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At least 199 records · Page 11

Toward The Development of Hailstorm Climatologies Derived From Reanalyses and Infared/Passive Microwave Satellite Imagers

Geostationary satellite imagers, such as those of the Geostationary Operational Environmental Satellite (GOES) and Meteosat series, provide both historical and near-real-time observations of cloud top patterns that are commonly associated with severe convection. Environmental conditions favorable for severe weather are thought to be represented well by reanalyses. Predicting exactly where convection and costly storm hazards like hail will occur using models or satellite imagery alone, however, is extremely challenging. The multivariate combination of satellite-observed cloud patterns with reanalysis environmental parameters, linked to United States Next Generation Weather Radar- (NEXRAD-) estimated Maximum Expected Size of Hail (MESH) using a deep neural network (DNN), enables estimation of potentially severe hail likelihood for any observed storm cell. These estimates are specifically designed to make hail likelihood distinctions based on satellite-indicated points of deep convection within environments favorable for storm development. We seek an approach that can be used to estimate climatological hailstorm frequency and risk throughout the historical satellite data record. This presentation demonstrates that statistical distributions of convective parameters from satellite and reanalysis show separation between non-severe/severe hailstorm classes for predictors including overshooting cloud top temperature and area characteristics, convective available potential energy, vertical wind shear, 500 hPa temperature, mid-level lapse rate, precipitable water, and convective inhibition. These complex, multivariate predictor relationships are exploited within a DNN to produce a hail likelihood metric with a critical success index of 0.504 and Heidke skill score of 0.403, which is exceptional among recent analogous hail studies. Furthermore, applications of the DNN to select case studies demonstrate good qualitative agreement between hail likelihood and MESH. These hail classifications are aggregated across an 11-year GOES-12/13 image database to derive a hail frequency and severity climatology, which denotes the Central Plains, the Midwest, and northwestern Mexico as being the most hail-prone regions within the domain studied. Opportunities for training and applying DNN-based hailstorm predictions to recently developed GOES-8/10/12/13/16 and Meteosat Second Generation convective storm detection and characterization climatologies over South America and South Africa, respectively, will also be presented.

Kristopher Bedka↗

The use of satellites in non-goestationary orbits for unloading geostationary communication satellite traffic peaks. Volume 2: Technical report

The part of the geostationary (GEO) orbital arc used for United States domestic fixed, communications service is rapidly becoming filled with satellites. One of the factors currently limiting its utilization is that communications satellites must be designed to have sufficient capacity to handle peak traffic leads, and thus are under utilized most of the time. A solution is to use satellites in suitable non-geostationary orbits to unload the traffic peaks. Three different designs for a non-geostationary orbit communications satellite system are presented for the 1995 time frame. The economic performance is analyzed and compared with geostationary satellites for two classes of service, trunking and customer premise service. The result is that the larger payload of the non-geostationary satellite offsets the burdens of increased complexity and worse radiation environment to give improved economic performance. Depending on ground terminal configuration, the improved economic performance of the space segment may be offset by increased ground terminal expenses.

Price, K.↗

Geostationary Meteorological Satellite-5 (GMS-5)

The Geostationary Meteorological Satellite (GMS-5), which is being developed by the National Space Development Agency of Japan (NASDA), is the fifth geostationary, spin stabilized, weather satellite. Its purposes are to observe cataclysmic events such as hurricanes, typhoons, and regional weather phenomena; to relay meteorological data from surface collection points to the Data Processing Center in Japan; and to transmit processing imaging data for facsimile reproduction. The satellite will be launched from the Tanegashima Space Center (TaSC) in Japan by a type H-II launch vehicle. The Deep Space Network (DSN) will support the transfer and drift orbit mission phases. The coverage will consist of the 26-m antennas as prime and the 34-m antenna at Madrid as backup support for launch through drift orbit. Maximum support will consist of two 8-hour tracks per station for a seven day period, plus 23 days of contingency support from all complexes. Information is given in tabular form for DSN support, frequency assignments, telemetry, command and tracking station responsibility.

