Error sources in the retrieval of aerosol information over bright surfaces from satellite measurements in the oxygen A band

NASA Astrophysics Data System (ADS)

Nanda, Swadhin; de Graaf, Martin; Sneep, Maarten; de Haan, Johan F.; Stammes, Piet; Sanders, Abram F. J.; Tuinder, Olaf; Pepijn Veefkind, J.; Levelt, Pieternel F.

2018-01-01

Retrieving aerosol optical thickness and aerosol layer height over a bright surface from measured top-of-atmosphere reflectance spectrum in the oxygen A band is known to be challenging, often resulting in large errors. In certain atmospheric conditions and viewing geometries, a loss of sensitivity to aerosol optical thickness has been reported in the literature. This loss of sensitivity has been attributed to a phenomenon known as critical surface albedo regime, which is a range of surface albedos for which the top-of-atmosphere reflectance has minimal sensitivity to aerosol optical thickness. This paper extends the concept of critical surface albedo for aerosol layer height retrievals in the oxygen A band, and discusses its implications. The underlying physics are introduced by analysing the top-of-atmosphere reflectance spectrum as a sum of atmospheric path contribution and surface contribution, obtained using a radiative transfer model. Furthermore, error analysis of an aerosol layer height retrieval algorithm is conducted over dark and bright surfaces to show the dependence on surface reflectance. The analysis shows that the derivative with respect to aerosol layer height of the atmospheric path contribution to the top-of-atmosphere reflectance is opposite in sign to that of the surface contribution - an increase in surface brightness results in a decrease in information content. In the case of aerosol optical thickness, these derivatives are anti-correlated, leading to large retrieval errors in high surface albedo regimes. The consequence of this anti-correlation is demonstrated with measured spectra in the oxygen A band from the GOME-2 instrument on board the Metop-A satellite over the 2010 Russian wildfires incident.

XCO2 Retrieval Errors from a PCA-based Approach to Fast Radiative Transfer

NASA Astrophysics Data System (ADS)

Somkuti, Peter; Boesch, Hartmut; Natraj, Vijay; Kopparla, Pushkar

2017-04-01

Multiple-scattering radiative transfer (RT) calculations are an integral part of forward models used to infer greenhouse gas concentrations in the shortwave-infrared spectral range from satellite missions such as GOSAT or OCO-2. Such calculations are, however, computationally expensive and, combined with the recent growth in data volume, necessitate the use of acceleration methods in order to make retrievals feasible on an operational level. The principle component analysis (PCA)-based approach to fast radiative transfer introduced by Natraj et al. 2005 is a spectral binning method, in which the many line-by-line monochromatic calculations are replaced by a small set of representative ones. From the PCA performed on the optical layer properties for a scene-dependent atmosphere, the results of the representative calculations are mapped onto all spectral points in the given band. Since this RT scheme is an approximation, the computed top-of-atmosphere radiances exhibit errors compared to the "full" line-by-line calculation. These errors ultimately propagate into the final retrieved greenhouse gas concentrations, and their magnitude depends on scene-dependent parameters such as aerosol loadings or viewing geometry. An advantage of this method is the ability to choose the degree of accuracy by increasing or decreasing the number of empirical orthogonal functions used for the reconstruction of the radiances. We have performed a large set of global simulations based on real GOSAT scenes and assess the retrieval errors induced by the fast RT approximation through linear error analysis. We find that across a wide range of geophysical parameters, the errors are for the most part smaller than ± 0.2 ppm and ± 0.06 ppm (out of roughly 400 ppm) for ocean and land scenes respectively. A fast RT scheme that produces low errors is important, since regional biases in XCO2 even in the low sub-ppm range can cause significant changes in carbon fluxes obtained from inversions (Chevallier et al. 2007).

Impacts of updated spectroscopy on thermal infrared retrievals of methane evaluated with HIPPO data

NASA Astrophysics Data System (ADS)

Alvarado, M. J.; Payne, V. H.; Cady-Pereira, K. E.; Hegarty, J. D.; Kulawik, S. S.; Wecht, K. J.; Worden, J. R.; Pittman, J. V.; Wofsy, S. C.

2014-09-01

Errors in the spectroscopic parameters used in the forward radiative transfer model can introduce altitude-, spatially-, and temporally-dependent biases in trace gas retrievals. For well-mixed trace gases such as methane, where the variability of tropospheric mixing ratios is relatively small, reducing such biases is particularly important. We use aircraft observations from all five missions of the HIAPER Pole-to-Pole Observations (HIPPO) of the Carbon Cycle and Greenhouse Gases Study to evaluate the impact of updates to spectroscopic parameters for methane (CH4), water vapor (H2O), and nitrous oxide (N2O) on thermal infrared retrievals of methane from the NASA Aura Tropospheric Emission Spectrometer (TES). We find that updates to the spectroscopic parameters for CH4 result in a substantially smaller mean bias in the retrieved CH4 when compared with HIPPO observations. After an N2O-based correction, the bias in TES methane upper tropospheric representative values for measurements between 50° S and 50° N decreases from 56.9 to 25.7 ppbv, while the bias in the lower tropospheric representative value increases only slightly (from 27.3 to 28.4 ppbv). For retrievals with less than 1.6 DOFS, the bias is reduced from 26.8 to 4.8 ppbv. We also find that updates to the spectroscopic parameters for N2O reduce the errors in the retrieved N2O profile.

Satellite Estimation of Daily Land Surface Water Vapor Pressure Deficit from AMSR- E

NASA Astrophysics Data System (ADS)

Jones, L. A.; Kimball, J. S.; McDonald, K. C.; Chan, S. K.; Njoku, E. G.; Oechel, W. C.

2007-12-01

Vapor pressure deficit (VPD) is a key variable for monitoring land surface water and energy exchanges, and estimating plant water stress. Multi-frequency day/night brightness temperatures from the Advanced Microwave Scanning Radiometer on EOS Aqua (AMSR-E) were used to estimate daily minimum and average near surface (2 m) air temperatures across a North American boreal-Arctic transect. A simple method for determining daily mean VPD (Pa) from AMSR-E air temperature retrievals was developed and validated against observations across a regional network of eight study sites ranging from boreal grassland and forest to arctic tundra. The method assumes that the dew point and minimum daily air temperatures tend to equilibrate in areas with low night time temperatures and relatively moist conditions. This assumption was tested by comparing the VPD algorithm results derived from site daily temperature observations against results derived from AMSR-E retrieved temperatures alone. An error analysis was conducted to determine the amount of error introduced in VPD estimates given known levels of error in satellite retrieved temperatures. Results indicate that the assumption generally holds for the high latitude study sites except for arid locations in mid-summer. VPD estimates using the method with AMSR-E retrieved temperatures compare favorably with site observations. The method can be applied to land surface temperature retrievals from any sensor with day and night surface or near-surface thermal measurements and shows potential for inferring near-surface wetness conditions where dense vegetation may hinder surface soil moisture retrievals from low-frequency microwave sensors. This work was carried out at The University of Montana, at San Diego State University, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

Semiparametric modeling: Correcting low-dimensional model error in parametric models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berry, Tyrus, E-mail: thb11@psu.edu; Harlim, John, E-mail: jharlim@psu.edu; Department of Meteorology, the Pennsylvania State University, 503 Walker Building, University Park, PA 16802-5013

2016-03-01

In this paper, a semiparametric modeling approach is introduced as a paradigm for addressing model error arising from unresolved physical phenomena. Our approach compensates for model error by learning an auxiliary dynamical model for the unknown parameters. Practically, the proposed approach consists of the following steps. Given a physics-based model and a noisy data set of historical observations, a Bayesian filtering algorithm is used to extract a time-series of the parameter values. Subsequently, the diffusion forecast algorithm is applied to the retrieved time-series in order to construct the auxiliary model for the time evolving parameters. The semiparametric forecasting algorithm consistsmore » of integrating the existing physics-based model with an ensemble of parameters sampled from the probability density function of the diffusion forecast. To specify initial conditions for the diffusion forecast, a Bayesian semiparametric filtering method that extends the Kalman-based filtering framework is introduced. In difficult test examples, which introduce chaotically and stochastically evolving hidden parameters into the Lorenz-96 model, we show that our approach can effectively compensate for model error, with forecasting skill comparable to that of the perfect model.« less

Information content and sensitivity of the 3β + 2α lidar measurement system for aerosol microphysical retrievals

NASA Astrophysics Data System (ADS)

Burton, Sharon P.; Chemyakin, Eduard; Liu, Xu; Knobelspiesse, Kirk; Stamnes, Snorre; Sawamura, Patricia; Moore, Richard H.; Hostetler, Chris A.; Ferrare, Richard A.

2016-11-01

There is considerable interest in retrieving profiles of aerosol effective radius, total number concentration, and complex refractive index from lidar measurements of extinction and backscatter at several wavelengths. The combination of three backscatter channels plus two extinction channels (3β + 2α) is particularly important since it is believed to be the minimum configuration necessary for the retrieval of aerosol microphysical properties and because the technological readiness of lidar systems permits this configuration on both an airborne and future spaceborne instrument. The second-generation NASA Langley airborne High Spectral Resolution Lidar (HSRL-2) has been making 3β + 2α measurements since 2012. The planned NASA Aerosol/Clouds/Ecosystems (ACE) satellite mission also recommends the 3β + 2α combination.Here we develop a deeper understanding of the information content and sensitivities of the 3β + 2α system in terms of aerosol microphysical parameters of interest. We use a retrieval-free methodology to determine the basic sensitivities of the measurements independent of retrieval assumptions and constraints. We calculate information content and uncertainty metrics using tools borrowed from the optimal estimation methodology based on Bayes' theorem, using a simplified forward model look-up table, with no explicit inversion. The forward model is simplified to represent spherical particles, monomodal log-normal size distributions, and wavelength-independent refractive indices. Since we only use the forward model with no retrieval, the given simplified aerosol scenario is applicable as a best case for all existing retrievals in the absence of additional constraints. Retrieval-dependent errors due to mismatch between retrieval assumptions and true atmospheric aerosols are not included in this sensitivity study, and neither are retrieval errors that may be introduced in the inversion process. The choice of a simplified model adds clarity to the understanding of the uncertainties in such retrievals, since it allows for separately assessing the sensitivities and uncertainties of the measurements alone that cannot be corrected by any potential or theoretical improvements to retrieval methodology but must instead be addressed by adding information content.The sensitivity metrics allow for identifying (1) information content of the measurements vs. a priori information; (2) error bars on the retrieved parameters; and (3) potential sources of cross-talk or "compensating" errors wherein different retrieval parameters are not independently captured by the measurements. The results suggest that the 3β + 2α measurement system is underdetermined with respect to the full suite of microphysical parameters considered in this study and that additional information is required, in the form of additional coincident measurements (e.g., sun-photometer or polarimeter) or a priori retrieval constraints. A specific recommendation is given for addressing cross-talk between effective radius and total number concentration.

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

2000-01-01

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Reduction of the misinformation effect by arousal induced after learning.

PubMed

English, Shaun M; Nielson, Kristy A

2010-11-01

Misinformation introduced after events have already occurred causes errors in later retrieval. Based on literature showing that arousal induced after learning enhances delayed retrieval, we investigated whether post-learning arousal can reduce the misinformation effect. 251 participants viewed four short film clips, each followed by a retention test, which for some participants included misinformation. Afterward, participants viewed another film clip that was either arousing or neutral. One week later, the arousal group recognized significantly more veridical details and endorsed significantly fewer misinformation items than the neutral group. The findings suggest that arousal induced after learning reduced source confusion, allowing participants to better retrieve accurate details and to better reject misinformation. Copyright © 2010 Elsevier B.V. All rights reserved.

Precise signal amplitude retrieval for a non-homogeneous diagnostic beam using complex interferometry approach

NASA Astrophysics Data System (ADS)

Krupka, M.; Kalal, M.; Dostal, J.; Dudzak, R.; Juha, L.

2017-08-01

Classical interferometry became widely used method of active optical diagnostics. Its more advanced version, allowing reconstruction of three sets of data from just one especially designed interferogram (so called complex interferogram) was developed in the past and became known as complex interferometry. Along with the phase shift, which can be also retrieved using classical interferometry, the amplitude modifications of the probing part of the diagnostic beam caused by the object under study (to be called the signal amplitude) as well as the contrast of the interference fringes can be retrieved using the complex interferometry approach. In order to partially compensate for errors in the reconstruction due to imperfections in the diagnostic beam intensity structure as well as for errors caused by a non-ideal optical setup of the interferometer itself (including the quality of its optical components), a reference interferogram can be put to a good use. This method of interferogram analysis of experimental data has been successfully implemented in practice. However, in majority of interferometer setups (especially in the case of the ones employing the wavefront division) the probe and the reference part of the diagnostic beam would feature different intensity distributions over their respective cross sections. This introduces additional error into the reconstruction of the signal amplitude and the fringe contrast, which cannot be resolved using the reference interferogram only. In order to deal with this error it was found that additional separately recorded images of the intensity distribution of the probe and the reference part of the diagnostic beam (with no signal present) are needed. For the best results a sufficient shot-to-shot stability of the whole diagnostic system is required. In this paper, efficiency of the complex interferometry approach for obtaining the highest possible accuracy of the signal amplitude reconstruction is verified using the computer generated complex and reference interferograms containing artificially introduced intensity variations in the probe and the reference part of the diagnostic beam. These sets of data are subsequently analyzed and the errors of the signal amplitude reconstruction are evaluated.

Impacts of updated spectroscopy on thermal infrared retrievals of methane evaluated with HIPPO data

NASA Astrophysics Data System (ADS)

Alvarado, M. J.; Payne, V. H.; Cady-Pereira, K. E.; Hegarty, J. D.; Kulawik, S. S.; Wecht, K. J.; Worden, J. R.; Pittman, J. V.; Wofsy, S. C.

2015-02-01

Errors in the spectroscopic parameters used in the forward radiative transfer model can introduce spatially, temporally, and altitude-dependent biases in trace gas retrievals. For well-mixed trace gases such as methane, where the variability of tropospheric mixing ratios is relatively small, reducing such biases is particularly important. We use aircraft observations from all five missions of the HIAPER Pole-to-Pole Observations (HIPPO) of the Carbon Cycle and Greenhouse Gases Study to evaluate the impact of updates to spectroscopic parameters for methane (CH4), water vapor (H2O), and nitrous oxide (N2O) on thermal infrared retrievals of methane from the NASA Aura Tropospheric Emission Spectrometer (TES). We find that updates to the spectroscopic parameters for CH4 result in a substantially smaller mean bias in the retrieved CH4 when compared with HIPPO observations. After an N2O-based correction, the bias in TES methane upper tropospheric representative values for measurements between 50° S and 50° N decreases from 56.9 to 25.7 ppbv, while the bias in the lower tropospheric representative value increases only slightly (from 27.3 to 28.4 ppbv). For retrievals with less than 1.6 degrees of freedom for signal (DOFS), the bias is reduced from 26.8 to 4.8 ppbv. We also find that updates to the spectroscopic parameters for N2O reduce the errors in the retrieved N2O profile.

Space-borne observation of methane from atmospheric infrared sounder version 6: validation and implications for data analysis

NASA Astrophysics Data System (ADS)

Xiong, X.; Weng, F.; Liu, Q.; Olsen, E.

2015-08-01

Atmospheric Methane (CH4) is generated as a standard product in recent version of the hyperspectral Atmospheric Infrared Sounder (AIRS-V6) aboard NASA's Aqua satellite at the NASA Goddard Earth Sciences Data and Information Services Center (NASA/GES/DISC). Significant improvements in AIRS-V6 was expected but without a thorough validation. This paper first introduced the improvements of CH4 retrieval in AIRS-V6 and some characterizations, then presented the results of validation using ~ 1000 aircraft profiles from several campaigns spread over a couple of years and in different regions. It was found the mean biases of AIRS CH4 at layers 343-441 and 441-575 hPa are -0.76 and -0.05 % and the RMS errors are 1.56 and 1.16 %, respectively. Further analysis demonstrates that the errors in the spring and in the high northern latitudes are larger than in other seasons or regions. The error is correlated with Degree of Freedoms (DOFs), particularly in the tropics or in the summer, and cloud amount, suggesting that the "observed" spatiotemporal variation of CH4 by AIRS is imbedded with some artificial impact from the retrieval sensitivity in addition to its variation in reality, so the variation of information content in the retrievals needs to be taken into account in data analysis of the retrieval products. Some additional filtering (i.e. rejection of profiles with obvious oscillation as well as those deviating greatly from the norm) for quality control is recommended for the users to better utilize AIRS-V6 CH4, and their implementation in the future versions of the AIRS retrieval algorithm is under consideration.

Analytic Perturbation Method for Estimating Ground Flash Fraction from Satellite Lightning Observations

NASA Technical Reports Server (NTRS)

Koshak, William; Solakiewicz, Richard

2013-01-01

An analytic perturbation method is introduced for estimating the lightning ground flash fraction in a set of N lightning flashes observed by a satellite lightning mapper. The value of N is large, typically in the thousands, and the observations consist of the maximum optical group area produced by each flash. The method is tested using simulated observations that are based on Optical Transient Detector (OTD) and Lightning Imaging Sensor (LIS) data. National Lightning Detection NetworkTM (NLDN) data is used to determine the flash-type (ground or cloud) of the satellite-observed flashes, and provides the ground flash fraction truth for the simulation runs. It is found that the mean ground flash fraction retrieval errors are below 0.04 across the full range 0-1 under certain simulation conditions. In general, it is demonstrated that the retrieval errors depend on many factors (i.e., the number, N, of satellite observations, the magnitude of random and systematic measurement errors, and the number of samples used to form certain climate distributions employed in the model).

Infrared Retrievals of Ice Cloud Properties and Uncertainties with an Optimal Estimation Retrieval Method

NASA Astrophysics Data System (ADS)

Wang, C.; Platnick, S. E.; Meyer, K.; Zhang, Z.

2014-12-01

We developed an optimal estimation (OE)-based method using infrared (IR) observations to retrieve ice cloud optical thickness (COT), cloud effective radius (CER), and cloud top height (CTH) simultaneously. The OE-based retrieval is coupled with a fast IR radiative transfer model (RTM) that simulates observations of different sensors, and corresponding Jacobians in cloudy atmospheres. Ice cloud optical properties are calculated using the MODIS Collection 6 (C6) ice crystal habit (severely roughened hexagonal column aggregates). The OE-based method can be applied to various IR space-borne and airborne sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the enhanced MODIS Airborne Simulator (eMAS), by optimally selecting IR bands with high information content. Four major error sources (i.e., the measurement error, fast RTM error, model input error, and pre-assumed ice crystal habit error) are taken into account in our OE retrieval method. We show that measurement error and fast RTM error have little impact on cloud retrievals, whereas errors from the model input and pre-assumed ice crystal habit significantly increase retrieval uncertainties when the cloud is optically thin. Comparisons between the OE-retrieved ice cloud properties and other operational cloud products (e.g., the MODIS C6 and CALIOP cloud products) are shown.

Cirrus Cloud Retrieval Using Infrared Sounding Data: Multilevel Cloud Errors.

NASA Astrophysics Data System (ADS)

Baum, Bryan A.; Wielicki, Bruce A.

1994-01-01

In this study we perform an error analysis for cloud-top pressure retrieval using the High-Resolution Infrared Radiometric Sounder (HIRS/2) 15-µm CO2 channels for the two-layer case of transmissive cirrus overlying an overcast, opaque stratiform cloud. This analysis includes standard deviation and bias error due to instrument noise and the presence of two cloud layers, the lower of which is opaque. Instantaneous cloud pressure retrieval errors are determined for a range of cloud amounts (0.1 1.0) and cloud-top pressures (850250 mb). Large cloud-top pressure retrieval errors are found to occur when a lower opaque layer is present underneath an upper transmissive cloud layer in the satellite field of view (FOV). Errors tend to increase with decreasing upper-cloud elective cloud amount and with decreasing cloud height (increasing pressure). Errors in retrieved upper-cloud pressure result in corresponding errors in derived effective cloud amount. For the case in which a HIRS FOV has two distinct cloud layers, the difference between the retrieved and actual cloud-top pressure is positive in all casts, meaning that the retrieved upper-cloud height is lower than the actual upper-cloud height. In addition, errors in retrieved cloud pressure are found to depend upon the lapse rate between the low-level cloud top and the surface. We examined which sounder channel combinations would minimize the total errors in derived cirrus cloud height caused by instrument noise and by the presence of a lower-level cloud. We find that while the sounding channels that peak between 700 and 1000 mb minimize random errors, the sounding channels that peak at 300—500 mb minimize bias errors. For a cloud climatology, the bias errors are most critical.

North Alabama Lightning Mapping Array (LMA): VHF Source Retrieval Algorithm and Error Analyses

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Solakiewicz, R. J.; Blakeslee, R. J.; Goodman, S. J.; Christian, H. J.; Hall, J.; Bailey, J.; Krider, E. P.; Bateman, M. G.; Boccippio, D.

2003-01-01

Two approaches are used to characterize how accurately the North Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and in time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA Marshall Space Flight Center (MSFC) and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix Theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50 ns, but all other possible errors (e.g., multiple sources per retrieval attempt) are neglected. The detailed spatial distributions of retrieval errors are provided. Given that the two methods are completely independent of one another, it is shown that they provide remarkably similar results. However, for many source locations, the Curvature Matrix Theory produces larger altitude error estimates than the (more realistic) Monte Carlo simulation.

Error Consistency Analysis Scheme for Infrared Ultraspectral Sounding Retrieval Error Budget Estimation

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, Larry, L.

2013-01-01

Great effort has been devoted towards validating geophysical parameters retrieved from ultraspectral infrared radiances obtained from satellite remote sensors. An error consistency analysis scheme (ECAS), utilizing fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of mean difference and standard deviation of error in both spectral radiance and retrieval domains. The retrieval error is assessed through ECAS without relying on other independent measurements such as radiosonde data. ECAS establishes a link between the accuracies of radiances and retrieved geophysical parameters. ECAS can be applied to measurements from any ultraspectral instrument and any retrieval scheme with its associated RTM. In this manuscript, ECAS is described and demonstrated with measurements from the MetOp-A satellite Infrared Atmospheric Sounding Interferometer (IASI). This scheme can be used together with other validation methodologies to give a more definitive characterization of the error and/or uncertainty of geophysical parameters retrieved from ultraspectral radiances observed from current and future satellite remote sensors such as IASI, the Atmospheric Infrared Sounder (AIRS), and the Cross-track Infrared Sounder (CrIS).

Error Analyses of the North Alabama Lightning Mapping Array (LMA)

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Solokiewicz, R. J.; Blakeslee, R. J.; Goodman, S. J.; Christian, H. J.; Hall, J. M.; Bailey, J. C.; Krider, E. P.; Bateman, M. G.; Boccippio, D. J.

2003-01-01

Two approaches are used to characterize how accurately the North Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and in time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA-MSFC and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50ns, but all other possible errors (e.g., multiple sources per retrieval attempt) are neglected. The detailed spatial distributions of retrieval errors are provided. Given that the two methods are completely independent of one another, it is shown that they provide remarkably similar results, except that the chi-squared theory produces larger altitude error estimates than the (more realistic) Monte Carlo simulation.

On Time/Space Aggregation of Fine-Scale Error Estimates (Invited)

NASA Astrophysics Data System (ADS)

Huffman, G. J.

2013-12-01

Estimating errors inherent in fine time/space-scale satellite precipitation data sets is still an on-going problem and a key area of active research. Complicating features of these data sets include the intrinsic intermittency of the precipitation in space and time and the resulting highly skewed distribution of precipitation rates. Additional issues arise from the subsampling errors that satellites introduce, the errors due to retrieval algorithms, and the correlated error that retrieval and merger algorithms sometimes introduce. Several interesting approaches have been developed recently that appear to make progress on these long-standing issues. At the same time, the monthly averages over 2.5°x2.5° grid boxes in the Global Precipitation Climatology Project (GPCP) Satellite-Gauge (SG) precipitation data set follow a very simple sampling-based error model (Huffman 1997) with coefficients that are set using coincident surface and GPCP SG data. This presentation outlines the unsolved problem of how to aggregate the fine-scale errors (discussed above) to an arbitrary time/space averaging volume for practical use in applications, reducing in the limit to simple Gaussian expressions at the monthly 2.5°x2.5° scale. Scatter diagrams with different time/space averaging show that the relationship between the satellite and validation data improves due to the reduction in random error. One of the key, and highly non-linear, issues is that fine-scale estimates tend to have large numbers of cases with points near the axes on the scatter diagram (one of the values is exactly or nearly zero, while the other value is higher). Averaging 'pulls' the points away from the axes and towards the 1:1 line, which usually happens for higher precipitation rates before lower rates. Given this qualitative observation of how aggregation affects error, we observe that existing aggregation rules, such as the Steiner et al. (2003) power law, only depend on the aggregated precipitation rate. Is this sufficient, or is it necessary to aggregate the precipitation error estimates across the time/space data cube used for averaging? At least for small time/space data cubes it would seem that the detailed variables that affect each precipitation error estimate in the aggregation, such as sensor type, land/ocean surface type, convective/stratiform type, and so on, drive variations that must be accounted for explicitly.

A weighted least squares approach to retrieve aerosol layer height over bright surfaces applied to GOME-2 measurements of the oxygen A band for forest fire cases over Europe

NASA Astrophysics Data System (ADS)

Nanda, Swadhin; Pepijn Veefkind, J.; de Graaf, Martin; Sneep, Maarten; Stammes, Piet; de Haan, Johan F.; Sanders, Abram F. J.; Apituley, Arnoud; Tuinder, Olaf; Levelt, Pieternel F.

2018-06-01

This paper presents a weighted least squares approach to retrieve aerosol layer height from top-of-atmosphere reflectance measurements in the oxygen A band (758-770 nm) over bright surfaces. A property of the measurement error covariance matrix is discussed, due to which photons travelling from the surface are given a higher preference over photons that scatter back from the aerosol layer. This is a potential source of biases in the estimation of aerosol properties over land, which can be mitigated by revisiting the design of the measurement error covariance matrix. The alternative proposed in this paper, which we call the dynamic scaling method, introduces a scene-dependent and wavelength-dependent modification in the measurement signal-to-noise ratio in order to influence this matrix. This method is generally applicable to other retrieval algorithms using weighted least squares. To test this method, synthetic experiments are done in addition to application to GOME-2A and GOME-2B measurements of the oxygen A band over the August 2010 Russian wildfires and the October 2017 Portugal wildfire plume over western Europe.

Updated MISR Dark Water Research Aerosol Retrieval Algorithm - Part 1: Coupled 1.1 km Ocean Surface Chlorophyll a Retrievals with Empirical Calibration Corrections

NASA Technical Reports Server (NTRS)

Limbacher, James A.; Kahn, Ralph A.

2017-01-01

As aerosol amount and type are key factors in the 'atmospheric correction' required for remote-sensing chlorophyll alpha concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chl(sub in situ) less than 1.5 mg m(exp -3), the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov- Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p greater than 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl less than 1.5 mg m(exp -3), MISR and MODIS show very good agreement: r = 0.96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

Updated MISR dark water research aerosol retrieval algorithm - Part 1: Coupled 1.1 km ocean surface chlorophyll a retrievals with empirical calibration corrections

NASA Astrophysics Data System (ADS)

Limbacher, James A.; Kahn, Ralph A.

2017-04-01

As aerosol amount and type are key factors in the atmospheric correction required for remote-sensing chlorophyll a concentration (Chl) retrievals, the Multi-angle Imaging SpectroRadiometer (MISR) can contribute to ocean color analysis despite a lack of spectral channels optimized for this application. Conversely, an improved ocean surface constraint should also improve MISR aerosol-type products, especially spectral single-scattering albedo (SSA) retrievals. We introduce a coupled, self-consistent retrieval of Chl together with aerosol over dark water. There are time-varying MISR radiometric calibration errors that significantly affect key spectral reflectance ratios used in the retrievals. Therefore, we also develop and apply new calibration corrections to the MISR top-of-atmosphere (TOA) reflectance data, based on comparisons with coincident MODIS (Moderate Resolution Imaging Spectroradiometer) observations and trend analysis of the MISR TOA bidirectional reflectance factors (BRFs) over three pseudo-invariant desert sites. We run the MISR research retrieval algorithm (RA) with the corrected MISR reflectances to generate MISR-retrieved Chl and compare the MISR Chl values to a set of 49 coincident SeaBASS (SeaWiFS Bio-optical Archive and Storage System) in situ observations. Where Chlin situ < 1.5 mg m-3, the results from our Chl model are expected to be of highest quality, due to algorithmic assumption validity. Comparing MISR RA Chl to the 49 coincident SeaBASS observations, we report a correlation coefficient (r) of 0.86, a root-mean-square error (RMSE) of 0.25, and a median absolute error (MAE) of 0.10. Statistically, a two-sample Kolmogorov-Smirnov test indicates that it is not possible to distinguish between MISR Chl and available SeaBASS in situ Chl values (p > 0.1). We also compare MODIS-Terra and MISR RA Chl statistically, over much broader regions. With about 1.5 million MISR-MODIS collocations having MODIS Chl < 1.5 mg m-3, MISR and MODIS show very good agreement: r = 0. 96, MAE = 0.09, and RMSE = 0.15. The new dark water aerosol/Chl RA can retrieve Chl in low-Chl, case I waters, independent of other imagers such as MODIS, via a largely physical algorithm, compared to the commonly applied statistical ones. At a minimum, MISR's multi-angle data should help reduce uncertainties in the MODIS-Terra ocean color retrieval where coincident measurements are made, while also allowing for a more robust retrieval of particle properties such as spectral single-scattering albedo.

The Quality Control of Data in a Clinical Database System—The Patient Identification Problem *

PubMed Central

Lai, J. Chi-Sang; Covvey, H.D.; Sevcik, K.C.; Wigle, E.D.

1981-01-01

Ensuring the accuracy of patient identification and the linkage of records with the appropriate patient owner is the first level of quality control of data in a clinical database system. Without a unique patient identifier, the fact that patient identity may be recorded at different places and times means that multiple identities may be associated with a given patient and new records associated with any of these identities. Even when a unique patient identifier is utilized, errors introduced in the data handling process can result in the same problems. The outcome is that the retrieval request for a given record may fail, or an erroneously identified record may be retrieved. We have studied each of the ways this fundamental problem occurs and propose a solution based on record linkage techniques to detect errors of this type. Specifically, we propose a patient identification scheme for the situation where no unique health identifier is available and detail a method to find patient records with erroneous identifiers.

