISSR data

NASA Astrophysics Data System (ADS)

Bai, Linyan; Xue, Yong; Cao, Chunxiang; Feng, Jianzhong; Zhang, Hao; Guang, Jie; Wang, Ying; Li, Yingjie; Mei, Linlu; Ai, Jianwen

2010-11-01

Atmospheric aerosol, as particulate matter suspended in the air, exists in a variety of forms such as dust, fume and mist. It deeply affects climate and land surface environment in both regional and global scales, and furthermore, lead to be hugely much influence on human health. For the sake of effectively monitoring it, many atmospheric aerosol observation networks are set up and provide associated informational services in the wide world, as well-known Aerosol robotic network (AERONET), Canadian Sunphotometer Network (AeroCan) and so forth. Given large-scale atmospheric aerosol monitoring, that satellite remote sensing data are used to inverse aerosol optical depth is one of available and effective approaches. Nowadays, special types of instruments aboard running satellites are applied to obtain related remote sensing data of retrieving atmospheric aerosol. However, atmospheric aerosol real-timely or near real-timely monitoring hasn't been accomplished. Nevertheless, retrievals, using Fengyun-2 VISSR data, are carried out and the above problem resolved to certain extent, especially over China. In this paper, the authors have developed a new retrieving model/mode to retrieve aerosol optical depth, using Fengyun-2 satellite data that were obtained by the VISSR aboard FY-2C and FY-2D. A series of the aerosol optical depth distribution maps with high time resolution were able to obtained, is helpful for understanding the forming mechanism, transport, influence and controlling approach of atmospheric aerosol.

Impact assessment of GPS radio occultation data on Antarctic analysis and forecast using WRF 3DVAR

NASA Astrophysics Data System (ADS)

Zhang, H.; Wee, T. K.; Liu, Z.; Lin, H. C.; Kuo, Y. H.

2016-12-01

This study assesses the impact of Global Positioning System (GPS) Radio Occultation (RO) refractivity data on the analysis and forecast in the Antarctic region. The RO data are continuously assimilated into the Weather Research and Forecasting (WRF) Model using the WRF 3DVAR along with other observations that were operationally available to the National Center for Environmental Prediction (NCEP) during a month period, October 2010, including the Advance Microwave Sounding Unit (AMSU) radiance data. For the month-long data assimilation experiments, three RO datasets are used: 1) The actual operational dataset, which was produced by the near real-time RO processing at that time and provided to weather forecasting centers; 2) a post-processed dataset with posterior clock and orbit estimates, and with improved RO processing algorithms; and, 3) another post-processed dataset, produced with a variational RO processing. The data impact is evaluated with comparing the forecasts and analyses to independent driftsonde observations that are made available through the Concordiasi field campaign, in addition to utilizing other traditional means of verification. A denial of RO data (while keeping all other observations) resulted in a remarkable quality degradation of analysis and forecast, indicating the high value of RO data over the Antarctic area. The post-processed RO data showed a significantly larger positive impact compared to the near real-time data, due to extra RO data from the TerraSAR-X satellite (unavailable at the time of the near real-time processing) as well as the supposedly improved data quality as a result of the post-processing. This strongly suggests that the future polar constellation of COSMIC-2 is vital. The variational RO processing further reduced the systematic and random errors in both analysis and forecasts, for instance, leading to a smaller background departure of AMSU radiance. This indicates that the variational RO processing provides an improved reference for the bias correction of satellite radiance, making the bias correction more effective. This study finds that advanced RO data processing algorithms may further enhance the high quality of RO data in high Southern latitudes.

Real Time Fire Reconnaissance Satellite Monitoring System Failure Model

NASA Astrophysics Data System (ADS)

Nino Prieto, Omar Ariosto; Colmenares Guillen, Luis Enrique

2013-09-01

In this paper the Real Time Fire Reconnaissance Satellite Monitoring System is presented. This architecture is a legacy of the Detection System for Real-Time Physical Variables which is undergoing a patent process in Mexico. The methodologies for this design are the Structured Analysis for Real Time (SA- RT) [8], and the software is carried out by LACATRE (Langage d'aide à la Conception d'Application multitâche Temps Réel) [9,10] Real Time formal language. The system failures model is analyzed and the proposal is based on the formal language for the design of critical systems and Risk Assessment; AltaRica. This formal architecture uses satellites as input sensors and it was adapted from the original model which is a design pattern for physical variation detection in Real Time. The original design, whose task is to monitor events such as natural disasters and health related applications, or actual sickness monitoring and prevention, as the Real Time Diabetes Monitoring System, among others. Some related work has been presented on the Mexican Space Agency (AEM) Creation and Consultation Forums (2010-2011), and throughout the International Mexican Aerospace Science and Technology Society (SOMECYTA) international congress held in San Luis Potosí, México (2012). This Architecture will allow a Real Time Fire Satellite Monitoring, which will reduce the damage and danger caused by fires which consumes the forests and tropical forests of Mexico. This new proposal, permits having a new system that impacts on disaster prevention, by combining national and international technologies and cooperation for the benefit of humankind.

Evolution of NASA's Near-Earth Tracking and Data Relay Satellite System (TDRSS)

NASA Technical Reports Server (NTRS)

Flaherty, Roger; Stocklin, Frank; Weinberg, Aaron

2006-01-01

NASA's Tracking and Data Relay Satellite System (TDRSS) is now in its 23rd year of operations and its spacecraft fleet includes three second-generation spacecraft launched since the year 2000; a figure illustrates the first generation TDRSS spacecraft. During this time frame the TDRSS has provided communications relay support to a broad range of missions, with emphasis on low-earth-orbiting (LEO) spacecraft that include unmanned science spacecraft (e.g., Hubble Space Telescope), and human spaceflight (Space Shuttle and Space Station). Furthermore, the TDRSS has consistently demonstrated its uniqueness and adaptability in several ways. First, its S- and K-band services, combined with its multi-band/steerable single-access (SA) antennas and ground-based configuration flexibility, have permitted the mission set to expand to unique users such as scientific balloons and launch vehicles. Second, the bent-pipe nature of the system has enabled the introduction of new/improved services via technology insertion and upgrades at each of the ground terminals; a specific example here is the Demand Access Service (DAS), which, for example, is currently providing science-alert support to NASA science missions Third, the bent-pipe nature of the system, combined with the flexible ground-terminal signal processing architecture has permitted the demonstration/vaIidation of new techniques/services/technologies via a real satellite channel; over the past 10+ years these have, for example, included demonstrations/evaluations of emerging modulation/coding techniques. Given NASA's emerging Exploration plans, with missions beginning later this decade and expanding for decades to come, NASA is currently planning the development of a seamless, NASA-wide architecture that must accommodate missions from near-earth to deep space. Near-earth elements include Ground-Network (GN) and Near-Earth Relay (NER) components and both must efficiently and seamlessly support missions that encompass: earth orbit, including dedicated science missions and lunar support/cargo vehicles; earth/moon transit; lunar in-situ operations; and other missions within approximately 2 million km of earth (e.g., at the sun/earth libration points). Given that the NER is an evolution of TDRSS, one element of this NASA-wide architecture development activity is a trade study of future NER architecture candidates. The present paper focuses on trade study aspects associated with the NER, highlights study elements, and provides representative interim results.

On the extraction of directional sea-wave spectra from synthetic- aperture radar-signal arrays without matched filtering.

USGS Publications Warehouse

Wildey, R.L.

1980-01-01

An economical method of digitally extracting sea-wave spectra from synthetic-aperture radar-signal records, which can be performed routinely in real or near-real time with the reception of telemetry from Seasat satellites, would be of value to a variety of scientific disciplines. This paper explores techniques for such data extraction and concludes that the mere fact that the desired result is devoid of phase information does not, of itself, lead to a simplification in data processing because of the nature of the modulation performed on the radar pulse by the backscattering surface. -from Author

Satellite data-relay activities in Arizona

USGS Publications Warehouse

Boner, F.C.; Blee, J.W.; Shope, W.G.

1985-01-01

The U.S. Geological Survey (USGS) Arizona District collects data from automated streamflow stations for a wide variety of uses. Data from these stations are provided to Federal, State, and local agencies that have a responsibility to issue flood warnings; to generate forecasts of water availability; to monitor flow to insure compliance with treaties and other legal mandates; and to manage reservoirs for hydropower, flood abatement, and municipal and irrigation water supply. In the mid-1970's, the escalation of data collection costs and a need for more timely data led the Arizona District to examine alternatives for remote data acquisition. On the basis of successful data communications experiments with NASA 's Landsat satellite, an operational system for satellite-data relay was developed in 1976 using the National Oceanic and Atmospheric Administrations 's (NOAA) Geostationary Operational Environmental Satellite (GOES). A total of 62 data collection platforms (DCP's) was operated in 1983. Satellite telemetry operations are controlled at the remote data-collection stations by small battery-operated data collection platforms. The DCP 's periodically collect data from the sensors, store the data in computer memory, and at preset times transmit the data to the GOES satellite. The satellite retransmits the data to Earth where a ground-receive station transmits or transfers the data by land communications to the USGS computer in Reston, Virginia, for processing. The satellite relay transfers the data from sensor to computer in minutes; therefore, the data are available to users on a near real-time basis. (Author 's abstract)

ERTS direct readout ground station study

NASA Technical Reports Server (NTRS)

1971-01-01

A system configuration which provides for a wide variety of user requirements is described. Two distinct user types are considered and optimized configurations are provided. Independent satellite transmission systems allow simultaneous signal transmission to Regional Collection Centers via a high data rate channel and to local users who require near real time consumption of lower rate data. In order to maximize the ultimate utility of this study effort, a parametric system description is given such that in essence a shopping list is provided. To achieve these results, it was necessary to consider all technical disciplines associated with high resolution satellite imaging systems including signal processing, modulation and coding, recording, and display techniques. A total systems study was performed.