Horii, M.↗

The ATS-F/Nimbus-F tracking and orbit determination experiment

The experiment described was conducted to demonstrate a procedure for tracking a near-earth satellite via a geostationary satellite without the aid of multiple ground station tracking. Another objective of the experiment was connected with the utilization of the broad tracking coverage provided by the geostationary satellite to obtain an improved geopotential solution. Questions of overall experiment implementation are discussed along with details regarding ground equipment, the ATS-F transponder, and the Nimbus-F transponder. Aspects of measurement evaluation are also examined, taking into account basic measurements, measurement interpretation, and approaches for orbit computation.

Schmid, P. E.↗

Cloud parameters from GOES visible and infrared radiances during the FIRE Cirrus IFO, October 1986

Visible (VIS, 0.65 micron) and infrared (IR, 10.5 microns) channels on geostationary satellites are the key elements of the International Satellite Cloud Climatology Project (ISCCP). All daytime ISCCP cloud parameters are derived from a combination of VIS and IR data. Validation and improvement of the ISCCP and other cloud retrieval algorithms are important components of the First ISCCP Regional Experiment (FIRE) Intensive Field Observations (IFO). Data from the Cirrus IFO (October 19 to November 2, 1986) over Wisconsin are available for validating cirrus cloud retrievals from satellites. The Geostationary Operational Environmental Satellite (GOES) located over the Equator at approximately 100 deg W provided nearly continuous measurements of VIS and IR radiances over the IFO areas. The preliminary results of cloud parameters derived from the IFO GOES data are presented. Cloud attitudes are first derived using an algorithms without corrections for cloud emissivity. These same parameters will then be computed from the same data relying on an emissivity correction algorithm based on correlative data taken during the Cirrus IFO.

Heck, Patrick W.↗

Destination-directed, packet-switching architecture for 30/20-GHz FDMA/TDM geostationary communications satellite network

A destination-directed packet switching architecture for a 30/20-GHz frequency division multiple access/time division multiplexed (FDMA/TDM) geostationary satellite communications network is discussed. Critical subsystems and problem areas are identified and addressed. Efforts have concentrated heavily on the space segment; however, the ground segment has been considered concurrently to ensure cost efficiency and realistic operational constraints.

Ivancic, William D.↗

Destination-directed, packet-switched architecture for a geostationary communications satellite network

A major goal of the Digital Systems Technology Branch at the NASA Lewis Research Center is to identify and develop critical digital components and technologies that either enable new commercial missions or significantly enhance the performance, cost efficiency, and/or reliability of existing and planned space communications systems. NASA envisions a need for low-data-rate, interactive, direct-to-the-user communications services for data, voice, facsimile, and video conferencing. The network would provide enhanced very-small-aperture terminal (VSAT) communications services and be capable of handling data rates of 64 kbps through 2.048 Mbps in 64-kbps increments. Efforts have concentrated heavily on the space segment; however, the ground segment has been considered concurrently to ensure cost efficiency and realistic operational constraints. The focus of current space segment developments is a flexible, high-throughput, fault-tolerant onboard information-switching processor (ISP) for a geostationary satellite communications network. The Digital Systems Technology Branch is investigating both circuit and packet architectures for the ISP. Destination-directed, packet-switched architectures for geostationary communications satellites are addressed.

Ivancic, William D.↗

Potential applications of digital, visible, and infrared data from geostationary environmental satellites

An hourly, digital data base from the Visible/Infrared Spin-Scan Radiometer (VISSR) instrument on the GOES-1 and SMS-2 geostationary satellites is described. Several examples of developmental applications of these quantitative digital data are presented. These include a review of recent attempts to develop products that are of use to meteorologists who provide services to aviation, agriculture, forestry, hydrology, oceanography, and climatology. The sample products include high resolution thermal gradients of land and ocean surfaces, thermal change analyses, fruit frost/freeze application, cloud-top altitude analysis, analysis of hurricane characteristics, and analyses of solar insolation.