Retrieval of the thickness of undeformed sea ice from C-band compact polarimetric SAR images

NASA Astrophysics Data System (ADS)

Zhang, X.; Dierking, W.; Zhang, J.; Meng, J. M.; Lang, H. T.

2015-10-01

In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric SAR images. The parameter is denoted as "CP-Ratio". In model simulations we investigated the sensitivity of CP-Ratio to the dielectric constant, thickness, surface roughness, and incidence angle. From the results of the simulations we deduced optimal conditions for the thickness retrieval. On the basis of C-band CTLR SAR data, which were generated from Radarsat-2 quad-polarization images acquired jointly with helicopter-borne sea ice thickness measurements in the region of the Sea of Labrador, we tested empirical equations for thickness retrieval. An exponential fit between CP-Ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region we found a root mean square (rms) error of 8 cm and a maximum correlation coefficient of 0.92 for the retrieval procedure when applying it on level ice of 0.9 m mean thickness.

a New Algorithm for the Aod Inversion from Noaa/avhrr Data

NASA Astrophysics Data System (ADS)

Sun, L.; Li, R.; Yu, H.

2018-04-01

The advanced very high resolution radiometer (AVHRR) data from the National Oceanic and Atmospheric Administration satellite is one of the earliest data applied in aerosol research. The dense dark vegetation (DDV) algorithm is a popular method for the present land aerosol retrieval. One of the most crucial steps in the DDV algorithm with AVHRR data is estimating the land surface reflectance (LSR). However, LSR cannot be easily estimated because of the lack of a 2.13 μm band. In this article, the moderate resolution imaging spectroradiometer (MODIS) vegetation index product (MYD13) is introduced to support the estimation of AVHRR LSR. The relationship between MODIS NDVI and the AVHRR LSR of the visible band is analysed to retrieve aerosol optical depth (AOD) from AVHRR data. Retrieval experiments are carried out in mid-eastern America. The AOD data from AErosol RObotic NETwork (AERONET) measurements are used to evaluate the aerosol retrieval from AVHRR data, the results indicate that about 74 % of the retrieved AOD are within the expected error range of ±(0.05 + 0.2), and a cross comparison of the AOD retrieval results with the MODIS aerosol product (MYD04) shows that the AOD datasets have a similar spatial distribution.

Lightning Radio Source Retrieval Using Advanced Lightning Direction Finder (ALDF) Networks

NASA Technical Reports Server (NTRS)

Koshak, William J.; Blakeslee, Richard J.; Bailey, J. C.

1998-01-01

A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from an Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing and arrival time of lightning radio emissions. Solutions for the plane (i.e., no Earth curvature) are provided that implement all of tile measurements mentioned above. Tests of the retrieval method are provided using computer-simulated data sets. We also introduce a quadratic planar solution that is useful when only three arrival time measurements are available. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in source location. Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. In the absence of measurement errors, quadratic root degeneracy (no source location ambiguity) is shown to exist exactly on the outer sensor baselines for arbitrary non-collinear network geometries. The accuracy of the quadratic planar method is tested with computer generated data sets. The results are generally better than those obtained from the three station linear planar method when bearing errors are about 2 deg. We also note some of the advantages and disadvantages of these methods over the nonlinear method of chi(sup 2) minimization employed by the National Lightning Detection Network (NLDN) and discussed in Cummins et al.(1993, 1995, 1998).

Data Retrieval Algorithms for Validating the Optical Transient Detector and the Lightning Imaging Sensor

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Blakeslee, R. J.; Bailey, J. C.

2000-01-01

A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from an Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing, and arrival time of lightning radio emissions. Solutions for the plane (i.e., no earth curvature) are provided that implement all of these measurements. The accuracy of the retrieval method is tested using computer-simulated datasets, and the relative influence of bearing and arrival time data an the outcome of the final solution is formally demonstrated. The algorithm is sufficiently accurate to validate NASA:s Optical Transient Detector and Lightning Imaging Sensor. A quadratic planar solution that is useful when only three arrival time measurements are available is also introduced. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in sc)iirce location, Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. For arbitrary noncollinear network geometries and in the absence of measurement errors, it is shown that the two quadratic roots are equivalent (no source location ambiguity) on the outer sensor baselines. The accuracy of the quadratic planar method is tested with computer-generated datasets, and the results are generally better than those obtained from the three-station linear planar method when bearing errors are about 2 deg.

System and method for phase retrieval for radio telescope and antenna control

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2013-01-01

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for radio phase retrieval. A system practicing the method gathers first data from radio waves associated with an object observed via a first aperture, gathers second data from radio waves associated with the object observed via an introduced second aperture associated with the first aperture, generates reduced noise data by incoherently subtracting the second data from the first data, and performs phase retrieval for the radio waves by modeling the reduced noise data using a single Fourier transform. The first and second apertures are at different positions, such as side by side. This approach can include determining a value Q which represents a ratio of wavelength times a focal ratio divided by pixel spacing. This information can be used to accurately measure and correct alignment errors or other optical system flaws in the apertures.

Modified retrieval algorithm for three types of precipitation distribution using x-band synthetic aperture radar

NASA Astrophysics Data System (ADS)

Xie, Yanan; Zhou, Mingliang; Pan, Dengke

2017-10-01

The forward-scattering model is introduced to describe the response of normalized radar cross section (NRCS) of precipitation with synthetic aperture radar (SAR). Since the distribution of near-surface rainfall is related to the rate of near-surface rainfall and horizontal distribution factor, a retrieval algorithm called modified regression empirical and model-oriented statistical (M-M) based on the volterra integration theory is proposed. Compared with the model-oriented statistical and volterra integration (MOSVI) algorithm, the biggest difference is that the M-M algorithm is based on the modified regression empirical algorithm rather than the linear regression formula to retrieve the value of near-surface rainfall rate. Half of the empirical parameters are reduced in the weighted integral work and a smaller average relative error is received while the rainfall rate is less than 100 mm/h. Therefore, the algorithm proposed in this paper can obtain high-precision rainfall information.

An operational retrieval algorithm for determining aerosol optical properties in the ultraviolet

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; L'Ecuyer, Tristan S.; Slusser, James R.; Stephens, Graeme L.; Goering, Christian D.

2008-02-01

This paper describes a number of practical considerations concerning the optimization and operational implementation of an algorithm used to characterize the optical properties of aerosols across part of the ultraviolet (UV) spectrum. The algorithm estimates values of aerosol optical depth (AOD) and aerosol single scattering albedo (SSA) at seven wavelengths in the UV, as well as total column ozone (TOC) and wavelength-independent asymmetry factor (g) using direct and diffuse irradiances measured with a UV multifilter rotating shadowband radiometer (UV-MFRSR). A novel method for cloud screening the irradiance data set is introduced, as well as several improvements and optimizations to the retrieval scheme which yield a more realistic physical model for the inversion and increase the efficiency of the algorithm. Introduction of a wavelength-dependent retrieval error budget generated from rigorous forward model analysis as well as broadened covariances on the a priori values of AOD, SSA and g and tightened covariances of TOC allows sufficient retrieval sensitivity and resolution to obtain unique solutions of aerosol optical properties as demonstrated by synthetic retrievals. Analysis of a cloud screened data set (May 2003) from Panther Junction, Texas, demonstrates that the algorithm produces realistic values of the optical properties that compare favorably with pseudo-independent methods for AOD, TOC and calculated Ångstrom exponents. Retrieval errors of all parameters (except TOC) are shown to be negatively correlated to AOD, while the Shannon information content is positively correlated, indicating that retrieval skill improves with increasing atmospheric turbidity. When implemented operationally on more than thirty instruments in the Ultraviolet Monitoring and Research Program's (UVMRP) network, this retrieval algorithm will provide a comprehensive and internally consistent climatology of ground-based aerosol properties in the UV spectral range that can be used for both validation of satellite measurements as well as regional aerosol and ultraviolet transmission studies.

A neural network for real-time retrievals of PWV and LWP from Arctic millimeter-wave ground-based observations.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cadeddu, M. P.; Turner, D. D.; Liljegren, J. C.

2009-07-01

This paper presents a new neural network (NN) algorithm for real-time retrievals of low amounts of precipitable water vapor (PWV) and integrated liquid water from millimeter-wave ground-based observations. Measurements are collected by the 183.3-GHz G-band vapor radiometer (GVR) operating at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility, Barrow, AK. The NN provides the means to explore the nonlinear regime of the measurements and investigate the physical boundaries of the operability of the instrument. A methodology to compute individual error bars associated with the NN output is developed, and a detailed error analysis of the network output is provided.more » Through the error analysis, it is possible to isolate several components contributing to the overall retrieval errors and to analyze the dependence of the errors on the inputs. The network outputs and associated errors are then compared with results from a physical retrieval and with the ARM two-channel microwave radiometer (MWR) statistical retrieval. When the NN is trained with a seasonal training data set, the retrievals of water vapor yield results that are comparable to those obtained from a traditional physical retrieval, with a retrieval error percentage of {approx}5% when the PWV is between 2 and 10 mm, but with the advantages that the NN algorithm does not require vertical profiles of temperature and humidity as input and is significantly faster computationally. Liquid water path (LWP) retrievals from the NN have a significantly improved clear-sky bias (mean of {approx}2.4 g/m{sup 2}) and a retrieval error varying from 1 to about 10 g/m{sup 2} when the PWV amount is between 1 and 10 mm. As an independent validation of the LWP retrieval, the longwave downwelling surface flux was computed and compared with observations. The comparison shows a significant improvement with respect to the MWR statistical retrievals, particularly for LWP amounts of less than 60 g/m{sup 2}.« less

Description and Sensitivity Analysis of the SOLSE/LORE-2 and SAGE III Limb Scattering Ozone Retrieval Algorithms

NASA Technical Reports Server (NTRS)

Loughman, R.; Flittner, D.; Herman, B.; Bhartia, P.; Hilsenrath, E.; McPeters, R.; Rault, D.

2002-01-01

The SOLSE (Shuttle Ozone Limb Sounding Experiment) and LORE (Limb Ozone Retrieval Experiment) instruments are scheduled for reflight on Space Shuttle flight STS-107 in July 2002. In addition, the SAGE III (Stratospheric Aerosol and Gas Experiment) instrument will begin to make limb scattering measurements during Spring 2002. The optimal estimation technique is used to analyze visible and ultraviolet limb scattered radiances and produce a retrieved ozone profile. The algorithm used to analyze data from the initial flight of the SOLSE/LORE instruments (on Space Shuttle flight STS-87 in November 1997) forms the basis of the current algorithms, with expansion to take advantage of the increased multispectral information provided by SOLSE/LORE-2 and SAGE III. We also present detailed sensitivity analysis for these ozone retrieval algorithms. The primary source of ozone retrieval error is tangent height misregistration (i.e., instrument pointing error), which is relevant throughout the altitude range of interest, and can produce retrieval errors on the order of 10-20 percent due to a tangent height registration error of 0.5 km at the tangent point. Other significant sources of error are sensitivity to stratospheric aerosol and sensitivity to error in the a priori ozone estimate (given assumed instrument signal-to-noise = 200). These can produce errors up to 10 percent for the ozone retrieval at altitudes less than 20 km, but produce little error above that level.

Preparations for Global Precipitation Measurement(GPM)Ground Validation

NASA Technical Reports Server (NTRS)

Bidwell, S. W.; Bibyk, I. K.; Duming, J. F.; Everett, D. F.; Smith, E. A.; Wolff, D. B.

2004-01-01

The Global Precipitation Measurement (GPM) program is an international partnership led by the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA). GPM will improve climate, weather, and hydro-meterorological forecasts through more frequent and more accurate measurement of precipitation across the globe. This paper describes the concept and the preparations for Ground Validation within the GPM program. Ground Validation (GV) plays a critical role in the program by investigating and quantitatively assessing the errors within the satellite retrievals. These quantitative estimates of retrieval errors will assist the scientific community by bounding the errors within their research products. The two fundamental requirements of the GPM Ground Validation program are: (1) error characterization of the precipitation retrievals and (2) continual improvement of the satellite retrieval algorithms. These two driving requirements determine the measurements, instrumentation, and location for ground observations. This paper describes GV plans for estimating the systematic and random components of retrieval error and for characterizing the spatial and temporal structure of the error. This paper describes the GPM program for algorithm improvement in which error models are developed and experimentally explored to uncover the physical causes of errors within the retrievals. GPM will ensure that information gained through Ground Validation is applied to future improvements in the spaceborne retrieval algorithms. This paper discusses the potential locations for validation measurement and research, the anticipated contributions of GPM's international partners, and the interaction of Ground Validation with other GPM program elements.

Mathematical Inversion of Lightning Data: Techniques and Applications

NASA Technical Reports Server (NTRS)

Koshak, William

2003-01-01

A survey of some interesting mathematical inversion studies dealing with radio, optical, and electrostatic measurements of lightning are presented. A discussion of why NASA is interested in lightning, what specific physical properties of lightning are retrieved, and what mathematical techniques are used to perform the retrievals are discussed. In particular, a relatively new multi-station VHF time-of-arrival (TOA) antenna network is now on-line in Northern Alabama and will be discussed. The network, called the Lightning Mapping Array (LMA), employs GPS timing and detects VHF radiation from discrete segments (effectively point emitters) that comprise the channel of lightning strokes within cloud and ground flashes. The LMA supports on-going ground-validation activities of the low Earth orbiting Lightning Imaging Sensor (LIS) satellite developed at NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama. The LMA also provides detailed studies of the distribution and evolution of thunderstorms and lightning in the Tennessee Valley, and offers interesting comparisons with other meteorological/geophysical datasets. In order to take full advantage of these benefits, it is essential that the LMA channel mapping accuracy (in both space and time) be fully characterized and optimized. A new channel mapping retrieval algorithm is introduced for this purpose. To characterize the spatial distribution of retrieval errors, the algorithm has been applied to analyze literally tens of millions of computer-simulated lightning VHF point sources that have been placed at various ranges, azimuths, and altitudes relative to the LMA network. Statistical results are conveniently summarized in high-resolution, color-coded, error maps.

Error analysis applied to several inversion techniques used for the retrieval of middle atmospheric constituents from limb-scanning MM-wave spectroscopic measurements

NASA Technical Reports Server (NTRS)

Puliafito, E.; Bevilacqua, R.; Olivero, J.; Degenhardt, W.

1992-01-01

The formal retrieval error analysis of Rodgers (1990) allows the quantitative determination of such retrieval properties as measurement error sensitivity, resolution, and inversion bias. This technique was applied to five numerical inversion techniques and two nonlinear iterative techniques used for the retrieval of middle atmospheric constituent concentrations from limb-scanning millimeter-wave spectroscopic measurements. It is found that the iterative methods have better vertical resolution, but are slightly more sensitive to measurement error than constrained matrix methods. The iterative methods converge to the exact solution, whereas two of the matrix methods under consideration have an explicit constraint, the sensitivity of the solution to the a priori profile. Tradeoffs of these retrieval characteristics are presented.

Errorless Learning in Cognitive Rehabilitation: A Critical Review

PubMed Central

Middleton, Erica L.; Schwartz, Myrna F.

2012-01-01

Cognitive rehabilitation research is increasingly exploring errorless learning interventions, which prioritize the avoidance of errors during treatment. The errorless learning approach was originally developed for patients with severe anterograde amnesia, who were deemed to be at particular risk for error learning. Errorless learning has since been investigated in other memory-impaired populations (e.g., Alzheimer's disease) and acquired aphasia. In typical errorless training, target information is presented to the participant for study or immediate reproduction, a method that prevents participants from attempting to retrieve target information from long-term memory (i.e., retrieval practice). However, assuring error elimination by preventing difficult (and error-permitting) retrieval practice is a potential major drawback of the errorless approach. This review begins with discussion of research in the psychology of learning and memory that demonstrates the importance of difficult (and potentially errorful) retrieval practice for robust learning and prolonged performance gains. We then review treatment research comparing errorless and errorful methods in amnesia and aphasia, where only the latter provides (difficult) retrieval practice opportunities. In each clinical domain we find the advantage of the errorless approach is limited and may be offset by the therapeutic potential of retrieval practice. Gaps in current knowledge are identified that preclude strong conclusions regarding a preference for errorless treatments over methods that prioritize difficult retrieval practice. We offer recommendations for future research aimed at a strong test of errorless learning treatments, which involves direct comparison with methods where retrieval practice effects are maximized for long-term gains. PMID:22247957

Retrieval of the thickness of undeformed sea ice from simulated C-band compact polarimetric SAR images

NASA Astrophysics Data System (ADS)

Zhang, Xi; Dierking, Wolfgang; Zhang, Jie; Meng, Junmin; Lang, Haitao

2016-07-01

In this paper we introduce a parameter for the retrieval of the thickness of undeformed first-year sea ice that is specifically adapted to compact polarimetric (CP) synthetic aperture radar (SAR) images. The parameter is denoted as the "CP ratio". In model simulations we investigated the sensitivity of the CP ratio to the dielectric constant, ice thickness, ice surface roughness, and radar incidence angle. From the results of the simulations we deduced optimal sea ice conditions and radar incidence angles for the ice thickness retrieval. C-band SAR data acquired over the Labrador Sea in circular transmit and linear receive (CTLR) mode were generated from RADARSAT-2 quad-polarization images. In comparison with results from helicopter-borne measurements, we tested different empirical equations for the retrieval of ice thickness. An exponential fit between the CP ratio and ice thickness provides the most reliable results. Based on a validation using other compact polarimetric SAR images from the same region, we found a root mean square (rms) error of 8 cm and a maximum correlation coefficient of 0.94 for the retrieval procedure when applying it to level ice between 0.1 and 0.8 m thick.

Accuracy of maximum likelihood and least-squares estimates in the lidar slope method with noisy data.

PubMed

Eberhard, Wynn L

2017-04-01

The maximum likelihood estimator (MLE) is derived for retrieving the extinction coefficient and zero-range intercept in the lidar slope method in the presence of random and independent Gaussian noise. Least-squares fitting, weighted by the inverse of the noise variance, is equivalent to the MLE. Monte Carlo simulations demonstrate that two traditional least-squares fitting schemes, which use different weights, are less accurate. Alternative fitting schemes that have some positive attributes are introduced and evaluated. The principal factors governing accuracy of all these schemes are elucidated. Applying these schemes to data with Poisson rather than Gaussian noise alters accuracy little, even when the signal-to-noise ratio is low. Methods to estimate optimum weighting factors in actual data are presented. Even when the weighting estimates are coarse, retrieval accuracy declines only modestly. Mathematical tools are described for predicting retrieval accuracy. Least-squares fitting with inverse variance weighting has optimum accuracy for retrieval of parameters from single-wavelength lidar measurements when noise, errors, and uncertainties are Gaussian distributed, or close to optimum when only approximately Gaussian.

Retrieving accurate temporal and spatial information about Taylor slug flows from non-invasive NIR photometry measurements

NASA Astrophysics Data System (ADS)

Helmers, Thorben; Thöming, Jorg; Mießner, Ulrich

2017-11-01

In this article, we introduce a novel approach to retrieve spatial- and time-resolved Taylor slug flow information from a single non-invasive photometric flow sensor. The presented approach uses disperse phase surface properties to retrieve the instantaneous velocity information from a single sensor's time-scaled signal. For this purpose, a photometric sensor system is simulated using a ray-tracing algorithm to calculate spatially resolved near-infrared transmission signals. At the signal position corresponding to the rear droplet cap, a correlation factor of the droplet's geometric properties is retrieved and used to extract the instantaneous droplet velocity from the real sensor's temporal transmission signal. Furthermore, a correlation for the rear cap geometry based on the a priori known total superficial flow velocity is developed, because the cap curvature is velocity sensitive itself. Our model for velocity derivation is validated, and measurements of a first prototype showcase the capability of the device. Long-term measurements visualize systematic fluctuations in droplet lengths, velocities, and frequencies that could otherwise, without the observation on a larger timescale, have been identified as measurement errors and not systematic phenomenas.

Global Precipitation Measurement (GPM) Ground Validation: Plans and Preparations

NASA Technical Reports Server (NTRS)

Schwaller, M.; Bidwell, S.; Durning, F. J.; Smith, E.

2004-01-01

The Global Precipitation Measurement (GPM) program is an international partnership led by the National Aeronautics and Space Administration (NASA) and the Japan Aerospace Exploration Agency (JAXA). GPM will improve climate, weather, and hydro-meteorological forecasts through more frequent and more accurate measurement of precipitation across the globe. This paper describes the concept, the planning, and the preparations for Ground Validation within the GPM program. Ground Validation (GV) plays an important role in the program by investigating and quantitatively assessing the errors within the satellite retrievals. These quantitative estimates of retrieval errors will assist the scientific community by bounding the errors within their research products. The two fundamental requirements of the GPM Ground Validation program are: (1) error characterization of the precipitation retrievals and (2) continual improvement of the satellite retrieval algorithms. These two driving requirements determine the measurements, instrumentation, and location for ground observations. This paper outlines GV plans for estimating the systematic and random components of retrieval error and for characterizing the spatial p d temporal structure of the error and plans for algorithm improvement in which error models are developed and experimentally explored to uncover the physical causes of errors within the retrievals. This paper discusses NASA locations for GV measurements as well as anticipated locations from international GPM partners. NASA's primary locations for validation measurements are an oceanic site at Kwajalein Atoll in the Republic of the Marshall Islands and a continental site in north-central Oklahoma at the U.S. Department of Energy's Atmospheric Radiation Measurement Program site.

ALDF Data Retrieval Algorithms for Validating the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS)

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Blakeslee, R. J.; Bailey, J. C.

1997-01-01

A linear algebraic solution is provided for the problem of retrieving the location and time of occurrence of lightning ground strikes from in Advanced Lightning Direction Finder (ALDF) network. The ALDF network measures field strength, magnetic bearing, and arrival time of lightning radio emissions and solutions for the plane (i.e.. no Earth curvature) are provided that implement all of these measurements. The accuracy of the retrieval method is tested using computer-simulated data sets and the relative influence of bearing and arrival time data on the outcome of the final solution is formally demonstrated. The algorithm is sufficiently accurate to validate NASA's Optical Transient Detector (OTD) and Lightning Imaging System (LIS). We also introduce a quadratic planar solution that is useful when only three arrival time measurements are available. The algebra of the quadratic root results are examined in detail to clarify what portions of the analysis region lead to fundamental ambiguities in source location. Complex root results are shown to be associated with the presence of measurement errors when the lightning source lies near an outer sensor baseline of the ALDF network. For arbitrary noncollinear network geometries and in the absence of measurement errors, it is shown that the two quadratic roots are equivalent (no source location ambiguity) on the outer sensor baselines. The accuracy of the quadratic planar method is tested with computer-generated data sets and the results are generally better than those obtained from the three station linear planar method when bearing errors are about 2 degrees.

Ozone Profile Retrievals from the OMPS on Suomi NPP

NASA Astrophysics Data System (ADS)

Bak, J.; Liu, X.; Kim, J. H.; Haffner, D. P.; Chance, K.; Yang, K.; Sun, K.; Gonzalez Abad, G.

2017-12-01

We verify and correct the Ozone Mapping and Profiler Suite (OMPS) Nadir Mapper (NM) L1B v2.0 data with the aim of producing accurate ozone profile retrievals using an optimal estimation based inversion method in the 302.5-340 nm fitting. The evaluation of available slit functions demonstrates that preflight-measured slit functions well represent OMPS measurements compared to derived Gaussian slit functions. Our OMPS fitting residuals contain significant wavelength and cross-track dependent biases, and thereby serious cross-track striping errors are found in preliminary retrievals, especially in the troposphere. To eliminate the systematic component of the fitting residuals, we apply "soft calibration" to OMPS radiances. With the soft calibration the amplitude of fitting residuals decreases from 1 % to 0.2 % over low/mid latitudes, and thereby the consistency of tropospheric ozone retrievals between OMPS and Ozone Monitoring Instrument (OMI) are substantially improved. A common mode correction is implemented for additional radiometric calibration, which improves retrievals especially at high latitudes where the amplitude of fitting residuals decreases by a factor of 2. We estimate the floor noise error of OMPS measurements from standard deviations of the fitting residuals. The derived error in the Huggins band ( 0.1 %) is 2 times smaller than OMI floor noise error and 2 times larger than OMPS L1B measurement error. The OMPS floor noise errors better constrain our retrievals for maximizing measurement information and stabilizing our fitting residuals. The final precision of the fitting residuals is less than 0.1 % in the low/mid latitude, with 1 degrees of freedom for signal for the tropospheric ozone, so that we meet the general requirements for successful tropospheric ozone retrievals. To assess if the quality of OMPS ozone retrievals could be acceptable for scientific use, we will characterize OMPS ozone profile retrievals, present error analysis, and validate retrievals using a reference dataset. The useful information on the vertical distribution of ozone is limited below 40 km only from OMPS NM measurements due to the absence of Hartley ozone wavelength. This shortcoming will be improved with the joint ozone profile retrieval using Nadir Profiler (NP) measurements covering the 250 to 310 nm range.

Propagation of erroneous data for the modulus of elasticity of periodontal ligament and gutta percha in FEM/FEA papers: a story of broken links.

PubMed

Ruse, N Dorin

2008-12-01

This brief review essay was triggered by the discovery of two errors that have been perpetuated in the dental literature for the last quarter century and is intended to alert the research community. An extensive search of the published literature, using PubMed and Web of Science search engines, electronic journal resources, and several trips to the library for manual retrievals of articles were used to retrieve hundreds of articles reporting on finite element modeling - finite element analysis (FEM/FEA) involving periodontal ligament (PDL) and gutta percha (GP). The literature search revealed that erroneous values for the modulus of elasticity of PDL and GP were introduced in 1980 and in 1983, respectively. The identified errors range between two to three orders of magnitude and have been used in hundreds of FEM/FEA papers. The finding casts serious doubts regarding the validity of the results published in hundreds of papers and highlights the importance of checking the references cited and citing, or at least confirming, primary sources rather than citing citations.

The Bidirectional Reflectance Distribution Function (BRDF) of the Ocean: Effects of Wave Representation

NASA Astrophysics Data System (ADS)

Eide, H.; Stamnes, K.; Ottaviani, M.

2004-12-01

The specular reflection of the Sun off the ocean, or sun glint, is of major concern for ocean remote sensing. Typically, data from in and around the sunglint region are discarded because of the unknown contribution to the measured radiances or because of sensor saturation. On the other hand, accurate knowledge of the sunglint properties enables retrievals of atmospheric parameters. The challenge of the ocean retrieval problem is to get the ``water leaving radiance'', Lw, by subtracting the Rayleigh scattering, aerosol scattering, water vapor, ozone, and sun glint from the measured radiances at the top of the atmosphere (TOA). Thus, the task is to correct for both the atmospheric contribution and for surface effects. Two simplifying assumptions that are frequently employed in ocean remote sensing are that the ocean BRDF is isotropic and that one can de-couple the radiative properties of the atmosphere from those of the surface. Our previous studies have shown that neglecting the inherit coupling between the atmosphere and surface can lead to large errors in the retrievals. In order to do retrievals over bright, as well as darker surfaces, it is necessary to account for this coupling between the surface and the atmosphere. In the present study we use models for the reflection of light off the ocean surface to calculate the ocean BRDF. The differences between the various models are investigated as is the effect of using different types of wave statistics (e.g. Cox Munk). We present results from calculations where we vary the wind speed and direction as well as other parameters affecting the ocean surface. The error introduced in ocean retrievals by assuming an isotropic BRDF is assessed, and methods for improved treatment of sunglint are suggested.

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

NASA Astrophysics Data System (ADS)

Tang, Wenjun; Qin, Jun; Yang, Kun; Liu, Shaomin; Lu, Ning; Niu, Xiaolei

2016-03-01

Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m-2 (or 19.1 %) and 22.1 W m-2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

NASA Astrophysics Data System (ADS)

Tang, W.; Qin, J.; Yang, K.; Liu, S.; Lu, N.; Niu, X.

2015-12-01

Cloud parameters (cloud mask, effective particle radius and liquid/ice water path) are the important inputs in determining surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy but their temporal resolution is too low to obtain high temporal resolution SSR retrievals. In order to obtain hourly cloud parameters, the Artificial Neural Network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multi-functional Transport Satellite (MTSAT) geostationary satellite signals. Meanwhile, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m-2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone and so on) are input to the model, we can derive SSR at high spatio-temporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River Basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m-2 (or 3.5 %) and 98.5 W m-2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m-2 (5.4 %); the RMSEs in daily and monthly-mean SSR estimates are 34.2 W m-2 (19.1 %) and 22.1 W m-2 (12.3 %), respectively. The accuracy is comparable or even higher than other two radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

An optimal-estimation-based aerosol retrieval algorithm using OMI near-UV observations

NASA Astrophysics Data System (ADS)

Jeong, U.; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.

2016-01-01

An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional look-up tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OE-based estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.

An Optimal-Estimation-Based Aerosol Retrieval Algorithm Using OMI Near-UV Observations

NASA Technical Reports Server (NTRS)

Jeong, U; Kim, J.; Ahn, C.; Torres, O.; Liu, X.; Bhartia, P. K.; Spurr, R. J. D.; Haffner, D.; Chance, K.; Holben, B. N.

2016-01-01

An optimal-estimation(OE)-based aerosol retrieval algorithm using the OMI (Ozone Monitoring Instrument) near-ultraviolet observation was developed in this study. The OE-based algorithm has the merit of providing useful estimates of errors simultaneously with the inversion products. Furthermore, instead of using the traditional lookup tables for inversion, it performs online radiative transfer calculations with the VLIDORT (linearized pseudo-spherical vector discrete ordinate radiative transfer code) to eliminate interpolation errors and improve stability. The measurements and inversion products of the Distributed Regional Aerosol Gridded Observation Network campaign in northeast Asia (DRAGON NE-Asia 2012) were used to validate the retrieved aerosol optical thickness (AOT) and single scattering albedo (SSA). The retrieved AOT and SSA at 388 nm have a correlation with the Aerosol Robotic Network (AERONET) products that is comparable to or better than the correlation with the operational product during the campaign. The OEbased estimated error represented the variance of actual biases of AOT at 388 nm between the retrieval and AERONET measurements better than the operational error estimates. The forward model parameter errors were analyzed separately for both AOT and SSA retrievals. The surface reflectance at 388 nm, the imaginary part of the refractive index at 354 nm, and the number fine-mode fraction (FMF) were found to be the most important parameters affecting the retrieval accuracy of AOT, while FMF was the most important parameter for the SSA retrieval. The additional information provided with the retrievals, including the estimated error and degrees of freedom, is expected to be valuable for relevant studies. Detailed advantages of using the OE method were described and discussed in this paper.