Improvements to the swath-level near-surface atmospheric state parameter retrievals within the NRL Ocean Surface Flux System (NFLUX)

NASA Astrophysics Data System (ADS)

May, J. C.; Rowley, C. D.; Meyer, H.

2017-12-01

The Naval Research Laboratory (NRL) Ocean Surface Flux System (NFLUX) is an end-to-end data processing and assimilation system used to provide near-real-time satellite-based surface heat flux fields over the global ocean. The first component of NFLUX produces near-real-time swath-level estimates of surface state parameters and downwelling radiative fluxes. The focus here will be on the satellite swath-level state parameter retrievals, namely surface air temperature, surface specific humidity, and surface scalar wind speed over the ocean. Swath-level state parameter retrievals are produced from satellite sensor data records (SDRs) from four passive microwave sensors onboard 10 platforms: the Special Sensor Microwave Imager/Sounder (SSMIS) sensor onboard the DMSP F16, F17, and F18 platforms; the Advanced Microwave Sounding Unit-A (AMSU-A) sensor onboard the NOAA-15, NOAA-18, NOAA-19, Metop-A, and Metop-B platforms; the Advanced Technology Microwave Sounder (ATMS) sensor onboard the S-NPP platform; and the Advanced Microwave Scannin Radiometer 2 (AMSR2) sensor onboard the GCOM-W1 platform. The satellite SDRs are translated into state parameter estimates using multiple polynomial regression algorithms. The coefficients to the algorithms are obtained using a bootstrapping technique with all available brightness temperature channels for a given sensor, in addition to a SST field. For each retrieved parameter for each sensor-platform combination, unique algorithms are developed for ascending and descending orbits, as well as clear vs cloudy conditions. Each of the sensors produces surface air temperature and surface specific humidity retrievals. The SSMIS and AMSR2 sensors also produce surface scalar wind speed retrievals. Improvement is seen in the SSMIS retrievals when separate algorithms are used for the even and odd scans, with the odd scans performing better than the even scans. Currently, NFLUX treats all SSMIS scans as even scans. Additional improvement in all of the surface retrievals comes from using a 3-hourly SST field, as opposed to a daily SST field.

Deepwater Horizon - Estimating surface oil volume distribution in real time

NASA Astrophysics Data System (ADS)

Lehr, B.; Simecek-Beatty, D.; Leifer, I.

2011-12-01

Spill responders to the Deepwater Horizon (DWH) oil spill required both the relative spatial distribution and total oil volume of the surface oil. The former was needed on a daily basis to plan and direct local surface recovery and treatment operations. The latter was needed less frequently to provide information for strategic response planning. Unfortunately, the standard spill observation methods were inadequate for an oil spill this size, and new, experimental, methods, were not ready to meet the operational demands of near real-time results. Traditional surface oil estimation tools for large spills include satellite-based sensors to define the spatial extent (but not thickness) of the oil, complemented with trained observers in small aircraft, sometimes supplemented by active or passive remote sensing equipment, to determine surface percent coverage of the 'thick' part of the slick, where the vast majority of the surface oil exists. These tools were also applied to DWH in the early days of the spill but the shear size of the spill prevented synoptic information of the surface slick through the use small aircraft. Also, satellite images of the spill, while large in number, varied considerably in image quality, requiring skilled interpretation of them to identify oil and eliminate false positives. Qualified staff to perform this task were soon in short supply. However, large spills are often events that overcome organizational inertia to the use of new technology. Two prime examples in DWH were the application of hyper-spectral scans from a high-altitude aircraft and more traditional fixed-wing aircraft using multi-spectral scans processed by use of a neural network to determine, respectively, absolute or relative oil thickness. But, with new technology, come new challenges. The hyper-spectral instrument required special viewing conditions that were not present on a daily basis and analysis infrastructure to process the data that was not available at the command post. Very few days provided sufficient observation quality and spatial coverage. Future application of this method will require solving both the observational and analysis challenges demonstrated at DWH. Similarly, the multi-spectral scanner results could only be interpreted by a handful of individuals, causing some logistical problems incorporating the observational results with the incident command decisions. This roadblock may go away as the spill response community becomes more familiar with the technology.

Development of a Near Real-Time Hail Damage Swath Identification Algorithm for Vegetation

NASA Technical Reports Server (NTRS)

Bell, Jordan R.; Molthan, Andrew L.; Schultz, Kori A.; McGrath, Kevin M.; Burks, Jason E.

2015-01-01

Every year in the Midwest and Great Plains, widespread greenness forms in conjunction with the latter part of the spring-summer growing season. This prevalent greenness forms as a result of the high concentration of agricultural areas having their crops reach their maturity before the fall harvest. This time of year also coincides with an enhanced hail frequency for the Great Plains (Cintineo et al. 2012). These severe thunderstorms can bring damaging winds and large hail that can result in damage to the surface vegetation. The spatial extent of the damage can relatively small concentrated area or be a vast swath of damage that is visible from space. These large areas of damage have been well documented over the years. In the late 1960s aerial photography was used to evaluate crop damage caused by hail. As satellite remote sensing technology has evolved, the identification of these hail damage streaks has increased. Satellites have made it possible to view these streaks in additional spectrums. Parker et al. (2005) documented two streaks using the Moderate Resolution Imaging Spectroradiometer (MODIS) that occurred in South Dakota. He noted the potential impact that these streaks had on the surface temperature and associated surface fluxes that are impacted by a change in temperature. Gallo et al. (2012) examined at the correlation between radar signatures and ground observations from storms that produced a hail damage swath in Central Iowa also using MODIS. Finally, Molthan et al. (2013) identified hail damage streaks through MODIS, Landsat-7, and SPOT observations of different resolutions for the development of a potential near-real time applications. The manual analysis of hail damage streaks in satellite imagery is both tedious and time consuming, and may be inconsistent from event to event. This study focuses on development of an objective and automatic algorithm to detect these areas of damage in a more efficient and timely manner. This study utilizes the MODIS sensor aboard the NASA Aqua satellite. Aqua was chosen due to an afternoon orbit over the United States when land surface temperatures are relatively warm and improve the contrast between damaged and undamaged areas. This orbit is also similar to the orbit of the Suomi-National Polar-orbiting Partnership (NPP) satellite. The Suomi NPP satellite hosts the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument, which is the next generation of a MODIS-like sensor in polar orbit.

Real-Time PPP Based on the Coupling Estimation of Clock Bias and Orbit Error with Broadcast Ephemeris.

PubMed

Pan, Shuguo; Chen, Weirong; Jin, Xiaodong; Shi, Xiaofei; He, Fan

2015-07-22

Satellite orbit error and clock bias are the keys to precise point positioning (PPP). The traditional PPP algorithm requires precise satellite products based on worldwide permanent reference stations. Such an algorithm requires considerable work and hardly achieves real-time performance. However, real-time positioning service will be the dominant mode in the future. IGS is providing such an operational service (RTS) and there are also commercial systems like Trimble RTX in operation. On the basis of the regional Continuous Operational Reference System (CORS), a real-time PPP algorithm is proposed to apply the coupling estimation of clock bias and orbit error. The projection of orbit error onto the satellite-receiver range has the same effects on positioning accuracy with clock bias. Therefore, in satellite clock estimation, part of the orbit error can be absorbed by the clock bias and the effects of residual orbit error on positioning accuracy can be weakened by the evenly distributed satellite geometry. In consideration of the simple structure of pseudorange equations and the high precision of carrier-phase equations, the clock bias estimation method coupled with orbit error is also improved. Rovers obtain PPP results by receiving broadcast ephemeris and real-time satellite clock bias coupled with orbit error. By applying the proposed algorithm, the precise orbit products provided by GNSS analysis centers are rendered no longer necessary. On the basis of previous theoretical analysis, a real-time PPP system was developed. Some experiments were then designed to verify this algorithm. Experimental results show that the newly proposed approach performs better than the traditional PPP based on International GNSS Service (IGS) real-time products. The positioning accuracies of the rovers inside and outside the network are improved by 38.8% and 36.1%, respectively. The PPP convergence speeds are improved by up to 61.4% and 65.9%. The new approach can change the traditional PPP mode because of its advantages of independence, high positioning precision, and real-time performance. It could be an alternative solution for regional positioning service before global PPP service comes into operation.