Miller, D. B.↗

Destination directed packet switch architecture for a 30/20 GHz FDMA/TDM geostationary communication satellite network

Emphasis is on a destination directed packet switching architecture for a 30/20 GHz frequency division multiplex access/time division multiplex (FDMA/TDM) geostationary satellite communication network. Critical subsystems and problem areas are identified and addressed. Efforts have concentrated heavily on the space segment; however, the ground segment was considered concurrently to ensure cost efficiency and realistic operational constraints.

Ivancic, William D.↗

The Geostationary Operational Satellite R Series SpaceWire Based Data System

The Geostationary Operational Environmental Satellite R-Series Program (GOES-R, S, T, and U) mission is a joint program between National Oceanic & Atmospheric Administration (NOAA) and National Aeronautics & Space Administration (NASA) Goddard Space Flight Center (GSFC). SpaceWire was selected as the science data bus as well as command and telemetry for the GOES instruments. GOES-R, S, T, and U spacecraft have a mission data loss requirement for all data transfers between the instruments and spacecraft requiring error detection and correction at the packet level. The GOES-R Reliable Data Delivery Protocol (GRDDP) [1] was developed in house to provide a means of reliably delivering data among various on board sources and sinks. The GRDDP was presented to and accepted by the European Cooperation for Space Standardization (ECSS) and is part of the ECSS Protocol Identification Standard [2]. GOES-R development and integration is complete and the observatory is scheduled for launch November 2016. Now that instrument to spacecraft integration is complete, GOES-R Project reviewed lessons learned to determine how the GRDDP could be revised to improve the integration process. Based on knowledge gained during the instrument to spacecraft integration process the following is presented to help potential GRDDP users improve their system designs and implementation.

Networks↗

The CHUVA Lightning Mapping Campaign

The primary science objective for the CHUVA lightning mapping campaign is to combine measurements of total lightning activity, lightning channel mapping, and detailed information on the locations of cloud charge regions of thunderstorms with the planned observations of the CHUVA (Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement) field campaign. The lightning campaign takes place during the CHUVA intensive observation period October-December 2011 in the vicinity of S o Luiz do Paraitinga with Brazilian, US, and European government, university and industry participants. Total lightning measurements that can be provided by ground-based regional 2-D and 3-D total lightning mapping networks coincident with overpasses of the Tropical Rainfall Measuring Mission Lightning Imaging Sensor (LIS) and the SEVIRI (Spinning Enhanced Visible and Infrared Imager) on the Meteosat Second Generation satellite in geostationary earth orbit will be used to generate proxy data sets for the next generation US and European geostationary satellites. Proxy data, which play an important role in the pre-launch mission development and in user readiness preparation, are used to develop and validate algorithms so that they will be ready for operational use quickly following the planned launch of the GOES-R Geostationary Lightning Mapper (GLM) in 2015 and the Meteosat Third Generation Lightning Imager (LI) in 2017. To date there is no well-characterized total lightning data set coincident with the imagers. Therefore, to take the greatest advantage of this opportunity to collect detailed and comprehensive total lightning data sets, test and validate multi-sensor nowcasting applications for the monitoring, tracking, warning, and prediction of severe and high impact weather, and to advance our knowledge of thunderstorm physics, extensive measurements from lightning mapping networks will be collected in conjunction with electric field mills, field change sensors, high speed cameras and other lightning sensors, dual-polarimetric radars, and aircraft in-situ microphysics which will allow for excellent cross-network inter-comparisons, assessments, and physical understanding.