Ultraspectral sounding retrieval error budget and estimation

NASA Astrophysics Data System (ADS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, Larrabee L.; Yang, Ping

2011-11-01

The ultraspectral infrared radiances obtained from satellite observations provide atmospheric, surface, and/or cloud information. The intent of the measurement of the thermodynamic state is the initialization of weather and climate models. Great effort has been given to retrieving and validating these atmospheric, surface, and/or cloud properties. Error Consistency Analysis Scheme (ECAS), through fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of absolute and standard deviation of differences in both spectral radiance and retrieved geophysical parameter domains. The retrieval error is assessed through ECAS without assistance of other independent measurements such as radiosonde data. ECAS re-evaluates instrument random noise, and establishes the link between radiometric accuracy and retrieved geophysical parameter accuracy. ECAS can be applied to measurements of any ultraspectral instrument and any retrieval scheme with associated RTM. In this paper, ECAS is described and demonstration is made with the measurements of the METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI).

Ultraspectral Sounding Retrieval Error Budget and Estimation

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, L. Larrabee; Yang, Ping

2011-01-01

The ultraspectral infrared radiances obtained from satellite observations provide atmospheric, surface, and/or cloud information. The intent of the measurement of the thermodynamic state is the initialization of weather and climate models. Great effort has been given to retrieving and validating these atmospheric, surface, and/or cloud properties. Error Consistency Analysis Scheme (ECAS), through fast radiative transfer model (RTM) forward and inverse calculations, has been developed to estimate the error budget in terms of absolute and standard deviation of differences in both spectral radiance and retrieved geophysical parameter domains. The retrieval error is assessed through ECAS without assistance of other independent measurements such as radiosonde data. ECAS re-evaluates instrument random noise, and establishes the link between radiometric accuracy and retrieved geophysical parameter accuracy. ECAS can be applied to measurements of any ultraspectral instrument and any retrieval scheme with associated RTM. In this paper, ECAS is described and demonstration is made with the measurements of the METOP-A satellite Infrared Atmospheric Sounding Interferometer (IASI)..

Simplified Approach Charts Improve Data Retrieval Performance

PubMed Central

Stewart, Michael; Laraway, Sean; Jordan, Kevin; Feary, Michael S.

2016-01-01

The effectiveness of different instrument approach charts to deliver minimum visibility and altitude information during airport equipment outages was investigated. Eighteen pilots flew simulated instrument approaches in three conditions: (a) normal operations using a standard approach chart (standard-normal), (b) equipment outage conditions using a standard approach chart (standard-outage), and (c) equipment outage conditions using a prototype decluttered approach chart (prototype-outage). Errors and retrieval times in identifying minimum altitudes and visibilities were measured. The standard-outage condition produced significantly more errors and longer retrieval times versus the standard-normal condition. The prototype-outage condition had significantly fewer errors and shorter retrieval times than did the standard-outage condition. The prototype-outage condition produced significantly fewer errors but similar retrieval times when compared with the standard-normal condition. Thus, changing the presentation of minima may reduce risk and increase safety in instrument approaches, specifically with airport equipment outages. PMID:28491009

Evaluation of the predicted error of the soil moisture retrieval from C-band SAR by comparison against modelled soil moisture estimates over Australia

PubMed Central

Doubková, Marcela; Van Dijk, Albert I.J.M.; Sabel, Daniel; Wagner, Wolfgang; Blöschl, Günter

2012-01-01

The Sentinel-1 will carry onboard a C-band radar instrument that will map the European continent once every four days and the global land surface at least once every twelve days with finest 5 × 20 m spatial resolution. The high temporal sampling rate and operational configuration make Sentinel-1 of interest for operational soil moisture monitoring. Currently, updated soil moisture data are made available at 1 km spatial resolution as a demonstration service using Global Mode (GM) measurements from the Advanced Synthetic Aperture Radar (ASAR) onboard ENVISAT. The service demonstrates the potential of the C-band observations to monitor variations in soil moisture. Importantly, a retrieval error estimate is also available; these are needed to assimilate observations into models. The retrieval error is estimated by propagating sensor errors through the retrieval model. In this work, the existing ASAR GM retrieval error product is evaluated using independent top soil moisture estimates produced by the grid-based landscape hydrological model (AWRA-L) developed within the Australian Water Resources Assessment system (AWRA). The ASAR GM retrieval error estimate, an assumed prior AWRA-L error estimate and the variance in the respective datasets were used to spatially predict the root mean square error (RMSE) and the Pearson's correlation coefficient R between the two datasets. These were compared with the RMSE calculated directly from the two datasets. The predicted and computed RMSE showed a very high level of agreement in spatial patterns as well as good quantitative agreement; the RMSE was predicted within accuracy of 4% of saturated soil moisture over 89% of the Australian land mass. Predicted and calculated R maps corresponded within accuracy of 10% over 61% of the continent. The strong correspondence between the predicted and calculated RMSE and R builds confidence in the retrieval error model and derived ASAR GM error estimates. The ASAR GM and Sentinel-1 have the same basic physical measurement characteristics, and therefore very similar retrieval error estimation method can be applied. Because of the expected improvements in radiometric resolution of the Sentinel-1 backscatter measurements, soil moisture estimation errors can be expected to be an order of magnitude less than those for ASAR GM. This opens the possibility for operationally available medium resolution soil moisture estimates with very well-specified errors that can be assimilated into hydrological or crop yield models, with potentially large benefits for land-atmosphere fluxes, crop growth, and water balance monitoring and modelling. PMID:23483015

Algorithm theoretical baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project

NASA Astrophysics Data System (ADS)

De Smedt, Isabelle; Theys, Nicolas; Yu, Huan; Danckaert, Thomas; Lerot, Christophe; Compernolle, Steven; Van Roozendael, Michel; Richter, Andreas; Hilboll, Andreas; Peters, Enno; Pedergnana, Mattia; Loyola, Diego; Beirle, Steffen; Wagner, Thomas; Eskes, Henk; van Geffen, Jos; Folkert Boersma, Klaas; Veefkind, Pepijn

2018-04-01

On board the Copernicus Sentinel-5 Precursor (S5P) platform, the TROPOspheric Monitoring Instrument (TROPOMI) is a double-channel, nadir-viewing grating spectrometer measuring solar back-scattered earthshine radiances in the ultraviolet, visible, near-infrared, and shortwave infrared with global daily coverage. In the ultraviolet range, its spectral resolution and radiometric performance are equivalent to those of its predecessor OMI, but its horizontal resolution at true nadir is improved by an order of magnitude. This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the S5P operational processor and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted. Finally, verification results based on the application of the algorithm to OMI measurements are presented, demonstrating the performances expected for TROPOMI.

The Error Structure of the SMAP Single and Dual Channel Soil Moisture Retrievals

NASA Astrophysics Data System (ADS)

Dong, Jianzhi; Crow, Wade T.; Bindlish, Rajat

2018-01-01

Knowledge of the temporal error structure for remotely sensed surface soil moisture retrievals can improve our ability to exploit them for hydrologic and climate studies. This study employs a triple collocation analysis to investigate both the total variance and temporal autocorrelation of errors in Soil Moisture Active and Passive (SMAP) products generated from two separate soil moisture retrieval algorithms, the vertically polarized brightness temperature-based single-channel algorithm (SCA-V, the current baseline SMAP algorithm) and the dual-channel algorithm (DCA). A key assumption made in SCA-V is that real-time vegetation opacity can be accurately captured using only a climatology for vegetation opacity. Results demonstrate that while SCA-V generally outperforms DCA, SCA-V can produce larger total errors when this assumption is significantly violated by interannual variability in vegetation health and biomass. Furthermore, larger autocorrelated errors in SCA-V retrievals are found in areas with relatively large vegetation opacity deviations from climatological expectations. This implies that a significant portion of the autocorrelated error in SCA-V is attributable to the violation of its vegetation opacity climatology assumption and suggests that utilizing a real (as opposed to climatological) vegetation opacity time series in the SCA-V algorithm would reduce the magnitude of autocorrelated soil moisture retrieval errors.

Stand-alone error characterisation of microwave satellite soil moisture using a Fourier method

USDA-ARS?s Scientific Manuscript database

Error characterisation of satellite-retrieved soil moisture (SM) is crucial for maximizing their utility in research and applications in hydro-meteorology and climatology. Error characteristics can provide insights for retrieval development and validation, and inform suitable strategies for data fus...

Modular error embedding

DOEpatents

Sandford, II, Maxwell T.; Handel, Theodore G.; Ettinger, J. Mark

1999-01-01

A method of embedding auxiliary information into the digital representation of host data containing noise in the low-order bits. The method applies to digital data representing analog signals, for example digital images. The method reduces the error introduced by other methods that replace the low-order bits with auxiliary information. By a substantially reverse process, the embedded auxiliary data can be retrieved easily by an authorized user through use of a digital key. The modular error embedding method includes a process to permute the order in which the host data values are processed. The method doubles the amount of auxiliary information that can be added to host data values, in comparison with bit-replacement methods for high bit-rate coding. The invention preserves human perception of the meaning and content of the host data, permitting the addition of auxiliary data in the amount of 50% or greater of the original host data.

The Potential of Clear Sky Carbon Dioxide Satellite Retrievals

NASA Astrophysics Data System (ADS)

Nelson, R.; O'Dell, C.

2013-12-01

It has been shown that neglecting scattering and absorption by aerosols and thin clouds can lead to significant errors in retrievals of the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from space-based measurements of near-infrared reflected sunlight. These clear sky retrievals, which assume no aerosol effects, are desirable because of their high computational efficiency relative to common full physics retrievals. Further, clear sky retrievals may be able to make higher quality measurements relative to the full physics approach because they may introduce fewer potential biases under certain circumstances. These biases can appear when we try to retrieve clouds and aerosols in the full physics methods when there are none actually present. Recent work has shown that intelligent pre-screening can remove soundings with large light-path modifications over ocean surfaces. In this work, we test the hypothesis that intelligent pre-screening of soundings may be successfully used over land surfaces as well as oceans, which would allow clear sky retrievals to be applicable over all surfaces. We also test the hypothesis that major light path modification effects associated with aerosols can be identified based on spectral tests at 0.76, 1.6, and 2 microns. This presentation summarizes our study of both simulated data and satellite observations from the GOSAT instrument in order to assess the effectiveness of using a clear sky retrieval algorithm coupled with intelligent pre-screening to accurately measure carbon dioxide from space-borne instruments.

Aged-related Neural Changes during Memory Conjunction Errors

PubMed Central

Giovanello, Kelly S.; Kensinger, Elizabeth A.; Wong, Alana T.; Schacter, Daniel L.

2013-01-01

Human behavioral studies demonstrate that healthy aging is often accompanied by increases in memory distortions or errors. Here we used event-related functional MRI to examine the neural basis of age-related memory distortions. We utilized the memory conjunction error paradigm, a laboratory procedure known to elicit high levels of memory errors. For older adults, right parahippocampal gyrus showed significantly greater activity during false than during accurate retrieval. We observed no regions in which activity was greater during false than during accurate retrieval for young adults. Young adults, however, showed significantly greater activity than old adults during accurate retrieval in right hippocampus. By contrast, older adults demonstrated greater activity than young adults during accurate retrieval in right inferior and middle prefrontal cortex. These data are consistent with the notion that age-related memory conjunction errors arise from dysfunction of hippocampal system mechanisms, rather than impairments in frontally-mediated monitoring processes. PMID:19445606

An Algorithm for Retrieving Land Surface Temperatures Using VIIRS Data in Combination with Multi-Sensors

PubMed Central

Xia, Lang; Mao, Kebiao; Ma, Ying; Zhao, Fen; Jiang, Lipeng; Shen, Xinyi; Qin, Zhihao

2014-01-01

A practical algorithm was proposed to retrieve land surface temperature (LST) from Visible Infrared Imager Radiometer Suite (VIIRS) data in mid-latitude regions. The key parameter transmittance is generally computed from water vapor content, while water vapor channel is absent in VIIRS data. In order to overcome this shortcoming, the water vapor content was obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The analyses on the estimation errors of vapor content and emissivity indicate that when the water vapor errors are within the range of ±0.5 g/cm2, the mean retrieval error of the present algorithm is 0.634 K; while the land surface emissivity errors range from −0.005 to +0.005, the mean retrieval error is less than 1.0 K. Validation with the standard atmospheric simulation shows the average LST retrieval error for the twenty-three land types is 0.734 K, with a standard deviation value of 0.575 K. The comparison between the ground station LST data indicates the retrieval mean accuracy is −0.395 K, and the standard deviation value is 1.490 K in the regions with vegetation and water cover. Besides, the retrieval results of the test data have also been compared with the results measured by the National Oceanic and Atmospheric Administration (NOAA) VIIRS LST products, and the results indicate that 82.63% of the difference values are within the range of −1 to 1 K, and 17.37% of the difference values are within the range of ±2 to ±1 K. In a conclusion, with the advantages of multi-sensors taken fully exploited, more accurate results can be achieved in the retrieval of land surface temperature. PMID:25397919

A New Understanding for the Rain Rate retrieval of Attenuating Radars Measurement

NASA Astrophysics Data System (ADS)

Koner, P.; Battaglia, A.; Simmer, C.

2009-04-01

The retrieval of rain rate from the attenuated radar (e.g. Cloud Profiling Radar on board of CloudSAT in orbit since June 2006) is a challenging problem. ĹEcuyer and Stephens [1] underlined this difficulty (for rain rates larger than 1.5 mm/h) and suggested the need of additional information (like path-integrated attenuations (PIA) derived from surface reference techniques or precipitation water path estimated from co-located passive microwave radiometer) to constrain the retrieval. It is generally discussed based on the optimal estimation theory that there are no solutions without constraining the problem in a case of visible attenuation because there is no enough information content to solve the problem. However, when the problem is constrained by the additional measurement of PIA, there is a reasonable solution. This raises the spontaneous question: Is all information enclosed in this additional measurement? This also contradicts with the information theory because one measurement can introduce only one degree of freedom in the retrieval. Why is one degree of freedom so important in the above problem? This question cannot be explained using the estimation and information theories of OEM. On the other hand, Koner and Drummond [2] argued that the OEM is basically a regularization method, where a-priori covariance is used as a stabilizer and the regularization strength is determined by the choices of the a-priori and error covariance matrices. The regularization is required for the reduction of the condition number of Jacobian, which drives the noise injection from the measurement and inversion spaces to the state space in an ill-posed inversion. In this work, the above mentioned question will be discussed based on the regularization theory, error mitigation and eigenvalue mathematics. References 1. L'Ecuyer TS and Stephens G. An estimation based precipitation retrieval algorithm for attenuating radar. J. Appl. Met., 2002, 41, 272-85. 2. Koner PK, Drummond JR. A comparison of regularization techniques for atmospheric trace gases retrievals. JQSRT 2008; 109:514-26.

XCO2 retrieval error over deserts near critical surface albedo

NASA Astrophysics Data System (ADS)

Zhang, Qiong; Shia, Run-Lie; Sander, Stanley P.; Yung, Yuk L.

2016-02-01

Large retrieval errors in column-weighted CO2 mixing ratio (XCO2) over deserts are evident in the Orbiting Carbon Observatory 2 version 7 L2 products. We argue that these errors are caused by the surface albedo being close to a critical surface albedo (αc). Over a surface with albedo close to αc, increasing the aerosol optical depth (AOD) does not change the continuum radiance. The spectral signature caused by changing the AOD is identical to that caused by changing the absorbing gas column. The degeneracy in the retrievals of AOD and XCO2 results in a loss of degrees of freedom and information content. We employ a two-stream-exact single scattering radiative transfer model to study the physical mechanism of XCO2 retrieval error over a surface with albedo close to αc. Based on retrieval tests over surfaces with different albedos, we conclude that over a surface with albedo close to αc, the XCO2 retrieval suffers from a significant loss of accuracy. We recommend a bias correction approach that has significantly improved the XCO2 retrieval from the California Laboratory for Atmospheric Remote Sensing data in the presence of aerosol loading.

Formaldehyde Distribution over North America: Implications for Satellite Retrievals of Formaldehyde Columns and Isoprene Emission

NASA Technical Reports Server (NTRS)

Millet, Dylan B.; Jacob, Daniel J.; Turquety, Solene; Hudman, Rynda C.; Wu, Shiliang; Anderson, Bruce E.; Fried, Alan; Walega, James; Heikes, Brian G.; Blake, Donald R.;

Assessment of Mars Atmospheric Temperature Retrievals from the Thermal Emission Spectrometer Radiances

NASA Technical Reports Server (NTRS)

Hoffman, Matthew J.; Eluszkiewicz, Janusz; Weisenstein, Deborah; Uymin, Gennady; Moncet, Jean-Luc

2012-01-01

Motivated by the needs of Mars data assimilation. particularly quantification of measurement errors and generation of averaging kernels. we have evaluated atmospheric temperature retrievals from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) radiances. Multiple sets of retrievals have been considered in this study; (1) retrievals available from the Planetary Data System (PDS), (2) retrievals based on variants of the retrieval algorithm used to generate the PDS retrievals, and (3) retrievals produced using the Mars 1-Dimensional Retrieval (M1R) algorithm based on the Optimal Spectral Sampling (OSS ) forward model. The retrieved temperature profiles are compared to the MGS Radio Science (RS) temperature profiles. For the samples tested, the M1R temperature profiles can be made to agree within 2 K with the RS temperature profiles, but only after tuning the prior and error statistics. Use of a global prior that does not take into account the seasonal dependence leads errors of up 6 K. In polar samples. errors relative to the RS temperature profiles are even larger. In these samples, the PDS temperature profiles also exhibit a poor fit with RS temperatures. This fit is worse than reported in previous studies, indicating that the lack of fit is due to a bias correction to TES radiances implemented after 2004. To explain the differences between the PDS and Ml R temperatures, the algorithms are compared directly, with the OSS forward model inserted into the PDS algorithm. Factors such as the filtering parameter, the use of linear versus nonlinear constrained inversion, and the choice of the forward model, are found to contribute heavily to the differences in the temperature profiles retrieved in the polar regions, resulting in uncertainties of up to 6 K. Even outside the poles, changes in the a priori statistics result in different profile shapes which all fit the radiances within the specified error. The importance of the a priori statistics prevents reliable global retrievals based a single a priori and strongly implies that a robust science analysis must instead rely on retrievals employing localized a priori information, for example from an ensemble based data assimilation system such as the Local Ensemble Transform Kalman Filter (LETKF).

Physical Validation of TRMM TMI and PR Monthly Rain Products Over Oklahoma

NASA Technical Reports Server (NTRS)

Fisher, Brad L.

2004-01-01

The Tropical Rainfall Measuring Mission (TRMM) provides monthly rainfall estimates using data collected by the TRMM satellite. These estimates cover a substantial fraction of the earth's surface. The physical validation of TRMM estimates involves corroborating the accuracy of spaceborne estimates of areal rainfall by inferring errors and biases from ground-based rain estimates. The TRMM error budget consists of two major sources of error: retrieval and sampling. Sampling errors are intrinsic to the process of estimating monthly rainfall and occur because the satellite extrapolates monthly rainfall from a small subset of measurements collected only during satellite overpasses. Retrieval errors, on the other hand, are related to the process of collecting measurements while the satellite is overhead. One of the big challenges confronting the TRMM validation effort is how to best estimate these two main components of the TRMM error budget, which are not easily decoupled. This four-year study computed bulk sampling and retrieval errors for the TRMM microwave imager (TMI) and the precipitation radar (PR) by applying a technique that sub-samples gauge data at TRMM overpass times. Gridded monthly rain estimates are then computed from the monthly bulk statistics of the collected samples, providing a sensor-dependent gauge rain estimate that is assumed to include a TRMM equivalent sampling error. The sub-sampled gauge rain estimates are then used in conjunction with the monthly satellite and gauge (without sub- sampling) estimates to decouple retrieval and sampling errors. The computed mean sampling errors for the TMI and PR were 5.9% and 7.796, respectively, in good agreement with theoretical predictions. The PR year-to-year retrieval biases exceeded corresponding TMI biases, but it was found that these differences were partially due to negative TMI biases during cold months and positive TMI biases during warm months.

The Community Cloud retrieval for CLimate (CC4CL) - Part 2: The optimal estimation approach

NASA Astrophysics Data System (ADS)

McGarragh, Gregory R.; Poulsen, Caroline A.; Thomas, Gareth E.; Povey, Adam C.; Sus, Oliver; Stapelberg, Stefan; Schlundt, Cornelia; Proud, Simon; Christensen, Matthew W.; Stengel, Martin; Hollmann, Rainer; Grainger, Roy G.

2018-06-01

The Community Cloud retrieval for Climate (CC4CL) is a cloud property retrieval system for satellite-based multispectral imagers and is an important component of the Cloud Climate Change Initiative (Cloud_cci) project. In this paper we discuss the optimal estimation retrieval of cloud optical thickness, effective radius and cloud top pressure based on the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm. Key to this method is the forward model, which includes the clear-sky model, the liquid water and ice cloud models, the surface model including a bidirectional reflectance distribution function (BRDF), and the "fast" radiative transfer solution (which includes a multiple scattering treatment). All of these components and their assumptions and limitations will be discussed in detail. The forward model provides the accuracy appropriate for our retrieval method. The errors are comparable to the instrument noise for cloud optical thicknesses greater than 10. At optical thicknesses less than 10 modeling errors become more significant. The retrieval method is then presented describing optimal estimation in general, the nonlinear inversion method employed, measurement and a priori inputs, the propagation of input uncertainties and the calculation of subsidiary quantities that are derived from the retrieval results. An evaluation of the retrieval was performed using measurements simulated with noise levels appropriate for the MODIS instrument. Results show errors less than 10 % for cloud optical thicknesses greater than 10. Results for clouds of optical thicknesses less than 10 have errors up to 20 %.

A new retrieval algorithm for tropospheric temperature, humidity and pressure profiling based on GNSS radio occultation data

NASA Astrophysics Data System (ADS)

Kirchengast, Gottfried; Li, Ying; Scherllin-Pirscher, Barbara; Schwärz, Marc; Schwarz, Jakob; Nielsen, Johannes K.

2017-04-01

The GNSS radio occultation (RO) technique is an important remote sensing technique for obtaining thermodynamic profiles of temperature, humidity, and pressure in the Earth's troposphere. However, due to refraction effects of both dry ambient air and water vapor in the troposphere, retrieval of accurate thermodynamic profiles at these lower altitudes is challenging and requires suitable background information in addition to the RO refractivity information. Here we introduce a new moist air retrieval algorithm aiming to improve the quality and robustness of retrieving temperature, humidity and pressure profiles in moist air tropospheric conditions. The new algorithm consists of four steps: (1) use of prescribed specific humidity and its uncertainty to retrieve temperature and its associated uncertainty; (2) use of prescribed temperature and its uncertainty to retrieve specific humidity and its associated uncertainty; (3) use of the previous results to estimate final temperature and specific humidity profiles through optimal estimation; (4) determination of air pressure and density profiles from the results obtained before. The new algorithm does not require elaborated matrix inversions which are otherwise widely used in 1D-Var retrieval algorithms, and it allows a transparent uncertainty propagation, whereby the uncertainties of prescribed variables are dynamically estimated accounting for their spatial and temporal variations. Estimated random uncertainties are calculated by constructing error covariance matrices from co-located ECMWF short-range forecast and corresponding analysis profiles. Systematic uncertainties are estimated by empirical modeling. The influence of regarding or disregarding vertical error correlations is quantified. The new scheme is implemented with static input uncertainty profiles in WEGC's current OPSv5.6 processing system and with full scope in WEGC's next-generation system, the Reference Occultation Processing System (rOPS). Results from both WEGC systems, current OPSv5.6 and next-generation rOPS, are shown and discussed, based on both insights from individual profiles and statistical ensembles, and compared to moist air retrieval results from the UCAR Boulder and ROM-SAF Copenhagen centers. The results show that the new algorithmic scheme improves the temperature, humidity and pressure retrieval performance, in particular also the robustness including for integrated uncertainty estimation for large-scale applications, over the previous algorithms. The new rOPS-implemented algorithm will therefore be used in the first large-scale reprocessing towards a tropospheric climate data record 2001-2016 by the rOPS, including its integrated uncertainty propagation.

Quantifying Uncertainties in Land Surface Microwave Emissivity Retrievals

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

2012-01-01

Uncertainties in the retrievals of microwave land surface emissivities were quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including SSM/I, TMI and AMSR-E, were studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors in the retrievals. Generally these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 14% (312 K) over desert and 17% (320 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.52% (26 K). In particular, at 85.0/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are mostly likely caused by rain/cloud contamination, which can lead to random errors up to 1017 K under the most severe conditions.

A Preliminary ZEUS Lightning Location Error Analysis Using a Modified Retrieval Theory

NASA Technical Reports Server (NTRS)

Elander, Valjean; Koshak, William; Phanord, Dieudonne

2004-01-01

The ZEUS long-range VLF arrival time difference lightning detection network now covers both Europe and Africa, and there are plans for further expansion into the western hemisphere. In order to fully optimize and assess ZEUS lightning location retrieval errors and to determine the best placement of future receivers expected to be added to the network, a software package is being developed jointly between the NASA Marshall Space Flight Center (MSFC) and the University of Nevada Las Vegas (UNLV). The software package, called the ZEUS Error Analysis for Lightning (ZEAL), will be used to obtain global scale lightning location retrieval error maps using both a Monte Carlo approach and chi-squared curvature matrix theory. At the core of ZEAL will be an implementation of an Iterative Oblate (IO) lightning location retrieval method recently developed at MSFC. The IO method will be appropriately modified to account for variable wave propagation speed, and the new retrieval results will be compared with the current ZEUS retrieval algorithm to assess potential improvements. In this preliminary ZEAL work effort, we defined 5000 source locations evenly distributed across the Earth. We then used the existing (as well as potential future ZEUS sites) to simulate arrival time data between source and ZEUS site. A total of 100 sources were considered at each of the 5000 locations, and timing errors were selected from a normal distribution having a mean of 0 seconds and a standard deviation of 20 microseconds. This simulated "noisy" dataset was analyzed using the IO algorithm to estimate source locations. The exact locations were compared with the retrieved locations, and the results are summarized via several color-coded "error maps."

Improvement of GPS radio occultation retrieval error of E region electron density: COSMIC measurement and IRI model simulation

NASA Astrophysics Data System (ADS)

Wu, Kang-Hung; Su, Ching-Lun; Chu, Yen-Hsyang

2015-03-01

In this article, we use the International Reference Ionosphere (IRI) model to simulate temporal and spatial distributions of global E region electron densities retrieved by the FORMOSAT-3/COSMIC satellites by means of GPS radio occultation (RO) technique. Despite regional discrepancies in the magnitudes of the E region electron density, the IRI model simulations can, on the whole, describe the COSMIC measurements in quality and quantity. On the basis of global ionosonde network and the IRI model, the retrieval errors of the global COSMIC-measured E region peak electron density (NmE) from July 2006 to July 2011 are examined and simulated. The COSMIC measurement and the IRI model simulation both reveal that the magnitudes of the percentage error (PE) and root mean-square-error (RMSE) of the relative RO retrieval errors of the NmE values are dependent on local time (LT) and geomagnetic latitude, with minimum in the early morning and at high latitudes and maximum in the afternoon and at middle latitudes. In addition, the seasonal variation of PE and RMSE values seems to be latitude dependent. After removing the IRI model-simulated GPS RO retrieval errors from the original COSMIC measurements, the average values of the annual and monthly mean percentage errors of the RO retrieval errors of the COSMIC-measured E region electron density are, respectively, substantially reduced by a factor of about 2.95 and 3.35, and the corresponding root-mean-square errors show averaged decreases of 15.6% and 15.4%, respectively. It is found that, with this process, the largest reduction in the PE and RMSE of the COSMIC-measured NmE occurs at the equatorial anomaly latitudes 10°N-30°N in the afternoon from 14 to 18 LT, with a factor of 25 and 2, respectively. Statistics show that the residual errors that remained in the corrected COSMIC-measured NmE vary in a range of -20% to 38%, which are comparable to or larger than the percentage errors of the IRI-predicted NmE fluctuating in a range of -6.5% to 20%.

A Lightning Channel Retrieval Algorithm for the North Alabama Lightning Mapping Array (LMA)

NASA Technical Reports Server (NTRS)

Koshak, William; Arnold, James E. (Technical Monitor)

2002-01-01

A new multi-station VHF time-of-arrival (TOA) antenna network is, at the time of this writing, coming on-line in Northern Alabama. The network, called the Lightning Mapping Array (LMA), employs GPS timing and detects VHF radiation from discrete segments (effectively point emitters) that comprise the channel of lightning strokes within cloud and ground flashes. The network will support on-going ground validation activities of the low Earth orbiting Lightning Imaging Sensor (LIS) satellite developed at NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama. It will also provide for many interesting and detailed studies of the distribution and evolution of thunderstorms and lightning in the Tennessee Valley, and will offer many interesting comparisons with other meteorological/geophysical wets associated with lightning and thunderstorms. In order to take full advantage of these benefits, it is essential that the LMA channel mapping accuracy (in both space and time) be fully characterized and optimized. In this study, a new revised channel mapping retrieval algorithm is introduced. The algorithm is an extension of earlier work provided in Koshak and Solakiewicz (1996) in the analysis of the NASA Kennedy Space Center (KSC) Lightning Detection and Ranging (LDAR) system. As in the 1996 study, direct algebraic solutions are obtained by inverting a simple linear system of equations, thereby making computer searches through a multi-dimensional parameter domain of a Chi-Squared function unnecessary. However, the new algorithm is developed completely in spherical Earth-centered coordinates (longitude, latitude, altitude), rather than in the (x, y, z) cartesian coordinates employed in the 1996 study. Hence, no mathematical transformations from (x, y, z) into spherical coordinates are required (such transformations involve more numerical error propagation, more computer program coding, and slightly more CPU computing time). The new algorithm also has a more realistic definition of source altitude that accounts for Earth oblateness (this can become important for sources that are hundreds of kilometers away from the network). In addition, the new algorithm is being applied to analyze computer simulated LMA datasets in order to obtain detailed location/time retrieval error maps for sources in and around the LMA network. These maps will provide a more comprehensive analysis of retrieval errors for LMA than the 1996 study did of LDAR retrieval errors. Finally, we note that the new algorithm can be applied to LDAR, and essentially any other multi-station TWA network that depends on direct line-of-site antenna excitation.

