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Model Adaptation for Prognostics in a Particle Filtering Framework
data.nasa.gov | Last Updated 2020-01-29T02:10:29.000ZOne of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation in conjunction with state tracking, and thus, produces a tuned model that can used for long term predictions. This feature of particle filters works in most part due to the fact that they are not subject to the “curse of dimensionality”, i.e. the exponential growth of computational complexity with state dimension. However, in practice, this property holds for “well-designed” particle filters only as dimensionality increases. This paper explores the notion of wellness of design in the context of predicting remaining useful life for individual discharge cycles of Li-ion batteries. Prognostic metrics are used to analyze the tradeoff between different model designs and prediction performance. Results demonstrate how sensitivity analysis may be used to arrive at a well- designed prognostic model that can take advantage of the model adaptation properties of a particle filter.*
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Earth Radiation Budget Experiment (ERBE) S-10 Wide Field of View (WFOV) Numerical Filter (NF) Earth Flux and Albedo
data.nasa.gov | Last Updated 2022-01-17T05:17:10.000ZERBE_S10_WFOV_NF_NAT_1 is the Earth Radiation Budget Experiment (ERBE) S-10 Wide Field of View (WFOV) Numerical Filter (NF) Earth Flux and Albedo data product. Data collection for this product is complete. It is available in the Native (NAT) Format. ERBE was a multi-satellite system designed to measure the Earth's radiation budget. The ERBE instruments flew on a mid-inclination National Aeronautics and Space Administration (NASA) Earth Radiation Budget Satellite (ERBS) and two sun-synchronous National Oceanic and Atmospheric Administration (NOAA) satellites (NOAA-9 and NOAA-10). Each satellite carried both a scanner and a non-scanner instrument package. The non-scanner instrument package contained four Earth-viewing channels and a solar monitor. The Earth-viewing channels had two spatial resolutions: a horizon-to-horizon view of the Earth, and a field-of-view limited to about 1000 km in diameter. The former was called WFOV and the latter the medium field-of-view (MFOV) channels. The solar monitor was a direct descendant of the Solar Maximum Mission's Active Cavity Radiometer Irradiance Monitor detector. Due to the concern for spectral flatness and high accuracy, all five of the channels were active cavity radiometers. The MFOV (medium-field-of-view) SF (shape factor) S-10 contained inverted daily, monthly hourly, and monthly averages of shortwave and long-wave radiant fluxes at the top-of-the-atmosphere for one month. This data set was produced for each of the satellites (ERBS and NOAA-9) and the combination of satellites, which were operational during the data month. The values for this data set were derived using the shape factor technique (Smith et al. 1986). As described in the Earth Radiant Fluxes and Albedo, Scanner S-9, Non-scanner S-10/S-10N User's Guide, the data contains a 30 byte header, 67 scale factors which were used to scale the data in the first record, and 26 scale factors which were used to scale the data in the second record. The data set also contained two records for each processed region. The first record was of fixed length (990 words) and contained averaged data. The second record was of variable length and contained individual hour box estimates. The length of the second record, in words, was calculated by multiplying the number of hour boxes (978th word of record one) by the number of values stored for each hour box (38 for the non-scanner).
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TOVS GLA MONTHLY GRIDS from NOAA-14 02 (TOVSAMNJ) at GES DISC
data.nasa.gov | Last Updated 2024-03-18T15:31:58.000ZThis dataset (TOVSAMNJ) contains the TIROS Operational Vertical Sounder (TOVS) level 3 geophysical parameters derived using data from NOAA-14 and the physical retrieval method of Susskind et al. (1984) and processed by the Satellite Data Utilization Office of the Goddard Laboratory for Atmospheres at NASA/GSFC. This method, which is hydrodynamic model- and a priori data-dependent, is designated as the so-called Path A scheme by the TOVS Pathfinder Science Working Group. The 20 channel High resolution Infrared Radiation Sounder 2 (HIRS2) and the 4 channel Microwave Sounding Unit (MSU) aboard the NOAA-xx series of Polar Orbiting Satellites are used to produce global fields of the 3-dimensional temperature-moisture structure of the atmosphere. In addition to profiles of temperature and moisture, the HIRS2/MSU data are used to derive important quantities such as land and sea surface temperature, outgoing longwave radiation, cloud fraction, cloudtop height, total ozone overburden and precipitation estimates. The Path A system steps through an interactive forecast-retrieval-analysis cycle. In each 6 hour synoptic period, a 2nd order General Circulation Model (Takacs et al., 1994) is used to generate the 6 hour forecast fields of temperature and humidity. These global fields are used as the first guess for all soundings occurring within a 6 hour time window centered upon the forecast time. These retrievals are then assimilated with all available insitu measurements (such as radiosonde and ship reports) in the 6 hour interval using an Optimal Interpolation (OI) analysis scheme developed by the Data Assimilation Office of the Goddard Laboratory for Atmospheres. This analysis is then used to specify the initial conditions for the next 6 hour forecast, thus completing the cycle. The retrieval algorithm itself is a physical method based on the iterative relaxation technique originally proposed by Chahine (1968). The basic approach consists of modifying the temperature profile from the previous iteration by an amount proportional to the difference between the observed brightness temperatures and the brightness temperatures computed from the trial parameters using the full radiative transfer equation applied at the observed satellite zenith angle. For the case of the temperature profile, the updated layer mean temperatures are given as a linear combination of multichannel brightness temperature differences with the coefficients given by the channel weighting functions. Constraints are imposed upon the solution in order to ensure stability and convergence of the iterative process. For more details see Susskind et al (1984). These Level 3 monthly mean products are in the netCDF format. Each data set is representative of a different monthly average time period and for one of nine satellites. All files contain the same number of geophysical parameter arrays with the AM and PM portions of the orbits treated separately. All data are mapped to a 1 degree longitude by 1 degree latitude global grid.
