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Interrogation, recording and location system to be carried on Nimbus B satellite as data link for surface network stations recording geophysical, oceanographic and meteorological data
Satellite laser ranging, satellite altimetry, and improved measurements of surface gravitational anomalies have broadened the data base on intermediate and short wavelength regions of the earth gravity field. The global data set served to develop new geopotential models with a resolution in spherical harmonics out to degree 180. The resolution was made possible using Seasat altimetry data containing 56,761 values of 1 x 1 deg gravity anomalies. Satellite-to-satellite tracking techniques involving the Geos-3 and Apollo spacecraft data for the sea surface temperature have yielded accurate intermediate wavelength gravity variations which correlate well with residual depth anomalies. Oceanic gravity anomalies have been computed directly from satellite altimetry or through statistical estimation using oceanic geoid heights. The data sets for gravimetric geoids have been compared with altimetric surfaces to identify areas which were of interest for geophysical investigation. Future data sets could become available from a proposed satellite-to-satellite Doppler tracking system (Gravsat) launched by NASA.
It has become increasingly important to conduct interdisciplinary environmental research assessments, both nationally and internationally. For this reason, the Committee for a Pilot Study on Database Interfaces was charged to review and advise on data interfacing activities. The committee used six case studies (1) to identify and understand the most important problems associated with collecting, integrating, and analyzing environmental data from local to global spatial scales and over a very wide range of temporal scales; and (2) to elaborate the common barriers to interfacing data of disparate sources and types. Consistent with the committee's charge, the primary focus was the interfacing of geophysical and ecological data. The case studies used by the committee were: The Impact Assessment Project for Drought Early Warning in the Sahel, The National Acid Precipitation Assessment Program, The H.J. Andrew Experimental Forest Long-Term Ecological Research Site, The Carbon Dioxide Information Analysis Center, The First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment, and The California Cooperative Oceanic Fisheries Investigation. The committee derived a number of lessons from the case studies, and these lessons are summarized at the end of each case study and analyzed in the last chapter. Some are generic in nature; others are more specific to a discipline or project. The conclusions and recommendations are based on the committee's analysis of the case studies and additional research. They are organized according to four major areas of barriers or challenges to the effective interfacing of diverse environmental data. In the final section the committee offers a set of broadly applicable principles (Ten Keys to Success) that can be used by scientists and data managers in planning and conducting interfacing activities.
Remote sensing offers the vantage of monitoring a vast area of the Earth continuously. Once developed and launched, a satellite gives years of service in collecting data from the land, the oceans, and the atmosphere. Since the 1980s, attempts have been made to relate disease occurrence with remotely sensed environmental and geophysical parameters, using data from Landsat, SPOT, AVHRR, and other satellites. With higher spatial resolution, the recent satellite sensors provide a new outlook for disease control. At sub-meter to I 10m resolution, surface types associated with disease carriers can be identified more accurately. The Ikonos panchromatic sensor with I m resolution, and the Advanced Land Imager with 1 Om resolution on the newly launched Earth Observing-1, both have displayed remarkable mapping capabilities. In addition, an entire array of geophysical parameters can now be measured or inferred from various satellites. Airborne remote sensing, with less concerns on instrument weight, size, and power consumption, also offers a low-cost alternative for regional applications. NASA/GSFC began to collaborate with the Mahidol University on malaria and filariasis control using remote sensing in late 2000. The objectives are: (1) To map the breeding sites for the major vector species; (2) To identify the potential sites for larvicide and insecticide applications; (3) To explore the linkage of vector population and transmission intensity to environmental variables; (4) To monitor the impact of climate change and human activities on vector population and transmission; and (5) To develop a predictive model for disease distribution. Field studies are being conducted in several provinces in Thailand. Data analyses will soon begin. Malaria data in South Korea are being used as surrogates for developing classification techniques. GIS has been shown to be invaluable in making the voluminous remote sensing data more readily understandable. It will be used throughout this study to clearly demonstrate the spatial relationship between the disease intensities, geophysical variables, and socioeconomic parameters. Asides from malaria and filariasis, application of remote sensing to the control of other diseases have been vigorously pursued by NASA's Environment and Health Initiative. The current program includes projects on Rift Valley fever, St. Louis encephalitis, dengue fever, ebola, African dust and diseases, meningitis, asthma, bartonellosis, cholera, and urban health concerns. Results from these projects indicate that remote sensing will play an increasingly important role in disease control in the future.
The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations - the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.