Improving Satellite Retrieved Infrared Sea Surface Temperatures in Aerosol-Contaminated Regions

NASA Astrophysics Data System (ADS)

Luo, B.; Minnett, P. J.; Szczodrak, G.; Kilpatrick, K. A.

2017-12-01

Infrared satellite observations of sea surface temperature (SST) have become essential for many applications in meteorology, climatology, and oceanography. Applications often require high accuracy SST data: for climate research and monitoring an absolute uncertainty of 0.1K and stability of better than 0.04K per decade are required. Tropospheric aerosol concentrations increase infrared signal attenuation and prevent the retrieval of accurate satellite SST. We compare satellite-derived skin SST with measurements from the Marine-Atmospheric Emitted Radiance Interferometer (M-AERI) deployed on ships during the Aerosols and Ocean Science Expeditions (AEROSE) and with quality-controlled drifter temperatures. After match-up with in-situ SST and filtering of cloud contaminated data, the results indicate that SST retrieved from MODIS (Moderate Resolution Imaging Spectroradiometer) aboard the Terra and Aqua satellites have negative (cool) biases compared to shipboard radiometric measurements. There is also a pronounced negative bias in the Saharan outflow area that can introduce SST errors >1 K at aerosol optical depths > 0.5. In this study, we present a new method to derive night-time Saharan Dust Index (SDI) algorithms based on simulated brightness temperatures at infrared wavelengths of 3.9, 10.8 and 12.0 μm, derived using RTTOV. We derived correction coefficients for Aqua MODIS measurements by regression of the SST errors against the SDI. The biases and standard deviations are reduced by 0.25K and 0.19K after the SDI correction. The goal of this study is to understand better the characteristics and physical mechanisms of aerosol effects on satellite retrieved infrared SST, as well as to derive empirical formulae for improved accuracies in aerosol-contaminated regions.

Monitoring carbon dioxide from space: Retrieval algorithm and flux inversion based on GOSAT data and using CarbonTracker-China

NASA Astrophysics Data System (ADS)

Yang, Dongxu; Zhang, Huifang; Liu, Yi; Chen, Baozhang; Cai, Zhaonan; Lü, Daren

2017-08-01

Monitoring atmospheric carbon dioxide (CO2) from space-borne state-of-the-art hyperspectral instruments can provide a high precision global dataset to improve carbon flux estimation and reduce the uncertainty of climate projection. Here, we introduce a carbon flux inversion system for estimating carbon flux with satellite measurements under the support of "The Strategic Priority Research Program of the Chinese Academy of Sciences—Climate Change: Carbon Budget and Relevant Issues". The carbon flux inversion system is composed of two separate parts: the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing (IAPCAS), and CarbonTracker-China (CT-China), developed at the Chinese Academy of Sciences. The Greenhouse gases Observing SATellite (GOSAT) measurements are used in the carbon flux inversion experiment. To improve the quality of the IAPCAS-GOSAT retrieval, we have developed a post-screening and bias correction method, resulting in 25%-30% of the data remaining after quality control. Based on these data, the seasonal variation of XCO2 (column-averaged CO2 dry-air mole fraction) is studied, and a strong relation with vegetation cover and population is identified. Then, the IAPCAS-GOSAT XCO2 product is used in carbon flux estimation by CT-China. The net ecosystem CO2 exchange is -0.34 Pg C yr-1 (±0.08 Pg C yr-1), with a large error reduction of 84%, which is a significant improvement on the error reduction when compared with in situ-only inversion.

GOSAT CO2 retrieval results using TANSO-CAI aerosol information over East Asia

NASA Astrophysics Data System (ADS)

KIM, M.; Kim, W.; Jung, Y.; Lee, S.; Kim, J.; Lee, H.; Boesch, H.; Goo, T. Y.

2015-12-01

In the satellite remote sensing of CO2, incorrect aerosol information could induce large errors as previous studies suggested. Many factors, such as, aerosol type, wavelength dependency of AOD, aerosol polarization effect and etc. have been main error sources. Due to these aerosol effects, large number of data retrieved are screened out in quality control, or retrieval errors tend to increase if not screened out, especially in East Asia where aerosol concentrations are fairly high. To reduce these aerosol induced errors, a CO2 retrieval algorithm using the simultaneous TANSO-CAI aerosol information is developed. This algorithm adopts AOD and aerosol type information as a priori information from the CAI aerosol retrieval algorithm. The CO2 retrieval algorithm based on optimal estimation method and VLIDORT, a vector discrete ordinate radiative transfer model. The CO2 algorithm, developed with various state vectors to find accurate CO2 concentration, shows reasonable results when compared with other dataset. This study concentrates on the validation of retrieved results with the ground-based TCCON measurements in East Asia and the comparison with the previous retrieval from ACOS, NIES, and UoL. Although, the retrieved CO2 concentration is lower than previous results by ppm's, it shows similar trend and high correlation with previous results. Retrieved data and TCCON measurements data are compared at three stations of Tsukuba, Saga, Anmyeondo in East Asia, with the collocation criteria of ±2°in latitude/longitude and ±1 hours of GOSAT passing time. Compared results also show similar trend with good correlation. Based on the TCCON comparison results, bias correction equation is calculated and applied to the East Asia data.

Clique-Based Neural Associative Memories with Local Coding and Precoding.

PubMed

Mofrad, Asieh Abolpour; Parker, Matthew G; Ferdosi, Zahra; Tadayon, Mohammad H

2016-08-01

Techniques from coding theory are able to improve the efficiency of neuroinspired and neural associative memories by forcing some construction and constraints on the network. In this letter, the approach is to embed coding techniques into neural associative memory in order to increase their performance in the presence of partial erasures. The motivation comes from recent work by Gripon, Berrou, and coauthors, which revisited Willshaw networks and presented a neural network with interacting neurons that partitioned into clusters. The model introduced stores patterns as small-size cliques that can be retrieved in spite of partial error. We focus on improving the success of retrieval by applying two techniques: doing a local coding in each cluster and then applying a precoding step. We use a slightly different decoding scheme, which is appropriate for partial erasures and converges faster. Although the ideas of local coding and precoding are not new, the way we apply them is different. Simulations show an increase in the pattern retrieval capacity for both techniques. Moreover, we use self-dual additive codes over field [Formula: see text], which have very interesting properties and a simple-graph representation.

Combined multispectral/hyperspectral remote sensing of tropospheric aerosols for quantification of their direct radiative effect

NASA Astrophysics Data System (ADS)

McGarragh, Gregory R.

Scattering and absorption of solar radiation by aerosols in the atmosphere has a direct radiative effect on the climate of the Earth. Unfortunately, according to the IPCC the uncertainties in aerosol properties and their effect on the climate system represent one of the largest uncertainties in climate change research. Related to aerosols, one of the largest uncertainties is the fraction of the incident radiation that is scattered rather than absorbed, or their single scattering albedo. In fact, differences in single scattering albedo have a significant impact on the magnitude of the cooling effect of aerosols (opposite to that of greenhouse gasses) which can even have a warming effect for strongly absorbing aerosols. Satellites provide a unique opportunity to measure aerosol properties on a global scale. Traditional approaches use multispectral measurements of intensity at a single view angle to retrieve at most two aerosol parameters over land but it is being realized that more detail is required for accurate quantification of the direct effect of aerosols, in particular its anthropogenic component, and therefore more measurement information is required. One approach to more advanced measurements is to use not only intensity measurements but also polarimetric measurements and to use multiple view angles. In this work we explore another alternative: the use of hyperspectral measurements in molecular absorption bands. Our study can be divided into three stages the first of which is the development of a fast radiative transfer model for rapid simulation of measurements. Our approach is matrix operator based and uses the Pade approximation for the matrix exponential to evaluate the homogeneous solution. It is shown that the method is two to four times faster than the standard and efficient discrete ordinate technique and is accurate to the 6th decimal place. The second part of our study forms the core and is divided into two chapters the first of which is a rigorous sensitivity and optimal estimation based information content study that explores the use of measurements made by a MODIS type instrument combined with measurements made by an instrument similar to GOSAT TANSO-FTS which supplies hyperspectral measurements of intensity and polarization in the O2 A-band and the 1.61- and 2.06-mu CO 2 bands. It is found that the use of the hyperspectral bands provides a means to separate the effects of the surface and aerosol absorption from effects related to aerosol single scattering parameters. The amount of information increases significantly when the CO2 bands are included rather than just the more traditional O2 A-band, when polarization measurements are included, and when measurements are made at multiple view angles. We then present a retrieval using co-located observations of MODIS and GOSAT TANSO-FTS which are both also co-located with AERONET sites for validation purposes. We introduce an optimal estimation retrieval and perform this retrieval on our co-located observations. We choose a complete state vector to maximize the use of the information in our measurements and use an a priori constraint and regularization to arrive at a stable solution. In addition to the retrieved parameters, we also calculate a self contained estimation of the retrieval error. Validation with AERONET, for retrievals using MODIS plus TANSO-FTS measurements of intensity and polarization in all three bands indicate accuracies within 15% for optical thickness, 10% for fine mode mean radius, 35% for coarse mode mean radius, 15% for the standard deviation of fine mode mean radius, 25% for the standard deviation of the coarse mode mean radius, 0.04 for the real part of the index of refraction, and 0.05 for single scattering albedo. In addition to the retrieved parameters, we also validate the estimated retrieval error and find that the estimations have distributions that are tighter and within the broader distributions of real errors relative to AERONET. The third part of our study uses the retrieval results to calculate radiative fluxes, errors, and sensitivities at solar wavelengths along with aerosol radiative effect and effect efficiency. In addition, we outline how to propagate the errors in the retrieval through the flux calculations to provide an error estimation of the fluxes. These results are then validated against the corresponding AERONET products. It was found that the flux results were most sensitive to single scattering albedo while the size distribution and real part of the index of refraction also have significant effects. Relative to AERONET our fluxes are less accurate than an independent AERONET validation, due to uncertainties in our satellite based retrieval with accuracies within 13 Wm-2 for TOA upward, 9 Wm-2 for BOA upward, and 30 Wm-2 for BOA downward. The estimated errors also contained uncertainties but were in fact more conservative than the actual errors.

Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

NASA Technical Reports Server (NTRS)

Tian, Yudong; Peters-Lidard, Christa D.; Harrison, Kenneth W.; Prigent, Catherine; Norouzi, Hamidreza; Aires, Filipe; Boukabara, Sid-Ahmed; Furuzawa, Fumie A.; Masunaga, Hirohiko

2013-01-01

Uncertainties in the retrievals of microwaveland-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors inthe retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.

Validation of aerosol optical depth uncertainties within the ESA Climate Change Initiative

NASA Astrophysics Data System (ADS)

Stebel, Kerstin; Povey, Adam; Popp, Thomas; Capelle, Virginie; Clarisse, Lieven; Heckel, Andreas; Kinne, Stefan; Klueser, Lars; Kolmonen, Pekka; de Leeuw, Gerrit; North, Peter R. J.; Pinnock, Simon; Sogacheva, Larisa; Thomas, Gareth; Vandenbussche, Sophie

2017-04-01

Uncertainty is a vital component of any climate data record as it provides the context with which to understand the quality of the data and compare it to other measurements. Therefore, pixel-level uncertainties are provided for all aerosol products that have been developed in the framework of the Aerosol_cci project within ESA's Climate Change Initiative (CCI). Validation of these estimated uncertainties is necessary to demonstrate that they provide a useful representation of the distribution of error. We propose a technique for the statistical validation of AOD (aerosol optical depth) uncertainty by comparison to high-quality ground-based observations and present results for ATSR (Along Track Scanning Radiometer) and IASI (Infrared Atmospheric Sounding Interferometer) data records. AOD at 0.55 µm and its uncertainty was calculated with three AOD retrieval algorithms using data from the ATSR instruments (ATSR-2 (1995-2002) and AATSR (2002-2012)). Pixel-level uncertainties were calculated through error propagation (ADV/ASV, ORAC algorithms) or parameterization of the error's dependence on the geophysical retrieval conditions (SU algorithm). Level 2 data are given as super-pixels of 10 km x 10 km. As validation data, we use direct-sun observations of AOD from the AERONET (AErosol RObotic NETwork) and MAN (Maritime Aerosol Network) sun-photometer networks, which are substantially more accurate than satellite retrievals. Neglecting the uncertainty in AERONET observations and possible issues with their ability to represent a satellite pixel area, the error in the retrieval can be approximated by the difference between the satellite and AERONET retrievals (herein referred to as "error"). To evaluate how well the pixel-level uncertainty represents the observed distribution of error, we look at the distribution of the ratio D between the "error" and the ATSR uncertainty. If uncertainties are well represented, D should be normally distributed and 68.3% of values should fall within the range [-1, +1]. A non-zero mean of D indicates the presence of residual systematic errors. If the fraction is smaller than 68%, uncertainties are underestimated; if it is larger, uncertainties are overestimated. For the three ATSR algorithms, we provide statistics and an evaluation at a global scale (separately for land and ocean/coastal regions), for high/low AOD regimes, and seasonal and regional statistics (e.g. Europe, N-Africa, East-Asia, N-America). We assess the long-term stability of the uncertainty estimates over the 17-year time series, and the consistency between ATSR-2 and AATSR results (during their period of overlap). Furthermore, we exploit the possibility to adapt the uncertainty validation concept to the IASI datasets. Ten-year data records (2007-2016) of dust AOD have been generated with four algorithms using IASI observations over the greater Sahara region [80°W - 120°E, 0°N - 40°N]. For validation, the coarse mode AOD at 0.55 μm from the AERONET direct-sun spectral deconvolution algorithm (SDA) product may be used as a proxy for desert dust. The uncertainty validation results for IASI are still tentative, as larger IASI pixel sizes and the conversion of the IASI AOD values from infrared to visible wavelengths for comparison to ground-based observations introduces large uncertainties.

Improved simulation of aerosol, cloud, and density measurements by shuttle lidar

NASA Technical Reports Server (NTRS)

Russell, P. B.; Morley, B. M.; Livingston, J. M.; Grams, G. W.; Patterson, E. W.

1981-01-01

Data retrievals are simulated for a Nd:YAG lidar suitable for early flight on the space shuttle. Maximum assumed vertical and horizontal resolutions are 0.1 and 100 km, respectively, in the boundary layer, increasing to 2 and 2000 km in the mesosphere. Aerosol and cloud retrievals are simulated using 1.06 and 0.53 microns wavelengths independently. Error sources include signal measurement, conventional density information, atmospheric transmission, and lidar calibration. By day, tenuous clouds and Saharan and boundary layer aerosols are retrieved at both wavelengths. By night, these constituents are retrieved, plus upper tropospheric, stratospheric, and mesospheric aerosols and noctilucent clouds. Density, temperature, and improved aerosol and cloud retrievals are simulated by combining signals at 0.35, 1.06, and 0.53 microns. Particlate contamination limits the technique to the cloud free upper troposphere and above. Error bars automatically show effect of this contamination, as well as errors in absolute density nonmalization, reference temperature or pressure, and the sources listed above. For nonvolcanic conditions, relative density profiles have rms errors of 0.54 to 2% in the upper troposphere and stratosphere. Temperature profiles have rms errors of 1.2 to 2.5 K and can define the tropopause to 0.5 km and higher wave structures to 1 or 2 km.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 1. Forward model, error analysis, and information content

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content.

PubMed

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-27

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness ( τ ), effective radius ( r eff ), and cloud-top height ( h ). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieve polarization aberration from image degradation: a new measurement method in DUV lithography

NASA Astrophysics Data System (ADS)

Xiang, Zhongbo; Li, Yanqiu

2017-10-01

Detailed knowledge of polarization aberration (PA) of projection lens in higher-NA DUV lithographic imaging is necessary due to its impact to imaging degradations, and precise measurement of PA is conductive to computational lithography techniques such as RET and OPC. Current in situ measurement method of PA thorough the detection of degradations of aerial images need to do linear approximation and apply the assumption of 3-beam/2-beam interference condition. The former approximation neglects the coupling effect of the PA coefficients, which would significantly influence the accuracy of PA retrieving. The latter assumption restricts the feasible pitch of test masks in higher-NA system, conflicts with the Kirhhoff diffraction model of test mask used in retrieving model, and introduces 3D mask effect as a source of retrieving error. In this paper, a new in situ measurement method of PA is proposed. It establishes the analytical quadratic relation between the PA coefficients and the degradations of aerial images of one-dimensional dense lines in coherent illumination through vector aerial imaging, which does not rely on the assumption of 3-beam/2- beam interference and linear approximation. In this case, the retrieval of PA from image degradation can be convert from the nonlinear system of m-quadratic equations to a multi-objective quadratic optimization problem, and finally be solved by nonlinear least square method. Some preliminary simulation results are given to demonstrate the correctness and accuracy of the new PA retrieving model.

Effects of vertical distribution of water vapor and temperature on total column water vapor retrieval error

NASA Technical Reports Server (NTRS)

Sun, Jielun

1993-01-01

Results are presented of a test of the physically based total column water vapor retrieval algorithm of Wentz (1992) for sensitivity to realistic vertical distributions of temperature and water vapor. The ECMWF monthly averaged temperature and humidity fields are used to simulate the spatial pattern of systematic retrieval error of total column water vapor due to this sensitivity. The estimated systematic error is within 0.1 g/sq cm over about 70 percent of the global ocean area; systematic errors greater than 0.3 g/sq cm are expected to exist only over a few well-defined regions, about 3 percent of the global oceans, assuming that the global mean value is unbiased.

[Study on Differential Optical Absorption Spectroscopy Data Processing Based on Chirp-Z Transformation].

PubMed

Zheng, Hai-ming; Li, Guang-jie; Wu, Hao

2015-06-01

Differential optical absorption spectroscopy (DOAS) is a commonly used atmospheric pollution monitoring method. Denoising of monitoring spectral data will improve the inversion accuracy. Fourier transform filtering method is effectively capable of filtering out the noise in the spectral data. But the algorithm itself can introduce errors. In this paper, a chirp-z transform method is put forward. By means of the local thinning of Fourier transform spectrum, it can retain the denoising effect of Fourier transform and compensate the error of the algorithm, which will further improve the inversion accuracy. The paper study on the concentration retrieving of SO2 and NO2. The results show that simple division causes bigger error and is not very stable. Chirp-z transform is proved to be more accurate than Fourier transform. Results of the frequency spectrum analysis show that Fourier transform cannot solve the distortion and weakening problems of characteristic absorption spectrum. Chirp-z transform shows ability in fine refactoring of specific frequency spectrum.

Reflected ray retrieval from radio occultation data using radio holographic filtering of wave fields in ray space

NASA Astrophysics Data System (ADS)

Gorbunov, Michael E.; Cardellach, Estel; Lauritsen, Kent B.

2018-03-01

Linear and non-linear representations of wave fields constitute the basis of modern algorithms for analysis of radio occultation (RO) data. Linear representations are implemented by Fourier Integral Operators, which allow for high-resolution retrieval of bending angles. Non-linear representations include Wigner Distribution Function (WDF), which equals the pseudo-density of energy in the ray space. Representations allow for filtering wave fields by suppressing some areas of the ray space and mapping the field back from the transformed space to the initial one. We apply this technique to the retrieval of reflected rays from RO observations. The use of reflected rays may increase the accuracy of the retrieval of the atmospheric refractivity. Reflected rays can be identified by the visual inspection of WDF or spectrogram plots. Numerous examples from COSMIC data indicate that reflections are mostly observed over oceans or snow, in particular over Antarctica. We introduce the reflection index that characterizes the relative intensity of the reflected ray with respect to the direct ray. The index allows for the automatic identification of events with reflections. We use the radio holographic estimate of the errors of the retrieved bending angle profiles of reflected rays. A comparison of indices evaluated for a large base of events including the visual identification of reflections indicated a good agreement with our definition of reflection index.

Bias Correction and Random Error Characterization for the Assimilation of HRDI Line-of-Sight Wind Measurements

NASA Technical Reports Server (NTRS)

Tangborn, Andrew; Menard, Richard; Ortland, David; Einaudi, Franco (Technical Monitor)

2001-01-01

A new approach to the analysis of systematic and random observation errors is presented in which the error statistics are obtained using forecast data rather than observations from a different instrument type. The analysis is carried out at an intermediate retrieval level, instead of the more typical state variable space. This method is carried out on measurements made by the High Resolution Doppler Imager (HRDI) on board the Upper Atmosphere Research Satellite (UARS). HRDI, a limb sounder, is the only satellite instrument measuring winds in the stratosphere, and the only instrument of any kind making global wind measurements in the upper atmosphere. HRDI measures doppler shifts in the two different O2 absorption bands (alpha and B) and the retrieved products are tangent point Line-of-Sight wind component (level 2 retrieval) and UV winds (level 3 retrieval). This analysis is carried out on a level 1.9 retrieval, in which the contributions from different points along the line-of-sight have not been removed. Biases are calculated from O-F (observed minus forecast) LOS wind components and are separated into a measurement parameter space consisting of 16 different values. The bias dependence on these parameters (plus an altitude dependence) is used to create a bias correction scheme carried out on the level 1.9 retrieval. The random error component is analyzed by separating the gamma and B band observations and locating observation pairs where both bands are very nearly looking at the same location at the same time. It is shown that the two observation streams are uncorrelated and that this allows the forecast error variance to be estimated. The bias correction is found to cut the effective observation error variance in half.

Simultaneous retrieval of the solar EUV flux and neutral thermospheric O, O2, N2, and temperature from twilight airglow

NASA Technical Reports Server (NTRS)

Fennelly, J. A.; Torr, D. G.; Richards, P. G.; Torr, M. R.

1994-01-01

We present a method to retrieve neutral thermospheric composition and the solar EUV flux from ground-based twilight optical measurements of the O(+) ((exp 2)P) 7320 A and O((exp 1)D) 6300 A airglow emissions. The parameters retrieved are the neutral temperature, the O, O2, N2 density profiles, and a scaling factor for the solar EUV flux spectrum. The temperature, solar EUV flux scaling factor, and atomic oxygen density are first retrieved from the 7320-A emission, which are then used with the 6300-A emission to retrieve the O2 and N2 densities. The retrieval techniques have been verified by computer simulations. We have shown that the retrieval technique is able to statistically retrieve values, between 200 and 400 km, within an average error of 3.1 + or - 0.6% for thermospheric temperature, 3.3 + or - 2.0% for atomic oxygen, 2.3 + or - 1.3% for molecular oxygen, and 2.4 + or - 1.3% for molecular nitrogen. The solar EUV flux scaling factor was found to have a retrieval error of 5.1 + or - 2.3%. All the above errors have a confidence level of 95%. The purpose of this paper is to prove the viability and usefulness of the retrieval technique by demonstrating the ability to retrieve known quantities under a realistic simulation of the measurement process, excluding systematic effects.

Lightning Charge Retrievals: Dimensional Reduction, LDAR Constraints, and a First Comparison with LIS Satellite Data

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Krider, E. P.; Murray, N.; Boccippio, D. J.

2007-01-01

A "dimensional reduction" (DR) method is introduced for analyzing lightning field changes (DELTAEs) whereby the number of unknowns in a discrete two-charge model is reduced from the standard eight (x, y, z, Q, x', y', z', Q') to just four (x, y, z, Q). The four unknowns (x, y, z, Q) are found by performing a numerical minimization of a chi-square function. At each step of the minimization, an Overdetermined Fixed Matrix (OFM) method is used to immediately retrieve the best "residual source" (x', y', z', Q'), given the values of (x, y, z, Q). In this way, all 8 parameters (x, y, z, Q, x', y', z', Q') are found, yet a numerical search of only 4 parameters (x, y, z, Q) is required. The DR method has been used to analyze lightning-caused DeltaEs derived from multiple ground-based electric field measurements at the NASA Kennedy Space Center (KSC) and USAF Eastern Range (ER). The accuracy of the DR method has been assessed by comparing retrievals with data provided by the Lightning Detection And Ranging (LDAR) system at the KSC-ER, and from least squares error estimation theory, and the method is shown to be a useful "stand-alone" charge retrieval tool. Since more than one charge distribution describes a finite set of DELTAEs (i.e., solutions are non-unique), and since there can exist appreciable differences in the physical characteristics of these solutions, not all DR solutions are physically acceptable. Hence, an alternative and more accurate method of analysis is introduced that uses LDAR data to constrain the geometry of the charge solutions, thereby removing physically unacceptable retrievals. The charge solutions derived from this method are shown to compare well with independent satellite- and ground-based observations of lightning in several Florida storms.

Triple collocation based merging of satellite soil moisture retrievals

USDA-ARS?s Scientific Manuscript database

We propose a method for merging soil moisture retrievals from space borne active and passive microwave instruments based on weighted averaging taking into account the error characteristics of the individual data sets. The merging scheme is parameterized using error variance estimates obtained from u...

Remember the source: dissociating frontal and parietal contributions to episodic memory.

PubMed

Donaldson, David I; Wheeler, Mark E; Petersen, Steve E

2010-02-01

Event-related fMRI studies reveal that episodic memory retrieval modulates lateral and medial parietal cortices, dorsal middle frontal gyrus (MFG), and anterior PFC. These regions respond more for recognized old than correctly rejected new words, suggesting a neural correlate of retrieval success. Despite significant efforts examining retrieval success regions, their role in retrieval remains largely unknown. Here we asked the question, to what degree are the regions performing memory-specific operations? And if so, are they all equally sensitive to successful retrieval, or are other factors such as error detection also implicated? We investigated this question by testing whether activity in retrieval success regions was associated with task-specific contingencies (i.e., perceived targetness) or mnemonic relevance (e.g., retrieval of source context). To do this, we used a source memory task that required discrimination between remembered targets and remembered nontargets. For a given region, the modulation of neural activity by a situational factor such as target status would suggest a more domain-general role; similarly, modulations of activity linked to error detection would suggest a role in monitoring and control rather than the accumulation of evidence from memory per se. We found that parietal retrieval success regions exhibited greater activity for items receiving correct than incorrect source responses, whereas frontal retrieval success regions were most active on error trials, suggesting that posterior regions signal successful retrieval whereas frontal regions monitor retrieval outcome. In addition, perceived targetness failed to modulate fMRI activity in any retrieval success region, suggesting that these regions are retrieval specific. We discuss the different functions that these regions may support and propose an accumulator model that captures the different pattern of responses seen in frontal and parietal retrieval success regions.

Scientific Impacts of Wind Direction Errors

NASA Technical Reports Server (NTRS)

Liu, W. Timothy; Kim, Seung-Bum; Lee, Tong; Song, Y. Tony; Tang, Wen-Qing; Atlas, Robert

2004-01-01

An assessment on the scientific impact of random errors in wind direction (less than 45 deg) retrieved from space-based observations under weak wind (less than 7 m/s ) conditions was made. averages, and these weak winds cover most of the tropical, sub-tropical, and coastal oceans. Introduction of these errors in the semi-daily winds causes, on average, 5% changes of the yearly mean Ekman and Sverdrup volume transports computed directly from the winds, respectively. These poleward movements of water are the main mechanisms to redistribute heat from the warmer tropical region to the colder high- latitude regions, and they are the major manifestations of the ocean's function in modifying Earth's climate. Simulation by an ocean general circulation model shows that the wind errors introduce a 5% error in the meridional heat transport at tropical latitudes. The simulation also shows that the erroneous winds cause a pile-up of warm surface water in the eastern tropical Pacific, similar to the conditions during El Nino episode. Similar wind directional errors cause significant change in sea-surface temperature and sea-level patterns in coastal oceans in a coastal model simulation. Previous studies have shown that assimilation of scatterometer winds improves 3-5 day weather forecasts in the Southern Hemisphere. When directional information below 7 m/s was withheld, approximately 40% of the improvement was lost

Feasibility Study of ASTER SWIR data prediction

NASA Astrophysics Data System (ADS)

Yamamoto, H.; Gonzalez, L.

2017-12-01

Observation by ASTER SWIR spectral bands are unavailable since 2008 due to anomalously high SWIR detector temperatures, but ASTER VNIR and TIR spectral bands are still valid. SWIR wavelength region is however very useful to determining the land cover or discriminating rock types, etc. In this work, we present the results of a feasibility study for the prediction of ASTER SWIR bands with artificial neural networks (ANN) using ASTER valid bands. The latter are selected over three types of ground data sets, representing desert, rocky and vegetated areas. The ASTER VNIR bands are atmospherically corrected, using the US standard 62 model, without aerosol correction. To optimize the training of the ANN, it is crucial to categorize the input data. In this goal, we have built a histogram using a simple linear combination of the 3 VNIR bands, that we call contrast histogram, to split the input ASTER data in 4 areas. For each of these 4 areas, we have built six ANN, one for each SWIR band to retrieve with 3 inputs and two layers with 5 hidden nodes each and one outputs layer. The training of the ANN is done using ASTER pixels selected over several millions of pixels in representative desert, green and rocky areas. The analysis of the ANN results demonstrates that 99 % of the pixels are reconstructed with less than 20% error in desert areas. In rocky areas, the errors do not exceed 30%. However, the errors can exceed 50% in vegetated areas. This led us to improve the ANN by introducing new spectral bands (1.24, 1.64, 2.13 μm) from TERRA MODIS that is time synchronized with ASTER. The measurements are pan-sharpened to match ASTER spatial resolution. Instead of using a contrast histogram, a NDVI histogram helps us to classify the input data. With the newly constructed ANNs, the quality of the retrieved SWIR values is perceptible in particular over vegetation ( 45% of the points with less than 20% errors), and even more over the desert and rocky areas ( 75% of the points with less than 10% errors). We demonstrate that it is possible to build ANNs that are capable of regenerating, with a reasonable error, the SWIR bands in deserts and mountainous, while SWIR reconstruction in vegetation areas is more difficult. Improvements can be envisaged by introducing missing elements such as snow or ice along with a better discrimination of the vegetation.

