961 resultados para Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E)


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A new method for radio-frequency interference (RFI) contamination identification over open oceans for the two C-subbands and X-band of Advanced Microwave Scanning Radiometer 2 (AMSR2) channel measurements is suggested. The method is based both on the AMSR2 brightness temperature (T-B) modeling and on the analysis of AMSR2 measurements over oceans. The joint analysis of T-B spectral differences allowed to identify the relations between them and the limits of their variability, which are ensured by the changes in the environmental conditions. It was found that the constraints, based on the ratio of spectral differences, are more regionally and seasonally independent than the spectral differences themselves. Although not all possible RFI combinations are considered, the developed simple criteria can be used to detect most RFI-contaminated pixels over the World Ocean for AMSR2 measurements in two C-subbands and the X-band.

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Ozone profiles from the Microwave Limb Sounder (MLS) onboard the Aura satellite of the NASA's Earth Observing System (EOS) were experimentally added to the European Centre for Medium-range Weather Forecasts (ECMWF) four-dimensional variational (4D-var) data assimilation system of version CY30R1, in which total ozone columns from Scanning Imaging Absorption Spectrometer for Atmospheric CHartographY (SCIAMACHY) onboard the Envisat satellite and partial profiles from the Solar Backscatter Ultraviolet (SBUV/2) instrument onboard the NOAA-16 satellite have been operationally assimilated. As shown by results for the autumn of 2005, additional constraints from MLS data significantly improved the agreement of the analyzed ozone fields with independent observations throughout most of the stratosphere, owing to the daily near-global coverage and good vertical resolution of MLS observations. The largest impacts were seen in the middle and lower stratosphere, where model deficiencies could not be effectively corrected by the operational observations without the additional information on the ozone vertical distribution provided by MLS. Even in the upper stratosphere, where ozone concentrations are mainly determined by rapid chemical processes, dense and vertically resolved MLS data helped reduce the biases related to model deficiencies. These improvements resulted in a more realistic and consistent description of spatial and temporal variations in stratospheric ozone, as demonstrated by cases in the dynamically and chemically active regions. However, combined assimilation of the often discrepant ozone observations might lead to underestimation of tropospheric ozone. In addition, model deficiencies induced large biases in the upper stratosphere in the medium-range (5-day) ozone forecasts.

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The design and manufacture of the band-defining filters and their associated dichroic beam splitter for the 11- and the 12-µm infrared channels of the advanced along-track scanning radiometer are described. The filter requirements that have led to the choice of coating designs, coating materials, disposition of coatings, and effects of polarization are discussed. Overall spectral throughputs of the filter and dichroic interaction for the two channels are also presented.

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We present five new cloud detection algorithms over land based on dynamic threshold or Bayesian techniques, applicable to the Advanced Along Track Scanning Radiometer (AATSR) instrument and compare these with the standard threshold based SADIST cloud detection scheme. We use a manually classified dataset as a reference to assess algorithm performance and quantify the impact of each cloud detection scheme on land surface temperature (LST) retrieval. The use of probabilistic Bayesian cloud detection methods improves algorithm true skill scores by 8-9 % over SADIST (maximum score of 77.93 % compared to 69.27 %). We present an assessment of the impact of imperfect cloud masking, in relation to the reference cloud mask, on the retrieved AATSR LST imposing a 2 K tolerance over a 3x3 pixel domain. We find an increase of 5-7 % in the observations falling within this tolerance when using Bayesian methods (maximum of 92.02 % compared to 85.69 %). We also demonstrate that the use of dynamic thresholds in the tests employed by SADIST can significantly improve performance, applicable to cloud-test data to provided by the Sea and Land Surface Temperature Radiometer (SLSTR) due to be launched on the Sentinel 3 mission (estimated 2014).