Real-Time PPP Based on the Coupling Estimation of Clock Bias and Orbit Error with Broadcast Ephemeris

PubMed Central

Pan, Shuguo; Chen, Weirong; Jin, Xiaodong; Shi, Xiaofei; He, Fan

2015-01-01

Satellite orbit error and clock bias are the keys to precise point positioning (PPP). The traditional PPP algorithm requires precise satellite products based on worldwide permanent reference stations. Such an algorithm requires considerable work and hardly achieves real-time performance. However, real-time positioning service will be the dominant mode in the future. IGS is providing such an operational service (RTS) and there are also commercial systems like Trimble RTX in operation. On the basis of the regional Continuous Operational Reference System (CORS), a real-time PPP algorithm is proposed to apply the coupling estimation of clock bias and orbit error. The projection of orbit error onto the satellite-receiver range has the same effects on positioning accuracy with clock bias. Therefore, in satellite clock estimation, part of the orbit error can be absorbed by the clock bias and the effects of residual orbit error on positioning accuracy can be weakened by the evenly distributed satellite geometry. In consideration of the simple structure of pseudorange equations and the high precision of carrier-phase equations, the clock bias estimation method coupled with orbit error is also improved. Rovers obtain PPP results by receiving broadcast ephemeris and real-time satellite clock bias coupled with orbit error. By applying the proposed algorithm, the precise orbit products provided by GNSS analysis centers are rendered no longer necessary. On the basis of previous theoretical analysis, a real-time PPP system was developed. Some experiments were then designed to verify this algorithm. Experimental results show that the newly proposed approach performs better than the traditional PPP based on International GNSS Service (IGS) real-time products. The positioning accuracies of the rovers inside and outside the network are improved by 38.8% and 36.1%, respectively. The PPP convergence speeds are improved by up to 61.4% and 65.9%. The new approach can change the traditional PPP mode because of its advantages of independence, high positioning precision, and real-time performance. It could be an alternative solution for regional positioning service before global PPP service comes into operation. PMID:26205276

Satellite and ground-based analysis of the effects on vegetation of continuous SO2 degassing at Turrialba volcano (Costa Rica) and its application to hazard management

NASA Astrophysics Data System (ADS)

Tortini, R.; van Manen, S. M.; Burson, B.; Carn, S. A.

2014-12-01

Turrialba is an active stratovolcano located 35 km northeast of San Jose, Costa Rica's capital city and socioeconomic hub. After over 100 years of quiescence Turrialba resumed activity in 1996 progressively increasing its degassing and seismic activity, showing continuous gas emissions since 2007. Intermittent phreatic explosions with ash emissions that have reached the capital have occurred since 2010. This activity has resulted in the temporary evacuation of two villages, closure of the National Park that comprises the summit region of the volcano and devastation of the local ecosystem. We combined a variety of satellite-based time series with ground-based measurements of ambient gas concentrations, element deposition and surveys of species richness to enable a comprehensive assessment of SO2 emissions and changes in vegetation. Satellite-based time-series were obtained from Landsat ETM+, Terra ASTER, Terra/Aqua MODIS and Aura OMI, with some of the data dating back to 2000. From 2007-2010 we observed emissions of SO2 and loss of vegetation healthiness (i.e. decrease of EVI2) downwind of the vents. From 2010 onwards these stabilized, but we observe an apparent decrease in agriculture. Other multi-temporal products, such as the ALOS PALSAR FNF data, confirm our observations. The exposure to the volcanic plume resulted in high soil acidity and significant uptake of certain heavy metals by vegetation; in contrast other elements are leached from the soil as a result of the acid deposition. These factors are likely to be responsible for decreased species richness and physiological damage observed at Turrialba. Our study shows ecological impacts, in terms of soil characteristics, vegetation composition and diversity and physiological damage of vegetation, which all correlate to fumigation by Turrialba's plume. Analyzing and relating the remote observations to conditions and impacts on the ground provides a better understanding of volcanic degassing, its impacts on vegetation and how satellite-based monitoring can be used to inform hazard management strategies related to land use and agricultural productivity in near-real time.

Real-Time and Post-Processed Georeferencing for Hyperpspectral Drone Remote Sensing

NASA Astrophysics Data System (ADS)

Oliveira, R. A.; Khoramshahi, E.; Suomalainen, J.; Hakala, T.; Viljanen, N.; Honkavaara, E.

2018-05-01

The use of drones and photogrammetric technologies are increasing rapidly in different applications. Currently, drone processing workflow is in most cases based on sequential image acquisition and post-processing, but there are great interests towards real-time solutions. Fast and reliable real-time drone data processing can benefit, for instance, environmental monitoring tasks in precision agriculture and in forest. Recent developments in miniaturized and low-cost inertial measurement systems and GNSS sensors, and Real-time kinematic (RTK) position data are offering new perspectives for the comprehensive remote sensing applications. The combination of these sensors and light-weight and low-cost multi- or hyperspectral frame sensors in drones provides the opportunity of creating near real-time or real-time remote sensing data of target object. We have developed a system with direct georeferencing onboard drone to be used combined with hyperspectral frame cameras in real-time remote sensing applications. The objective of this study is to evaluate the real-time georeferencing comparing with post-processing solutions. Experimental data sets were captured in agricultural and forested test sites using the system. The accuracy of onboard georeferencing data were better than 0.5 m. The results showed that the real-time remote sensing is promising and feasible in both test sites.

Computing and Visualizing Reachable Volumes for Maneuvering Satellites

NASA Astrophysics Data System (ADS)

Jiang, M.; de Vries, W.; Pertica, A.; Olivier, S.

2011-09-01

Detecting and predicting maneuvering satellites is an important problem for Space Situational Awareness. The spatial envelope of all possible locations within reach of such a maneuvering satellite is known as the Reachable Volume (RV). As soon as custody of a satellite is lost, calculating the RV and its subsequent time evolution is a critical component in the rapid recovery of the satellite. In this paper, we present a Monte Carlo approach to computing the RV for a given object. Essentially, our approach samples all possible trajectories by randomizing thrust-vectors, thrust magnitudes and time of burn. At any given instance, the distribution of the "point-cloud" of the virtual particles defines the RV. For short orbital time-scales, the temporal evolution of the point-cloud can result in complex, multi-reentrant manifolds. Visualization plays an important role in gaining insight and understanding into this complex and evolving manifold. In the second part of this paper, we focus on how to effectively visualize the large number of virtual trajectories and the computed RV. We present a real-time out-of-core rendering technique for visualizing the large number of virtual trajectories. We also examine different techniques for visualizing the computed volume of probability density distribution, including volume slicing, convex hull and isosurfacing. We compare and contrast these techniques in terms of computational cost and visualization effectiveness, and describe the main implementation issues encountered during our development process. Finally, we will present some of the results from our end-to-end system for computing and visualizing RVs using examples of maneuvering satellites.

Graphic Server: A real time system for displaying and monitoring telemetry data of several satellites

NASA Technical Reports Server (NTRS)

Douard, Stephane

1994-01-01

Known as a Graphic Server, the system presented was designed for the control ground segment of the Telecom 2 satellites. It is a tool used to dynamically display telemetry data within graphic pages, also known as views. The views are created off-line through various utilities and then, on the operator's request, displayed and animated in real time as data is received. The system was designed as an independent component, and is installed in different Telecom 2 operational control centers. It enables operators to monitor changes in the platform and satellite payloads in real time. It has been in operation since December 1991.

SAR sensors onboard small satellites - Problems and prospectives

NASA Astrophysics Data System (ADS)

Perrotta, Giorgio

A system concept based on a constellation of 4 to 6 lightsats in low inclined circular orbits is presented. Each satellite carries a SAR sensor with two antennas, resulting in 5-m resolution and continuous coverage of the earth belt between 50 deg N and 50 deg S latitude, with typical revisit intervals of a few hours. Such a system appears highly suitable for tactical applications and can be adapted to the needs of conventional disarmament verification. The system can be used for: surface and subsurface sea traffic surveillance; near real-time tracking of oil spills; early warning of events preceding natural disasters; and rapid assessment of postdisaster damage. The system can also support and complement other remote sensing satellites providing, for example, the HF components of the effects of the interaction between meteorological events and soil, vegetation, and national resources in general.

Investigating Montara platform oil spill accident by implementing RST-OIL approach.

NASA Astrophysics Data System (ADS)

Satriano, Valeria; Ciancia, Emanuele; Coviello, Irina; Di Polito, Carmine; Lacava, Teodosio; Pergola, Nicola; Tramutoli, Valerio

2016-04-01

Oil Spills represent one of the most harmful events to marine ecosystems and their timely detection is crucial for their mitigation and management. The potential of satellite data for their detection and monitoring has been largely investigated. Traditional satellite techniques usually identify oil spill presence applying a fixed threshold scheme only after the occurrence of an event, which make them not well suited for their prompt identification. The Robust Satellite Technique (RST) approach, in its oil spill detection version (RST-OIL), being based on the comparison of the latest satellite acquisition with its historical value, previously identified, allows the automatic and near real-time detection of events. Such a technique has been already successfully applied on data from different sources (AVHRR-Advanced Very High Resolution Radiometer and MODIS-Moderate Resolution Imaging Spectroradiometer) showing excellent performance in detecting oil spills both during day- and night-time conditions, with an high level of sensitivity (detection also of low intensity events) and reliability (no false alarm on scene). In this paper, RST-OIL has been implemented on MODIS thermal infrared data for the analysis of the Montara Platform (Timor Sea - Australia) oil spill disaster occurred in August 2009. Preliminary achievements are presented and discussed in this paper.

Real-time sensor validation and fusion for distributed autonomous sensors

NASA Astrophysics Data System (ADS)

Yuan, Xiaojing; Li, Xiangshang; Buckles, Bill P.

2004-04-01

Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

Near real-time monitoring systems for adaptive management and improved forest governance

NASA Astrophysics Data System (ADS)

Musinsky, J.; Tabor, K.; Cano, A.