Earth observing (EO) mission portfolios provide data on many geophysical parameters that collectively inform our understanding of the Earth system. To observe large-scale climate trends, it is important to collect data on many parameters over time. However, gaps may occur between missions due to formulation complexity, development delays, and uncertain events in operations. These gaps may impact the ability to provide sustained measurements. Developing a balanced EO mission portfolio is key to supporting study of the Earth system. Yet, decision-making at the portfolio level is a complex task because missions often address multiple parameters. Currently, the likelihood of data gaps is often assessed for an individual parameter, but decisions and events can impact data collection for many parameters. This poster introduces a modeling approach that supports management of the many parameter impacts of decisions and uncertain events. The approach provides a foundation for analyzing changeability in EO mission portfolios. Changeability analysis provides insight into a portfolio’s sensitivity to changes caused by decisions or uncertain events. The model is developed to analyze two aspects of changeability, robustness and flexibility, in EO mission portfolios. In context of these portfolios, the authors define robustness as a portfolio’s ability to provide sustained measurements despite future uncertainties, and they define flexibility as the availability of decision alternatives that contribute to parameter coverage at little detriment to the rest of the portfolio. The proposed model characterizes a portfolio’s sensitivity to change by capturing mission-parameter interconnectivity and redundancy in parameter coverage. The model can be analyzed to identify events that can create substantial gaps, thereby revealing focus areas for mitigation efforts. The model can also be analyzed to identify gap mitigation decisions that may improve parameter coverage with little detriment to the rest of the portfolio, thereby revealing favorable pathways for portfolio improvement. Developing a process for identifying these threats and opportunities will be the focus of future work. A parallel poster proposes a standard for visualizing and communicating portfolio-level impacts of decisions and uncertain events.
Heat Capacity Mapping Mission thermal-inertia images of a diversity of terrains and geologic settings were examined in conjunction with topographic, geologic, geophysical, and LANDSAT data. The images were found to have attributes similar to bedrock maps. In the Cascades region, two new features were identified and a method was developed to characterize regional terranes using linear feature data. Two northeast-trending Lineaments were discovered in the Overthrust Belt of Montana and Idaho. The longer of the two extends from the Idaho-Oregon border, through the Idaho batholith and across the Lewis thrust. It coincides, along segments, with mapped faults and an aeromagnetic pattern change. A major lineament crossing the Colorado Plateau and the Southern Rocky Mountians was detected on several thermal-inertial images and evidence was found for the existence of a geologic discontinuity. Vegetation-covered areas in Richfield and the Silver City quadrangle (Arizona and New Mexico) displayed thermal-inertia differences within heavily vegetation areas although no apreciable correlation was found between vegetation cover and thermal inertia. Resistant ridges and knolls have high thermal inertias and thermal-inertia contrasts occurred at lithologic and fault contacts. In the heavy vegetated Pinaleno Mountains, Arizona, a Lithologic unit obscured on LANDSAT MSS data due to the vegetation cover, exhibited a thermal-inertia contrast with its surroundings.
Observing systems simulation experiments (OSSE's) provide a powerful tool to assess the impact of proposed satellite borne observing systems on meteorological applications models. We describe the results of an OSSE conducted to assess the impact of data from a low power lidar wind sensor on the forecast accuracy of a global spectral numerical weather prediction (NWP) model, the Air Force Geophysics Laboratory Global Data Assimilation System. The instrument would be operating at near-infrared wavelengths thereby increasing the backscatter signal relative to comparable infrared lidar.
Precipitation recycling is the contribution of evaporation within a region to precipitation in that same region. The recycling rate is a diagnostic measure of the potential for interactions between land surface hydrology and regional climate. In this paper we present a model for describing the seasonal and spatial variability of the recycling process. The precipitation recycling ratio, rho, is the basic variable in describing the recycling process. Rho is the fraction of precipitation at a certain location and time which is contributed by evaporation within the region under study. The recycling model is applied in studyiing the hydrologic cycle in the Amazon basin. It is estimated that about 25% of all the rain that falls in the Amazon basin is contributed by evaporation within the basin. This estimate is based on analysis of a data set supplied by the European Centre for Medium-range Weather Forecasts (ECMWF). The same analysis is repeated using a different data set from the Geophysical Fluid Dynamics Laboratory (GFDL). Based on this data set, the recycling ratio is estimated to be 35%. The seasonal variability of the recycling ratio is small compared with the yearly average. The new estimates of the recycling ratio are compared with results of previous studies, and the differences are explained.
