Calibration and Validation of EarthCARE’s Cloud Profiling Radar Data Products using NASA’s Airborne and Spaceborne assets
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A compiled set of in situ data is important to evaluate the quality of ocean-colour satellite-data records. Here we describe the data compiled for the validation of the ocean-colour products from the ESA Ocean Colour Climate Change Initiative (OC-CCI). The data were acquired from several sources (MOBY, BOUSSOLE, AERONET-OC, SeaBASS, NOMAD, MERMAID, AMT, ICES, HOT, GePCO), span between 1997 and 2012, and have a global distribution. Observations of the following variables were compiled: spectral remote-sensing reflectances, concentrations of chlorophyll a, spectral inherent optical properties and spectral diffuse attenuation coefficients. The data were from multi-project archives acquired via the open internet services or from individual projects, acquired directly from data providers. Methodologies were implemented for homogenisation, quality control and merging of all data. No changes were made to the original data, other than averaging of observations that were close in time and space, elimination of some points after quality control and conversion to a standard format. The final result is a merged table designed for validation of satellite-derived ocean-colour products and available in text format. Metadata of each in situ measurement (original source, cruise or experiment, principal investigator) were preserved throughout the work and made available in the final table. Using all the data in a validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. By making available the metadata, it is also possible to analyse each set of data separately. The compiled data are available at doi:10.1594PANGAEA.854832 (Valente et al., 2015).
Three dimensional aerodynamic data, required to validate and/or indicate necessary refinements to inviscid and viscous analyses of the flow through turbomachine blade rows, are discussed. Instrumentation and capabilities for pressure measurement, probe insertion and traversing, and flow visualization are reviewed. Advanced measurement techniques including Laser Doppler Anemometers, are considered. Data processing is reviewed. Predictions were correlated with the experimental data. A flow visualization technique using helium filled soap bubbles was demonstrated.
The wealth of in-situ measurements gathered during Tropical Rain Measuring Mission (TRMM) field campaigns over a wide range of tropical conditions constitute an important data source for evaluating the quality of global model forecasts and assimilated datasets. In this study we use selected observations of cloud microphysics and atmospheric sounding from TEFLUN-1998, SCEMEX-1998, and TRMMLBA-1999 to examine the assimilation and forecast fields produced by the operational GEOS-3 (Goddard Earth Observing System - version 3) global data assimilation system (DAS) and a new finite-volume DAS under development at the Data Assimilation Office. Additionally, TRMM field campaign measurements are used to verify the impact of assimilating rainfall and moisture data derived from TRMM Microwave Imager and Special Sensor Microwave/Imager instruments on the GEOS analysis. We will also explore issues concerning the 'error of representativeness' in using in-situ observations of quantities with large spatial and temporal variability such as precipitation for validating gridded global data products.
Major elements of an experiment called the Infrared Sensing Aeroheating Flight Experiment are discussed. The primary experiment goal is to provide reentry global temperature images from infrared measurements to define the characteristics of hypersonic boundary-layer transition during flight. Specifically, the experiment is to identify, monitor, and quantity hypersonic boundary layer windward surface transition of the X-33 vehicle during flight. In addition, the flight data will serve as a calibration and validation of current boundary layer transition prediction techniques, provide benchmark laminar, transitional, and fully turbulent global aeroheating data in order to validate existing wind tunnel and computational results, and to advance aeroheating technology. Shuttle Orbiter data from STS-96 used to validate the data acquisition and data reduction to global temperatures, in order to mitigate the experiment risks prior to the maiden flight of the X-33, is discussed. STS-96 reentry midwave (3-5 micron) infrared data were collected at the Ballistic Missile Defense Organization/Innovative Sciences and Technology Experimentation Facility site at NASA-Kennedy Space Center and subsequently mapped into global temperature contours using ground calibrations only. A series of image mapping techniques have been developed in order to compare each frame of infrared data with thermocouple data collected during the flight. Comparisons of the ground calibrated global temperature images with the corresponding thermocouple data are discussed. The differences are shown to be generally less than about 5%, which is comparable to the expected accuracy of both types of aeroheating measurements.