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The curing of a thermosetting polymer materials utilized on micro-electronics packaging applications can be performed using microwave systems. The use of microwave energy enables the cure process to be completed more rapidly than with alternative approaches due to the ability to heat volumetrically. Furthermore, advanced dual-section microwave systems enable curing of individual components on a chip-on-board assembly. The dielectric properties of thermosetting polymer materials, commonly used in microelectronics packaging applications, vary significantly with temperature and degree of cure. The heating rate within a material subjected to an electric field is primarily dependant on the dielectric loss properties of the material itself. This article examines the variation in dielectric properties of a commercially available encapsulant paste with frequency and temperature and the resulting influence on the cure process. The 'FAMOBS' dual section microwave system and its application to microelectronics manufacture are described. The measurement of the dielectric properties of 'Henkel EO1080' encapsulant paste uses a commercially available 'dielectric probe kit' and is described in this paper. The FAMOBS heating system is used to encapsulate a small op-amp chip. A numerical model formulated to assess the cure process in thermosetting polymer materials under microwave heating is outlined. Numerical results showing that the microwave processing systems is capable of rapidly and evenly curing thermosetting polymer materials are presented.

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The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data.

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We establish a methodology for calculating uncertainties in sea surface temperature estimates from coefficient based satellite retrievals. The uncertainty estimates are derived independently of in-situ data. This enables validation of both the retrieved SSTs and their uncertainty estimate using in-situ data records. The total uncertainty budget is comprised of a number of components, arising from uncorrelated (eg. noise), locally systematic (eg. atmospheric), large scale systematic and sampling effects (for gridded products). The importance of distinguishing these components arises in propagating uncertainty across spatio-temporal scales. We apply the method to SST data retrieved from the Advanced Along Track Scanning Radiometer (AATSR) and validate the results for two different SST retrieval algorithms, both at a per pixel level and for gridded data. We find good agreement between our estimated uncertainties and validation data. This approach to calculating uncertainties in SST retrievals has a wider application to data from other instruments and retrieval of other geophysical variables.

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The normalised difference vegetation index (NDVI) has evolved as a primary tool for monitoring continental-scale vegetation changes and interpreting the impact of short to long-term climatic events on the biosphere. The objective of this research was to assess the nature of relationships between precipitation and vegetation condition, as measured by the satellite-derived NDVI within South Australia. The correlation, timing and magnitude of the NDVI response to precipitation were examined for different vegetation formations within the State (forest, scrubland, shrubland, woodland and grassland). Results from this study indicate that there are strong relationships between precipitation and NDVI both spatially and temporally within South Australia. Differences in the timing of the NDVI response to precipitation were evident among the five vegetation formations. The most significant relationship between rainfall and NDVI was within the forest formation. Negative correlations between NDVI and precipitation events indicated that vegetation green-up is a result of seasonal patterns in precipitation. Spatial patterns in the average NDVI over the study period closely resembled the boundaries of the five classified vegetation formations within South Australia. Spatial variability within the NDVI data set over the study period differed greatly between and within the vegetation formations examined depending on the location within the state. ACRONYMS AVHRR Advanced Very High Resolution Radiometer ENVSAEnvironments of South Australia EOS Terra-Earth Observing System EVIEnhanced Vegetation Index MODIS Moderate Resolution Imaging Spectro-radiometer MVC Maximum Value Composite NDVINormalised Difference Vegetation Index NIRNear Infra-Red NOAANational Oceanic and Atmospheric Administration SPOT Systeme Pour l’Observation de la Terre. [ABSTRACT FROM AUTHOR]

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We propose an atom localization scheme for a four-level alkaline earth atom via a classical standing-wave field, and give the analytical expressions of the localization peak positions as well as the widths versus the parameters of the optical fields. We show that the probability of finding the atom at a particular position can be increased from 1/4 to 1/3 or 1/2 by adjusting the detuning of the probe field and the Rabi frequencies of the optical fields. Furthermore, the localization precision can be dramatically enhanced by increasing the intensity of the standing-wave field or decreasing the detuning of the probe field. The analytical results are quite accordant to the numerical solutions.