2012-12-01

The destruction and degradation of the world's forests from deforestation, illegal logging and fire has wide-ranging environmental and economic impacts, including biodiversity loss, the degradation of ecosystem services and the emission of greenhouse gases. In an effort to strengthen local capacity to respond to these threats, Conservation International has developed a suite of near real-time satellite monitoring systems generating daily alerts, maps and reports of forest fire, fire risk, deforestation and degradation that are used by national and sub-national government agencies, NGO's, scientists, communities, and the media to respond to and report on threats to forest resources. Currently, the systems support more than 1000 subscribers from 45 countries, focusing on Madagascar, Indonesia, Bolivia and Peru. This presentation will explore the types of innovative applications users have found for these data, challenges they've encountered in data acquisition and accuracy, and feedback they've given on the usefulness of these systems for REDD+ implementation, protected areas management and improved forest governance.;

Using CATS Near-Real-time Lidar Observations to Monitor and Constrain Volcanic Sulfur Dioxide (SO2) Forecasts

NASA Technical Reports Server (NTRS)

Hughes, E. J.; Yorks, J.; Krotkov, N. A.; da Silva, A. M.; Mcgill, M.

2016-01-01

An eruption of Italian volcano Mount Etna on 3 December 2015 produced fast-moving sulfur dioxide (SO2) and sulfate aerosol clouds that traveled across Asia and the Pacific Ocean, reaching North America in just 5 days. The Ozone Profiler and Mapping Suite's Nadir Mapping UV spectrometer aboard the U.S. National Polar-orbiting Partnership satellite observed the horizontal transport of the SO2 cloud. Vertical profiles of the colocated volcanic sulfate aerosols were observed between 11.5 and 13.5 km by the new Cloud Aerosol Transport System (CATS) space-based lidar aboard the International Space Station. Backward trajectory analysis estimates the SO2 cloud altitude at 7-12 km. Eulerian model simulations of the SO2 cloud constrained by CATS measurements produced more accurate dispersion patterns compared to those initialized with the back trajectory height estimate. The near-real-time data processing capabilities of CATS are unique, and this work demonstrates the use of these observations to monitor and model volcanic clouds.

Using CATS Near-Real-Time Lidar Observations to Monitor and Constrain Volcanic Sulfur Dioxide (SO2) Forecasts

NASA Technical Reports Server (NTRS)

Hughes, E. J.; Yorks, J.; Krotkov, N. A.; Da Silva, A. M.; McGill, M.

2016-01-01

An eruption of Italian volcano Mount Etna on 3 December 2015 produced fast-moving sulfur dioxide (SO2) and sulfate aerosol clouds that traveled across Asia and the Pacific Ocean, reaching North America in just 5days. The Ozone Profiler and Mapping Suite's Nadir Mapping UV spectrometer aboard the U.S. National Polar-orbiting Partnership satellite observed the horizontal transport of the SO2 cloud. Vertical profiles of the colocated volcanic sulfate aerosols were observed between 11.5 and 13.5 km by the new Cloud Aerosol Transport System (CATS) space-based lidar aboard the International Space Station. Backward trajectory analysis estimates the SO2 cloud altitude at 7-12 km. Eulerian model simulations of the SO2 cloud constrained by CATS measurements produced more accurate dispersion patterns compared to those initialized with the back trajectory height estimate. The near-real-time data processing capabilities of CATS are unique, and this work demonstrates the use of these observations to monitor and model volcanic clouds.

A Modern Operating System for Near-real-time Environmental Observatories

NASA Astrophysics Data System (ADS)

Orcutt, John; Vernon, Frank

2014-05-01

The NSF Ocean Observatory Initiative (OOI) provided an opportunity for expanding the capabilities for managing open, near-real-time (latencies of seconds) data from ocean observatories. The sensors deployed in this system largely return data from seafloor, cabled fiber optic cables as well as satellite telemetry. Bandwidth demands range from high-definition movies to the transmission of data via Iridium satellite. The extended Internet also provides an opportunity to not only return data, but to also control the sensors and platforms that comprise the observatory. The data themselves are openly available to any users. In order to provide heightened network security and overall reliability, the connections to and from the sensors/platforms are managed without Layer 3 of the Internet, but instead rely upon message passing using an open protocol termed Advanced Queuing Messaging Protocol (AMQP). The highest bandwidths in the system are in the Regional Scale Network (RSN) off Oregon and Washington and on the continent with highly reliable network connections between observatory components at 10 Gbps. The maintenance of metadata and life cycle histories of sensors and platforms is critical for providing data provenance over the years. The integrated cyberinfrastructure is best thought of as an operating system for the observatory - like the data, the software is also open and can be readily applied to new observatories, for example, in the rapidly evolving Arctic.

Comparison of tropospheric NO2 from in situ aircraft measurements with near-real-time and standard product data from OMI

NASA Astrophysics Data System (ADS)

Bucsela, E. J.; Perring, A. E.; Cohen, R. C.; Boersma, K. F.; Celarier, E. A.; Gleason, J. F.; Wenig, M. O.; Bertram, T. H.; Wooldridge, P. J.; Dirksen, R.; Veefkind, J. P.

2008-08-01

We present an analysis of in situ NO2 measurements from aircraft experiments between summer 2004 and spring 2006. The data are from the INTEX-A, PAVE, and INTEX-B campaigns and constitute the most comprehensive set of tropospheric NO2 profiles to date. Profile shapes from INTEX-A and PAVE are found to be qualitatively similar to annual mean profiles from the GEOS-Chem model. Using profiles from the INTEX-B campaign, we perform error-weighted linear regressions to compare the Ozone Monitoring Instrument (OMI) tropospheric NO2 columns from the near-real-time product (NRT) and standard product (SP) with the integrated in situ columns. Results indicate that the OMI SP algorithm yields NO2 amounts lower than the in situ columns by a factor of 0.86 (±0.2) and that NO2 amounts from the NRT algorithm are higher than the in situ data by a factor of 1.68 (±0.6). The correlation between the satellite and in situ data is good (r = 0.83) for both algorithms. Using averaging kernels, the influence of the algorithm's a priori profiles on the satellite retrieval is explored. Results imply that air mass factors from the a priori profiles are on average slightly larger (˜10%) than those from the measured profiles, but the differences are not significant.

Ka-Band Propagation Studies using the ACTS Propagation Terminal and the CSU-CHILL Multiparameter Radar

NASA Technical Reports Server (NTRS)

Bringi, V. N.; Beaver, John

1996-01-01

One of the first experimental communications satellites using Ka-band technology is the NASA Advanced Communications Technology Satellite (ACTS). In September 1993, ACTS was deployed into a geostationary orbit near 100 degrees W longitude by the space shuttle Discovery. The ACTS system supports both communication and propagation experiments at the 20/30 GHz frequency bands. The propagation experiment involves multi-year attenuation measurements along the satellite-Earth slant path.

Real-Time and Seamless Monitoring of Ground-Level PM2.5 Using Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Li, Tongwen; Zhang, Chengyue; Shen, Huanfeng; Yuan, Qiangqiang; Zhang, Liangpei

2018-04-01

Satellite remote sensing has been reported to be a promising approach for the monitoring of atmospheric PM2.5. However, the satellite-based monitoring of ground-level PM2.5 is still challenging. First, the previously used polar-orbiting satellite observations, which can be usually acquired only once per day, are hard to monitor PM2.5 in real time. Second, many data gaps exist in satellitederived PM2.5 due to the cloud contamination. In this paper, the hourly geostationary satellite (i.e., Harawari-8) observations were adopted for the real-time monitoring of PM2.5 in a deep learning architecture. On this basis, the satellite-derived PM2.5 in conjunction with ground PM2.5 measurements are incorporated into a spatio-temporal fusion model to fill the data gaps. Using Wuhan Urban Agglomeration as an example, we have successfully derived the real-time and seamless PM2.5 distributions. The results demonstrate that Harawari-8 satellite-based deep learning model achieves a satisfactory performance (out-of-sample cross-validation R2 = 0.80, RMSE = 17.49 μg/m3) for the estimation of PM2.5. The missing data in satellite-derive PM2.5 are accurately recovered, with R2 between recoveries and ground measurements of 0.75. Overall, this study has inherently provided an effective strategy for the realtime and seamless monitoring of ground-level PM2.5.

Coherent backscattering effect in spectra of icy satellites and its modeling using multi-sphere T-matrix (MSTM) code for layers of particles

NASA Astrophysics Data System (ADS)

Pitman, Karly M.; Kolokolova, Ludmilla; Verbiscer, Anne J.; Mackowski, Daniel W.; Joseph, Emily C. S.

2017-12-01

The coherent backscattering effect (CBE), the constructive interference of light scattering in particulate surfaces (e.g., regolith), manifests as a non-linear increase in reflectance, or opposition surge, and a narrow negative polarization feature at small solar phase angles. Due to a strong dependence of the amplitude and angular width of this opposition surge on the absorptive characteristics of the surface material, CBE also produces phase-angle-dependent variations in the near-infrared spectra. In this paper we present a survey of such variations in the spectra of icy satellites of Saturn obtained by the Cassini spacecraft's Visual and Infrared Mapping Spectrometer (VIMS) and in the ground-based spectra of Oberon, a satellite of Uranus, obtained with TripleSpec, a cross-dispersed near-infrared spectrometer on the Astrophysical Research Consortium 3.5-m telescope located at the Apache Point Observatory near Sunspot, New Mexico. The paper also presents computer modeling of the saturnian satellite spectra and their phase-angle variations using the most recent version of the Multi-Sphere T-Matrix (MSTM) code developed to simulate light scattering by layers of randomly distributed spherical particles. The modeling allowed us not only to reproduce the observed effects but also to estimate characteristics of the icy particles that cover the surfaces of Rhea, Dione, and Tethys.