Major elements of an experiment called the Infrared Sensing Aeroheating Flight Experiment are discussed. The primary experiment goal is to provide reentry global temperature images from infrared measurements to define the characteristics of hypersonic boundary-layer transition during flight. Specifically, the experiment is to identify, monitor, and quantify hypersonic boundary layer windward surface transition of the X-33 vehicle during flight. In addition, the flight data will serve as a calibration and validation of current boundary layer transition prediction techniques, provide benchmark laminar, transitional, and fully turbulent global aeroheating data in order to validate existing wind tunnel and computational results, and to advance aeroheating technology. Shuttle Orbiter data from STS-96 used to validate the data acquisition and data reduction to global temperatures, in order to mitigate the experiment risks prior to the maiden flight of the X-33, is discussed. STS-96 reentry mid-wave (3-5 Pm) infrared data were collected at the Ballistic Missile Defense Organization/Innovative Sciences and Technology Experimentation Facility site at NASA-Kennedy Space Center and subsequently mapped into global temperature contours using ground calibrations only. A series of image mapping techniques have been developed in order to compare each frame of infrared data with thermocouple data collected during the flight. Comparisons of the ground calibrated global temperature images with the corresponding thermocouple data are discussed. The differences are shown to be generally less than about 5%, which is comparable to the expected accuracy of both types of aeroheating measurements.
A description of the sea surface height variabilities during 1986-1988 in the tropical Pacific Ocean is presented on the basis of Geosat altimeter data and a tropical Pacific Ocean GCM (OGCM) forced with observed winds from Florida State University. Both data sets are validated against in situ sea-level measurements at 12 selected sea-level stations in the equatorial Pacific and were found to be in good agreement with these measurements with correlation coefficients of 0.69 for Geosat and 0.71 for OGCM. The Geosat altimeter data are capable of describing sea surface height variabilities during 1986-1988 in the tropical Pacific, in particular, the seasonal cycle, the 1987 El Nino and 1988 La Nina episodes, and the December 1986 equatorial Kelvin wave event. The OGCM-simulated surface dynamic height is found to be sensitive to different surface wind products.
This grant provided partial support for participation in the SAGE III Ozone Loss and Validation Experiment. The NASA-sponsored SOLVE mission was conducted Jointly with the European Commission-sponsored Third European Stratospheric Experiment on Ozone (THESEO 2000). Researchers examined processes that control ozone amounts at mid to high latitudes during the arctic winter and acquired correlative data needed to validate the Stratospheric Aerosol and Gas Experiment (SAGE) III satellite measurements that are used to quantitatively assess high-latitude ozone loss. The campaign began in September 1999 with intercomparison flights out of NASA Dryden Flight Research Center in Edwards. CA. and continued through March 2000. with midwinter deployments out of Kiruna. Sweden. SOLVE was co-sponsored by the Upper Atmosphere Research Program (UARP). Atmospheric Effects of Aviation Project (AEAP). Atmospheric Chemistry Modeling and Analysis Program (ACMAP). and Earth Observing System (EOS) of NASA's Earth Science Enterprise (ESE) as part of the validation program for the SAGE III instrument.
Terrain Relative Navigation (TRN) systems localize a spacecraft with respect to a map of the surface by comparing descent imagery to that reference map. The spacecraft position estimates can only be as accurate as the reference map itself. Accurate map products that are based on orbital reconnaissance data must be validated for navigation applications to ensure that all relevant error sources are minimized. Currently available map products have been generated for scientific applications, so the need for accurate TRN maps remains a gap to be filled for upcoming lunar lander missions, in particular missions to the South Pole region. Additionally, representative high-resolution maps that contain lander-scale features are needed for successful development and testing of Hazard Detection (HD) systems. This paper describes one of NASA’s current efforts to develop benchmark data sets that can be used for developing and testing TRN and HD algorithms as well as suggested processes and metrics for generating and validating lunar maps that can be used for navigation and hazard detection.
Terrain Relative Navigation (TRN) systems that localize a spacecraft with respect to a map of the surface by comparing descent imagery to that reference map can only be as accurate as the reference map itself. Accurate map products that are based on orbital reconnaissance data must be validated for navigation applications to ensure that all relevant error sources are minimized. Currently available map products have been generated for scientific applications, so the need for accurate TRN maps remains a gap to be filled for upcoming lunar lander missions, in particular missions to the South Pole region. Additionally, representative high-resolution maps that contain lander-scale features are needed for successful development and testing of Hazard Detection (HD) systems. This paper describes one of NASA’s current efforts to develop benchmark data sets that can be used for developing and testing TRN and HD algorithms as well as suggested processes and metrics for generating and validating lunar maps that can be used for navigation and hazard detection.