Propagation of spectral characterization errors of imaging spectrometers at level-1 and its correction within a level-2 recalibration scheme

NASA Astrophysics Data System (ADS)

Vicent, Jorge; Alonso, Luis; Sabater, Neus; Miesch, Christophe; Kraft, Stefan; Moreno, Jose

2015-09-01

The uncertainties in the knowledge of the Instrument Spectral Response Function (ISRF), barycenter of the spectral channels and bandwidth / spectral sampling (spectral resolution) are important error sources in the processing of satellite imaging spectrometers within narrow atmospheric absorption bands. The exhaustive laboratory spectral characterization is a costly engineering process that differs from the instrument configuration in-flight given the harsh space environment and harmful launching phase. The retrieval schemes at Level-2 commonly assume a Gaussian ISRF, leading to uncorrected spectral stray-light effects and wrong characterization and correction of the spectral shift and smile. These effects produce inaccurate atmospherically corrected data and are propagated to the final Level-2 mission products. Within ESA's FLEX satellite mission activities, the impact of the ISRF knowledge error and spectral calibration at Level-1 products and its propagation to Level-2 retrieved chlorophyll fluorescence has been analyzed. A spectral recalibration scheme has been implemented at Level-2 reducing the errors in Level-1 products below the 10% error in retrieved fluorescence within the oxygen absorption bands enhancing the quality of the retrieved products. The work presented here shows how the minimization of the spectral calibration errors requires an effort both for the laboratory characterization and for the implementation of specific algorithms at Level-2.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content

PubMed Central

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2018-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available. PMID:29707470

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Efficient Methods to Assimilate Satellite Retrievals Based on Information Content. Part 2; Suboptimal Retrieval Assimilation

NASA Technical Reports Server (NTRS)

Joiner, J.; Dee, D. P.

1998-01-01

One of the outstanding problems in data assimilation has been and continues to be how best to utilize satellite data while balancing the tradeoff between accuracy and computational cost. A number of weather prediction centers have recently achieved remarkable success in improving their forecast skill by changing the method by which satellite data are assimilated into the forecast model from the traditional approach of assimilating retrievals to the direct assimilation of radiances in a variational framework. The operational implementation of such a substantial change in methodology involves a great number of technical details, e.g., pertaining to quality control procedures, systematic error correction techniques, and tuning of the statistical parameters in the analysis algorithm. Although there are clear theoretical advantages to the direct radiance assimilation approach, it is not obvious at all to what extent the improvements that have been obtained so far can be attributed to the change in methodology, or to various technical aspects of the implementation. The issue is of interest because retrieval assimilation retains many practical and logistical advantages which may become even more significant in the near future when increasingly high-volume data sources become available. The central question we address here is: how much improvement can we expect from assimilating radiances rather than retrievals, all other things being equal? We compare the two approaches in a simplified one-dimensional theoretical framework, in which problems related to quality control and systematic error correction are conveniently absent. By assuming a perfect radiative transfer model and perfect knowledge of radiance and background error covariances, we are able to formulate a nonlinear local error analysis for each assimilation method. Direct radiance assimilation is optimal in this idealized context, while the traditional method of assimilating retrievals is suboptimal because it ignores the cross-covariances between background errors and retrieval errors. We show that interactive retrieval assimilation (where the same background used for assimilation is also used in the retrieval step) is equivalent to direct assimilation of radiances with suboptimal analysis weights. We illustrate and extend these theoretical arguments with several one-dimensional assimilation experiments, where we estimate vertical atmospheric profiles using simulated data from both the High-resolution InfraRed Sounder 2 (HIRS2) and the future Atmospheric InfraRed Sounder (AIRS).

Estimation of land surface heat fluxes based on visible infrared imaging radiometer suite data: case study in northern China

NASA Astrophysics Data System (ADS)

Li, Xiaojun; Xin, Xiaozhou; Peng, Zhiqing; Zhang, Hailong; Li, Li; Shao, Shanshan; Liu, Qinhuo

2017-10-01

Evapotranspiration (ET) plays an important role in surface-atmosphere interactions and can be monitored using remote sensing data. The visible infrared imaging radiometer suite (VIIRS) sensor is a generation of optical satellite sensors that provide daily global coverage at 375- to 750-m spatial resolutions with 22 spectral channels (0.412 to 12.05 μm) and capable of monitoring ET from regional to global scales. However, few studies have focused on methods of acquiring ET from VIIRS images. The objective of this study is to introduce an algorithm that uses the VIIRS data and meteorological variables to estimate the energy budgets of land surfaces, including the net radiation, soil heat flux, sensible heat flux, and latent heat fluxes. A single-source model that based on surface energy balance equation is used to obtain surface heat fluxes within the Zhangye oasis in China. The results were validated using observations collected during the HiWATER (Heihe Watershed Allied Telemetry Experimental Research) project. To facilitate comparison, we also use moderate resolution imaging spectrometer (MODIS) data to retrieve the regional surface heat fluxes. The validation results show that it is feasible to estimate the turbulent heat flux based on the VIIRS sensor and that these data have certain advantages (i.e., the mean bias error of sensible heat flux is 15.23 W m-2) compared with MODIS data (i.e., the mean bias error of sensible heat flux is -29.36 W m-2). Error analysis indicates that, in our model, the accuracies of the estimated sensible heat fluxes rely on the errors in the retrieved surface temperatures and the canopy heights.

The dorsal stream contribution to phonological retrieval in object naming

PubMed Central

Faseyitan, Olufunsho; Kim, Junghoon; Coslett, H. Branch

2012-01-01

Meaningful speech, as exemplified in object naming, calls on knowledge of the mappings between word meanings and phonological forms. Phonological errors in naming (e.g. GHOST named as ‘goath’) are commonly seen in persisting post-stroke aphasia and are thought to signal impairment in retrieval of phonological form information. We performed a voxel-based lesion-symptom mapping analysis of 1718 phonological naming errors collected from 106 individuals with diverse profiles of aphasia. Voxels in which lesion status correlated with phonological error rates localized to dorsal stream areas, in keeping with classical and contemporary brain-language models. Within the dorsal stream, the critical voxels were concentrated in premotor cortex, pre- and postcentral gyri and supramarginal gyrus with minimal extension into auditory-related posterior temporal and temporo-parietal cortices. This challenges the popular notion that error-free phonological retrieval requires guidance from sensory traces stored in posterior auditory regions and points instead to sensory-motor processes located further anterior in the dorsal stream. In a separate analysis, we compared the lesion maps for phonological and semantic errors and determined that there was no spatial overlap, demonstrating that the brain segregates phonological and semantic retrieval operations in word production. PMID:23171662

The error structure of the SMAP single and dual channel soil moisture retrievals

USDA-ARS?s Scientific Manuscript database

Knowledge of the temporal error structure for remotely-sensed surface soil moisture retrievals can improve our ability to exploit them for hydrology and climate studies. This study employs a triple collocation type analysis to investigate both the total variance and temporal auto-correlation of erro...

Reconstruction of Atmospheric Tracer Releases with Optimal Resolution Features: Concentration Data Assimilation

NASA Astrophysics Data System (ADS)

Singh, Sarvesh Kumar; Turbelin, Gregory; Issartel, Jean-Pierre; Kumar, Pramod; Feiz, Amir Ali

2015-04-01

The fast growing urbanization, industrialization and military developments increase the risk towards the human environment and ecology. This is realized in several past mortality incidents, for instance, Chernobyl nuclear explosion (Ukraine), Bhopal gas leak (India), Fukushima-Daichi radionuclide release (Japan), etc. To reduce the threat and exposure to the hazardous contaminants, a fast and preliminary identification of unknown releases is required by the responsible authorities for the emergency preparedness and air quality analysis. Often, an early detection of such contaminants is pursued by a distributed sensor network. However, identifying the origin and strength of unknown releases following the sensor reported concentrations is a challenging task. This requires an optimal strategy to integrate the measured concentrations with the predictions given by the atmospheric dispersion models. This is an inverse problem. The measured concentrations are insufficient and atmospheric dispersion models suffer from inaccuracy due to the lack of process understanding, turbulence uncertainties, etc. These lead to a loss of information in the reconstruction process and thus, affect the resolution, stability and uniqueness of the retrieved source. An additional well known issue is the numerical artifact arisen at the measurement locations due to the strong concentration gradient and dissipative nature of the concentration. Thus, assimilation techniques are desired which can lead to an optimal retrieval of the unknown releases. In general, this is facilitated within the Bayesian inference and optimization framework with a suitable choice of a priori information, regularization constraints, measurement and background error statistics. An inversion technique is introduced here for an optimal reconstruction of unknown releases using limited concentration measurements. This is based on adjoint representation of the source-receptor relationship and utilization of a weight function which exhibits a priori information about the unknown releases apparent to the monitoring network. The properties of the weight function provide an optimal data resolution and model resolution to the retrieved source estimates. The retrieved source estimates are proved theoretically to be stable against the random measurement errors and their reliability can be interpreted in terms of the distribution of the weight functions. Further, the same framework can be extended for the identification of the point type releases by utilizing the maximum of the retrieved source estimates. The inversion technique has been evaluated with the several diffusion experiments, like, Idaho low wind diffusion experiment (1974), IIT Delhi tracer experiment (1991), European Tracer Experiment (1994), Fusion Field Trials (2007), etc. In case of point release experiments, the source parameters are mostly retrieved close to the true source parameters with least error. Primarily, the proposed technique overcomes two major difficulties incurred in the source reconstruction: (i) The initialization of the source parameters as required by the optimization based techniques. The converged solution depends on their initialization. (ii) The statistical knowledge about the measurement and background errors as required by the Bayesian inference based techniques. These are hypothetically assumed in case of no prior knowledge.

AOT Retrieval Procedure for Distributed Measurements With Low-Cost Sun Photometers

NASA Astrophysics Data System (ADS)

Toledo, F.; Garrido, C.; Díaz, M.; Rondanelli, R.; Jorquera, S.; Valdivieso, P.

2018-01-01

We propose a new application of inexpensive light-emitting diode (LED)-based Sun photometers, consisting of measuring the aerosol optical thickness (AOT) with high resolution within metropolitan scales. Previously, these instruments have been used at continental scales by the GLOBE program, but this extension is already covered by more expensive and higher-precision instruments of the AERONET global network. For this we built an open source two-channeled LED-based Sun photometer based on previous developments, with improvements in the hardware, software, and modifications on the calibration procedure. Among these we highlight the use of MODTRAN to characterize the effect introduced by using LED sensors in the AOT retrieval, an open design available for the scientific community and a calibration procedure that takes advantage of a CIMEL Sun photometer located within the city, enables the intercomparison of several LED Sun photometers with a common reference. We estimated the root-mean-square error in the AOT retrieved by the prototypes as 0.006 at the 564 nm and 0.009 at the 408 nm. This error is way under the magnitude of the AOT daily cycle variability measured by us in our campaigns, even for distances closer than 15 km. In addition to inner city campaigns, we also show aerosol-tracing applications by measuring AOT variations from the city of Santiago to the Andes glaciers. Measuring AOT at high spatial resolution in urban areas can improve our understanding of urban scale aerosol circulation, providing information for solar energy planning, health policies, and climatological studies, among others.

Learning to Fail in Aphasia: An Investigation of Error Learning in Naming

PubMed Central

Middleton, Erica L.; Schwartz, Myrna F.

2013-01-01

Purpose To determine if the naming impairment in aphasia is influenced by error learning and if error learning is related to type of retrieval strategy. Method Nine participants with aphasia and ten neurologically-intact controls named familiar proper noun concepts. When experiencing tip-of-the-tongue naming failure (TOT) in an initial TOT-elicitation phase, participants were instructed to adopt phonological or semantic self-cued retrieval strategies. In the error learning manipulation, items evoking TOT states during TOT-elicitation were randomly assigned to a short or long time condition where participants were encouraged to continue to try to retrieve the name for either 20 seconds (short interval) or 60 seconds (long). The incidence of TOT on the same items was measured on a post test after 48-hours. Error learning was defined as a higher rate of recurrent TOTs (TOT at both TOT-elicitation and post test) for items assigned to the long (versus short) time condition. Results In the phonological condition, participants with aphasia showed error learning whereas controls showed a pattern opposite to error learning. There was no evidence for error learning in the semantic condition for either group. Conclusion Error learning is operative in aphasia, but dependent on the type of strategy employed during naming failure. PMID:23816662

A Bayesian approach to microwave precipitation profile retrieval

NASA Technical Reports Server (NTRS)

Evans, K. Franklin; Turk, Joseph; Wong, Takmeng; Stephens, Graeme L.

1995-01-01

A multichannel passive microwave precipitation retrieval algorithm is developed. Bayes theorem is used to combine statistical information from numerical cloud models with forward radiative transfer modeling. A multivariate lognormal prior probability distribution contains the covariance information about hydrometeor distribution that resolves the nonuniqueness inherent in the inversion process. Hydrometeor profiles are retrieved by maximizing the posterior probability density for each vector of observations. The hydrometeor profile retrieval method is tested with data from the Advanced Microwave Precipitation Radiometer (10, 19, 37, and 85 GHz) of convection over ocean and land in Florida. The CP-2 multiparameter radar data are used to verify the retrieved profiles. The results show that the method can retrieve approximate hydrometeor profiles, with larger errors over land than water. There is considerably greater accuracy in the retrieval of integrated hydrometeor contents than of profiles. Many of the retrieval errors are traced to problems with the cloud model microphysical information, and future improvements to the algorithm are suggested.

Columnar aerosol properties over oceans by combining surface and aircraft measurements: sensitivity analysis.

PubMed

Zhang, T; Gordon, H R

1997-04-20

We report a sensitivity analysis for the algorithm presented by Gordon and Zhang [Appl. Opt. 34, 5552 (1995)] for inverting the radiance exiting the top and bottom of the atmosphere to yield the aerosol-scattering phase function [P(?)] and single-scattering albedo (omega(0)). The study of the algorithm's sensitivity to radiometric calibration errors, mean-zero instrument noise, sea-surface roughness, the curvature of the Earth's atmosphere, the polarization of the light field, and incorrect assumptions regarding the vertical structure of the atmosphere, indicates that the retrieved omega(0) has excellent stability even for very large values (~2) of the aerosol optical thickness; however, the error in the retrieved P(?) strongly depends on the measurement error and on the assumptions made in the retrieval algorithm. The retrieved phase functions in the blue are usually poor compared with those in the near infrared.

Prediction Error Demarcates the Transition from Retrieval, to Reconsolidation, to New Learning

ERIC Educational Resources Information Center

Sevenster, Dieuwke; Beckers, Tom; Kindt, Merel

2014-01-01

Although disrupting reconsolidation is promising in targeting emotional memories, the conditions under which memory becomes labile are still unclear. The current study showed that post-retrieval changes in expectancy as an index for prediction error may serve as a read-out for the underlying processes engaged by memory reactivation. Minor…

Reconsolidation from negative emotional pictures: is successful retrieval required?

PubMed

Finn, Bridgid; Roediger, Henry L; Rosenzweig, Emily

2012-10-01

Finn and Roediger (Psychological science 22:781-786, 2011) found that when a negative emotional picture was presented immediately after a successful retrieval, later test performance was enhanced as compared to when a neutral picture or a blank screen had been shown. This finding implicates the period immediately following retrieval as playing an important role in determining later retention via reconsolidation. In two new experiments, we investigated whether successful retrieval was required to show the enhancing effect of negative emotion on later recall. In both experiments, the participants studied Swahili-English vocabulary pairs, took an intervening cued-recall test, and were given a final cued-recall test on all items. In Experiment 1, we tested a distinctiveness explanation of the effect. The results showed that neither presentation of a negative picture just prior to successful retrieval nor presentation of a positive picture after successful retrieval produced the enhancing effect that was seen when negative pictures were presented after successful retrieval. In Experiment 2, we tested whether the enhancing effect would occur when a negative picture followed an unsuccessful retrieval attempt with feedback, and a larger enhancement effect occurred after errors of commission than after errors of omission. These results indicate that effort in retrieving is critical to the enhancing effect shown with negative pictures; whether the target is produced by the participant or given by an external source following a commission error does not matter. We interpret these results as support for semantic enrichment as a key element in producing the enhancing effect of negative pictures that are presented after a retrieval attempt.

Cirrus Cloud Optical Thickness and Effective Diameter Retrieved by MODIS: Impacts of Single Habit Assumption, 3-D Radiative Effects, and Cloud Inhomogeneity

NASA Astrophysics Data System (ADS)

Zhou, Yongbo; Sun, Xuejin; Mielonen, Tero; Li, Haoran; Zhang, Riwei; Li, Yan; Zhang, Chuanliang

2018-01-01

For inhomogeneous cirrus clouds, cloud optical thickness (COT) and effective diameter (De) provided by the Moderate Resolution Imaging Spectrometer (MODIS) Collection 6 cloud products are associated with errors due to the single habit assumption (SHA), independent pixel assumption (IPA), photon absorption effect (PAE), and plane-parallel assumption (PPA). SHA means that every cirrus cloud is assumed to have the same shape habit of ice crystals. IPA errors are caused by three-dimensional (3D) radiative effects. PPA and PAE errors are caused by cloud inhomogeneity. We proposed a method to single out these different errors. These errors were examined using the Spherical Harmonics Discrete Ordinate Method simulations done for the MODIS 0.86 μm and 2.13 μm bands. Four midlatitude and tropical cirrus cases were studied. For the COT retrieval, the impacts of SHA and IPA were especially large for optically thick cirrus cases. SHA errors in COT varied distinctly with scattering angles. For the De retrieval, SHA decreased De under most circumstances. PAE decreased De for optically thick cirrus cases. For the COT and De retrievals, the dominant error source was SHA for overhead sun whereas for oblique sun, it could be any of SHA, IPA, and PAE, varying with cirrus cases and sun-satellite viewing geometries. On the domain average, the SHA errors in COT (De) were within -16.1%-42.6% (-38.7%-2.0%), whereas the 3-D radiative effects- and cloud inhomogeneity-induced errors in COT (De) were within -5.6%-19.6% (-2.9%-8.0%) and -2.6%-0% (-3.7%-9.8%), respectively.

Validation of YCAR algorithm over East Asia TCCON sites

NASA Astrophysics Data System (ADS)

Kim, W.; Kim, J.; Jung, Y.; Lee, H.; Goo, T. Y.; Cho, C. H.; Lee, S.

2016-12-01

In order to reduce the retrieval error of TANSO-FTS column averaged CO2 concentration (XCO2) induced by aerosol, we develop the Yonsei university CArbon Retrieval (YCAR) algorithm using aerosol information from TANSO-Cloud and Aerosol Imager (TANSO-CAI), providing simultaneous aerosol optical depth properties for the same geometry and optical path along with the FTS. Also we validate the retrieved results using ground-based TCCON measurement. Particularly this study first utilized the measurements at Anmyeondo, the only TCCON site located in South Korea, which can improve the quality of validation in East Asia. After the post screening process, YCAR algorithms have higher data availability by 33 - 85 % than other operational algorithms (NIES, ACOS, UoL). Although the YCAR algorithm has higher data availability, regression analysis with TCCON measurements are better or similar to other algorithms; Regression line of YCAR algorithm is close to linear identity function with RMSE of 2.05, bias of - 0.86 ppm. According to error analysis, retrieval error of YCAR algorithm is 1.394 - 1.478 ppm at East Asia. In addition, spatio-temporal sampling error of 0.324 - 0.358 ppm for each single sounding retrieval is also analyzed with Carbon Tracker - Asia data. These results of error analysis reveal the reliability and accuracy of latest version of our YCAR algorithm. Both XCO2 values retrieved using YCAR algorithm on TANSO-FTS and TCCON measurements show the consistent increasing trend about 2.3 - 2.6 ppm per year. Comparing to the increasing rate of global background CO2 amount measured in Mauna Loa, Hawaii (2 ppm per year), the increasing trend in East Asia shows about 30% higher trend due to the rapid increase of CO2 emission from the source region.

CALIPSO-Inferred Aerosol Direct Radiative Effects: Bias Estimates Using Ground-Based Raman Lidars

NASA Technical Reports Server (NTRS)

Thorsen, Tyler; Fu, Qiang

2016-01-01

Observational constraints on the change in the radiative energy budget caused by the presence of aerosols, i.e. the aerosol direct radiative effect (DRE), have recently been made using observations from the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO). CALIPSO observations have the potential to provide improved global estimates of aerosol DRE compared to passive sensor-derived estimates due to CALIPSO's ability to perform vertically-resolved aerosol retrievals over all surface types and over cloud. In this study we estimate the uncertainties in CALIPSO-inferred aerosol DRE using multiple years of observations from the Atmospheric Radiation Measurement (ARM) program's Raman lidars (RL) at midlatitude and tropical sites. Examined are assumptions about the ratio of extinction-to-backscatter (i.e. the lidar ratio) made by the CALIPSO retrievals, which are needed to retrieve the aerosol extinction profile. The lidar ratio is shown to introduce minimal error in the mean aerosol DRE at the top-of-atmosphere and surface. It is also shown that CALIPSO is unable to detect all radiatively-significant aerosol, resulting in an underestimate in the magnitude of the aerosol DRE by 30-50%. Therefore, global estimates of the aerosol DRE inferred from CALIPSO observations are likely too weak.

Effects of Systematic and Random Errors on the Retrieval of Particle Microphysical Properties from Multiwavelength Lidar Measurements Using Inversion with Regularization

NASA Technical Reports Server (NTRS)

Ramirez, Daniel Perez; Whiteman, David N.; Veselovskii, Igor; Kolgotin, Alexei; Korenskiy, Michael; Alados-Arboledas, Lucas

2013-01-01

In this work we study the effects of systematic and random errors on the inversion of multiwavelength (MW) lidar data using the well-known regularization technique to obtain vertically resolved aerosol microphysical properties. The software implementation used here was developed at the Physics Instrumentation Center (PIC) in Troitsk (Russia) in conjunction with the NASA/Goddard Space Flight Center. Its applicability to Raman lidar systems based on backscattering measurements at three wavelengths (355, 532 and 1064 nm) and extinction measurements at two wavelengths (355 and 532 nm) has been demonstrated widely. The systematic error sensitivity is quantified by first determining the retrieved parameters for a given set of optical input data consistent with three different sets of aerosol physical parameters. Then each optical input is perturbed by varying amounts and the inversion is repeated. Using bimodal aerosol size distributions, we find a generally linear dependence of the retrieved errors in the microphysical properties on the induced systematic errors in the optical data. For the retrievals of effective radius, number/surface/volume concentrations and fine-mode radius and volume, we find that these results are not significantly affected by the range of the constraints used in inversions. But significant sensitivity was found to the allowed range of the imaginary part of the particle refractive index. Our results also indicate that there exists an additive property for the deviations induced by the biases present in the individual optical data. This property permits the results here to be used to predict deviations in retrieved parameters when multiple input optical data are biased simultaneously as well as to study the influence of random errors on the retrievals. The above results are applied to questions regarding lidar design, in particular for the spaceborne multiwavelength lidar under consideration for the upcoming ACE mission.

Performance Analysis of Grey-World-based Feature Detection and Matching for Mobile Positioning Systems

NASA Astrophysics Data System (ADS)

Bejuri, Wan Mohd Yaakob Wan; Mohamad, Mohd Murtadha

2014-11-01

This paper introduces a new grey-world-based feature detection and matching algorithm, intended for use with mobile positioning systems. This approach uses a combination of a wireless local area network (WLAN) and a mobile phone camera to determine positioning in an illumination environment using a practical and pervasive approach. The signal combination is based on retrieved signal strength from the WLAN access point and the image processing information from the building hallways. The results show our method can handle information better than Harlan Hile's method relative to the illumination environment, producing lower illumination error in five (5) different environments.

Multi-layer Retrievals of Greenhouse Gases from a Combined Use of GOSAT TANSO-FTS SWIR and TIR

NASA Astrophysics Data System (ADS)

Kikuchi, N.; Kuze, A.; Kataoka, F.; Shiomi, K.; Hashimoto, M.; Suto, H.; Knuteson, R. O.; Iraci, L. T.; Yates, E. L.; Gore, W.; Tanaka, T.; Yokota, T.

2016-12-01

The TANSO-FTS sensor onboard GOSAT has three frequency bands in the shortwave infrared (SWIR) and the fourth band in the thermal infrared (TIR). Observations of high-resolution spectra of reflected sunlight in the SWIR are extensively utilized to retrieve column-averaged concentrations of the major greenhouse gases such as carbon dioxide (XCO2) and methane (XCH4). Although global XCO2 and XCH4 distribution retrieved from SWIR data can reduce the uncertainty in the current knowledge about sources and sinks of these gases, information on the vertical profiles would be more useful to constrain the surface flux and also to identify the local emission sources. Based on the degrees of freedom for signal, Kulawik et al. (2016, IWGGMS-12 presentation) shows that 2-layer information on the concentration of CO2 can be extracted from TANSO-FTS SWIR measurements, and the retrieval error is predicted to be about 5 ppm in the lower troposphere. In this study, we present multi-layer retrievals of CO2 and CH4 from a combined use of measurements of TANSO-FTS SWIR and TIR. We selected GOSAT observations at Railroad Valley Playa in Nevada, USA, which is a vicarious calibration site for TANSO-FTS, as we have various ancillary data including atmospheric temperature and humidity taken by a radiosonde, surface temperature, and surface emissivity with a ground based FTS. All of these data are useful especially for retrievals using TIR spectra. Currently, we use the 700-800 cm-1 and 1200-1300 cm-1 TIR windows for CO2 and CH4 retrievals, respectively, in addition to the SWIR bands. We found that by adding TIR windows, 3-layer information can be extracted, and the predicted retrieval error in the CO2 concentration was reduced about 1 ppm in the lower troposphere. We expect that the retrieval error could be further reduced by optimizing TIR windows and by reducing systematic forward model errors.

Error analysis of the greenhouse-gases monitor instrument short wave infrared XCO2 retrieval algorithm

NASA Astrophysics Data System (ADS)

Wu, Hao; Wang, Xianhua; Ye, Hanhan; Jiang, Yun; Duan, Fenghua

2018-01-01

We developed an algorithm (named GMI_XCO2) to retrieve the global column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO2) for greenhouse-gases monitor instrument (GMI) and directional polarized camera (DPC) on the GF-5 satellite. This algorithm is designed to work in cloudless atmospheric conditions with aerosol optical thickness (AOT)<0.3. To quantify the uncertainty level of the retrieved XCO2 when the aerosols and cirrus clouds occurred in retrieving XCO2 with the GMI short wave infrared (SWIR) data, we analyzed the errors rate caused by the six types of aerosols and cirrus clouds. The results indicated that in AOT range of 0.05 to 0.3 (550 nm), the uncertainties of aerosols could lead to errors of -0.27% to 0.59%, -0.32% to 1.43%, -0.10% to 0.49%, -0.12% to 1.17%, -0.35% to 0.49%, and -0.02% to -0.24% for rural, dust, clean continental, maritime, urban, and soot aerosols, respectively. The retrieval results presented a large error due to cirrus clouds. In the cirrus optical thickness range of 0.05 to 0.8 (500 nm), the most underestimation is up to 26.25% when the surface albedo is 0.05. The most overestimation is 8.1% when the surface albedo is 0.65. The retrieval results of GMI simulation data demonstrated that the accuracy of our algorithm is within 4 ppm (˜1%) using the simultaneous measurement of aerosols and clouds from DPC. Moreover, the speed of our algorithm is faster than full-physics (FP) methods. We verified our algorithm with Greenhouse-gases Observing Satellite (GOSAT) data in Beijing area during 2016. The retrieval errors of most observations are within 4 ppm except for summer. Compared with the results of GOSAT, the correlation coefficient is 0.55 for the whole year data, increasing to 0.62 after excluding the summer data.

Melody Alignment and Similarity Metric for Content-Based Music Retrieval

NASA Astrophysics Data System (ADS)

Zhu, Yongwei; Kankanhalli, Mohan S.

2003-01-01

Music query-by-humming has attracted much research interest recently. It is a challenging problem since the hummed query inevitably contains much variation and inaccuracy. Furthermore, the similarity computation between the query tune and the reference melody is not easy due to the difficulty in ensuring proper alignment. This is because the query tune can be rendered at an unknown speed and it is usually an arbitrary subsequence of the target reference melody. Many of the previous methods, which adopt note segmentation and string matching, suffer drastically from the errors in the note segmentation, which affects retrieval accuracy and efficiency. Some methods solve the alignment issue by controlling the speed of the articulation of queries, which is inconvenient because it forces users to hum along a metronome. Some other techniques introduce arbitrary rescaling in time but this is computationally very inefficient. In this paper, we introduce a melody alignment technique, which addresses the robustness and efficiency issues. We also present a new melody similarity metric, which is performed directly on melody contours of the query data. This approach cleanly separates the alignment and similarity measurement in the search process. We show how to robustly and efficiently align the query melody with the reference melodies and how to measure the similarity subsequently. We have carried out extensive experiments. Our melody alignment method can reduce the matching candidate to 1.7% with 95% correct alignment rate. The overall retrieval system achieved 80% recall in the top 10 rank list. The results demonstrate the robustness and effectiveness the proposed methods.

Retrieving Storm Electric Fields From Aircraft Field Mill Data. Part 2; Applications

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Mach, D. M.; Christian, H. J.; Stewart, M. F.; Bateman, M. G.

2005-01-01

The Lagrange multiplier theory and "pitch down method" developed in Part I of this study are applied to complete the calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the method performs well in computer simulations. For mill measurement errors of 1 V/m and a 5 V/m error in the mean fair weather field function, the 3-D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair weather field was also tested using computer simulations. For mill measurement errors of 1 V/m, the method retrieves the 3-D storm field to within an error of about 8% if the fair weather field estimate is typically within 1 V/m of the true fair weather field. Using this side constraint and data from fair weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. The resulting calibration matrix was then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably with the results obtained from earlier calibration analyses that were based on iterative techniques.

Assessing systematic errors in GOSAT CO2 retrievals by comparing assimilated fields to independent CO2 data

NASA Astrophysics Data System (ADS)

Baker, D. F.; Oda, T.; O'Dell, C.; Wunch, D.; Jacobson, A. R.; Yoshida, Y.; Partners, T.

