Interdisciplinary User Perspective: Leveraging Earth Observation Data to Study Interdependence of Water, Energy, and Food Systems
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Explore the source record for details and available documents.
Abstract not provided.
Abstract not provided.
NASDA's new Advanced Earth Observing Satellite (ADEOS) is scheduled for launch in August, 1996. ADEOS carries 8 sensors to observe earth environmental phenomena and sends their data to NASDA, NASA, and other foreign ground stations around the world. The downlink data bit rate for ADEOS is 126 MB/s and the total volume of data is about 100 GB per day. To archive and manage such a large quantity of data with high reliability and easy accessibility it was necessary to develop a new mass storage system with a catalogue information database using advanced database management technology. The data will be archived and maintained in the Master Data Storage Subsystem (MDSS) which is one subsystem in NASDA's new Earth Observation data and Information System (EOIS). The MDSS is based on a SONY ID1 digital tape robotics system. This paper provides an overview of the EOIS system, with a focus on the Master Data Storage Subsystem and the NASDA Earth Observation Center (EOC) archive policy for earth observation satellite data.
Observational data that was acquired during the West European Satellite Triangulation (WEST) program and the International Satellite Geodesy Experiment (ISAGEX) campaign was obtained for the purpose of performing a geometric solution to improve the present values of coordinates of the European stations in the OSU WN14 solutions, adding some new stations and assessing the quality of the WN14 solution with the help of the additional data available. The status of the data as received, the preprocessing required and the preliminary tests carried out for the initial screening of the data are described. The adjustment computations carried out and the results of the adjustments are discussed.
Data from the Phobos 2 Imaging Spectrometer for Mars (ISM), compiled by Mustard et al. (1993), and other observations support the existence of komatiitic lavas on Mars. Mustard et al. (1993) determined from ISM data that the composition of the low-albedo materials covering the Syrtis Major plateau originally consisted of augite-bearing basalt containing both augite and pigeonite, with no appreciable amount of olivine. This description is consistent with a komatiitic basalt. Komatiite is significant for the Earth because it contains a high amount of MgO, implying generation under unique circumstances compared to more typical basaltic compositions and may be similarly important for Mars.
Systematic long-term field observations have played a vital role in advancing atmospheric research over the past several decades. The use of these observations has expanded from primarily characterizing atmospheric processes and trends to evaluating satellite measurements, assessing models, and improving air quality forecasts. Consequently, the demand for atmospheric chemistry observational data have dramatically increased in terms of scope and coverage of measurements (i.e., parameters/species, spatiotemporal extent). In addition to high quality measurements, certain data reporting standards need to be agreed to ensure the data can be readily exchanged and are sufficiently documented to enable adequate use in different research activities. To this end, WMO has developed and implemented measurement guidelines and community practices for meteorology, climatology, atmospheric and hydrological sciences. In addition, the WMO Expert Team on Metadata Standards manages and evolves the existing metadata standards for the WMO Information System WIS and WMO Integrated Global Observing System WIGOS to support consistent and interoperable data descriptions, ensure relevance to research, and to apply data science principles. This team draws on a wide range of expertise from the research community, including atmospheric measurements, modeling, data management, and data science. The current activities include development of key performance indicators, vocabularies for metadata and the evolution of metadata standards to lower the barrier of application to weather/climate/water/environment data for all communities and the weather enterprise. This presentation intends to promote awareness of ongoing progress and actively solicit community feedback.
The dataset archives observed and model-simulated turbulence intensity and meteorological profiles and timeseries at the Air-Sea Interaction Tower (ASIT) of Woods Hole Oceanographic Institution’s Martha’s Vineyard Coastal Observatory (MVCO). The observational data were measured by lidar and buoy deployed at ASIT. The simulated profiles and timeseries data are interpolated in time and/or space according to observations. Simulations were carried out for the mid-Atlantic region using the revised Weather Research and Forecasting (WRF) model version 4.2 that incorporates the implementation of online turbulence intensity (TI) calculations (Tai et al. 2023). The simulated atmospheric profiles at the Shell Exploration and Production Corporation's Tension Leg Platforms Ursa and Mars are archived. Physics parameterizations chosen for the simulations include the Thompson microphysics parameterization, Mellor-Yamada-Nakanishi Niino (MYNN) boundary layer parameterization, Mellor-Yamada-Janjic surface layer parameterization, Unified Noah land-surface parameterization, and the RRTMG longwave and shortwave radiation parameterization. Initial and boundary conditions are taken from NOAA’s High-Resolution Rapid Refresh (HRRR) product. The JPL 0.01-degree Level 4 Multiscale Ultrahigh Resolution (MUR) Global Foundation Sea Surface Temperature (SST) Analysis (V4.1) data are used as the model’s SST forcing.
Observations of Cosmic-ray electrons are difficult due to the large flux of cosmic ray hadrons. The event selection efficiency and background levels can be estimated from flight data for the ATIC instrument. This reduces the dependence upon Monte Carlo simulations, which show differences between different codes, thereby reducing the systematic errors resulting from analyses that only use simulations. This paper discusses some of the methods used in the ATIC analysis to determine the detection efficiency and background level for the flight data.