Goodman, Steven J.↗

Breaking Barriers: Integrating Geo-Leo Aerosol Data with an Open-Source Approach

The scientific community is still examining the novel data from geostationary satellite observations and evaluating methods for effectively fusing the polar observations with various spatial and temporal resolutions. However, the merged data will present a significant ""Big Data"" challenge, including processing, storage, data discoverability, accessibility, and migration within cloud computing environments. We have developed an open-source package to fuse aerosol optical depths (AOD) products from six satellite sensors in the past four years (2019~2023), and this presentation will update our recent progress. Using this Python-based package, we produced a level 3 global (AOD) product in a quarter-degree spatial resolution every half-hour, fusing the Level 2 AOD data with the Dark Target aerosol retrieval algorithm from six satellites: three geostationary (GOES-16/17 and Himawari-8) with high temporal resolution, and three polar orbiting (TERRA/MODIS, AQUA/MODIS, and SNPP-VIIRS) with global coverage. By integrating these observations, the diurnal cycle of global AOD in this fused product can be characterized at local, regional, and global scales. Furthermore, we are committed to openness and transparency by providing our package and its associated functionalities as open-source. Our dedication to adhering to the FAIR, CARE, and TRUST principles ensures that our users can rely on the integrity and ethical standards of our work. For instance of Interoperability, this package fuses remote sensing products on demand into desired temporal and spatial domains. It can be run in a central processing unit (CPU) or a Graphics processing unit (GPU) mode. This package will empower researchers and practitioners to use satellite and sensor data efficiently in various applications and research.

Xiaohua Pan↗

SatCORPS Global Cloud Composite (GCC): the Design and Delivery of A High Quality, High Resolution, Global Cloud Product Available in Near-Real Time

The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) supports the development of an analysis ready and cloud-optimized data transformation pipeline and geospatial service enablement of a global cloud composite (GCC) product derived from global geostationary satellite imagery. This geospatial service will be available at high temporal and spatial resolution via the SatCORPS web mapping application for visualization and analysis as well as direct ingestion to common geospatial software and custom programming. The resulting global cloud composite products from the processing pipeline can then be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. Near real time global observations are created through the composition of five geostationary satellites that provides modelling and forecasting communities with the capability to provide high quality and timely information to start the projection process. The Global Cloud Composite product combines information from geostationary satellites, GOES-16, GOES-17, Himawari-8, Meteosat-11 and Meteosat-9 to create a single global composite netcdf file and images using the different products within the netcdf file. The SatCORPS team, though our Global Cloud Composite (GCC) product and web-based visualization tools including Geographical Information System (GIS) services provide near real time global cloud product information to both automated processes and traditional web users that is timely and high quality derived from geostationary satellites. The Global Cloud Composite product takes advantage of the scalable processing resources provided by the AWS batch service to provide new composites every thirty minutes. Because information from each of the low earth orbiting satellites is available on schedules tuned to the specific satellite, the processing algorithm temporally composites the final dataset as each satellite’s information becomes available. The SatCORPS team has leveraged our experience using Amazon Web Services (AWS) to build a low latency high availability tool that allows end users both human and automated to acquire high quality and high-resolution Geostationary Earth Orbiting (GEO) information at zero cost to the end user. This presentation will describe how we architected and implemented the service as well as lessons learned based on our experiences both developing and operating the system. The lessons learned include how we integrated multiple services including Amazon Batch, Amazon S3 and Amazon Lambda service to create a low cost but high-performance processing system that is capable of identifying and processing the most appropriate satellite overpass information into global cloud composites. We will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global composited cloud research products with very low latency that we see that as filling a rapidly growing need in the research and modelling community with no up-front nor ongoing costs associated with downloading or using the information.

AWS AMCE SMCE GCC SATCORPS GLOBAL CLOUD COMPOSITE ↗

The provision of spectrum for feeder links of non-geostationary mobile satellites

The possibility of sharing spectrum in the 30/20 GHz band between geostationary fixed-satellite systems and feeder-links of low-earth orbit (LEO) mobile-satellite systems is addressed, taking into account that International Telecommunications Union (ITU) Radio Regulation 2613 would be a factor in such sharing. Interference into each network in both the uplink at 30 GHz and the downlink at 20 GHz is considered. It is determined that if sharing were to take place the mobile-satellite may have to cease transmission often for intervals up to 10 seconds, may have to use high-gain tracking antennas on its spacecraft, and may find it an advantage to use code-division multiple access. An alternate solution suggested is to designate a band 50 to 100 MHz wide at 28 and 18 GHz to be used primarily for feeder links to LEO systems.