Spatiotemporal Visualization of Time-Series Satellite-Derived CO2 Flux Data Using Volume Rendering and Gpu-Based Interpolation on a Cloud-Driven Digital Earth

NASA Astrophysics Data System (ADS)

Wu, S.; Yan, Y.; Du, Z.; Zhang, F.; Liu, R.

2017-10-01

The ocean carbon cycle has a significant influence on global climate, and is commonly evaluated using time-series satellite-derived CO2 flux data. Location-aware and globe-based visualization is an important technique for analyzing and presenting the evolution of climate change. To achieve realistic simulation of the spatiotemporal dynamics of ocean carbon, a cloud-driven digital earth platform is developed to support the interactive analysis and display of multi-geospatial data, and an original visualization method based on our digital earth is proposed to demonstrate the spatiotemporal variations of carbon sinks and sources using time-series satellite data. Specifically, a volume rendering technique using half-angle slicing and particle system is implemented to dynamically display the released or absorbed CO2 gas. To enable location-aware visualization within the virtual globe, we present a 3D particlemapping algorithm to render particle-slicing textures onto geospace. In addition, a GPU-based interpolation framework using CUDA during real-time rendering is designed to obtain smooth effects in both spatial and temporal dimensions. To demonstrate the capabilities of the proposed method, a series of satellite data is applied to simulate the air-sea carbon cycle in the China Sea. The results show that the suggested strategies provide realistic simulation effects and acceptable interactive performance on the digital earth.

Toward a real-time in vivo dosimetry system using plastic scintillation detectors

PubMed Central

Archambault, Louis; Briere, Tina M.; Pönisch, Falk; Beaulieu, Luc; Kuban, Deborah A.; Lee, Andrew; Beddar, Sam

2010-01-01

Purpose In this work, we present and validate a plastic scintillation detector (PSD) system designed for real-time multi-probe in vivo measurements. Methods and Materials The PSDs were built with a dose-sensitive volume of 0.4 mm3. PSDs were assembled into modular detector patches, each containing 5 closely packed PSDs. Continuous dose readings were performed every 150 ms, with a gap between consecutive readings of less than 0.3 ms. We first studied the effect of electron multiplication. We then assessed system performance in acrylic and anthropomorphic pelvic phantoms. Results The PSDs are compatible with clinical rectal balloons and are easily inserted into the anthropomorphic phantom. With an electron multiplication average gain factor of 40, a twofold increase in the signal-to-noise ratio was observed, making near real-time dosimetry feasible. Under calibration conditions, the PSDs agreed with ion chamber measurements to 0.08%. Precision, evaluated as a function of the total dose delivered, ranged from 2.3% at 2 cGy to 0.4% at 200 cGy. Conclusion Real-time PSD measurements are highly accurate and precise. These PSDs can be mounted onto rectal balloons, transforming these clinical devices into in vivo dose detectors without modifying current clinical practice. Real-time monitoring of the dose delivered near the rectum during prostate radiation therapy should help radiation oncologists protect this sensitive normal structure. PMID:20231074

A Recommendation on SLR Ranging to Future Global Navigation Satellite Systems

NASA Astrophysics Data System (ADS)

Labrecque, J. L.; Miller, J. J.; Pearlman, M.

2008-12-01

The multi-agency US Geodetic Requirements Working Group has recommended that Satellite Laser Retro- reflectors be installed on GPS III satellites as a principal component of the Positioning, Navigation, and Timing mandate of the Global Positioning System. The Working Group, which includes NASA, NGA, NOAA, NRL, USGS, and the USNO, echoes the Global Geodetic Observing System recommendation that SLR retro- reflectors be installed on all GNSS satellites. It is further recommended that the retro-reflectors conform to and hopefully exceed the minimum standard of the International Laser Ranging Service for retro-reflector cross sections of 100 million square meters for the HEO GNSS satellites to insure sufficiently accurate ranging by the global network of satellite laser ranging systems. The objective of this recommendation is to contribute to the improvement in the International Terrestrial Reference Frame, and its derivative the WGS84 reference frame, through continuing improvements in the characterization of the GPS orbits and clocks. Another objective is to provide an independent means of assessing the interoperability and accuracy of the GNSS systems and regional augmentation systems. The ranging to GNSS-mounted retro-reflectors will constitute a significant new means of space-based collocation to constrain the tie between the GPS and SLR networks that constitute over 50% of the data from which the ITRF is derived. The recommendation for the installation of SLR retro-reflectors aboard future GPS satellites is one of a number of efforts aimed at improving the accuracy and stability of ITRF. These steps are being coordinated with and supportive of the efforts of the GGOS and its services such at the VLBI2010 initiative, developing a next generation geodetic network, near real-time GPS positioning and EOP determination, and numerous efforts in the improvement of geodetic algorithms for GPS, SLR, VLBI, DORIS, and the determination of the ITRF. If past is prologue, the requirements of accuracy placed upon GNSS systems will continue to evolve at a factor of ten per decade for the lifetime of the GPS III, extending to 2025 and beyond. Global societal priorities such as sea level change measurement already require a factor of ten or more improvement in the accuracy and stability of the ITRF. Increasing accuracy requirements by civilian users for precision positioning and time keeping will certainly continue to grow at an exponential rate. The PNT accuracy of our GNSS systems will keep pace with these societal needs only if we equip the GNSS systems with the capability to identify and further reduce systematic errors.

Enhanced attosecond pulse generation in the vacuum ultraviolet using a two-colour driving field for high harmonic generation

NASA Astrophysics Data System (ADS)

Matía-Hernando, P.; Witting, T.; Walke, D. J.; Marangos, J. P.; Tisch, J. W. G.

2018-03-01

High-harmonic radiation in the extreme ultraviolet and soft X-ray spectral regions can be used to generate attosecond pulses and to obtain structural and dynamic information in atoms and molecules. However, these sources typically suffer from a limited photon flux. An additional issue at lower photon energies is the appearance of satellites in the time domain, stemming from insufficient temporal gating and the spectral filtering required for the isolation of attosecond pulses. Such satellites limit the temporal resolution. The use of multi-colour driving fields has been proven to enhance the harmonic yield and provide additional control, using the relative delays between the different spectral components for waveform shaping. We describe here a two-colour high-harmonic source that combines a few-cycle near-infrared pulse with a multi-cycle second harmonic pulse, with both relative phase and carrier-envelope phase stabilization. We observe strong modulations in the harmonic flux, and present simulations and experimental results supporting the suppression of satellites in sub-femtosecond pulses at 20 eV compared to the single colour field case, an important requirement for attosecond pump-probe measurements.

Landsat Time-Series Analysis Opens New Approaches for Regional Glacier Mapping

NASA Astrophysics Data System (ADS)

Winsvold, S. H.; Kääb, A.; Nuth, C.; Altena, B.

2016-12-01

The archive of Landsat satellite scenes is important for mapping of glaciers, especially as it represents the longest running and continuous satellite record of sufficient resolution to track glacier changes over time. Contributing optical sensors newly launched (Landsat 8 and Sentinel-2A) or upcoming in the near future (Sentinel-2B), will promote very high temporal resolution of optical satellite images especially in high-latitude regions. Because of the potential that lies within such near-future dense time series, methods for mapping glaciers from space should be revisited. We present application scenarios that utilize and explore dense time series of optical data for automatic mapping of glacier outlines and glacier facies. Throughout the season, glaciers display a temporal sequence of properties in optical reflection as the seasonal snow melts away, and glacier ice appears in the ablation area and firn in the accumulation area. In one application scenario presented we simulated potential future seasonal resolution using several years of Landsat 5TM/7ETM+ data, and found a sinusoidal evolution of the spectral reflectance for on-glacier pixels throughout a year. We believe this is because of the short wave infrared band and its sensitivity to snow grain size. The parameters retrieved from the fitting sinus curve can be used for glacier mapping purposes, thus we also found similar results using e.g. the mean of summer band ratio images. In individual optical mapping scenes, conditions will vary (e.g., snow, ice, and clouds) and will not be equally optimal over the entire scene. Using robust statistics on stacked pixels reveals a potential for synthesizing optimal mapping scenes from a temporal stack, as we present in a further application scenario. The dense time series available from satellite imagery will also promote multi-temporal and multi-sensor based analyses. The seasonal pattern of snow and ice on a glacier seen in the optical time series can in the summer season also be observed using radar backscatter series. Optical sensors reveal the reflective properties at the surface, while radar sensors may penetrate the surface revealing properties from a certain volume.In an outlook to this contribution we have explored how we can combine information from SAR and optical sensor systems for different purposes.

Near-infrared high-resolution real-time omnidirectional imaging platform for drone detection

NASA Astrophysics Data System (ADS)

Popovic, Vladan; Ott, Beat; Wellig, Peter; Leblebici, Yusuf

2016-10-01

Recent technological advancements in hardware systems have made higher quality cameras. State of the art panoramic systems use them to produce videos with a resolution of 9000 x 2400 pixels at a rate of 30 frames per second (fps).1 Many modern applications use object tracking to determine the speed and the path taken by each object moving through a scene. The detection requires detailed pixel analysis between two frames. In fields like surveillance systems or crowd analysis, this must be achieved in real time.2 In this paper, we focus on the system-level design of multi-camera sensor acquiring near-infrared (NIR) spectrum and its ability to detect mini-UAVs in a representative rural Swiss environment. The presented results show the UAV detection from the trial that we conducted during a field trial in August 2015.

Access NASA Satellite Global Precipitation Data Visualization on YouTube

NASA Astrophysics Data System (ADS)

Liu, Z.; Su, J.; Acker, J. G.; Huffman, G. J.; Vollmer, B.; Wei, J.; Meyer, D. J.