2012-12-01

Measurements of column CO2 concentration from space are now being taken at a spatial and temporal density that permits regional CO2 sources and sinks to be estimated. Systematic errors in the satellite retrievals must be minimized for these estimates to be useful, however. CO2 retrievals from the TANSO instrument aboard the GOSAT satellite are compared to similar column retrievals from the Total Carbon Column Observing Network (TCCON) as the primary method of validation; while this is a powerful approach, it can only be done for overflights of 10-20 locations and has not, for example, permitted validation of GOSAT data over the oceans or deserts. Here we present a complementary approach that uses a global atmospheric transport model and flux inversion method to compare different types of CO2 measurements (GOSAT, TCCON, surface in situ, and aircraft) at different locations, at the cost of added transport error. The measurements from any single type of data are used in a variational carbon data assimilation method to optimize surface CO2 fluxes (with a CarbonTracker prior), then the corresponding optimized CO2 concentration fields are compared to those data types not inverted, using the appropriate vertical weighting. With this approach, we find that GOSAT column CO2 retrievals from the ACOS project (version 2.9 and 2.10) contain systematic errors that make the modeled fit to the independent data worse. However, we find that the differences between the GOSAT data and our prior model are correlated with certain physical variables (aerosol amount, surface albedo, correction to total column mass) that are likely driving errors in the retrievals, independent of CO2 concentration. If we correct the GOSAT data using a fit to these variables, then we find the GOSAT data to improve the fit to independent CO2 data, which suggests that the useful information in the measurements outweighs the negative impact of the remaining systematic errors. With this assurance, we compare the flux estimates given by assimilating the ACOS GOSAT retrievals to similar ones given by NIES GOSAT column retrievals, bias-corrected in a similar manner. Finally, we have found systematic differences on the order of a half ppm between column CO2 integrals from 18 TCCON sites and those given by assimilating NOAA in situ data (both surface and aircraft profile) in this approach. We assess how these differences change in switching to a newer version of the TCCON retrieval software.

Dynamic statistical optimization of GNSS radio occultation bending angles: advanced algorithm and performance analysis

NASA Astrophysics Data System (ADS)

Li, Y.; Kirchengast, G.; Scherllin-Pirscher, B.; Norman, R.; Yuan, Y. B.; Fritzer, J.; Schwaerz, M.; Zhang, K.

2015-08-01

We introduce a new dynamic statistical optimization algorithm to initialize ionosphere-corrected bending angles of Global Navigation Satellite System (GNSS)-based radio occultation (RO) measurements. The new algorithm estimates background and observation error covariance matrices with geographically varying uncertainty profiles and realistic global-mean correlation matrices. The error covariance matrices estimated by the new approach are more accurate and realistic than in simplified existing approaches and can therefore be used in statistical optimization to provide optimal bending angle profiles for high-altitude initialization of the subsequent Abel transform retrieval of refractivity. The new algorithm is evaluated against the existing Wegener Center Occultation Processing System version 5.6 (OPSv5.6) algorithm, using simulated data on two test days from January and July 2008 and real observed CHAllenging Minisatellite Payload (CHAMP) and Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) measurements from the complete months of January and July 2008. The following is achieved for the new method's performance compared to OPSv5.6: (1) significant reduction of random errors (standard deviations) of optimized bending angles down to about half of their size or more; (2) reduction of the systematic differences in optimized bending angles for simulated MetOp data; (3) improved retrieval of refractivity and temperature profiles; and (4) realistically estimated global-mean correlation matrices and realistic uncertainty fields for the background and observations. Overall the results indicate high suitability for employing the new dynamic approach in the processing of long-term RO data into a reference climate record, leading to well-characterized and high-quality atmospheric profiles over the entire stratosphere.

Topographical gradients of semantics and phonology revealed by temporal lobe stimulation.

PubMed

Miozzo, Michele; Williams, Alicia C; McKhann, Guy M; Hamberger, Marla J

2017-02-01

Word retrieval is a fundamental component of oral communication, and it is well established that this function is supported by left temporal cortex. Nevertheless, the specific temporal areas mediating word retrieval and the particular linguistic processes these regions support have not been well delineated. Toward this end, we analyzed over 1000 naming errors induced by left temporal cortical stimulation in epilepsy surgery patients. Errors were primarily semantic (lemon → "pear"), phonological (horn → "corn"), non-responses, and delayed responses (correct responses after a delay), and each error type appeared predominantly in a specific region: semantic errors in mid-middle temporal gyrus (TG), phonological errors and delayed responses in middle and posterior superior TG, and non-responses in anterior inferior TG. To the extent that semantic errors, phonological errors and delayed responses reflect disruptions in different processes, our results imply topographical specialization of semantic and phonological processing. Specifically, results revealed an inferior-to-superior gradient, with more superior regions associated with phonological processing. Further, errors were increasingly semantically related to targets toward posterior temporal cortex. We speculate that detailed semantic input is needed to support phonological retrieval, and thus, the specificity of semantic input increases progressively toward posterior temporal regions implicated in phonological processing. Hum Brain Mapp 38:688-703, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Random Error in Judgment: The Contribution of Encoding and Retrieval Processes

ERIC Educational Resources Information Center

Pleskac, Timothy J.; Dougherty, Michael R.; Rivadeneira, A. Walkyria; Wallsten, Thomas S.

2009-01-01

Theories of confidence judgments have embraced the role random error plays in influencing responses. An important next step is to identify the source(s) of these random effects. To do so, we used the stochastic judgment model (SJM) to distinguish the contribution of encoding and retrieval processes. In particular, we investigated whether dividing…

Single-footprint retrievals for AIRS using a fast TwoSlab cloud-representation model and the SARTA all-sky infrared radiative transfer algorithm

NASA Astrophysics Data System (ADS)

DeSouza-Machado, Sergio; Larrabee Strow, L.; Tangborn, Andrew; Huang, Xianglei; Chen, Xiuhong; Liu, Xu; Wu, Wan; Yang, Qiguang

2018-01-01

One-dimensional variational retrievals of temperature and moisture fields from hyperspectral infrared (IR) satellite sounders use cloud-cleared radiances (CCRs) as their observation. These derived observations allow the use of clear-sky-only radiative transfer in the inversion for geophysical variables but at reduced spatial resolution compared to the native sounder observations. Cloud clearing can introduce various errors, although scenes with large errors can be identified and ignored. Information content studies show that, when using multilayer cloud liquid and ice profiles in infrared hyperspectral radiative transfer codes, there are typically only 2-4 degrees of freedom (DOFs) of cloud signal. This implies a simplified cloud representation is sufficient for some applications which need accurate radiative transfer. Here we describe a single-footprint retrieval approach for clear and cloudy conditions, which uses the thermodynamic and cloud fields from numerical weather prediction (NWP) models as a first guess, together with a simple cloud-representation model coupled to a fast scattering radiative transfer algorithm (RTA). The NWP model thermodynamic and cloud profiles are first co-located to the observations, after which the N-level cloud profiles are converted to two slab clouds (TwoSlab; typically one for ice and one for water clouds). From these, one run of our fast cloud-representation model allows an improvement of the a priori cloud state by comparing the observed and model-simulated radiances in the thermal window channels. The retrieval yield is over 90 %, while the degrees of freedom correlate with the observed window channel brightness temperature (BT) which itself depends on the cloud optical depth. The cloud-representation and scattering package is benchmarked against radiances computed using a maximum random overlap (RMO) cloud scheme. All-sky infrared radiances measured by NASA's Atmospheric Infrared Sounder (AIRS) and NWP thermodynamic and cloud profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model are used in this paper.

Zero- to low-field MRI with averaging of concomitant gradient fields.

PubMed

Meriles, Carlos A; Sakellariou, Dimitris; Trabesinger, Andreas H; Demas, Vasiliki; Pines, Alexander

2005-02-08

Magnetic resonance imaging (MRI) encounters fundamental limits in circumstances in which the static magnetic field is not sufficiently strong to truncate unwanted, so-called concomitant components of the gradient field. This limitation affects the attainable optimal image fidelity and resolution most prominently in low-field imaging. In this article, we introduce the use of pulsed magnetic-field averaging toward relaxing these constraints. It is found that the image of an object can be retrieved by pulsed low fields in the presence of the full spatial variation of the imaging encoding gradient field even in the absence of the typical uniform high-field time-independent contribution. In addition, error-compensation schemes can be introduced through the application of symmetrized pulse sequences. Such schemes substantially mitigate artifacts related to evolution in strong magnetic-field gradients, magnetic fields that vary in direction and orientation, and imperfections of the applied field pulses.

Recent Theoretical Advances in Analysis of AIRS/AMSU Sounding Data

NASA Technical Reports Server (NTRS)

Susskind, Joel

2007-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. This paper describes the AIRS Science Team Version 5.0 retrieval algorithm. Starting in early 2007, the Goddard DAAC will use this algorithm to analyze near real time AIRS/AMSU observations. These products are then made available to the scientific community for research purposes. The products include twice daily measurements of the Earth's three dimensional global temperature, water vapor, and ozone distribution as well as cloud cover. In addition, accurate twice daily measurements of the earth's land and ocean temperatures are derived and reported. Scientists use this important set of observations for two major applications. They provide important information for climate studies of global and regional variability and trends of different aspects of the earth's atmosphere. They also provide information for researchers to improve the skill of weather forecasting. A very important new product of the AIRS Version 5 algorithm is accurate case-by-case error estimates of the retrieved products. This heightens their utility for use in both weather and climate applications. These error estimates are also used directly for quality control of the retrieved products. Version 5 also allows for accurate quality controlled AIRS only retrievals, called "Version 5 AO retrievals" which can be used as a backup methodology if AMSU fails. Examples of the accuracy of error estimates and quality controlled retrieval products of the AIRS/AMSU Version 5 and Version 5 AO algorithms are given, and shown to be significantly better than the previously used Version 4 algorithm. Assimilation of Version 5 retrievals are also shown to significantly improve forecast skill, especially when the case-by-case error estimates are utilized in the data assimilation process.

Adaptive neuro-fuzzy inference system for temperature and humidity profile retrieval from microwave radiometer observations

NASA Astrophysics Data System (ADS)

Ramesh, K.; Kesarkar, A. P.; Bhate, J.; Venkat Ratnam, M.; Jayaraman, A.

2015-01-01

The retrieval of accurate profiles of temperature and water vapour is important for the study of atmospheric convection. Recent development in computational techniques motivated us to use adaptive techniques in the retrieval algorithms. In this work, we have used an adaptive neuro-fuzzy inference system (ANFIS) to retrieve profiles of temperature and humidity up to 10 km over the tropical station Gadanki (13.5° N, 79.2° E), India. ANFIS is trained by using observations of temperature and humidity measurements by co-located Meisei GPS radiosonde (henceforth referred to as radiosonde) and microwave brightness temperatures observed by radiometrics multichannel microwave radiometer MP3000 (MWR). ANFIS is trained by considering these observations during rainy and non-rainy days (ANFIS(RD + NRD)) and during non-rainy days only (ANFIS(NRD)). The comparison of ANFIS(RD + NRD) and ANFIS(NRD) profiles with independent radiosonde observations and profiles retrieved using multivariate linear regression (MVLR: RD + NRD and NRD) and artificial neural network (ANN) indicated that the errors in the ANFIS(RD + NRD) are less compared to other retrieval methods. The Pearson product movement correlation coefficient (r) between retrieved and observed profiles is more than 92% for temperature profiles for all techniques and more than 99% for the ANFIS(RD + NRD) technique Therefore this new techniques is relatively better for the retrieval of temperature profiles. The comparison of bias, mean absolute error (MAE), RMSE and symmetric mean absolute percentage error (SMAPE) of retrieved temperature and relative humidity (RH) profiles using ANN and ANFIS also indicated that profiles retrieved using ANFIS(RD + NRD) are significantly better compared to the ANN technique. The analysis of profiles concludes that retrieved profiles using ANFIS techniques have improved the temperature retrievals substantially; however, the retrieval of RH by all techniques considered in this paper (ANN, MVLR and ANFIS) has limited success.

Propagation based phase retrieval of simulated intensity measurements using artificial neural networks

NASA Astrophysics Data System (ADS)

Kemp, Z. D. C.

2018-04-01

Determining the phase of a wave from intensity measurements has many applications in fields such as electron microscopy, visible light optics, and medical imaging. Propagation based phase retrieval, where the phase is obtained from defocused images, has shown significant promise. There are, however, limitations in the accuracy of the retrieved phase arising from such methods. Sources of error include shot noise, image misalignment, and diffraction artifacts. We explore the use of artificial neural networks (ANNs) to improve the accuracy of propagation based phase retrieval algorithms applied to simulated intensity measurements. We employ a phase retrieval algorithm based on the transport-of-intensity equation to obtain the phase from simulated micrographs of procedurally generated specimens. We then train an ANN with pairs of retrieved and exact phases, and use the trained ANN to process a test set of retrieved phase maps. The total error in the phase is significantly reduced using this method. We also discuss a variety of potential extensions to this work.

The GRAPE aerosol retrieval algorithm

NASA Astrophysics Data System (ADS)

Thomas, G. E.; Poulsen, C. A.; Sayer, A. M.; Marsh, S. H.; Dean, S. M.; Carboni, E.; Siddans, R.; Grainger, R. G.; Lawrence, B. N.

2009-11-01

The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations - this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.

The GRAPE aerosol retrieval algorithm

NASA Astrophysics Data System (ADS)

Thomas, G. E.; Poulsen, C. A.; Sayer, A. M.; Marsh, S. H.; Dean, S. M.; Carboni, E.; Siddans, R.; Grainger, R. G.; Lawrence, B. N.

2009-04-01

The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations - this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.

Effect of stratospheric aerosol layers on the TOMS/SBUV ozone retrieval

NASA Technical Reports Server (NTRS)

Torres, O.; Ahmad, Zia; Pan, L.; Herman, J. R.; Bhartia, P. K.; Mcpeters, R.

1994-01-01

An evaluation of the optical effects of stratospheric aerosol layers on total ozone retrieval from space by the TOMS/SBUV type instruments is presented here. Using the Dave radiative transfer model we estimate the magnitude of the errors in the retrieved ozone when polar stratospheric clouds (PSC's) or volcanic aerosol layers interfere with the measurements. The largest errors are produced by optically thick water ice PSC's. Results of simulation experiments on the effect of the Pinatubo aerosol cloud on the Nimbus-7 and Meteor-3 TOMS products are presented.

Observations of cloud liquid water path over oceans: Optical and microwave remote sensing methods

NASA Technical Reports Server (NTRS)

Lin, Bing; Rossow, William B.

1994-01-01

Published estimates of cloud liquid water path (LWP) from satellite-measured microwave radiation show little agreement, even about the relative magnitudes of LWP in the tropics and midlatitudes. To understand these differences and to obtain more reliable estimate, optical and microwave LWP retrieval methods are compared using the International Satellite Cloud Climatology Project (ISCCP) and special sensor microwave/imager (SSM/I) data. Errors in microwave LWP retrieval associated with uncertainties in surface, atmosphere, and cloud properties are assessed. Sea surface temperature may not produce great LWP errors, if accurate contemporaneous measurements are used in the retrieval. An uncertainty of estimated near-surface wind speed as high as 2 m/s produces uncertainty in LWP of about 5 mg/sq cm. Cloud liquid water temperature has only a small effect on LWP retrievals (rms errors less than 2 mg/sq cm), if errors in the temperature are less than 5 C; however, such errors can produce spurious variations of LWP with latitude and season. Errors in atmospheric column water vapor (CWV) are strongly coupled with errors in LWP (for some retrieval methods) causing errors as large as 30 mg/sq cm. Because microwave radiation is much less sensitive to clouds with small LWP (less than 7 mg/sq cm) than visible wavelength radiation, the microwave results are very sensitive to the process used to separate clear and cloudy conditions. Different cloud detection sensitivities in different microwave retrieval methods bias estimated LWP values. Comparing ISCCP and SSM/I LWPs, we find that the two estimated values are consistent in global, zonal, and regional means for warm, nonprecipitating clouds, which have average LWP values of about 5 mg/sq cm and occur much more frequently than precipitating clouds. Ice water path (IWP) can be roughly estimated from the differences between ISCCP total water path and SSM/I LWP for cold, nonprecipitating clouds. IWP in the winter hemisphere is about 3 times the LWP but only half the LWP in the summer hemisphere. Precipitating clouds contribute significantly to monthly, zonal mean LWP values determined from microwave, especially in the intertropical convergence zone (ITCZ), because they have almost 10 times the liquid water (cloud plus precipitation) of nonprecipitating clouds on average. There are significant differences among microwave LWP estimates associated with the treatment of precipitating clouds.

Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

NASA Technical Reports Server (NTRS)

Feng, Qian; Hsu, N. Christina; Yang, Ping; Tsay, Si-Chee

2011-01-01

The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

Information Content and Sensitivity of the 3β+2α Lidar Measurement System for Microphysical Retrievals

NASA Astrophysics Data System (ADS)

Burton, S. P.; Liu, X.; Chemyakin, E.; Hostetler, C. A.; Stamnes, S.; Moore, R.; Sawamura, P.; Ferrare, R. A.; Knobelspiesse, K. D.

2015-12-01

There is considerable interest in retrieving aerosol effective radius, number concentration and refractive index from lidar measurements of extinction and backscatter at several wavelengths. The 3 backscatter + 2 extinction (3β+2α) combination is particularly important since the planned NASA Aerosol-Clouds-Ecosystem (ACE) mission recommends this combination of measurements. The 2nd-generation NASA Langley airborne High Spectral Resolution Lidar (HSRL-2) has been making 3β+2α measurements since 2012. Here we develop a deeper understanding of the information content and sensitivities of the 3β+2α system in terms of aerosol microphysical parameters of interest. We determine best case results using a retrieval-free methodology. We calculate information content and uncertainty metrics from Optimal Estimation techniques using only a simplified forward model look-up table, with no explicit inversion. Simplifications include spherical particles, mono-modal log-normal size distributions, and wavelength-independent refractive indices. Since we only use the forward model with no retrieval, our results are applicable as a best case for all existing retrievals. Retrieval-dependent errors due to mismatch between the assumptions and true atmospheric aerosols are not included. The sensitivity metrics allow for identifying (1) information content of the measurements versus a priori information; (2) best-case error bars on the retrieved parameters; and (3) potential sources of cross-talk or "compensating" errors wherein different retrieval parameters are not independently captured by the measurements. These results suggest that even in the best case, this retrieval system is underdetermined. Recommendations are given for addressing cross-talk between effective radius and number concentration. A potential solution to the under-determination problem is a combined active (lidar) and passive (polarimeter) retrieval, which is the subject of a new funded NASA project by our team.

Enhanced storage capacity with errors in scale-free Hopfield neural networks: An analytical study.

PubMed

Kim, Do-Hyun; Park, Jinha; Kahng, Byungnam

2017-01-01

The Hopfield model is a pioneering neural network model with associative memory retrieval. The analytical solution of the model in mean field limit revealed that memories can be retrieved without any error up to a finite storage capacity of O(N), where N is the system size. Beyond the threshold, they are completely lost. Since the introduction of the Hopfield model, the theory of neural networks has been further developed toward realistic neural networks using analog neurons, spiking neurons, etc. Nevertheless, those advances are based on fully connected networks, which are inconsistent with recent experimental discovery that the number of connections of each neuron seems to be heterogeneous, following a heavy-tailed distribution. Motivated by this observation, we consider the Hopfield model on scale-free networks and obtain a different pattern of associative memory retrieval from that obtained on the fully connected network: the storage capacity becomes tremendously enhanced but with some error in the memory retrieval, which appears as the heterogeneity of the connections is increased. Moreover, the error rates are also obtained on several real neural networks and are indeed similar to that on scale-free model networks.

Characterization and error analysis of an operational retrieval algorithm for estimating column ozone and aerosol properties from ground-based ultra-violet irradiance measurements

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; L'Ecuyer, Tristan; Slusser, James; Stephens, Graeme; Krotkov, Nick; Davis, John; Goering, Christian

2005-08-01

Extensive sensitivity and error characteristics of a recently developed optimal estimation retrieval algorithm which simultaneously determines aerosol optical depth (AOD), aerosol single scatter albedo (SSA) and total ozone column (TOC) from ultra-violet irradiances are described. The algorithm inverts measured diffuse and direct irradiances at 7 channels in the UV spectral range obtained from the United States Department of Agriculture's (USDA) UV-B Monitoring and Research Program's (UVMRP) network of 33 ground-based UV-MFRSR instruments to produce aerosol optical properties and TOC at all seven wavelengths. Sensitivity studies of the Tropospheric Ultra-violet/Visible (TUV) radiative transfer model performed for various operating modes (Delta-Eddington versus n-stream Discrete Ordinate) over domains of AOD, SSA, TOC, asymmetry parameter and surface albedo show that the solutions are well constrained. Realistic input error budgets and diagnostic and error outputs from the retrieval are analyzed to demonstrate the atmospheric conditions under which the retrieval provides useful and significant results. After optimizing the algorithm for the USDA site in Panther Junction, Texas the retrieval algorithm was run on a cloud screened set of irradiance measurements for the month of May 2003. Comparisons to independently derived AOD's are favorable with root mean square (RMS) differences of about 3% to 7% at 300nm and less than 1% at 368nm, on May 12 and 22, 2003. This retrieval method will be used to build an aerosol climatology and provide ground-truthing of satellite measurements by running it operationally on the USDA UV network database.

Extending "Deep Blue" aerosol retrieval coverage to cases of absorbing aerosols above clouds: Sensitivity analysis and first case studies

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-05-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty ˜25-50% (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty ˜10-20%, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

A novel algorithm for laser self-mixing sensors used with the Kalman filter to measure displacement

NASA Astrophysics Data System (ADS)

Sun, Hui; Liu, Ji-Gou

2018-07-01

This paper proposes a simple and effective method for estimating the feedback level factor C in a self-mixing interferometric sensor. It is used with a Kalman filter to retrieve the displacement. Without the complicated and onerous calculation process of the general C estimation method, a final equation is obtained. Thus, the estimation of C only involves a few simple calculations. It successfully retrieves the sinusoidal and aleatory displacement by means of simulated self-mixing signals in both weak and moderate feedback regimes. To deal with the errors resulting from noise and estimate bias of C and to further improve the retrieval precision, a Kalman filter is employed following the general phase unwrapping method. The simulation and experiment results show that the retrieved displacement using the C obtained with the proposed method is comparable to the joint estimation of C and α. Besides, the Kalman filter can significantly decrease measurement errors, especially the error caused by incorrectly locating the peak and valley positions of the signal.

Creating a Satellite-Based Record of Tropospheric Ozone

NASA Technical Reports Server (NTRS)

Oetjen, Hilke; Payne, Vivienne H.; Kulawik, Susan S.; Eldering, Annmarie; Worden, John; Edwards, David P.; Francis, Gene L.; Worden, Helen M.

2013-01-01

The TES retrieval algorithm has been applied to IASI radiances. We compare the retrieved ozone profiles with ozone sonde profiles for mid-latitudes for the year 2008. We find a positive bias in the IASI ozone profiles in the UTLS region of up to 22 %. The spatial coverage of the IASI instrument allows sampling of effectively the same air mass with several IASI scenes simultaneously. Comparisons of the root-mean-square of an ensemble of IASI profiles to theoretical errors indicate that the measurement noise and the interference of temperature and water vapour on the retrieval together mostly explain the empirically derived random errors. The total degrees of freedom for signal of the retrieval for ozone are 3.1 +/- 0.2 and the tropospheric degrees of freedom are 1.0 +/- 0.2 for the described cases. IASI ozone profiles agree within the error bars with coincident ozone profiles derived from a TES stare sequence for the ozone sonde station at Bratt's Lake (50.2 deg N, 104.7 deg W).

Retrieval of Areal-averaged Spectral Surface Albedo from Transmission Data Alone: Computationally Simple and Fast Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kassianov, Evgueni I.; Barnard, James C.; Flynn, Connor J.

We introduce and evaluate a simple retrieval of areal-averaged surface albedo using ground-based measurements of atmospheric transmission alone at five wavelengths (415, 500, 615, 673 and 870nm), under fully overcast conditions. Our retrieval is based on a one-line semi-analytical equation and widely accepted assumptions regarding the weak spectral dependence of cloud optical properties, such as cloud optical depth and asymmetry parameter, in the visible and near-infrared spectral range. To illustrate the performance of our retrieval, we use as input measurements of spectral atmospheric transmission from Multi-Filter Rotating Shadowband Radiometer (MFRSR). These MFRSR data are collected at two well-established continental sitesmore » in the United States supported by the U.S. Department of Energy’s (DOE’s) Atmospheric Radiation Measurement (ARM) Program and National Oceanic and Atmospheric Administration (NOAA). The areal-averaged albedos obtained from the MFRSR are compared with collocated and coincident Moderate Resolution Imaging Spectroradiometer (MODIS) white-sky albedo. In particular, these comparisons are made at four MFRSR wavelengths (500, 615, 673 and 870nm) and for four seasons (winter, spring, summer and fall) at the ARM site using multi-year (2008-2013) MFRSR and MODIS data. Good agreement, on average, for these wavelengths results in small values (≤0.01) of the corresponding root mean square errors (RMSEs) for these two sites. The obtained RMSEs are comparable with those obtained previously for the shortwave albedos (MODIS-derived versus tower-measured) for these sites during growing seasons. We also demonstrate good agreement between tower-based daily-averaged surface albedos measured for “nearby” overcast and non-overcast days. Thus, our retrieval originally developed for overcast conditions likely can be extended for non-overcast days by interpolating between overcast retrievals.« less

An analysis of errors in special sensor microwave imager evaporation estimates over the global oceans

NASA Technical Reports Server (NTRS)

Esbensen, S. K.; Chelton, D. B.; Vickers, D.; Sun, J.

1993-01-01

The method proposed by Liu (1984) is used to estimate monthly averaged evaporation over the global oceans from 1 yr of special sensor microwave imager (SDSM/I) data. Intercomparisons involving SSM/I and in situ data are made over a wide range of oceanic conditions during August 1987 and February 1988 to determine the source of errors in the evaporation estimates. The most significant spatially coherent evaporation errors are found to come from estimates of near-surface specific humidity, q. Systematic discrepancies of over 2 g/kg are found in the tropics, as well as in the middle and high latitudes. The q errors are partitioned into contributions from the parameterization of q in terms of the columnar water vapor, i.e., the Liu q/W relationship, and from the retrieval algorithm for W. The effects of W retrieval errors are found to be smaller over most of the global oceans and due primarily to the implicitly assumed vertical structures of temperature and specific humidity on which the physically based SSM/I retrievals of W are based.

What is the Uncertainty in MODIS Aerosol Optical Depth in the Vicinity of Clouds?

NASA Technical Reports Server (NTRS)

Patadia, Falguni; Levy, Rob; Mattoo, Shana

2017-01-01

MODIS dark-target (DT) algorithm retrieves aerosol optical depth (AOD) using a Look Up Table (LUT) approach. Global comparison of AOD (Collection 6 ) with ground-based sun photometer gives an Estimated Error (EE) of +/-(0.04 + 10%) over ocean. However, EE does not represent per-retrieval uncertainty. For retrievals that are biased high compared to AERONET, here we aim to closely examine the contribution of biases due to presence of clouds and per-pixel retrieval uncertainty. We have characterized AOD uncertainty at 550 nm, due to standard deviation of reflectance in 10 km retrieval region, uncertainty related to gas (H2O, O3) absorption, surface albedo, and aerosol models. The uncertainty in retrieved AOD seems to lie within the estimated over ocean error envelope of +/-(0.03+10%). Regions between broken clouds tend to have higher uncertainty. Compared to C6 AOD, a retrieval omitting observations in the vicinity of clouds (< or = 1 km) is biased by about +/- 0.05. For homogeneous aerosol distribution, clear sky retrievals show near zero bias. Close look at per-pixel reflectance histograms suggests retrieval possibility using median reflectance values.

The effect of unsuccessful retrieval on children's subsequent learning.

PubMed

Carneiro, Paula; Lapa, Ana; Finn, Bridgid

2018-02-01

It is well known that successful retrieval enhances subsequent adults' learning by promoting long-term retention. Recent research has also found benefits from unsuccessful retrieval, but the evidence is not as clear-cut when the participants are children. In this study, we employed a methodology based on guessing-the weak associate paradigm-to test whether children can learn from generated errors or whether errors are harmful for learning. We tested second- and third-grade children in Experiment 1 and tested preschool and kindergarten children in Experiment 2. With slight differences in the method, in both experiments children heard the experimenter saying one word (cue) and were asked to guess an associate word (guess condition) or to listen to the correspondent target-associated word (study condition), followed by corrective feedback in both conditions. At the end of the guessing phase, the children undertook a cued-recall task in which they were presented with each cue and were asked to say the corrected target. Together, the results showed that older children-those in kindergarten and early elementary school-benefited from unsuccessful retrieval. Older children showed more correct responses and fewer errors in the guess condition. In contrast, preschoolers produced similar levels of correct and error responses in the two conditions. In conclusion, generating errors seems to be beneficial for future learning of children older than 5years. Copyright © 2017 Elsevier Inc. All rights reserved.

Retrieving Storm Electric Fields from Aircrfaft Field Mill Data: Part II: Applications

NASA Technical Reports Server (NTRS)

Koshak, William; Mach, D. M.; Christian H. J.; Stewart, M. F.; Bateman M. G.

2006-01-01

The Lagrange multiplier theory developed in Part I of this study is applied to complete a relative calibration of a Citation aircraft that is instrumented with six field mill sensors. When side constraints related to average fields are used, the Lagrange multiplier method performs well in computer simulations. For mill measurement errors of 1 V m(sup -1) and a 5 V m(sup -1) error in the mean fair-weather field function, the 3D storm electric field is retrieved to within an error of about 12%. A side constraint that involves estimating the detailed structure of the fair-weather field was also tested using computer simulations. For mill measurement errors of 1 V m(sup -l), the method retrieves the 3D storm field to within an error of about 8% if the fair-weather field estimate is typically within 1 V m(sup -1) of the true fair-weather field. Using this type of side constraint and data from fair-weather field maneuvers taken on 29 June 2001, the Citation aircraft was calibrated. Absolute calibration was completed using the pitch down method developed in Part I, and conventional analyses. The resulting calibration matrices were then used to retrieve storm electric fields during a Citation flight on 2 June 2001. The storm field results are encouraging and agree favorably in many respects with results derived from earlier (iterative) techniques of calibration.

On Combining Thermal-Infrared and Radio-Occultation Data of Saturn's Atmosphere

NASA Technical Reports Server (NTRS)

Flasar, F. M.; Schinder, P. J.; Conrath, B. J.