Validation of the CALIOP data products remains an ongoing task for the CALIPSO team. Validating the optical properties of aerosols located above clouds is especially difficult, because independent measurements are usually not available. In this presentation we analyze 532-nm aerosol optical depth (AOD) above clouds, comparing results from the standard CALIOP algorithm with two alternate algorithms applied to CALIOP data acquired along the transport pathways of African dust and biomass burning aerosols. Multiple years of the CALIPSO nighttime data (2007-2012) were examined. The analysis was limited to cases where there are opaque water clouds below aerosol layers that can be used as a reference to retrieve AOD of the overlying aerosol layer.
The use of fluid lensing technology on UAVs is presented as a novel means for 3D imaging of aquatic ecosystems from above the water's surface at the centimeter scale. Preliminary results are presented from airborne fluid lensing campaigns conducted over the coral reefs of Ofu Island, American Samoa (2013) and the stromatolite reefs of Shark Bay, Western Australia (2014), covering a combined area of 15km2. These reef ecosystems were revealed with centimetre-scale 2D resolution, and an accompanying 3D bathymetry model was derived using fluid lensing, Structure from Motion and UAV position data. Data products were validated from in-situ survey methods including underwater calibration targets, depth measurements and millimetre-scale high-dynamic range gigapixel photogrammetry. Fluid lensing is an experimental technology that uses water transmitting wavelengths to passively image underwater objects at high-resolution by exploiting time-varying optical lensing events caused by surface waves. Fluid lensing data are captured from low-altitude, cost-effective electric UAVs to achieve multispectral imagery and bathymetry models at the centimetre scale over regional areas. As a passive system, fluid lensing is presently limited by signal-to-noise ratio and water column inherent optical properties to approximately 10 m depth over visible wavelengths in clear waters. The datasets derived from fluid lensing present the first centimetre-scale images of a reef acquired from above the ocean surface, without wave distortion. The 3D multispectral data distinguish coral, fish and invertebrates in American Samoa, and reveal previously undocumented, morphologically distinct, stromatolite structures in Shark Bay. These findings suggest fluid lensing and multirotor electric drones represent a promising advance in the remote sensing of aquatic environments at the centimetre scale, or 'reef scale' relevant to the conservation of reef ecosystems. Pending further development and validation of fluid lensing methods, these technologies present a solution for large-scale 3D surveys of shallow aquatic habitats with centimetre-scale spatial resolution and hourly temporal sampling.
A flexible fuzzy set preference model first requires approximate methodologies for implementation. Fuzzy sets must be defined for each individual consumer using computer software, requiring a minimum of time and expertise on the part of the consumer. The amount of information needed in defining sets must also be established. The model itself must adapt fully to the subject's choice of attributes (vague or precise), attribute levels, and importance weights. The resulting individual-level model should be fully adapted to each consumer. The methodologies needed to develop this model will be equally useful in a new generation of intelligent systems which interact with ordinary consumers, controlling electronic devices through fuzzy expert systems or making recommendations based on a variety of inputs. The power of personal computers and their acceptance by consumers has yet to be fully utilized to create interactive knowledge systems that fully adapt their function to the user. Understanding individual consumer preferences is critical to the design of new products and the estimation of demand (market share) for existing products, which in turn is an input to management systems concerned with production and distribution. The question of what to make, for whom to make it and how much to make requires an understanding of the customer's preferences and the trade-offs that exist between alternatives. Conjoint analysis is a widely used methodology which de-composes an overall preference for an object into a combination of preferences for its constituent parts (attributes such as taste and price), which are combined using an appropriate combination function. Preferences are often expressed using linguistic terms which cannot be represented in conjoint models. Current models are also not implemented an individual level, making it difficult to reach meaningful conclusions about the cause of an individual's behavior from an aggregate model. The combination of complex aggregate models and vague linguistic preferences has greatly limited the usefulness and predictive validity of existing preference models. A fuzzy set preference model that uses linguistic variables and a fully interactive implementation should be able to simultaneously address these issues and substantially improve the accuracy of demand estimates. The parallel implementation of crisp and fuzzy conjoint models using identical data not only validates the fuzzy set model but also provides an opportunity to assess the impact of fuzzy set definitions and individual attribute choices implemented in the interactive methodology developed in this research. The generalized experimental tools needed for conjoint models can also be applied to many other types of intelligent systems.