2017-12-01

Since the satellite era began, NASA has collected a large volume of Earth science observations for research and applications around the world. Satellite data at 12 NASA data centers can also be used for STEM activities such as disaster events, climate change, etc. However, accessing satellite data can be a daunting task for non-professional users such as teachers and students because of unfamiliarity of terminology, disciplines, data formats, data structures, computing resources, processing software, programing languages, etc. Over the years, many efforts have been developed to improve satellite data access, but barriers still exist for non-professionals. In this presentation, we will present our latest activity that uses the popular online video sharing web site, YouTube, to access visualization of global precipitation datasets at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). With YouTube, users can access and visualize a large volume of satellite data without necessity to learn new software or download data. The dataset in this activity is the 3-hourly TRMM (Tropical Rainfall Measuring Mission) Multi-satellite Precipitation Analysis (TMPA). The video consists of over 50,000 data files collected since 1998 onwards, covering a zone between 50°N-S. The YouTube video will last 36 minutes for the entire dataset record (over 19 years). Since the time stamp is on each frame of the video, users can begin at any time by dragging the time progress bar. This precipitation animation will allow viewing precipitation events and processes (e.g., hurricanes, fronts, atmospheric rivers, etc.) on a global scale. The next plan is to develop a similar animation for the GPM (Global Precipitation Measurement) Integrated Multi-satellitE Retrievals for GPM (IMERG). The IMERG provides precipitation on a near-global (60°N-S) coverage at half-hourly time interval, showing more details on precipitation processes and development, compared to the 3-hourly TMPA product. The entire video will contain more than 330,000 files and will last 3.6 hours. Future plans include development of fly-over videos for orbital data for an entire satellite mission or project. All videos will be uploaded and available at the GES DISC site on YouTube (https://www.youtube.com/user/NASAGESDISC).

Combining the Observations from Different GNSS (Invited)

NASA Astrophysics Data System (ADS)

Dach, R.; Lutz, S.; Schaer, S.; Bock, H.; Jäggi, A.; Meindl, M.; Ostini, L.; Thaller, D.; Steinbach, A.; Beutler, G.; Steigenberger, P.

2009-12-01

For a very long time GPS has clearly dominated the use of GNSS measurements for scientific purposes. This picture is changing: we are moving from a GPS-only to a multi-GNSS world. This is, e.g., reflected by changing the meaning of the abbreviation IGS in March 2005 from International GPS to GNSS Service. The current situation can be described as follows: GPS has the leading role in the GNSS because it has provided a very stable satellite constellation over many years. Some of the currently active GPS satellites are nearly 15 years old. These old satellites are expected to be decommissioned within the next years. On the other hand, due to the increasing number of active GLONASS satellites and the improved density of multi-GNSS tracking stations in the IGS network, the quality of the GLONASS orbits has drastically improved during the last years. The European Galileo system is under development: currently two test satellites (GIOVE-A and GIOVE-B) are in orbit. The IOV (in-orbit-validation phase) will start soon. Also the first test satellites for the Chinese Compass system are in space. For the maximum benefit the observations of these GNSS will be processed in a combined multi-GNSS analysis in future. CODE (Center for Orbit Determination in Europe) is a joint venture between the Astronomical Institute of the University Bern (AIUB, Bern, Switzerland), the Federal Office of Topography (swisstopo, Wabern, Switzerland), the Federal Agency for Cartography and Geodesy (BKG, Frankfurt am Main, Germany), and the Institut für Astronomische und Physikalische Geodäsie of the Technische Universität München (IAPG/TUM, Munich, Germany). It acts as one of the global analysis centers of the IGS and has started in May 2003 with a rigorous combined processing of GPS and GLONASS measurements for the final, rapid, and even ultra-rapid product lines. All contributions from CODE to the IGS are in fact multi-GNSS products -- the only exception is the satellite and receiver clock corrections. The procedure to derive the satellite and receiver clock corrections is under the transition from the currently operational GPS-only to the multi-GNSS mode including GPS and GLONASS. When CODE started with its multi-GNSS processing more than 6 years ago the network density and the number of active GLONASS satellites was very limited. Nowadays this situation has changed, which brings us into the position to review the strategy to combine the measurements from different GNSS in the data analysis. The presentation will discuss the advantages and disadvantages of the highest (only one constant inter-system bias) and lowest (a minimum number of common parameters) possible correlation between the observations of the individual GNSS.

Merging climate and multi-sensor time-series data in real-time drought monitoring across the U.S.A.

USGS Publications Warehouse

Brown, Jesslyn F.; Miura, T.; Wardlow, B.; Gu, Yingxin

2011-01-01

Droughts occur repeatedly in the United States resulting in billions of dollars of damage. Monitoring and reporting on drought conditions is a necessary function of government agencies at multiple levels. A team of Federal and university partners developed a drought decision- support tool with higher spatial resolution relative to traditional climate-based drought maps. The Vegetation Drought Response Index (VegDRI) indicates general canopy vegetation condition assimilation of climate, satellite, and biophysical data via geospatial modeling. In VegDRI, complementary drought-related data are merged to provide a comprehensive, detailed representation of drought stress on vegetation. Time-series data from daily polar-orbiting earth observing systems [Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS)] providing global measurements of land surface conditions are ingested into VegDRI. Inter-sensor compatibility is required to extend multi-sensor data records; thus, translations were developed using overlapping observations to create consistent, long-term data time series. 

Latency features of SafetyNet ground systems architecture for the National Polar-orbiting Operational Environmental Satellite System (NPOESS)

NASA Astrophysics Data System (ADS)

Duda, James L.; Mulligan, Joseph; Valenti, James; Wenkel, Michael

2005-01-01

A key feature of the National Polar-orbiting Operational Environmental Satellite System (NPOESS) is the Northrop Grumman Space Technology patent-pending innovative data routing and retrieval architecture called SafetyNetTM. The SafetyNetTM ground system architecture for the National Polar-orbiting Operational Environmental Satellite System (NPOESS), combined with the Interface Data Processing Segment (IDPS), will together provide low data latency and high data availability to its customers. The NPOESS will cut the time between observation and delivery by a factor of four when compared with today's space-based weather systems, the Defense Meteorological Satellite Program (DMSP) and NOAA's Polar-orbiting Operational Environmental Satellites (POES). SafetyNetTM will be a key element of the NPOESS architecture, delivering near real-time data over commercial telecommunications networks. Scattered around the globe, the 15 unmanned ground receptors are linked by fiber-optic systems to four central data processing centers in the U. S. known as Weather Centrals. The National Environmental Satellite, Data and Information Service; Air Force Weather Agency; Fleet Numerical Meteorology and Oceanography Center, and the Naval Oceanographic Office operate the Centrals. In addition, this ground system architecture will have unused capacity attendant with an infrastructure that can accommodate additional users.

The Ozone Monitoring Instrument: overview of 14 years in space

NASA Astrophysics Data System (ADS)

Levelt, Pieternel F.; Joiner, Joanna; Tamminen, Johanna; Pepijn Veefkind, J.; Bhartia, Pawan K.; Stein Zweers, Deborah C.; Duncan, Bryan N.; Streets, David G.; Eskes, Henk; van der A, Ronald; McLinden, Chris; Fioletov, Vitali; Carn, Simon; de Laat, Jos; DeLand, Matthew; Marchenko, Sergey; McPeters, Richard; Ziemke, Jerald; Fu, Dejian; Liu, Xiong; Pickering, Kenneth; Apituley, Arnoud; González Abad, Gonzalo; Arola, Antti; Boersma, Folkert; Miller, Christopher Chan; Chance, Kelly; de Graaf, Martin; Hakkarainen, Janne; Hassinen, Seppo; Ialongo, Iolanda; Kleipool, Quintus; Krotkov, Nickolay; Li, Can; Lamsal, Lok; Newman, Paul; Nowlan, Caroline; Suleiman, Raid; Gijsbert Tilstra, Lieuwe; Torres, Omar; Wang, Huiqun; Wargan, Krzysztof

2018-04-01

This overview paper highlights the successes of the Ozone Monitoring Instrument (OMI) on board the Aura satellite spanning a period of nearly 14 years. Data from OMI has been used in a wide range of applications and research resulting in many new findings. Due to its unprecedented spatial resolution, in combination with daily global coverage, OMI plays a unique role in measuring trace gases important for the ozone layer, air quality, and climate change. With the operational very fast delivery (VFD; direct readout) and near real-time (NRT) availability of the data, OMI also plays an important role in the development of operational services in the atmospheric chemistry domain.