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The National Oceanic and Atmospheric Administration (NOAA), in cooperation with the New Jersey Marine Sciences Consortium (NJMSC), hosted a workshop at Rutgers University on 19-21 September 2005 to explore ways to link the U.S. Integrated Ocean Observing System (IOOS) to the emerging infrastructure of the National Water Quality Monitoring Network (NWQMN). Participating partners included the Mid-Atlantic Coastal Ocean Observing Regional Association, U.S. Geological Survey, Rutgers University Coastal Ocean Observing Laboratory, and the New Jersey Sea Grant College. The workshop was designed to highlight the importance of ecological and human health linkages in the movement of materials, nutrients, organisms and contaminants along the Delaware Bay watershed-estuary-coastal waters gradient (hereinafter, the “Delaware Bay Ecosystem [DBE]”), and to address specific water quality issues in the mid-Atlantic region, especially the area comprising the Delaware River drainage and near-shore waters. Attendees included federal, state and municipal officials, coastal managers, members of academic and research institutions, and industry representatives. The primary goal of the effort was to identify key management issues and related scientific questions that could be addressed by a comprehensive IOOS-NWQMN infrastructure (US Commission on Ocean Policy 2004; U.S. Ocean Action Plan 2004). At a minimum, cooperative efforts among the three federal agencies (NOAA, USGS and EPA) involved in water quality monitoring were required. Further and recommended by the U.S. Commission on Ocean Policy, outreach to states, regional organizations, and tribes was necessary to develop an efficient system of data gathering, quality assurance and quality control protocols, product development, and information dissemination.

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Sustainable development depends on maintaining ecosystem services which are concentrated in coastal marine and estuarine ecosystems. Analyses of the science needed to manage human uses of ecosystem services have concentrated on terrestrial ecosystems. Our focus is on the provision of multidisciplinary data needed to inform adaptive, ecosystem-based approaches (EBAs) for maintaining coastal ecosystem services based on comparative ecosystem analyses. Key indicators of pressures on coastal ecosystems, ecosystem states and the impacts of changes in states on services are identified for monitoring and analysis at a global coastal network of sentinel sites nested in the ocean-climate observing system. Biodiversity is targeted as the “master” indicator because of its importance to a broad spectrum of services. Ultimately, successful implementation of EBAs will depend on establishing integrated, holistic approaches to ocean governance that oversee the development of integrated, operational ocean observing systems based on the data and information requirements specified by a broad spectrum of stakeholders for sustainable development. Sustained engagement of such a spectrum of stakeholders on a global scale is not feasible. The global coastal network will need to be customized locally and regionally based on priorities established by stakeholders in their respective regions. The E.U. Marine Strategy Framework Directive and the U.S. Recommendations of the Interagency Ocean Policy Task Force are important examples of emerging regional scale approaches. The effectiveness of these policies will depend on the co-evolution of ocean policy and the observing system under the auspices of integrated ocean governance.

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Ecosystem-based approaches (EBAs) to managing anthropogenic pressures on ecosystems, adapting to changes in ecosystem states (indicators of ecosystem health), and mitigating the impacts of state changes on ecosystem services are needed for sustainable development. EBAs are informed by integrated ecosystem assessments (IEAs) that must be compiled and updated frequently for EBAs to be effective. Frequently updated IEAs depend on the sustained provision of data and information on pressures, state changes, and impacts of state changes on services. Nowhere is this truer than in the coastal zone, where people and ecosystem services are concentrated and where anthropogenic pressures converge. This study identifies the essential indicator variables required for the sustained provision of frequently updated IEAs, and offers an approach to establishing a global network of coastal observations within the framework of the Global Ocean Observing System. The need for and challenges of capacity-building are highlighted, and examples are given of current programmes that could contribute to the implementation of a coastal ocean observing system of systems on a global scale. This illustrates the need for new approaches to ocean governance that can achieve coordinated integration of existing programmes and technologies as a first step towards this goal.