Bowen, Robert R.↗

Development of Carbon Flux Model Using ABI Data Over the Conterminous US

The satellite-driven carbon flux estimation has been playing important role to estimate continental-scale carbon budget. One of the biggest recent advances in the satellite-driven carbon flux modeling is utilization of high-frequent geostationary satellites to estimate diurnal cycle in carbon fluxes. The satellite based carbon flux estimation used the polar orbiting satellite sensors (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)), which allow us to observe target regions only once during the day. The new generation of geostationary satellite sensors provide frequent observations, often less than every 10 minutes. Here, we use GOES Advanced Baseline Imager (ABI) data to estimate hourly NEE over the conterminous US. We used the Terrestrial Observation Prediction System (TOPS) model for estimating hourly NEE. TOPS is a diagnostic ecosystem process model that simulates the fluxes of carbon and water through vegetation in response to climate variability. For the climate input, we developed hourly climate data using the same algorithm with NASA Earth Exchange Gridded Daily Meteorology (NEX-GDM) datasets based on machine learning techniques. The hourly climate data includes precipitation, maximum temperature, minimum temperature, dew point temperature, and solar radiation were derived from the Geostationary observations. The spatial patterns of ecosystem parameters used in TOPS are optimized using satellite Solar Induced Fluorescence (SIF) data. The high frequency GPP estimations from geostationary satellite sensors make it comparable to the instantaneous SIF data than daily GPP. We also used Ameriflux data for optimization of model parameters and the validation of the output. The derived data addresses the diurnal dynamics of carbon cycling at large scales and should help in reducing the uncertainties in carbon budget studies.

geostationary satellite↗

Generation of Land Surface Reflectance with Combined Geo-KOMPSAT-2A AMI and Himawari 8 AHI Observations

The latest generation of geostationary satellites has opened a new era of Earth observations with unprecedented spatiotemporal resolution and spectral range. Together with GOES 16/17 ABI, FY4-A AGRI, and Himawari-8 AHI, a new Korean geostationary satellite (Geo-KOMPSAT-2A AMI) has operationally collected a full-disk image in 16 channels every ten minutes since July 2019, allowing diurnal land surface monitoring over a large proportion of Asia and all of Oceania. Retrieving accurate surface reflectance (SR) over land from GK-2A/AMI is a challenging but high priority objective. One of the challenges is the absence of a spectral band in the 2.2 m SWIR range from AMI, which is required by many atmospheric correction algorithms to retrieve atmospheric aerosol properties. To remedy this issue, we adopt a strategy that combines concurrent GK-2A/AMI and Himawari 8/AHI observations in order to derive AMI SR. We have adapted the NASA Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to process the data stream from Himawari 8/AHI. The advantages of the MAIAC algorithm is its capability to exploit the high temporal frequency and varying illumination geometry of the geostationary data for advanced cloud/snow detection, aerosol retrieval, and characterization of surface bidirectional reflectance properties. Leveraging the similarities of spectral bands and the sun-target-sensor geometry between AMI and AHI, we are able to create denser time series of observations and enhanced BRDF samples over most of the spatial coverage of AMI (and AHI). The combined stereo-type observations not only help derive SR for AMI but also enhance retrievals of the corresponding AHI surface products. We evaluate the resulting AMI SR using ground (AERONET) observations and corresponding MODIS products. Further, we discuss potential challenges in utilizing the geostationary satellite data for land surface monitoring.

geostationary satellite↗

Potential applications of a high altitude powered platform in the ocean/coastal zone community

The results of a survey of the ocean/coastal zone community conducted for the NASA Wallops Flight Center to identify potential applications of a high altitude powered platform (HAPP) are presented. Such a platform would stationkeep at 70,000 feet for up to a year over a given location and make frequent high resolution observations, or serve as a regional communications link. The survey results indicate user interest among scientific researchers, operational agencies and private industry. It is felt that such a platform would combine the desirable characteristics of both geostationary satellites (wide area, frequent observation) and aircraft (high resolution). As a result a concept for an operational HAPP system in the form of a 'mesoscale geostationary satellite' system evolved. Such a system could employ many of the same technologies used in current NASA and NOAA geostationary satellite programs. A set of generalized instrument requirements for HAPP borne sensors is also presented.

Escoe, D.↗