Gravitational potential data from GRACE are being used to study mass redistribution within and between the atmosphere, hydrosphere, cryosphere, and solid Earth. The GRACE data are made available in a reference frame with its origin at the center of mass of the Earth system (geocenter) while many other geophysical models and data sets refer to a reference frame attached to the Earth's surface. Changes in the offset between these reference frames (geocenter motion) must be accounted for when GRACE data are used to quantify surface mass changes. In this study, we developed a technique for co‐estimation of geocenter motion and gravitational potential field seamlessly from degree 1 to 90 by simultaneously inverting a set of globally‐distributed GPS displacement time series and the temporally‐varying GRACE gravity data. We found that the effect of geocenter motion was evident particularly in the GPS time series of horizontal displacements. Our estimates of geocenter motion are most consistent with the Satellite Laser Ranging (SLR) results within 1 mm in X and Z components and a submillimeter in Y component, when compared to monthly variability averaged over the period of 2003–2016. The overall magnitude of the degree‐1 (l = 1) surface mass load is estimated to be ~3 cm in equivalent water height annually migrating south‐westward from Europe (December–January) to the South Pacific (June–July). Our results also show that dense GPS network data improve water storage recovery in major river basins in the United States and Europe by contributing significantly to the recovery of higher‐degree (l ≥ ~20) geopotential coefficients.
Space science information systems involve accessing vast data bases. There is a need for an automatic process by which properties of the whole data set can be assimilated and presented to the user. Where data are in the form of spectrograms, phenomena can be detected by pattern recognition techniques. Presented are the first results obtained by applying unsupervised Artificial Neural Networks (ANN's) to the classification of magnetospheric wave spectra. The networks used here were a simple unsupervised Hamming network run on a PC and a more sophisticated CALM network run on a Sparc workstation. The ANN's were compared in their geophysical data recognition performance. CALM networks offer such qualities as fast learning, superiority in generalizing, the ability to continuously adapt to changes in the pattern set, and the possibility to modularize the network to allow the inter-relation between phenomena and data sets. This work is the first step toward an information system interface being developed at Sussex, the Whole Information System Expert (WISE). Phenomena in the data are automatically identified and provided to the user in the form of a data occurrence morphology, the Whole Information System Data Occurrence Morphology (WISDOM), along with relationships to other parameters and phenomena.
During the past several years, the 440-MHz radar at Millstone Hill has been modified to detect coherent echoes from clear-air turbulence in the stratosphere/troposphere (S/T) over the altitude range 4-25 km. Two distinct modes of data acquisition have been developed, and data reduction programs have been completed for one of these modes. This mode (I-mode) transmits a 10 microsec (1.5 km) pulse on the fully steerable antenna. Typically, the antenna is set at a low elevation angle (e.g., 15 deg.) to reduce the altitude resolution to approximately 1 km., and power spectra are collected at some 40 range gates. The antenna may be scanned in azimuth to obtain the total wind vector, held fixed to monitor wave motion, or scanned in elevation to monitor the horizontal extent of the turbulent activity. This steerability gives Millstone a flexible system to focus on localized events, such as lee waves or convective storms. An additional advantage at low elevations is the relatively large Doppler shift of the signal, since the LOS velocity contains a large component of the horizontal velocity. This shift separates the turbulence signal sufficiently far from the ground clutter to allow the spectral moments to be readily inferred. Some 500 hours of S/T I-mode data have been reduced to geophysical parameters, and reside on a data base at Millstone Hill.
The Upper Atmosphere Research Satellite (UARS) is a NASA program aimed at improving our knowledge of the physical and chemical processes controlling the stratosphere, mesosphere, and lower thermosphere, emphasizing those levels that are known to be particularly susceptible to change by human activities. The spacecraft was launched by the Space Shuttle Discovery on September 12, 1991 into a near-circular orbit at 585 km altitude and 57 deg inclination. Measurements include vertical profiles of temperature, many trace gases, and horizontal wind velocities, as well as solar energy inputs. Many of the limb-scanning instruments can measure to as high as 80 deg latitude, providing near-global coverage. The mission is supported by a large international correlative measurement program, yielding data both for validation of the UARS measurements and for complementary scientific studies. A dedicated data system provides rapid processing to geophysical quantities and makes these data available to UARS scientists.