The Ozone Monitoring Instrument: overview of 14 years in space

NASA Technical Reports Server (NTRS)

Tamminen, Johanna; Veefkind, J. Pepijn; van der A, Ronald; Miller, Christopher Chan; Ialongo, Iolanda; Kleipool, Quintus; Lamsal, Lok N.; Wang, Huiqun; Bhartia, Pawan K.; Zweers, Deborah C. Stein;

Influence of satellite alerts on the efficiency of aircraft monitoring of maritime oil pollution in German waters

NASA Astrophysics Data System (ADS)

Helmke, Peer; Baschek, Björn; Hunsänger, Thomas; Kranz, Susanne

2014-10-01

For detecting accidental and illegal pollution by mineral oil, the German exclusive economic zone and surrounding waters have been monitored by aircraft operationally for more than 25 years. Aircraft surveillance uses predominantly Side-Looking-Airborne-Radar for visualization of the effect of oil to smoothen capillary waves. A set of near range sensors complements the remote sensing data available for the human operator to classify the detected features as "mineral oil", "natural phenomenon", "other substance" or "unknown" pollution. Today, as an add-on to aerial surveillance, the German Central Command of Maritime Emergencies uses the operational satellite service "CleanSeaNet" provided by the European Maritime Safety Agency: Radar satellite data is analyzed in near real time and alerts of potential pollution are sent out. Shortly after receiving the results, aircraft surveillance flights are started by the 3rd Naval Air Wing and the locations of the satellite alerts are checked. Thus, a combined system of satellite and aerial surveillance is in place. The German Federal Institute of Hydrology, BfG, has access to the data of the pollution events detected during these flights and the corresponding meta-data of flights and satellite images. In this work, a period of two years of this data is analyzed. The probability to detect pollutions is evaluated for (A) flight missions associated with satellite scenes, and (B) additional flights performed independently from satellite scenes. Thus, the influence of satellite alerts on the efficiency of aircraft monitoring is investigated. Coverage and coordination of the monitoring by aircraft and satellite are assessed and implications for the operational monitoring are discussed.

DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

NASA Astrophysics Data System (ADS)

Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.

2017-12-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remotesensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud/shadow mask from geostationary satellite data iscritical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds, which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoder-decoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multi-spectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

Long-term autonomous volcanic gas monitoring with Multi-GAS at Mount St. Helens, Washington, and Augustine Volcano, Alaska

NASA Astrophysics Data System (ADS)

Kelly, P. J.; Ketner, D. M.; Kern, C.; Lahusen, R. G.; Lockett, C.; Parker, T.; Paskievitch, J.; Pauk, B.; Rinehart, A.; Werner, C. A.

2015-12-01

In recent years, the USGS Volcano Hazards Program has worked to implement continuous real-time in situ volcanic gas monitoring at volcanoes in the Cascade Range and Alaska. The main goal of this ongoing effort is to better link the compositions of volcanic gases to other real-time monitoring data, such as seismicity and deformation, in order to improve baseline monitoring and early detection of volcanic unrest. Due to the remote and difficult-to-access nature of volcanic-gas monitoring sites in the Cascades and Alaska, we developed Multi-GAS instruments that can operate unattended for long periods of time with minimal direct maintenance from field personnel. Our Multi-GAS stations measure H2O, CO2, SO2, and H2S gas concentrations, are comprised entirely of commercial off-the-shelf components, and are powered by small solar energy systems. One notable feature of our Multi-GAS stations is that they include a unique capability to perform automated CO2, SO2, and H2S sensor verifications using portable gas standards while deployed in the field, thereby allowing for rigorous tracking of sensor performances. In addition, we have developed novel onboard data-processing routines that allow diagnostic and monitoring data - including gas ratios (e.g. CO2/SO2) - to be streamed in real time to internal observatory and public web pages without user input. Here we present over one year of continuous data from a permanent Multi-GAS station installed in August 2014 in the crater of Mount St. Helens, Washington, and several months of data from a station installed near the summit of Augustine Volcano, Alaska in June 2015. Data from the Mount St. Helens Multi-GAS station has been streaming to a public USGS site since early 2015, a first for a permanent Multi-GAS site. Neither station has detected significant changes in gas concentrations or compositions since they were installed, consistent with low levels of seismicity and deformation.

The Fire Locating and Modeling of Burning Emissions (FLAMBE) Project

NASA Astrophysics Data System (ADS)

Reid, J. S.; Prins, E. M.; Westphal, D.; Richardson, K.; Christopher, S.; Schmidt, C.; Theisen, M.; Eck, T.; Reid, E. A.

2001-12-01

The Fire Locating and Modeling of Burning Emissions (FLAMBE) project was initiated by NASA, the US Navy and NOAA to monitor biomass burning and burning emissions on a global scale. The idea behind the mission is to integrate remote sensing data with global and regional transport models in real time for the purpose of providing the scientific community with smoke and fire products for planning and research purposes. FLAMBE is currently utilizing real time satellite data from GOES satellites, fire products based on the Wildfire Automated Biomass Burning Algorithm (WF_ABBA) are generated for the Western Hemisphere every 30 minutes with only a 90 minute processing delay. We are currently collaborating with other investigators to gain global coverage. Once generated, the fire products are used to input smoke fluxes into the NRL Aerosol Analysis and Prediction System, where advection forecasts are performed for up to 6 days. Subsequent radiative transfer calculations are used to estimate top of atmosphere and surface radiative forcing as well as surface layer visibility. Near real time validation is performed using field data collected by Aerosol Robotic Network (AERONET) Sun photometers. In this paper we fully describe the FLAMBE project and data availability. Preliminary result from the previous year will also be presented, with an emphasis on the development of algorithms to determine smoke emission fluxes from individual fire products. Comparisons to AERONET Sun photometer data will be made.

A two-step framework for reconstructing remotely sensed land surface temperatures contaminated by cloud

NASA Astrophysics Data System (ADS)

Zeng, Chao; Long, Di; Shen, Huanfeng; Wu, Penghai; Cui, Yaokui; Hong, Yang

2018-07-01

Land surface temperature (LST) is one of the most important parameters in land surface processes. Although satellite-derived LST can provide valuable information, the value is often limited by cloud contamination. In this paper, a two-step satellite-derived LST reconstruction framework is proposed. First, a multi-temporal reconstruction algorithm is introduced to recover invalid LST values using multiple LST images with reference to corresponding remotely sensed vegetation index. Then, all cloud-contaminated areas are temporally filled with hypothetical clear-sky LST values. Second, a surface energy balance equation-based procedure is used to correct for the filled values. With shortwave irradiation data, the clear-sky LST is corrected to the real LST under cloudy conditions. A series of experiments have been performed to demonstrate the effectiveness of the developed approach. Quantitative evaluation results indicate that the proposed method can recover LST in different surface types with mean average errors in 3-6 K. The experiments also indicate that the time interval between the multi-temporal LST images has a greater impact on the results than the size of the contaminated area.

Recent Enhancements in NOAA's JPSS Land Product Suite and Key Operational Applications

NASA Astrophysics Data System (ADS)

Csiszar, I. A.; Yu, Y.; Zhan, X.; Vargas, M.; Ek, M. B.; Zheng, W.; Wu, Y.; Smirnova, T. G.; Benjamin, S.; Ahmadov, R.; James, E.; Grell, G. A.

2017-12-01

A suite of operational land products has been produced as part of NOAA's Joint Polar Satellite System (JPSS) program to support a wide range of operational applications in environmental monitoring, prediction, disaster management and mitigation, and decision support. The Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership (NPP) and the operational JPSS satellite series forms the basis of six fundamental and multiple additional added-value environmental data records (EDRs). A major recent improvement in the land-based VIIRS EDRs has been the development of global gridded products, providing a format and science content suitable for ingest into NOAA's operational land surface and coupled numerical weather prediction models. VIIRS near-real-time Green Vegetation Fraction is now in the process of testing for full operational use, while land surface temperature and albedo are under testing and evaluation. The operational 750m VIIRS active fire product, including fire radiative power, is used to support emission modeling and air quality applications. Testing the evaluation for operational NOAA implementation of the improved 375m VIIRS active fire product is also underway. Added-value and emerging VIIRS land products include vegetation health, phenology, near-real-time surface type and surface condition change, and other biogeophysical variables. As part of the JPSS program, a global soil moisture data product has also been generated from the Advanced Microwave Scanning Radiometer 2 (AMSR2) sensor on the GCOM-W1 (Global Change Observation Mission - Water 1) satellite since July 2012. This product is included in the blended NESDIS Soil Moisture Operational Products System, providing soil moisture data as a critical input for land surface modeling.

Understanding climatological, instantaneous and reference VTEC maps, its variability, its relation to STEC and its assimilation by VTEC models

NASA Astrophysics Data System (ADS)

Orus, R.; Prieto-Cerdeira, R.

2012-12-01

As the next Solar Maximum peak is approaching, forecasted for the late 2013, it is a good opportunity to study the ionospheric behaviour in such conditions and how this behaviour can be estimated and corrected by existing climatological models - e.g.. NeQuick, International Reference Ionosphere (IRI)- , as well as, GNSS driven models, such as Klobuchar, NeQuick Galileo, SBAS MOPS (EGNOS and WAAS corrections) and Near Real Time Global Ionospheric Maps (GIM) or regional Maps computed by different institutions. In this framework, technology advances allow to increase the computational and radio frequency channels capabilities of low-cost receivers embedded in handheld devices (such mobile phones, pads, trekking clocks, photo-cameras, etc). This may enable the active use of received ionospheric data or correction parameters from different data sources. The study is centred in understanding the ionosphere but focusing on its impact on the position error for low-cost single-frequency receivers. This study tests optimal ways to take advantage of a big amount of Real or Near Real Time ionospheric information and the way to combine various corrections in order to reach a better navigation solution. In this context, the use of real time estimation vTEC data coming from EGNOS or WAAS or near real time GIMs are used to feed the standard GPS single-frequency ionospheric correction models (Klobuchar) and get enhanced Ionospheric corrections with minor changes on the navigation software. This is done by using a Taylor expansion over the 8 coefficients send by GPS. Moreover, the same datasets are used to assimilate it in NeQuick, for broadcast coefficients, as well as, for grid assimilation. As a side product, electron density profiles in Near Real Time could be estimated with data assimilated from different ionospheric sources. Finally, the ionospheric delay estimation for multi-constellation receivers could take benefit from a common and more accurate ionospheric model being able to reduce the position error due to ionosphere. Therefore, a performance study of the different models to navigate with GNSS will be presented in different ionospheric conditions and using different sources for the model adjustment, keeping the real time capability of the receivers.