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ASO L4 Lidar Snow Water Equivalent 50m UTM Grid V001
data.nasa.gov | Last Updated 2022-01-17T05:08:23.000ZThis data set contains 50 m gridded snow water equivalent (SWE) values collected as part of the NASA/JPL Airborne Snow Observatory (ASO) aircraft survey campaigns. The data were derived from the <a href="https://nsidc.org/data/aso_50m_sd">ASO L4 Lidar Snow Depth 50m UTM Grid</a> data product and from modeled snow density.
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SnowEx17 Boise State University Terrestrial Laser Scanner (TLS) Point Cloud V001
data.nasa.gov | Last Updated 2022-01-17T05:55:02.000ZThis data set contains terrestrial laser scanner (TLS) point cloud data collected as part of the 2017 SnowEx campaign in Grand Mesa, Colorado. Data were collected under both snow-off (September 2016) and snow-on (February 2017) conditions, at both open and forested locations. Multiple scans were conducted at each site and registered together using common targets. Each point contains X, Y, and Z coordinates (Easting, Northing, and Elevation), as well as intensity (i). These TLS data can be used to determine snow depth and explore the interactions between snow and vegetation.
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Bio-optical properties of the different water masses in the Gulf of St. Lawrence
data.nasa.gov | Last Updated 2023-04-17T13:03:21.000ZThe St. Lawrence ecosystem is a complex environment influenced by a variety of physical forces (runoff, winds, tides, bathymetry) that sustains a diverse food web going from phytoplankton to whales. Chlorophyll concentration is thus an important variable to measure at the scale of the ecosystem. Because of its large size, remote sensing is the only available tool to measure chlorophyll distribution in the St. Lawrence using ocean color imagery. To fully utilize this type of data, it is however important to have a sound knowledge of the bio-optical properties of the different water masses in the system. A St. Lawrence SeaWiFS program was thus built to gather this knowledge beginning in 1997.
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PHOENIX MARS ROBOTIC ARM CAMERA 5 NORMAL OPS V1.0
data.nasa.gov | Last Updated 2023-01-26T20:52:37.000ZThe Robotic Arm Camera (RAC) experiment on the Mars Phoenix Lander consists of one instrument component plus command electronics. This RAC Imaging Operations RDR data set contains normal data from the Robotic Arm Camera (RAC).
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TES/Aura L3 Ozone Daily Gridded V006
data.nasa.gov | Last Updated 2022-01-17T05:58:51.000ZTL3O3D_6 is the Tropospheric Emission Spectrometer (TES)/Aura L3 Ozone Daily Gridded Version 6 data product. TES was an instrument aboard NASA's Aura satellite and was launched from California on July 15, 2004. Data collection for TES is complete. This data product consists of daily atmospheric temperature and volume mixing ratio (VMR) for the atmospheric species, which were provided at 2 degree latitude by 4 degree longitude spatial grids and at a subset of TES standard pressure levels. The TES Science Data Processing L3 subsystem interpolated the L2 atmospheric profiles collected in a Global Survey onto a global grid uniform in latitude and longitude to provide a 3-D representation of the distribution of atmospheric gasses. Daily and monthly averages of L2 profiles and browse images are available. The L3 standard data products were composed of L3 HDF-EOS grid data. A separate product file is produced for each different atmospheric species. TES obtains data in two basic observation modes: Limb or Nadir. The product file may have contained, in separate folders, limb data, nadir data, or both folders may be present. Specific to L3 processing are the terms Daily and Monthly representing the approximate time coverage of the L3 products. However, the input data granules to the L3 process are completed Global Surveys; in other words a Global Survey was not split in relation to time when input to the L3 processes even if they exceeded the usual understood meanings of a day or month. More specifically, Daily L3 products represented a single Global Survey (approximately 26 hours) and Monthly L3 products represented Global Surveys that were initiated within that calendar month. The data granules defined for L3 standard products were daily and monthly. Details of the format of this product can be found in the TES Data Products Specifications (DPS).