As the space industry continues to strive for more efficient launch vehicles, it must rely on increasingly accurate predictive models. Verification of models typically requires physical testing. Flight data measurements offer the most real and therefore the most accurate data for model correlation. As NASA prepares for the inaugural launch of Space Launch System (SLS), Artemis-1, they must rely heavily on predictive system models to ensure flight safety. NASA has implemented a Development Flight Instrumentation (DFI) system in hopes of recovering useful flight data to aid in model correlation. Historically, some of the most important flight measurements are those that monitor the potentially destructive dynamic interaction of the structural and propellant modes – a phenomenon known as pogo. Pogo is a dynamic instability that can occur on a launch vehicle during any phase of ascent. During this investigation an end-to-end assessment of the Artemis-I Pogo-related DFI was performed to identify any obstacles inherent in the current instrumentation system which may prevent successful measurement of the data necessary to validate the current predictive models of the Main Propulsion System (MPS). Input drive signals were approximated and applied to a system-level SLS state-space model to derive predicted pressure and acceleration responses. These predicted responses were then fed through a simulation of the data acquisition process in order to recover predicted measurements. Finally, a mock Flight Data Analysis (FDA) was performed to assess the ability of these measurements to meet the Flight Test Objectives (FTO).
Plasma processing is a key processing stop in integrated circuit manufacturing. Low pressure, high density plum reactors are widely used for etching and deposition. Inductively coupled plasma (ICP) source has become popular recently in many processing applications. In order to accelerate equipment and process design, an understanding of the physics and chemistry, particularly, plasma power coupling, plasma and processing uniformity and mechanism is important. This understanding is facilitated by comprehensive modeling and simulation as well as plasma diagnostics to provide the necessary data for model validation which are addressed in this presentation. We have developed a complete code for simulating an ICP reactor and the model consists of transport of electrons, ions, and neutrals, Poisson's equation, and Maxwell's equation along with gas flow and energy equations. Results will be presented for chlorine and fluorocarbon plasmas and compared with data from Langmuir probe, mass spectrometry and FTIR.
The Stratospheric Aerosol and Gas Experiment III (SAGE III) instrument installed on the International Space Station (ISS) has completed three years of data collection and production of science data products. The SAGE III/ISS is a solar and lunar occultation instrument that scans the light from the Sun and Moon through the limb of the Earth’s atmosphere to produce vertical profiles of aerosol, ozone, water vapor, and other trace gases. It continues the legacy of previous SAGE instruments dating back to the 1970s to provide data continuity of stratospheric constituents critical for assessing trends in the ozone layer. This presentation shows the validation results of comparing SAGE III/ISS ozone and water vapor vertical profiles with those of in situ and satellite data.
The MODerate resolution Imaging Spectroradiometer (MODIS) currently aboard both the Terra and Aqua satellites produces a suite of products designed to characterize global aerosol distribution, optical thickness and particle size. Never before has a space-borne instrument been able to provide such detailed information, complementing field and modeling efforts to produce a comprehensive picture of aerosol characteristics. The three years of Terra-MODIS data have been validated by comparing with co-located AERONET observations of aerosol optical thickness and derivations of aerosol size parameters. Some 8000 comparison points located at 133 AERONET sites around the globe show that the MODIS aerosol optical thickness retrievals are accurate to within the pre-launch expectations. MODIS-derived size parameters are also compared with AERONET retrievals and found to agree well for fine-mode dominated aerosol regimes. Aerosol regimes dominated by dust aerosol are less accurate, attributed to what is thought to be nonsphericity. Errors due to nonsphericity will be reduced by introducing a new set of empirical phase functions, derived without any assumptions of particle shape. The major innovation that MODIS bring to the field of remote sensing of aerosol is the measure of particle size and the separation of finemode and coarsemode dominated aerosol regimes. Particle size can separate finemode man-made aerosols created during combustion, from larger natural aerosols originating from salt spray or wind erosion. This separation allows for the calculation of aerosol radiative effect and the estimation of the man-made aerosol radiative forcing. MODIS can also be used in regional studies of aerosol-cloud interaction that affect the global radiative and hydrological cycles.
The objectives of this presentation are: (1) Share lessons learned from a recent exercise in CFD validation of protuberance heating (2) Impact of experimental data reduction assumptions and techniques on validation activity (3) Advanced data reduction techniques may provide useful data from non-typical test methods (4) Significance of the recovery factor for high-speed flows (5) Show typical results of the Lag turbulence model on protuberances (6) Introduce and inform the listener of a protuberance heating dataset which will soon be available for comparison