One conclusion derived from the study of meteorites is that some of them - most irons, stony irons, some achondrites - hail from asteroids that were heated to the point where metallic cores and basaltic crusts were formed. Telescopic observations show that there remains only one large asteroid with a basaltic crust, 4 Vesta; present day mean radius 263 km. The largest clan of achondrites, the howardite, eucrite and diogenite (HED) meteorites, represent the crust of their parent asteroid. Diogenites are cumulate harzburgites and orthopyroxenites from the lower crust whilst eucrites are cumulate gabbros, diabases and basalts from the upper crust. Howardites are impact-engendered breccias of diogenites and eucrites. A strong case can be made that HEDs are derived from Vesta. The NASA Dawn spacecraft orbited Vesta for 14 months returning data allowing geological, mineralogical, compositional and geophysical interpretations of Vesta's surface and structure. Combined with geochemical and petrological observations of HED meteorites, differentiation models for Vesta can be developed. Proto-Vesta probably consisted of primitive chondritic materials. Compositional evidence, primarily from basaltic eucrites, indicates that Vesta was melted to high degree (>=50%) which facilitated homogenization of the silicate phase and separation of immiscible Fe,Ni metal plus Fe sulphide into a core. Geophysical models based on Dawn data support a core of ~110 km radius. The silicate melt vigorously convected and initially followed a path of equilibrium crystallization forming a harzburgitic mantle, possibly overlying a dunitic restite. Once the fraction of crystals was sufficient to cause convective lockup, the remaining melt collected between the mantle and the cool thermal boundary layer. This melt undergoes fractional crystallization to form a dominantly orthopyroxenite (diogenite) lower crust. The initial thermal boundary layer of primitive chondritic material is gradually replaced by a mafic crust through impact disruption and foundering. The quenched mafic crust thickens over time through magma extrusion/intrusion. Melt from the residual magma ocean intrudes and penetrates the mafic crust forming cumulate eucrite plutons, and dikes, sills and flows of basaltic eucrite composition. The post-differentiation vestan structure is thus not too dissimilar from that of terrestrial planets: (i) a metallic core; (ii) an ultramafic mantle comprised of a lower dunitic layer (if melting was substantially <100%) and an upper cumulate harzburgitic layer; (iii) a lower crust of harzburgitic and orthopyroxenitic cumulates; and (iv) an upper mafic crust of basalts and diabases (melt compositions) with cumulate gabbro intrusions. Impacts have excavated to the lower crust and delivered howardites, eucrites and diogenites to Earth, but there is yet no evidence demonstrating excavation of the vestan mantlle.
Another type of geophysical observation has proved to be very useful in the study of thermal cooling of the oceanic lithosphere. It is the geoid height derivative with respect to plate age, a quantity computed from the short wavelength geoid step across fracture zones measured by altimeter satellites. Two categories of simples models are proposed to describe cooling and contraction of the oceanic lithosphere with age. Both plate model and half space model, give almost similar results up to ages of 50 to 70 ma, but predict quite distinct behavior of seafloor depth, heat flow and other parameters in old basins. Tests of thermal models are based on heat flow and topography data. However, heat flow is not very sensitive to the form of the thermal model. Large areas of the ocean floor are particularly shallow, and as a result topography data may not be very appropriate to discriminate between plate and half space models, and no clear concensus on a preferred model yet exists.
A representative set of data from ISIS 2 covering a range of operating modes and geophysical conditions is presented. The data show the typical values and range of ionospheric and magnetospheric characteristics, as viewed from 1400 km with the ISIS 2 instruments. The definition of each data set depends partly on geophysical parameters and partly on satellite operating mode. Preceding the data set is a description of the organizational parameters and a review of the objectives and general characteristics of the data set. The data are shown as a selection from 12 different data formats. Each data has a different selection of formats, but uniformity of a given format selection is preserved throughout each data set.
The application of the penetrator to a Mars Return Sample Mission (MRSM) has direct advantages to meet science objectives and mission safety. Based on engineering data and work currently conducted at Ball Aerospace Systems Division, the concept of penetrators as scientific instruments is entirely practical. The primary utilization of a penetrator for MRSM would be to optimize the selection of the sample site location and to help in selection of the actual sample to be returned to Earth. It is recognized that the amount of sample to be returned is very limited, therefore the selection of the sample site is critical to the success of the mission. The following mission scenario is proposed. The site selection of a sample to be acquired will be performed by science working groups. A decision will be reached and a set of target priorities established based on data to give geochemical, geophysical and geological information. The first task of a penetrator will be to collect data at up to 4 to 6 possible landing sites. The penetrator can include geophysical, geochemical, geological and engineering instruments to confirm that scientific data requirements at that site will be met. This in situ near real-time data, collected prior to final targeting of the lander, will insure that the sample site is both scientifically valuable and also that it is reachable within limits of the capability of the lander.
The National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) provides data and information on snow and ice processes, especially pertaining to interactions among snow, ice, atmosphere and ocean, in support of research on global change detection and model validation, and provides general data and information services to cryospheric and polar processes research community. The NSIDC DAAC is an integral part of the multi-agency-funded support for snow and ice data management services at NSIDC. The Moderate Resolution Imaging Spectroradiometer (MODIS) will be flown on the first Earth Observation System (EOS) platform (AM-1) in 1998. The MODIS Instrument Science Team is developing geophysical products from data collected by the MODIS instrument, including snow and ice products which will be archived and distributed by NSIDC DAAC. The MODIS snow and ice mapping algorithms will generate global snow, lake ice, and sea ice cover products on a daily basis. These products will augment the existing record of satellite-derived snow cover and sea ice products that began about 30 years ago. The characteristics of these products, their utility, and comparisons to other data set are discussed. Current developments and issues are summarized.