2008-01-01

Radio-occultation and thermal-infrared measurements are complementary investigations for sounding planetary atmospheres. The vertical resolution afforded by radio occultations is typically approximately 1 km or better, whereas that from infrared sounding is often comparable to a scale height. On the other hand, an instrument like CIRS can easily generate global maps of temperature and composition, whereas occultation soundings are usually distributed more sparsely. The starting point for radio-occultation inversions is determining the residual Doppler-shifted frequency, that is the shift in frequency from what it would be in the absence of the atmosphere. Hence the positions and relative velocities of the spacecraft, target atmosphere, and DSN receiving station must be known to high accuracy. It is not surprising that the inversions can be susceptible to sources of systematic errors. Stratospheric temperature profiles on Titan retrieved from Cassini radio occultations were found to be very susceptible to errors in the reconstructed spacecraft velocities (approximately equal to 1 mm/s). Here the ability to adjust the spacecraft ephemeris so that the profiles matched those retrieved from CIRS limb sounding proved to be critical in mitigating this error. A similar procedure can be used for Saturn, although the sensitivity of its retrieved profiles to this type of error seems to be smaller. One issue that has appeared in inverting the Cassini occultations by Saturn is the uncertainty in its equatorial bulge, that is, the shape in its iso-density surfaces at low latitudes. Typically one approximates that surface as a geopotential surface by assuming a barotropic atmosphere. However, the recent controversy in the equatorial winds, i.e., whether they changed between the Voyager (1981) era and later (after 1996) epochs of Cassini and some Hubble observations, has made it difficult to know the exact shape of the surface, and it leads to uncertainties in the retrieved temperature profiles of one to a few kelvins. This propagates into errors in the retrieved helium abundance, which makes use of thermal-infrared spectra and synthetic spectra computed with retrieved radio-occultation temperature profiles. The highest abundances are retrieved with the faster Voyager-era winds, but even these abundances are somewhat smaller than those retrieved from the thermal-infrared data alone (albeit with larger formal errors). The helium abundance determination is most sensitive to temperatures in the upper troposphere. Further progress may include matching the radio-occultation profiles with those from CIRS limb sounding in the upper stratosphere.

Threshold raw retrieved contrast in coronagraphs is limited by internal polarization

NASA Astrophysics Data System (ADS)

Breckinridge, James

The objective of this work is to provide the exoplanet program with an accurate model of the coronagraph complex point spread function, methods to correct chromatic aberration in the presence of polarization aberrations, device requirements to minimize and compensate for these aberrations at levels needed for exoplanet coronagraphy, and exoplanet retrieval algorithms in the presence of polarizaiton aberrations. Currently, space based coronagraphs are designed and performance analyzed using scalar wave aberration theory. Breckinridge, Lam & Chipman (2015) PASP 127: 445-468 and Breckinridge & Oppenheimer (2004) ApJ 600: 1091-1098 showed that astronomical telescopes designed for exoplanet and precision astrometric science require polarization or vector-wave analysis. Internal instrument polarization limits both threshold raw contrast and measurements of the vector wave properties of the electromagnetic radiation from stars, exoplanets, gas and dust. The threshold raw contrast obtained using only scalar wave theory is much more optimistic than that obtained using the more hardware-realistic vector wave theory. Internal polarization reduces system contrast, increases scattered light, alters radiometric measurements, distorts diffraction-limited star images and reduces signal-to-noise ratio. For example, a vector-wave analysis shows that the WFIRST-CGI instrument will have a threshold raw contrast of 10-7 not the 10-8 forecasted using the scalar wave analysis given in the WFIRST-CGI 2015 report. The physical nature of the complex point spread function determines the exoplanet scientific yield of coronagraphs. We propose to use the Polaris-M polarization aberration ray-tracing software developed at the College of Optical Science of the University of Arizona to ray trace both a "typical" exoplanet coronagraph system as well as the WFIRST-CGI system. Threshold raw contrast and the field across the complex PSF will be calculated as a function of optical device vector E&M requirements on: 1. Lyot coronagraph mask and stop size, configuration, location and composition, 2. Uniformity of the complex reflectance of the highly reflecting metal mirrors with their dielectric overcoats, and 3. Opto-mechanical layout. Once these requirements are developed polarization aberration mitigation studies can begin to identify a practical solution to compensate polarization errors, not unlike the more developed technology of A/O compensates for pointing and manufacturing errors. Several methods to compensate for chromatic aberration in coronagraphs further compounds the complex PSF errors that require compensation to maximize the best retrieved raw contrast in the presence of exoplanets in the vicinity of stars. Internal instrument polarization introduces partial coherence into the wavefront to distort the speckle-pattern complex-field in the dark hole. An additional factor that determines retrieved raw contrast is our ability to effectively process the polarizationdistorted field within the dark hole. This study is essential to the correct calculation of exoplanet coronagraph science yield, development of requirements on subsystem devices (mirrors, stops, masks, spectrometers, wavefront error mitigation optics and opto-mechanical layout) and the development of exoplanet retrieval algorithms.

A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

NASA Astrophysics Data System (ADS)

Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

2017-07-01

Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100-200 % for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASC measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18 % difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36 % for the individual events. Use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122 % for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. More accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.

Retrieval of high-spectral-resolution lidar for atmospheric aerosol optical properties profiling

NASA Astrophysics Data System (ADS)

Liu, Dong; Luo, Jing; Yang, Yongying; Cheng, Zhongtao; Zhang, Yupeng; Zhou, Yudi; Duan, Lulin; Su, Lin

2015-10-01

High-spectral-resolution lidars (HSRLs) are increasingly being developed for atmospheric aerosol remote sensing applications due to the straightforward and independent retrieval of aerosol optical properties without reliance on assumptions about lidar ratio. In HSRL technique, spectral discrimination between scattering from molecules and aerosol particles is one of the most critical processes, which needs to be accomplished by means of a narrowband spectroscopic filter. To ensure a high retrieval accuracy of an HSRL system, the high-quality design of its spectral discrimination filter should be made. This paper reviews the available algorithms that were proposed for HSRLs and makes a general accuracy analysis of the HSRL technique focused on the spectral discrimination, in order to provide heuristic guidelines for the reasonable design of the spectral discrimination filter. We introduce a theoretical model for retrieval error evaluation of an HSRL instrument with general three-channel configuration. Monte Carlo (MC) simulations are performed to validate the correctness of the theoretical model. Results from both the model and MC simulations agree very well, and they illustrate one important, although not well realized fact: a large molecular transmittance and a large spectral discrimination ratio (SDR, i.e., ratio of the molecular transmittance to the aerosol transmittance) are beneficial t o promote the retrieval accuracy. The application of the conclusions obtained in this paper in the designing of a new type of spectroscopic filter, that is, the field-widened Michelson interferometer, is illustrated in detail. These works are with certain universality and expected to be useful guidelines for HSRL community, especially when choosing or designing the spectral discrimination filter.

A Prediction Error-driven Retrieval Procedure for Destabilizing and Rewriting Maladaptive Reward Memories in Hazardous Drinkers

PubMed Central

Das, Ravi K.; Gale, Grace; Hennessy, Vanessa; Kamboj, Sunjeev K.

2018-01-01

Maladaptive reward memories (MRMs) can become unstable following retrieval under certain conditions, allowing their modification by subsequent new learning. However, robust (well-rehearsed) and chronologically old MRMs, such as those underlying substance use disorders, do not destabilize easily when retrieved. A key determinate of memory destabilization during retrieval is prediction error (PE). We describe a retrieval procedure for alcohol MRMs in hazardous drinkers that specifically aims to maximize the generation of PE and therefore the likelihood of MRM destabilization. The procedure requires explicitly generating the expectancy of alcohol consumption and then violating this expectancy (withholding alcohol) following the presentation of a brief set of prototypical alcohol cue images (retrieval + PE). Control procedures involve presenting the same cue images, but allow alcohol to be consumed, generating minimal PE (retrieval-no PE) or generate PE without retrieval of alcohol MRMs, by presenting orange juice cues (no retrieval + PE). Subsequently, we describe a multisensory disgust-based counterconditioning procedure to probe MRM destabilization by re-writing alcohol cue-reward associations prior to reconsolidation. This procedure pairs alcohol cues with images invoking pathogen disgust and an extremely bitter-tasting solution (denatonium benzoate), generating gustatory disgust. Following retrieval + PE, but not no retrieval + PE or retrieval-no PE, counterconditioning produces evidence of MRM rewriting as indexed by lasting reductions in alcohol cue valuation, attentional capture, and alcohol craving. PMID:29364255

Uncertainty of Passive Imager Cloud Optical Property Retrievals to Instrument Radiometry and Model Assumptions: Examples from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Galina; Meyer, Kerry; Amarasinghe, Nandana; Arnold, G. Thomas; Zhang, Zhibo; King, Michael D.

2013-01-01

The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.

Uncertainty of passive imager cloud retrievals to instrument radiometry and model assumptions: Examples from MODIS Collection 6

NASA Astrophysics Data System (ADS)

Platnick, S.; Wind, G.; Amarasinghe, N.; Arnold, G. T.; Zhang, Z.; Meyer, K.; King, M. D.

2013-12-01

The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VIS/NIR channel paired with a 1.6, 2.1, and 3.7 μm spectral channel. The MOD06 forward model is derived from a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1° aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. In Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 μm band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 μm, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.

Factors that influence search termination decisions in free recall: an examination of response type and confidence.

PubMed

Unsworth, Nash; Brewer, Gene A; Spillers, Gregory J

2011-09-01

In three experiments search termination decisions were examined as a function of response type (correct vs. incorrect) and confidence. It was found that the time between the last retrieved item and the decision to terminate search (exit latency) was related to the type of response and confidence in the last item retrieved. Participants were willing to search longer when the last retrieved item was a correct item vs. an incorrect item and when the confidence was high in the last retrieved item. It was also found that the number of errors retrieved during the recall period was related to search termination decisions such that the more errors retrieved, the more likely participants were to terminate the search. Finally, it was found that knowledge of overall search set size influenced the time needed to search for items, but did not influence search termination decisions. Copyright © 2011 Elsevier B.V. All rights reserved.

Wind Retrieval Algorithms for the IWRAP and HIWRAP Airborne Doppler Radars with Applications to Hurricanes

NASA Technical Reports Server (NTRS)

Guimond, Stephen Richard; Tian, Lin; Heymsfield, Gerald M.; Frasier, Stephen J.

2013-01-01

Algorithms for the retrieval of atmospheric winds in precipitating systems from downward-pointing, conically-scanning airborne Doppler radars are presented. The focus in the paper is on two radars: the Imaging Wind and Rain Airborne Profiler(IWRAP) and the High-altitude IWRAP (HIWRAP). The IWRAP is a dual-frequency (Cand Ku band), multi-beam (incidence angles of 30 50) system that flies on the NOAAWP-3D aircraft at altitudes of 2-4 km. The HIWRAP is a dual-frequency (Ku and Kaband), dual-beam (incidence angles of 30 and 40) system that flies on the NASA Global Hawk aircraft at altitudes of 18-20 km. Retrievals of the three Cartesian wind components over the entire radar sampling volume are described, which can be determined using either a traditional least squares or variational solution procedure. The random errors in the retrievals are evaluated using both an error propagation analysis and a numerical simulation of a hurricane. These analyses show that the vertical and along-track wind errors have strong across-track dependence with values of 0.25 m s-1 at nadir to 2.0 m s-1 and 1.0 m s-1 at the swath edges, respectively. The across-track wind errors also have across-track structure and are on average, 3.0 3.5 m s-1 or 10 of the hurricane wind speed. For typical rotated figure four flight patterns through hurricanes, the zonal and meridional wind speed errors are 2 3 m s-1.Examples of measured data retrievals from IWRAP during an eyewall replacement cycle in Hurricane Isabel (2003) and from HIWRAP during the development of Tropical Storm Matthew (2010) are shown.

Broadband CARS spectral phase retrieval using a time-domain Kramers–Kronig transform

PubMed Central

Liu, Yuexin; Lee, Young Jong; Cicerone, Marcus T.

2014-01-01

We describe a closed-form approach for performing a Kramers–Kronig (KK) transform that can be used to rapidly and reliably retrieve the phase, and thus the resonant imaginary component, from a broadband coherent anti-Stokes Raman scattering (CARS) spectrum with a nonflat background. In this approach we transform the frequency-domain data to the time domain, perform an operation that ensures a causality criterion is met, then transform back to the frequency domain. The fact that this method handles causality in the time domain allows us to conveniently account for spectrally varying nonresonant background from CARS as a response function with a finite rise time. A phase error accompanies KK transform of data with finite frequency range. In examples shown here, that phase error leads to small (<1%) errors in the retrieved resonant spectra. PMID:19412273

Feasibility of retrieving dust properties and total column water vapor from solar spectra measured using a lander camera on Mars

NASA Astrophysics Data System (ADS)

Manago, Naohiro; Noguchi, Katsuyuki; Hashimoto, George L.; Senshu, Hiroki; Otobe, Naohito; Suzuki, Makoto; Kuze, Hiroaki

2017-12-01

Dust and water vapor are important constituents in the Martian atmosphere, exerting significant influence on the heat balance of the atmosphere and surface. We have developed a method to retrieve optical and physical properties of Martian dust from spectral intensities of direct and scattered solar radiation to be measured using a multi-wavelength environmental camera onboard a Mars lander. Martian dust is assumed to be composed of silicate-like substrate and hematite-like inclusion, having spheroidal shape with a monomodal gamma size distribution. Error analysis based on simulated data reveals that appropriate combinations of three bands centered at 450, 550, and 675 nm wavelengths and 4 scattering angles of 3°, 10°, 50°, and 120° lead to good retrieval of four dust parameters, namely, aerosol optical depth, effective radius and variance of size distribution, and volume mixing ratio of hematite. Retrieval error increases when some of the observational parameters such as color ratio or aureole are omitted from the retrieval. Also, the capability of retrieving total column water vapor is examined through observations of direct and scattered solar radiation intensities at 925, 935, and 972 nm. The simulation and error analysis presented here will be useful for designing an environmental camera that can elucidate the dust and water vapor properties in a future Mars lander mission.

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-01-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

Global height-resolved methane retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp

NASA Astrophysics Data System (ADS)

Siddans, Richard; Knappett, Diane; Kerridge, Brian; Waterfall, Alison; Hurley, Jane; Latter, Barry; Boesch, Hartmut; Parker, Robert

2017-11-01

This paper describes the global height-resolved methane (CH4) retrieval scheme for the Infrared Atmospheric Sounding Interferometer (IASI) on MetOp, developed at the Rutherford Appleton Laboratory (RAL). The scheme precisely fits measured spectra in the 7.9 micron region to allow information to be retrieved on two independent layers centred in the upper and lower troposphere. It also uses nitrous oxide (N2O) spectral features in the same spectral interval to directly retrieve effective cloud parameters to mitigate errors in retrieved methane due to residual cloud and other geophysical variables. The scheme has been applied to analyse IASI measurements between 2007 and 2015. Results are compared to model fields from the MACC greenhouse gas inversion and independent measurements from satellite (GOSAT), airborne (HIPPO) and ground (TCCON) sensors. The estimated error on methane mixing ratio in the lower- and upper-tropospheric layers ranges from 20 to 100 and from 30 to 40 ppbv, respectively, and error on the derived column-average ranges from 20 to 40 ppbv. Vertical sensitivity extends through the lower troposphere, though it decreases near to the surface. Systematic differences with the other datasets are typically < 10 ppbv regionally and < 5 ppbv globally. In the Southern Hemisphere, a bias of around 20 ppbv is found with respect to MACC, which is not explained by vertical sensitivity or found in comparison of IASI to TCCON. Comparisons to HIPPO and MACC support the assertion that two layers can be independently retrieved and provide confirmation that the estimated random errors on the column- and layer-averaged amounts are realistic. The data have been made publically available via the Centre for Environmental Data Analysis (CEDA) data archive (Siddans, 2016).

Altitude Registration of Limb-Scattered Radiation

NASA Technical Reports Server (NTRS)

Moy, Leslie; Bhartia, Pawan K.; Jaross, Glen; Loughman, Robert; Kramarova, Natalya; Chen, Zhong; Taha, Ghassan; Chen, Grace; Xu, Philippe

2017-01-01

One of the largest constraints to the retrieval of accurate ozone profiles from UV backscatter limb sounding sensors is altitude registration. Two methods, the Rayleigh scattering attitude sensing (RSAS) and absolute radiance residual method (ARRM), are able to determine altitude registration to the accuracy necessary for long-term ozone monitoring. The methods compare model calculations of radiances to measured radiances and are independent of onboard tracking devices. RSAS determines absolute altitude errors, but, because the method is susceptible to aerosol interference, it is limited to latitudes and time periods with minimal aerosol contamination. ARRM, a new technique introduced in this paper, can be applied across all seasons and altitudes. However, it is only appropriate for relative altitude error estimates. The application of RSAS to Limb Profiler (LP) measurements from the Ozone Mapping and Profiler Suite (OMPS) on board the Suomi NPP (SNPP) satellite indicates tangent height (TH) errors greater than 1 km with an absolute accuracy of +/-200 m. Results using ARRM indicate a approx. 300 to 400m intra-orbital TH change varying seasonally +/-100 m, likely due to either errors in the spacecraft pointing or in the geopotential height (GPH) data that we use in our analysis. ARRM shows a change of approx. 200m over 5 years with a relative accuracy (a long-term accuracy) of 100m outside the polar regions.

The US-DOE ARM/ASR Effort in Quantifying Uncertainty in Ground-Based Cloud Property Retrievals (Invited)

NASA Astrophysics Data System (ADS)

Xie, S.; Protat, A.; Zhao, C.

2013-12-01

One primary goal of the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program is to obtain and retrieve cloud microphysical properties from detailed cloud observations using ground-based active and passive remote sensors. However, there is large uncertainty in the retrieved cloud property products. Studies have shown that the uncertainty could arise from instrument limitations, measurement errors, sampling errors, retrieval algorithm deficiencies in assumptions, as well as inconsistent input data and constraints used by different algorithms. To quantify the uncertainty in cloud retrievals, a scientific focus group, Quantification of Uncertainties In Cloud Retrievals (QUICR), was recently created by the DOE Atmospheric System Research (ASR) program. This talk will provide an overview of the recent research activities conducted within QUICR and discuss its current collaborations with the European cloud retrieval community and future plans. The goal of QUICR is to develop a methodology for characterizing and quantifying uncertainties in current and future ARM cloud retrievals. The Work at LLNL was performed under the auspices of the U. S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research by Lawrence Livermore National Laboratory under contract No. DE-AC52-07NA27344. LLNL-ABS-641258.

Ground-based remote sensing of thin clouds in the Arctic

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Zhao, C.

2012-11-01

This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" where absorption by water vapor is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in two micro-windows, constrained by the transmission through clouds of stratospheric ozone emission. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius, visible optical depth, number concentration, and water path are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement program (ARM) North Slope of Alaska - Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with ground-based microwave radiometer measurements of liquid water path. Compared to other retrieval methods, advantages of this technique include its ability to characterize thin clouds year round, that water vapor is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies.

CALIPSO-Inferred Aerosol Direct Radiative Effects: Bias Estimates Using Ground-Based Raman Lidars

NASA Technical Reports Server (NTRS)

Thorsen, Tyler; Fu, Qiang

2015-01-01

Observational constraints on the change in the radiative energy budget caused by the presence of aerosols, i.e. the aerosol direct radiative effect (DRE), have recently been made using observations from the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO). CALIPSO observations have the potential to provide improved global estimates of aerosol DRE compared to passive sensor-derived estimates due to CALIPSO's ability to perform vertically-resolved aerosol retrievals over all surface types and over cloud. In this study we estimate the uncertainties in CALIPSO-inferred aerosol DRE using multiple years of observations from the Atmospheric Radiation Measurement (ARM) program's Raman lidars (RL) at mid-latitude and tropical sites. Examined are assumptions about the ratio of extinction-to-backscatter (i.e. the lidar ratio) made by the CALIPSO retrievals, which are needed to retrieve the aerosol extinction profile. The lidar ratio is shown to introduce minimal error in the mean aerosol DRE at the top-of-atmosphere and surface. It is also shown that CALIPSO is unable to detect all radiatively-significant aerosol, resulting in an underestimate in the magnitude of the aerosol DRE by 30â€"50%. Therefore, global estimates of the aerosol DRE inferred from CALIPSO observations are likely too weak.

A Module for Assimilating Hyperspectral Infrared Retrieved Profiles into the Gridpoint Statistical Interpolation System for Unique Forecasting Applications

NASA Technical Reports Server (NTRS)

Berndt, Emily; Zavodsky, Bradley; Srikishen, Jayanthi; Blankenship, Clay

2015-01-01

Hyperspectral infrared sounder radiance data are assimilated into operational modeling systems however the process is computationally expensive and only approximately 1% of available data are assimilated due to data thinning as well as the fact that radiances are restricted to cloud-free fields of view. In contrast, the number of hyperspectral infrared profiles assimilated is much higher since the retrieved profiles can be assimilated in some partly cloudy scenes due to profile coupling other data, such as microwave or neural networks, as first guesses to the retrieval process. As the operational data assimilation community attempts to assimilate cloud-affected radiances, it is possible that the use of retrieved profiles might offer an alternative methodology that is less complex and more computationally efficient to solve this problem. The NASA Short-term Prediction Research and Transition (SPoRT) Center has assimilated hyperspectral infrared retrieved profiles into Weather Research and Forecasting Model (WRF) simulations using the Gridpoint Statistical Interpolation (GSI) System. Early research at SPoRT demonstrated improved initial conditions when assimilating Atmospheric Infrared Sounder (AIRS) thermodynamic profiles into WRF (using WRF-Var and assigning more appropriate error weighting to the profiles) to improve regional analysis and heavy precipitation forecasts. Successful early work has led to more recent research utilizing WRF and GSI for applications including the assimilation of AIRS profiles to improve WRF forecasts of atmospheric rivers and assimilation of AIRS, Cross-track Infrared and Microwave Sounding Suite (CrIMSS), and Infrared Atmospheric Sounding Interferometer (IASI) profiles to improve model representation of tropopause folds and associated non-convective wind events. Although more hyperspectral infrared retrieved profiles can be assimilated into model forecasts, one disadvantage is the retrieved profiles have traditionally been assigned the same error values as the rawinsonde observations when assimilated with GSI. Typically, satellitederived profile errors are larger and more difficult to quantify than traditional rawinsonde observations (especially in the boundary layer), so it is important to appropriately assign observation errors within GSI to eliminate potential spurious innovations and analysis increments that can sometimes arise when using retrieved profiles. The goal of this study is to describe modifications to the GSI source code to more appropriately assimilate hyperspectral infrared retrieved profiles and outline preliminary results that show the differences between a model simulation that assimilated the profiles as rawinsonde observations and one that assimilated the profiles in a module with the appropriate error values.

GNSS Clock Error Impacts on Radio Occultation Retrievals

NASA Astrophysics Data System (ADS)

Weiss, Jan; Sokolovskiy, Sergey; Schreiner, Bill; Yoon, Yoke

2017-04-01

We assess the impacts of GPS and GLONASS clock errors on radio occultation retrieval of bending angle, refractivity, and temperature from low Earth orbit. The major contributing factor is the interpretation of GNSS clock offsets sampled at 30 sec or longer intervals. Using 1 Hz GNSS clock estimates as truth we apply several interpolation and fitting schemes to evaluate how they affect the accuracy of atmospheric retrieval products. The results are organized by GPS and GLONASS space vehicle and the GNSS clock interpolation/fitting scheme. We find that bending angle error is roughly similar for all current GPS transmitters (about 0.7 mcrad) but note some differences related to the type of atomic oscillator onboard the transmitter satellite. GLONASS bending angle errors show more variation over the constellation and are approximately two times larger than GPS. An investigation of the transmitter clock spectra reveals this is due to more power in periods between 2-10 sec. Retrieved refractivity and temperature products show clear differences between GNSS satellite generations, and indicate that GNSS clocks sampled at intervals smaller than 5 sec significantly improve accuracy, particularly for GLONASS. We conclude by summarizing the tested GNSS clock estimation and application strategies in the context of current and future radio occultation missions.

The validation of the Yonsei CArbon Retrieval algorithm with improved aerosol information using GOSAT measurements

NASA Astrophysics Data System (ADS)

Jung, Yeonjin; Kim, Jhoon; Kim, Woogyung; Boesch, Hartmut; Goo, Tae-Young; Cho, Chunho

2017-04-01

Although several CO2 retrieval algorithms have been developed to improve our understanding about carbon cycle, limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. Based on an optimal estimation method, the Yonsei CArbon Retrieval (YCAR) algorithm was developed to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) using the Greenhouse Gases Observing SATellite (GOSAT) measurements with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) are the most important factors in CO2 retrievals since AOPs are assumed as fixed parameters during retrieval process, resulting in significant XCO2 retrieval error up to 2.5 ppm. In this study, to reduce these errors caused by inaccurate aerosol optical information, the YCAR algorithm improved with taking into account aerosol optical properties as well as aerosol vertical distribution simultaneously. The CO2 retrievals with two difference aerosol approaches have been analyzed using the GOSAT spectra and have been evaluated throughout the comparison with collocated ground-based observations at several Total Carbon Column Observing Network (TCCON) sites. The improved YCAR algorithm has biases of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, with smaller biases and higher correlation coefficients compared to the GOSAT operational algorithm. In addition, the XCO2 retrievals will be validated at other TCCON sites and error analysis will be evaluated. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties. This study would be expected to provide useful information in estimating carbon sources and sinks.

Characterization of in Band Stray Light in SBUV-2 Instruments

NASA Technical Reports Server (NTRS)

Huang, L. K.; DeLand, M. T.; Taylor, S. L.; Flynn, L. E.

2014-01-01

Significant in-band stray light (IBSL) error at solar zenith angle (SZA) values larger than 77deg near sunset in 4 SBUV/2 (Solar Backscattered Ultraviolet) instruments, on board the NOAA-14, 17, 18 and 19 satellites, has been characterized. The IBSL error is caused by large surface reflection and scattering of the air-gapped depolarizer in front of the instrument's monochromator aperture. The source of the IBSL error is direct solar illumination of instrument components near the aperture rather than from earth shine. The IBSL contamination at 273 nm can reach 40% of earth radiance near sunset, which results in as much as a 50% error in the retrieved ozone from the upper stratosphere. We have analyzed SBUV/2 albedo measurements on both the dayside and nightside to develop an empirical model for the IBSL error. This error has been corrected in the V8.6 SBUV/2 ozone retrieval.

Reliable absolute analog code retrieval approach for 3D measurement

NASA Astrophysics Data System (ADS)

Yu, Shuang; Zhang, Jing; Yu, Xiaoyang; Sun, Xiaoming; Wu, Haibin; Chen, Deyun

2017-11-01

The wrapped phase of phase-shifting approach can be unwrapped by using Gray code, but both the wrapped phase error and Gray code decoding error can result in period jump error, which will lead to gross measurement error. Therefore, this paper presents a reliable absolute analog code retrieval approach. The combination of unequal-period Gray code and phase shifting patterns at high frequencies are used to obtain high-frequency absolute analog code, and at low frequencies, the same unequal-period combination patterns are used to obtain the low-frequency absolute analog code. Next, the difference between the two absolute analog codes was employed to eliminate period jump errors, and a reliable unwrapped result can be obtained. Error analysis was used to determine the applicable conditions, and this approach was verified through theoretical analysis. The proposed approach was further verified experimentally. Theoretical analysis and experimental results demonstrate that the proposed approach can perform reliable analog code unwrapping.

Uncertainties in Cloud Phase and Optical Thickness Retrievals from the Earth Polychromatic Imaging Camera (EPIC)

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (less than 2 percent) due to the particle- size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 percent, although for thin clouds (COT less than 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

PubMed Central

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2018-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study. PMID:29619116

Evaluation of the OMI Cloud Pressures Derived from Rotational Raman Scattering by Comparisons with other Satellite Data and Radiative Transfer Simulations

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Joiner, Joanna; Spurr, Robert; Bhartia, Pawan K.; Levelt, Pieternel; Stephens, Graeme

2009-01-01

In this paper we examine differences between cloud pressures retrieved from the Ozone Monitoring Instrument (OMI) using the ultraviolet rotational Raman scattering (RRS) algorithm and those from the thermal infrared (IR) Aqua/MODIS. Several cloud data sets are currently being used in OMI trace gas retrieval algorithms including climatologies based on IR measurements and simultaneous cloud parameters derived from OMI. From a validation perspective, it is important to understand the OMI retrieved cloud parameters and how they differ with those derived from the IR. To this end, we perform radiative transfer calculations to simulate the effects of different geophysical conditions on the OMI RRS cloud pressure retrievals. We also quantify errors related to the use of the Mixed Lambert-Equivalent Reflectivity (MLER) concept as currently implemented of the OMI algorithms. Using properties from the Cloudsat radar and MODIS, we show that radiative transfer calculations support the following: (1) The MLER model is adequate for single-layer optically thick, geometrically thin clouds, but can produce significant errors in estimated cloud pressure for optically thin clouds. (2) In a two-layer cloud, the RRS algorithm may retrieve a cloud pressure that is either between the two cloud decks or even beneath the top of the lower cloud deck because of scattering between the cloud layers; the retrieved pressure depends upon the viewing geometry and the optical depth of the upper cloud deck. (3) Absorbing aerosol in and above a cloud can produce significant errors in the retrieved cloud pressure. (4) The retrieved RRS effective pressure for a deep convective cloud will be significantly higher than the physical cloud top pressure derived with thermal IR.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC).

PubMed

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

A Simple and Universal Aerosol Retrieval Algorithm for Landsat Series Images Over Complex Surfaces

NASA Astrophysics Data System (ADS)

Wei, Jing; Huang, Bo; Sun, Lin; Zhang, Zhaoyang; Wang, Lunche; Bilal, Muhammad

2017-12-01

Operational aerosol optical depth (AOD) products are available at coarse spatial resolutions from several to tens of kilometers. These resolutions limit the application of these products for monitoring atmospheric pollutants at the city level. Therefore, a simple, universal, and high-resolution (30 m) Landsat aerosol retrieval algorithm over complex urban surfaces is developed. The surface reflectance is estimated from a combination of top of atmosphere reflectance at short-wave infrared (2.22 μm) and Landsat 4-7 surface reflectance climate data records over densely vegetated areas and bright areas. The aerosol type is determined using the historical aerosol optical properties derived from the local urban Aerosol Robotic Network (AERONET) site (Beijing). AERONET ground-based sun photometer AOD measurements from five sites located in urban and rural areas are obtained to validate the AOD retrievals. Terra MODerate resolution Imaging Spectrometer Collection (C) 6 AOD products (MOD04) including the dark target (DT), the deep blue (DB), and the combined DT and DB (DT&DB) retrievals at 10 km spatial resolution are obtained for comparison purposes. Validation results show that the Landsat AOD retrievals at a 30 m resolution are well correlated with the AERONET AOD measurements (R2 = 0.932) and that approximately 77.46% of the retrievals fall within the expected error with a low mean absolute error of 0.090 and a root-mean-square error of 0.126. Comparison results show that Landsat AOD retrievals are overall better and less biased than MOD04 AOD products, indicating that the new algorithm is robust and performs well in AOD retrieval over complex surfaces. The new algorithm can provide continuous and detailed spatial distributions of AOD during both low and high aerosol loadings.