Innovative Approaches for the Dissemination of Near Real-time Geostationary Satellite Data for Terrestrial and Space Weather Applications

NASA Astrophysics Data System (ADS)

Jedlovec, G.; McGrath, K.; Meyer, P. J.; Berndt, E.

2017-12-01

A GOES-R series receiving station has been installed at the NASA Marshall Space Flight Center (MSFC) to support GOES-16 transition-to-operations projects of NASA's Earth science program and provide a community portal for GOES-16 data access. This receiving station is comprised of a 6.5-meter dish; motor-driven positioners; Quorum feed and demodulator; and three Linux workstations for ingest, processing, display, and subsequent product generation. The Community Satellite Processing Package (CSPP) is used to process GOES Rebroadcast data from the Advanced Baseline Imager (ABI), Geostationary Lightning Mapper (GLM), Solar Ultraviolet Imager (SUVI), Extreme Ultraviolet and X-ray Irradiance Sensors (EXIS), and Space Environment In-Situ Suite (SEISS) into Level 1b and Level 2 files. GeoTIFFs of the imagery from several of these instruments are ingested into an Esri Arc Enterprise Web Map Service (WMS) server with tiled imagery displayable through a web browser interface or by connecting directly to the WMS with a Geographic Information System software package. These data also drive a basic web interface where users can manually zoom to and animate regions of interest or acquire similar results using a published Application Program Interface. While not as interactive as a WMS-driven interface, this system is much more expeditious with generating and distributing requested imagery. The legacy web capability enacted for the predecessor GOES Imager currently supports approximately 500,000 unique visitors each month. Dissemination capabilities have been refined to support a significantly larger number of anticipated users. The receiving station also supports NASA's Short-term Prediction, Research, and Transition Center's (SPoRT) project activities to dissemination near real-time ABI RGB products to National Weather Service National Centers, including the Satellite Analysis Branch, National Hurricane Center, Ocean Prediction Center, and Weather Prediction Center, where they are displayed in N-AWIPS and AWIPS II. The multitude of additional real-time data users include the U.S. Coast Guard, Federal Aviation Administration, and The Weather Company. A second antenna is being installed for the ingest, processing, and dissemination of GOES-S data.

Operational Space Weather Models: Trials, Tribulations and Rewards

NASA Astrophysics Data System (ADS)

Schunk, R. W.; Scherliess, L.; Sojka, J. J.; Thompson, D. C.; Zhu, L.

2009-12-01

There are many empirical, physics-based, and data assimilation models that can probably be used for space weather applications and the models cover the entire domain from the surface of the Sun to the Earth’s surface. At Utah State University we developed two physics-based data assimilation models of the terrestrial ionosphere as part of a program called Global Assimilation of Ionospheric Measurements (GAIM). One of the data assimilation models is now in operational use at the Air Force Weather Agency (AFWA) in Omaha, Nebraska. This model is a Gauss-Markov Kalman Filter (GAIM-GM) model, and it uses a physics-based model of the ionosphere and a Kalman filter as a basis for assimilating a diverse set of real-time (or near real-time) measurements. The physics-based model is the Ionosphere Forecast Model (IFM), which is global and covers the E-region, F-region, and topside ionosphere from 90 to 1400 km. It takes account of five ion species (NO+, O2+, N2+, O+, H+), but the main output of the model is a 3-dimensional electron density distribution at user specified times. The second data assimilation model uses a physics-based Ionosphere-Plasmasphere Model (IPM) and an ensemble Kalman filter technique as a basis for assimilating a diverse set of real-time (or near real-time) measurements. This Full Physics model (GAIM-FP) is global, covers the altitude range from 90 to 30,000 km, includes six ions (NO+, O2+, N2+, O+, H+, He+), and calculates the self-consistent ionospheric drivers (electric fields and neutral winds). The GAIM-FP model is scheduled for delivery in 2012. Both of these GAIM models assimilate bottom-side Ne profiles from a variable number of ionosondes, slant TEC from a variable number of ground GPS/TEC stations, in situ Ne from four DMSP satellites, line-of-sight UV emissions measured by satellites, and occultation data. Quality control algorithms for all of the data types are provided as an integral part of the GAIM models and these models take account of latent data (up to 3 hours). The trials, tribulations and rewards of constructing and maintaining operational data assimilation models will be discussed.

Multi-carrier mobile TDMA system with active array antenna

NASA Technical Reports Server (NTRS)

Suzuki, Ryutaro; Matsumoto, Yasushi; Hamamoto, Naokazu

1990-01-01

A multi-carrier time division multiple access (TDMA) is proposed for the future mobile satellite communications systems that include a multi-satellite system. This TDMA system employs the active array antenna in which the digital beam forming technique is adopted to control the antenna beam direction. The antenna beam forming is carried out at the base band frequency by using the digital signal processing technique. The time division duplex technique is applied for the TDM/TDMA burst format, in order not to overlap transmit and receive timing.

Korea Earth Observation Satellite Program

NASA Astrophysics Data System (ADS)

Baek, Myung-Jin; Kim, Zeen-Chul

via Korea Aerospace Research Institute (KARI) as the prime contractor in the area of Korea earth observation satellite program to enhance Korea's space program development capability. In this paper, Korea's on-going and future earth observation satellite programs are introduced: KOMPSAT- 1 (Korea Multi Purpose Satellite-1), KOMPSAT-2 and Communication, Broadcasting and Meteorological Satellite (CBMS) program. KOMPSAT-1 satellite successfully launched in December 1999 with Taurus launch vehicle. Since launch, KOMPSAT-1 is downlinking images of Korea Peninsular every day. Until now, KOMPSAT-1 has been operated more than 2 and half years without any major hardware malfunction for the mission operation. KOMPSAT-1 payload has 6.6m panchromatic spatial resolution at 685 km on-orbit and the spacecraft bus had NASA TOMS-EP (Total Ozone Mapping Spectrometer-Earth Probe) spacecraft bus heritage designed and built by TRW, U.S.A.KOMPSAT-1 program was international co-development program between KARI and TRW funded by Korean Government. be launched in 2004. Main mission objective is to provide geo-information products based on the multi-spectral high resolution sensor called Multi-Spectral Camera (MSC) which will provide 1m panchromatic and 4m multi-spectral high resolution images. ELOP of Israel is the prime contractor of the MSC payload system and KARI is the total system prime contractor including spacecraft bus development and ground segment. KARI also has the contract with Astrium of Europe for the purpose of technical consultation and hardware procurement. Based on the experience throughout KOMPSAT-1 and KOMPSAT-2 space system development, Korea is expecting to establish the infrastructure of developing satellite system. Currently, KOMPSAT-2 program is in the critical design stage. are scheduled to launch in 2008 and in 2014, respectively. The mission of CBMS consists of two areas. One is of space technology test for the communications mission, and the other is of a real- time environmental observation for meteorological mission on the geosynchronous orbit for public services. The CBMS is expected to weigh about 2 ~ 2.5 tons, and 6 channels of Ka-band and S- band transponder are equipped for communications service and observation payloads such as meteorological and ocean sensors. To increase the reliability of the first CBMS, a cooperative development with advanced foreign companies of the space business is being considered.

(abstract) TOPEX/Poseidon: Four Years of Synoptic Oceanography

NASA Technical Reports Server (NTRS)

Fu, Lee-Lueng

1996-01-01

Exceeding all expectations of measurement precision and accuracy, the US/France TOPEX/Poseidon satellite mission is now in its 5th year. Returning more than 98 percent of the altimetric data, the measured global geocentric height of the sea surface has provided unprecedented opportunities to address a host of scientific problems ranging from the dynamics of ocean circulation to the distribution of internal tidal energy. Scientific highlights of this longest-running altimetric satellite mission include improvements in our understanding of the dynamics and thermodynamics of the large-scale ocean variability, such as, the properties of planetary waves; the energetics of basin-wide gyres; the heat budget of the ocean; and the ocean's response to wind forcing. For the first time, oceanographers have quantitative descriptions of a dynamic variable of the physical state of the global oceans available in near-real-time.

Hydrodynamic characteristics in the Levantine Basin in autumn 2016 - The CINEL experiment (CIrculation and water mass properties in the North-Eastern Levantine)

NASA Astrophysics Data System (ADS)

Mauri, Elena; Poulain, Pierre-Marie; Gerin, Riccardo; Hayes, Dan; Gildor, Hezi; Kokkini, Zoi

2017-04-01

During the CINEL experiment, currents and thermohaline properties of the water masses in the eastern areas of the Levantine Basin (Mediterranean Sea) were monitored with mobile autonomous systems in October-December 2016. Two gliders were operated together with satellite-tracked drifters and Argo floats to study the complex circulation features governing the dynamics near the coast and in the open sea. Strong mesoscale and sub-basin scale eddies were detected and were crossed several times by the gliders during the experiment. The physical and biogeochemical parameters were sampled, showing peculiar characteristics in some of the mesoscale features and a probable interaction with a persistent coastal current off Israel. The in-situ observations were interpreted in concert with the distribution of tracers (sea surface temperature, chlorophyll) and altimetry data obtained from satellites. Numerical simulations with a high resolution model in which deep profiles of temperature and salinity from gliders were assimilated, were used in near-real time to fine tune the observational array and to help with the interpretation of the local dynamics.