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VIIRS/NPP BRDF/Albedo Snow Status Daily L3 Global 30ArcSec CMG V001
data.nasa.gov | Last Updated 2024-05-27T13:06:38.000ZThe NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) Bidirectional Reflectance Distribution Function (BRDF) and Albedo Snow Status product (VNP43D52) is produced daily using 16 days of data at 30 arc second (1,000 meter) resolution. Data are temporally weighted to the ninth day, which is reflected in the file name. The VNP43D product suite is provided in a Climate Modeling Grid (CMG), which covers the entire globe for use in climate simulation models. Due to the large file size, each VNP43D product contains just one data layer for each of the parameters included in the VNP43MA2 (https://doi.org/10.5067/VIIRS/VNP43MA2.001) product. VNP43D40 through VNP43D53 are the 30 arc second BRDF/Albedo Quality values, the Local Solar Noon values, the Valid Observations of the moderate resolution bands (M1 through M5, M7, M8, M10, and M11) plus the Day/Night Band (DNB), the Snow Status, and the Uncertainty. Details regarding methodology are available on the VNP43MA2 product page and in the Algorithm Theoretical Basis Document (ATBD). VNP43D52 contains the snow status quality layer, which identifies each pixel as either “Snow-free Albedo Retrieved” or “Snow Albedo Retrieved” for the acquisition period.
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TOVS GLA MONTHLY GRIDS from NOAA-6 02 (TOVSAMNA) at GES DISC
data.nasa.gov | Last Updated 2024-03-18T15:31:55.000ZThis dataset (TOVSAMNA) contains the TIROS Operational Vertical Sounder (TOVS) level 3 geophysical parameters derived using data from NOAA-6 and the physical retrieval method of Susskind et al. (1984) and processed by the Satellite Data Utilization Office of the Goddard Laboratory for Atmospheres at NASA/GSFC. This method, which is hydrodynamic model- and a priori data-dependent, is designated as the so-called Path A scheme by the TOVS Pathfinder Science Working Group. The 20 channel High resolution Infrared Radiation Sounder 2 (HIRS2) and the 4 channel Microwave Sounding Unit (MSU) aboard the NOAA-xx series of Polar Orbiting Satellites are used to produce global fields of the 3-dimensional temperature-moisture structure of the atmosphere. In addition to profiles of temperature and moisture, the HIRS2/MSU data are used to derive important quantities such as land and sea surface temperature, outgoing longwave radiation, cloud fraction, cloudtop height, total ozone overburden and precipitation estimates. The Path A system steps through an interactive forecast-retrieval-analysis cycle. In each 6 hour synoptic period, a 2nd order General Circulation Model (Takacs et al., 1994) is used to generate the 6 hour forecast fields of temperature and humidity. These global fields are used as the first guess for all soundings occurring within a 6 hour time window centered upon the forecast time. These retrievals are then assimilated with all available insitu measurements (such as radiosonde and ship reports) in the 6 hour interval using an Optimal Interpolation (OI) analysis scheme developed by the Data Assimilation Office of the Goddard Laboratory for Atmospheres. This analysis is then used to specify the initial conditions for the next 6 hour forecast, thus completing the cycle. The retrieval algorithm itself is a physical method based on the iterative relaxation technique originally proposed by Chahine (1968). The basic approach consists of modifying the temperature profile from the previous iteration by an amount proportional to the difference between the observed brightness temperatures and the brightness temperatures computed from the trial parameters using the full radiative transfer equation applied at the observed satellite zenith angle. For the case of the temperature profile, the updated layer mean temperatures are given as a linear combination of multichannel brightness temperature differences with the coefficients given by the channel weighting functions. Constraints are imposed upon the solution in order to ensure stability and convergence of the iterative process. For more details see Susskind et al (1984). These Level 3 monthly mean products are in the netCDF format. Each data set is representative of a different monthly average time period and for one of nine satellites. All files contain the same number of geophysical parameter arrays with the AM and PM portions of the orbits treated separately. All data are mapped to a 1 degree longitude by 1 degree latitude global grid.