Cloud Liquid Water Path Comparisons from Passive Microwave and Solar Reflectance Satellite Measurements: Assessment of Sub-Field-of-View Cloud Effects in Microwave Retrievals

NASA Technical Reports Server (NTRS)

Greenwald, Thomas J.; Christopher, Sundar A.; Chou, Joyce

1997-01-01

Satellite observations of the cloud liquid water path (LWP) are compared from special sensor microwave imager (SSM/I) measurements and GOES 8 imager solar reflectance (SR) measurements to ascertain the impact of sub-field-of-view (FOV) cloud effects on SSM/I 37 GHz retrievals. The SR retrievals also incorporate estimates of the cloud droplet effective radius derived from the GOES 8 3.9-micron channel. The comparisons consist of simultaneous collocated and full-resolution measurements and are limited to nonprecipitating marine stratocumulus in the eastern Pacific for two days in October 1995. The retrievals from these independent methods are consistent for overcast SSM/I FOVS, with RMS differences as low as 0.030 kg/sq m, although biases exist for clouds with more open spatial structure, where the RMS differences increase to 0.039 kg/sq m. For broken cloudiness within the SSM/I FOV the average beam-filling error (BFE) in the microwave retrievals is found to be about 22% (average cloud amount of 73%). This systematic error is comparable with the average random errors in the microwave retrievals. However, even larger BFEs can be expected for individual FOVs and for regions with less cloudiness. By scaling the microwave retrievals by the cloud amount within the FOV, the systematic BFE can be significantly reduced but with increased RMS differences of O.046-0.058 kg/sq m when compared to the SR retrievals. The beam-filling effects reported here are significant and are expected to impact directly upon studies that use instantaneous SSM/I measurements of cloud LWP, such as cloud classification studies and validation studies involving surface-based or in situ data.

Estimating surface soil moisture from SMAP observations using a Neural Network technique.

PubMed

Kolassa, J; Reichle, R H; Liu, Q; Alemohammad, S H; Gentine, P; Aida, K; Asanuma, J; Bircher, S; Caldwell, T; Colliander, A; Cosh, M; Collins, C Holifield; Jackson, T J; Martínez-Fernández, J; McNairn, H; Pacheco, A; Thibeault, M; Walker, J P

2018-01-01

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m 3 m -3 , 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m 3 m -3 , 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-04-01

This paper presents an investigation of the expected uncertainties of a single-channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC Sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single-channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single-channel COT retrieval is feasible for EPIC. For ice clouds, single-channel retrieval errors are minimal (< 2 %) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 %, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Technical note: Intercomparison of three AATSR Level 2 (L2) AOD products over China

NASA Astrophysics Data System (ADS)

Che, Yahui; Xue, Yong; Mei, Linlu; Guang, Jie; She, Lu; Guo, Jianping; Hu, Yincui; Xu, Hui; He, Xingwei; Di, Aojie; Fan, Cheng

2016-08-01

One of four main focus areas of the PEEX initiative is to establish and sustain long-term, continuous, and comprehensive ground-based, airborne, and seaborne observation infrastructure together with satellite data. The Advanced Along-Track Scanning Radiometer (AATSR) aboard ENVISAT is used to observe the Earth in dual view. The AATSR data can be used to retrieve aerosol optical depth (AOD) over both land and ocean, which is an important parameter in the characterization of aerosol properties. In recent years, aerosol retrieval algorithms have been developed both over land and ocean, taking advantage of the features of dual view, which can help eliminate the contribution of Earth's surface to top-of-atmosphere (TOA) reflectance. The Aerosol_cci project, as a part of the Climate Change Initiative (CCI), provides users with three AOD retrieval algorithms for AATSR data, including the Swansea algorithm (SU), the ATSR-2ATSR dual-view aerosol retrieval algorithm (ADV), and the Oxford-RAL Retrieval of Aerosol and Cloud algorithm (ORAC). The validation team of the Aerosol-CCI project has validated AOD (both Level 2 and Level 3 products) and AE (Ångström Exponent) (Level 2 product only) against the AERONET data in a round-robin evaluation using the validation tool of the AeroCOM (Aerosol Comparison between Observations and Models) project. For the purpose of evaluating different performances of these three algorithms in calculating AODs over mainland China, we introduce ground-based data from CARSNET (China Aerosol Remote Sensing Network), which was designed for aerosol observations in China. Because China is vast in territory and has great differences in terms of land surfaces, the combination of the AERONET and CARSNET data can validate the L2 AOD products more comprehensively. The validation results show different performances of these products in 2007, 2008, and 2010. The SU algorithm performs very well over sites with different surface conditions in mainland China from March to October, but it slightly underestimates AOD over barren or sparsely vegetated surfaces in western China, with mean bias error (MBE) ranging from 0.05 to 0.10. The ADV product has the same precision with a low root mean square error (RMSE) smaller than 0.2 over most sites and the same error distribution as the SU product. The main limits of the ADV algorithm are underestimation and applicability; underestimation is particularly obvious over the sites of Datong, Lanzhou, and Urumchi, where the dominant land cover is grassland, with an MBE larger than 0.2, and the main aerosol sources are coal combustion and dust. The ORAC algorithm has the ability to retrieve AOD at different ranges, including high AOD (larger than 1.0); however, the stability deceases significantly with increasing AOD, especially when AOD > 1.0. In addition, the ORAC product is consistent with the CARSNET product in winter (December, January, and February), whereas other validation results lack matches during winter.

A New, More Physically Based Algorithm, for Retrieving Aerosol Properties over Land from MODIS

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Kaufman, Yoram J.; Remer, Lorraine A.; Mattoo, Shana

2004-01-01

The MOD Imaging Spectrometer (MODIS) has been successfully retrieving aerosol properties, beginning in early 2000 from Terra and from mid 2002 from Aqua. Over land, the retrieval algorithm makes use of three MODIS channels, in the blue, red and infrared wavelengths. As part of the validation exercises, retrieved spectral aerosol optical thickness (AOT) has been compared via scatterplots against spectral AOT measured by the global Aerosol Robotic NETwork (AERONET). On one hand, global and long term validation looks promising, with two-thirds (average plus and minus one standard deviation) of all points falling between published expected error bars. On the other hand, regression of these points shows a positive y-offset and a slope less than 1.0. For individual regions, such as along the U.S. East Coast, the offset and slope are even worse. Here, we introduce an overhaul of the algorithm for retrieving aerosol properties over land. Some well-known weaknesses in the current aerosol retrieval from MODIS include: a) rigid assumptions about the underlying surface reflectance, b) limited aerosol models to choose from, c) simplified (scalar) radiative transfer (RT) calculations used to simulate satellite observations, and d) assumption that aerosol is transparent in the infrared channel. The new algorithm attempts to address all four problems: a) The new algorithm will include surface type information, instead of fixed ratios of the reflectance in the visible channels to the mid-IR reflectance. b) It will include updated aerosol optical properties to reflect the growing aerosol retrieved from eight-plus years of AERONE". operation. c) The effects of polarization will be including using vector RT calculations. d) Most importantly, the new algorithm does not assume that aerosol is transparent in the infrared channel. It will be an inversion of reflectance observed in the three channels (blue, red, and infrared), rather than iterative single channel retrievals. Thus, this new formulation of the MODIS aerosol retrieval over land includes more physically based surface, aerosol and radiative transfer with fewer potentially erroneous assumptions.

A similarity retrieval approach for weighted track and ambient field of tropical cyclones

NASA Astrophysics Data System (ADS)

Li, Ying; Xu, Luan; Hu, Bo; Li, Yuejun

2018-03-01

Retrieving historical tropical cyclones (TC) which have similar position and hazard intensity to the objective TC is an important means in TC track forecast and TC disaster assessment. A new similarity retrieval scheme is put forward based on historical TC track data and ambient field data, including ERA-Interim reanalysis and GFS and EC-fine forecast. It takes account of both TC track similarity and ambient field similarity, and optimal weight combination is explored subsequently. Result shows that both the distance and direction errors of TC track forecast at 24-hour timescale follow an approximately U-shape distribution. They tend to be large when the weight assigned to track similarity is close to 0 or 1.0, while relatively small when track similarity weight is from 0.2˜0.7 for distance error and 0.3˜0.6 for direction error.

Using string alignment in a query-by-humming system for real world applications

NASA Astrophysics Data System (ADS)

Sailer, Christian

2005-09-01

Though query by humming (i.e., retrieving music or information about music by singing a characteristic melody) has been a popular research topic during the past decade, few approaches have reached a level of usefulness beyond mere scientific interest. One of the main problems is the inherent contradiction between error tolerance and dicriminative power in conventional melody matching algorithms that rely on a melody contour approach to handle intonation or transcription errors. Adopting the string matching/alignment techniques from bioinformatics to melody sequences allows to directly assess the similarity between two melodies. This method takes an MPEG-7 compliant melody sequence (i.e., a list of note intervals and length ratios) as query and evaluates the steps necessary to transform it into the reference sequence. By introducing a musically founded cost-of-replace function and an adequate post processing, this method yields a measure for melodic similarity. Thus it is possible to construct a query by humming system that can properly discriminate between thousands of melodies and still be sufficiently error tolerant to be used by untrained singers. The robustness has been verified in extensive tests and real world applications.

Retrieval of background surface reflectance with BRD components from pre-running BRDF

NASA Astrophysics Data System (ADS)

Choi, Sungwon; Lee, Kyeong-Sang; Jin, Donghyun; Lee, Darae; Han, Kyung-Soo

2016-10-01

Many countries try to launch satellite to observe the Earth surface. As important of surface remote sensing is increased, the reflectance of surface is a core parameter of the ground climate. But observing the reflectance of surface by satellite have weakness such as temporal resolution and being affected by view or solar angles. The bidirectional effects of the surface reflectance may make many noises to the time series. These noises can lead to make errors when determining surface reflectance. To correct bidirectional error of surface reflectance, using correction model for normalized the sensor data is necessary. A Bidirectional Reflectance Distribution Function (BRDF) is making accuracy higher method to correct scattering (Isotropic scattering, Geometric scattering, Volumetric scattering). To correct bidirectional error of surface reflectance, BRDF was used in this study. To correct bidirectional error of surface reflectance, we apply Bidirectional Reflectance Distribution Function (BRDF) to retrieve surface reflectance. And we apply 2 steps for retrieving Background Surface Reflectance (BSR). The first step is retrieving Bidirectional Reflectance Distribution (BRD) coefficients. Before retrieving BSR, we did pre-running BRDF to retrieve BRD coefficients to correct scatterings (Isotropic scattering, Geometric scattering, Volumetric scattering). In pre-running BRDF, we apply BRDF with observed surface reflectance of SPOT/VEGETATION (VGT-S1) and angular data to get BRD coefficients for calculating scattering. After that, we apply BRDF again in the opposite direction with BRD coefficients and angular data to retrieve BSR as a second step. As a result, BSR has very similar reflectance to one of VGT-S1. And reflectance in BSR is shown adequate. The highest reflectance of BSR is not over 0.4μm in blue channel, 0.45μm in red channel, 0.55μm in NIR channel. And for validation we compare reflectance of clear sky pixel from SPOT/VGT status map data. As a result of comparing BSR with VGT-S1, bias is from 0.0116 to 0.0158 and RMSE is from 0.0459 to 0.0545. They are very reasonable results, so we confirm that BSR is similar to VGT-S1. And weakness of this study is missing pixel in BSR which are observed less time to retrieve BRD components. If missing pixels are filled, BSR is better to retrieve surface products with more accuracy. And we think that after filling the missing pixel and being more accurate, it can be useful data to retrieve surface product which made by surface reflectance like cloud masking and retrieving aerosol.

On the effect of surface emissivity on temperature retrievals. [for meteorology

NASA Technical Reports Server (NTRS)

Kornfield, J.; Susskind, J.

1977-01-01

The paper is concerned with errors in temperature retrieval caused by incorrectly assuming that surface emissivity is equal to unity. An error equation that applies to present-day atmospheric temperature sounders is derived, and the bias errors resulting from various emissivity discrepancies are calculated. A model of downward flux is presented and used to determine the effective downward flux. In the 3.7-micron region of the spectrum, emissivities of 0.6 to 0.9 have been observed over land. At a surface temperature of 290 K, if the true emissivity is 0.6 and unit emissivity is assumed, the error would be approximately 11 C. In the 11-micron region, the maximum deviation of the surface emissivity from unity was 0.05.

Comparison of a single-view and a double-view aerosol optical depth retrieval algorithm

NASA Astrophysics Data System (ADS)

Henderson, Bradley G.; Chylek, Petr

2003-11-01

We compare the results of a single-view and a double-view aerosol optical depth (AOD) retrieval algorithm applied to image pairs acquired over NASA Stennis Space Center, Mississippi. The image data were acquired by the Department of Energy's (DOE) Multispectral Thermal Imager (MTI), a pushbroom satellite imager with 15 bands from the visible to the thermal infrared. MTI has the ability to acquire imagery in pairs in which the first image is a near-nadir view and the second image is off-nadir with a zenith angle of approximately 60°. A total of 15 image pairs were used in the analysis. For a given image pair, AOD retrieval is performed twice---once using a single-view algorithm applied to the near-nadir image, then again using a double-view algorithm. Errors for both retrievals are computed by comparing the results to AERONET AOD measurements obtained at the same time and place. The single-view algorithm showed an RMS error about the mean of 0.076 in AOD units, whereas the double-view algorithm showed a modest improvement with an RMS error of 0.06. The single-view errors show a positive bias which is presumed to be a result of the empirical relationship used to determine ground reflectance in the visible. A plot of AOD error of the double-view algorithm versus time shows a noticeable trend which is interpreted to be a calibration drift. When this trend is removed, the RMS error of the double-view algorithm drops to 0.030. The single-view algorithm qualitatively appears to perform better during the spring and summer whereas the double-view algorithm seems to be less sensitive to season.

Hartman Testing of X-Ray Telescopes

NASA Technical Reports Server (NTRS)

Saha, Timo T.; Biskasch, Michael; Zhang, William W.

2013-01-01

Hartmann testing of x-ray telescopes is a simple test method to retrieve and analyze alignment errors and low-order circumferential errors of x-ray telescopes and their components. A narrow slit is scanned along the circumference of the telescope in front of the mirror and the centroids of the images are calculated. From the centroid data, alignment errors, radius variation errors, and cone-angle variation errors can be calculated. Mean cone angle, mean radial height (average radius), and the focal length of the telescope can also be estimated if the centroid data is measured at multiple focal plane locations. In this paper we present the basic equations that are used in the analysis process. These equations can be applied to full circumference or segmented x-ray telescopes. We use the Optical Surface Analysis Code (OSAC) to model a segmented x-ray telescope and show that the derived equations and accompanying analysis retrieves the alignment errors and low order circumferential errors accurately.

Importance of interpolation and coincidence errors in data fusion

NASA Astrophysics Data System (ADS)

Ceccherini, Simone; Carli, Bruno; Tirelli, Cecilia; Zoppetti, Nicola; Del Bianco, Samuele; Cortesi, Ugo; Kujanpää, Jukka; Dragani, Rossana

2018-02-01

The complete data fusion (CDF) method is applied to ozone profiles obtained from simulated measurements in the ultraviolet and in the thermal infrared in the framework of the Sentinel 4 mission of the Copernicus programme. We observe that the quality of the fused products is degraded when the fusing profiles are either retrieved on different vertical grids or referred to different true profiles. To address this shortcoming, a generalization of the complete data fusion method, which takes into account interpolation and coincidence errors, is presented. This upgrade overcomes the encountered problems and provides products of good quality when the fusing profiles are both retrieved on different vertical grids and referred to different true profiles. The impact of the interpolation and coincidence errors on number of degrees of freedom and errors of the fused profile is also analysed. The approach developed here to account for the interpolation and coincidence errors can also be followed to include other error components, such as forward model errors.

Visualizing and improving the robustness of phase retrieval algorithms

DOE PAGES

Tripathi, Ashish; Leyffer, Sven; Munson, Todd; ...

2015-06-01

Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.

Visualizing and improving the robustness of phase retrieval algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tripathi, Ashish; Leyffer, Sven; Munson, Todd

Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.

TMS evidence for a selective role of the precuneus in source memory retrieval.

PubMed

Bonnì, Sonia; Veniero, Domenica; Mastropasqua, Chiara; Ponzo, Viviana; Caltagirone, Carlo; Bozzali, Marco; Koch, Giacomo

2015-04-01

The posteromedial cortex including the precuneus (PC) is thought to be involved in episodic memory retrieval. Here we used continuous theta burst stimulation (cTBS) to disentangle the role of the precuneus in the recognition memory process in a sample of healthy subjects. During the encoding phase, subjects were presented with a series of colored pictures. Afterwards, during the retrieval phase, all previously presented items and a sample of new pictures were presented in black, and subjects were asked to indicate whether each item was new or old, and in the latter case to indicate the associated color. cTBS was delivered over PC, posterior parietal cortex (PPC) and vertex before the retrieval phase. The data were analyzed in terms of hits, false alarms, source errors and omissions. cTBS over the precuneus, but not over the PPC or the vertex, induced a selective decrease in source memory errors, indicating an improvement in context retrieval. All the other accuracy measurements were unchanged. These findings suggest a direct implication of the precuneus in successful context-dependent retrieval. Copyright © 2015 Elsevier B.V. All rights reserved.

Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land

NASA Astrophysics Data System (ADS)

Lipponen, Antti; Mielonen, Tero; Pitkänen, Mikko R. A.; Levy, Robert C.; Sawyer, Virginia R.; Romakkaniemi, Sami; Kolehmainen, Ville; Arola, Antti

2018-03-01

We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (0.47, 0.55, 0.64, and 2.1 µm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BAR significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29 % in the AOD root mean square error and decrease of about 80 % in the median bias of AOD were found globally when the BAR was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05+15 %) expected error envelope increased from 55 to 76 %. In addition to retrieving the values of AOD, FMF, and surface reflectance, the BAR also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BAR algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.

Integrated Path Differential Absorption Lidar Optimizations Based on Pre-Analyzed Atmospheric Data for ASCENDS Mission Applications

NASA Technical Reports Server (NTRS)

Pliutau, Denis; Prasad, Narasimha S.

2012-01-01

In this paper a modeling method based on data reductions is investigated which includes pre analyzed MERRA atmospheric fields for quantitative estimates of uncertainties introduced in the integrated path differential absorption methods for the sensing of various molecules including CO2. This approach represents the extension of our existing lidar modeling framework previously developed and allows effective on- and offline wavelength optimizations and weighting function analysis to minimize the interference effects such as those due to temperature sensitivity and water vapor absorption. The new simulation methodology is different from the previous implementation in that it allows analysis of atmospheric effects over annual spans and the entire Earth coverage which was achieved due to the data reduction methods employed. The effectiveness of the proposed simulation approach is demonstrated with application to the mixing ratio retrievals for the future ASCENDS mission. Independent analysis of multiple accuracy limiting factors including the temperature, water vapor interferences, and selected system parameters is further used to identify favorable spectral regions as well as wavelength combinations facilitating the reduction in total errors in the retrieved XCO2 values.

A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

DOE PAGES

Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

2017-07-20

Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100–200% for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASCmore » measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18% difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36% for the individual events. The use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122% for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. Furthermore, accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.« less

A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall-speed observations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cooper, Steven J.; Wood, Norman B.; L'Ecuyer, Tristan S.

Estimates of snowfall rate as derived from radar reflectivities alone are non-unique. Different combinations of snowflake microphysical properties and particle fall speeds can conspire to produce nearly identical snowfall rates for given radar reflectivity signatures. Such ambiguities can result in retrieval uncertainties on the order of 100–200% for individual events. Here, we use observations of particle size distribution (PSD), fall speed, and snowflake habit from the Multi-Angle Snowflake Camera (MASC) to constrain estimates of snowfall derived from Ka-band ARM zenith radar (KAZR) measurements at the Atmospheric Radiation Measurement (ARM) North Slope Alaska (NSA) Climate Research Facility site at Barrow. MASCmore » measurements of microphysical properties with uncertainties are introduced into a modified form of the optimal-estimation CloudSat snowfall algorithm (2C-SNOW-PROFILE) via the a priori guess and variance terms. Use of the MASC fall speed, MASC PSD, and CloudSat snow particle model as base assumptions resulted in retrieved total accumulations with a -18% difference relative to nearby National Weather Service (NWS) observations over five snow events. The average error was 36% for the individual events. The use of different but reasonable combinations of retrieval assumptions resulted in estimated snowfall accumulations with differences ranging from -64 to +122% for the same storm events. Retrieved snowfall rates were particularly sensitive to assumed fall speed and habit, suggesting that in situ measurements can help to constrain key snowfall retrieval uncertainties. Furthermore, accurate knowledge of these properties dependent upon location and meteorological conditions should help refine and improve ground- and space-based radar estimates of snowfall.« less

Interoperative Biopsy Site Relocalization in Endoluminal Surgery.

PubMed

Vemuri, Anant Suraj; Nicolau, Stephane; Sportes, Adrien; Marescaux, Jacques; Soler, Luc; Ayache, Nicholas

2016-09-01

Barrett's oesophagus, a premalignant condition of the oesophagus has been on a rise in the recent years. The standard diagnostic protocol for Barrett's involves obtaining biopsies at suspicious regions along the oesophagus. The localization and tracking of these biopsy sites "interoperatively" poses a significant challenge for providing targeted treatments and tracking disease progression. This paper proposes an approach to provide guided navigation and relocalization of the biopsy sites using an electromagnetic tracking system. The characteristic of our approach over existing ones is the integration of an electromagnetic sensor at the flexible endoscope tip, so that the endoscopic camera depth inside the oesophagus can be computed in real time, allowing to retrieve and display an image from a previous exploration at the same depth. We first describe our system setup and methodology for interoperative registration. We then propose three incremental experiments of our approach. First, on synthetic data with realistic noise model to analyze the error bounds of our system. The second on in vivo pig data using an optical tracking system to provide a pseudo ground truth. Accuracy results obtained were consistent with the synthetic experiments despite uncertainty introduced due to breathing motion, and remain inside acceptable error margin according to medical experts. Finally, a third experiment designed using data from pigs to simulate a real task of biopsy site relocalization, and evaluated by ten gastro-intestinal experts. It clearly demonstrated the benefit of our system toward assisted guidance by improving the biopsy site retrieval rate from 47.5% to 94%.

A Proposed Extension to the Soil Moisture and Ocean Salinity Level 2 Algorithm for Mixed Forest and Moderate Vegetation Pixels

NASA Technical Reports Server (NTRS)

Panciera, Rocco; Walker, Jeffrey P.; Kalma, Jetse; Kim, Edward

2011-01-01

The Soil Moisture and Ocean Salinity (SMOS)mission, launched in November 2009, provides global maps of soil moisture and ocean salinity by measuring the L-band (1.4 GHz) emission of the Earth's surface with a spatial resolution of 40-50 km.Uncertainty in the retrieval of soilmoisture over large heterogeneous areas such as SMOS pixels is expected, due to the non-linearity of the relationship between soil moisture and the microwave emission. The current baseline soilmoisture retrieval algorithm adopted by SMOS and implemented in the SMOS Level 2 (SMOS L2) processor partially accounts for the sub-pixel heterogeneity of the land surface, by modelling the individual contributions of different pixel fractions to the overall pixel emission. This retrieval approach is tested in this study using airborne L-band data over an area the size of a SMOS pixel characterised by a mix Eucalypt forest and moderate vegetation types (grassland and crops),with the objective of assessing its ability to correct for the soil moisture retrieval error induced by the land surface heterogeneity. A preliminary analysis using a traditional uniform pixel retrieval approach shows that the sub-pixel heterogeneity of land cover type causes significant errors in soil moisture retrieval (7.7%v/v RMSE, 2%v/v bias) in pixels characterised by a significant amount of forest (40-60%). Although the retrieval approach adopted by SMOS partially reduces this error, it is affected by errors beyond the SMOS target accuracy, presenting in particular a strong dry bias when a fraction of the pixel is occupied by forest (4.1%v/v RMSE,-3.1%v/v bias). An extension to the SMOS approach is proposed that accounts for the heterogeneity of vegetation optical depth within the SMOS pixel. The proposed approach is shown to significantly reduce the error in retrieved soil moisture (2.8%v/v RMSE, -0.3%v/v bias) in pixels characterised by a critical amount of forest (40-60%), at the limited cost of only a crude estimate of the optical depth of the forested area (better than 35% uncertainty). This study makes use of an unprecedented data set of airborne L-band observations and ground supporting data from the National Airborne Field Experiment 2005 (NAFE'05), which allowed accurate characterisation of the land surface heterogeneity over an area equivalent in size to a SMOS pixel.

Validation and Error Characterization for the Global Precipitation Measurement

NASA Technical Reports Server (NTRS)

Bidwell, Steven W.; Adams, W. J.; Everett, D. F.; Smith, E. A.; Yuter, S. E.

2003-01-01

The Global Precipitation Measurement (GPM) is an international effort to increase scientific knowledge on the global water cycle with specific goals of improving the understanding and the predictions of climate, weather, and hydrology. These goals will be achieved through several satellites specifically dedicated to GPM along with the integration of numerous meteorological satellite data streams from international and domestic partners. The GPM effort is led by the National Aeronautics and Space Administration (NASA) of the United States and the National Space Development Agency (NASDA) of Japan. In addition to the spaceborne assets, international and domestic partners will provide ground-based resources for validating the satellite observations and retrievals. This paper describes the validation effort of Global Precipitation Measurement to provide quantitative estimates on the errors of the GPM satellite retrievals. The GPM validation approach will build upon the research experience of the Tropical Rainfall Measuring Mission (TRMM) retrieval comparisons and its validation program. The GPM ground validation program will employ instrumentation, physical infrastructure, and research capabilities at Supersites located in important meteorological regimes of the globe. NASA will provide two Supersites, one in a tropical oceanic and the other in a mid-latitude continental regime. GPM international partners will provide Supersites for other important regimes. Those objectives or regimes not addressed by Supersites will be covered through focused field experiments. This paper describes the specific errors that GPM ground validation will address, quantify, and relate to the GPM satellite physical retrievals. GPM will attempt to identify the source of errors within retrievals including those of instrument calibration, retrieval physical assumptions, and algorithm applicability. With the identification of error sources, improvements will be made to the respective calibration, assumption, or algorithm. The instrumentation and techniques of the Supersites will be discussed. The GPM core satellite, with its dual-frequency radar and conically scanning radiometer, will provide insight into precipitation drop-size distributions and potentially increased measurement capabilities of light rain and snowfall. The ground validation program will include instrumentation and techniques commensurate with these new measurement capabilities.

Sensitivities of simulated satellite views of clouds to subgrid-scale overlap and condensate heterogeneity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.

Satellite simulators are often used to account for limitations in satellite retrievals of cloud properties in comparisons between models and satellite observations. The purpose of the simulator framework is to enable more robust evaluation of model cloud properties, so that di erences between models and observations can more con dently be attributed to model errors. However, these simulators are subject to uncertainties themselves. A fundamental uncertainty exists in connecting the spatial scales at which cloud properties are retrieved with those at which clouds are simulated in global models. In this study, we create a series of sensitivity tests using 4more » km global model output from the Multiscale Modeling Framework to evaluate the sensitivity of simulated satellite retrievals when applied to climate models whose grid spacing is many tens to hundreds of kilometers. In particular, we examine the impact of cloud and precipitation overlap and of condensate spatial variability. We find the simulated retrievals are sensitive to these assumptions. Specifically, using maximum-random overlap with homogeneous cloud and precipitation condensate, which is often used in global climate models, leads to large errors in MISR and ISCCP-simulated cloud cover and in CloudSat-simulated radar reflectivity. To correct for these errors, an improved treatment of unresolved clouds and precipitation is implemented for use with the simulator framework and is shown to substantially reduce the identified errors.« less

High speed phase retrieval of in-line holograms by the assistance of corresponding off-axis holograms.

PubMed

Orzó, László

2015-06-29

Retrieving correct phase information from an in-line hologram is difficult as the object wave field and the diffractions of the zero order and the conjugate object term overlap. The existing iterative numerical phase retrieval methods are slow, especially in the case of high Fresnel number systems. Conversely, the reconstruction of the object wave field from an off-axis hologram is simple, but due to the applied spatial frequency filtering the achievable resolution is confined. Here, a new, high-speed algorithm is introduced that efficiently incorporates the data of an auxiliary off-axis hologram in the phase retrieval of the corresponding in-line hologram. The efficiency of the introduced combined phase retrieval method is demonstrated by simulated and measured holograms.

Correction of Rayleigh Scattering Effects in Cloud Optical Thickness Retrievals

NASA Technical Reports Server (NTRS)

Wang, Meng-Hua; King, Michael D.

1997-01-01

We present results that demonstrate the effects of Rayleigh scattering on the 9 retrieval of cloud optical thickness at a visible wavelength (0.66 Am). The sensor-measured radiance at a visible wavelength (0.66 Am) is usually used to infer remotely the cloud optical thickness from aircraft or satellite instruments. For example, we find that without removing Rayleigh scattering effects, errors in the retrieved cloud optical thickness for a thin water cloud layer (T = 2.0) range from 15 to 60%, depending on solar zenith angle and viewing geometry. For an optically thick cloud (T = 10), on the other hand, errors can range from 10 to 60% for large solar zenith angles (0-60 deg) because of enhanced Rayleigh scattering. It is therefore particularly important to correct for Rayleigh scattering contributions to the reflected signal from a cloud layer both (1) for the case of thin clouds and (2) for large solar zenith angles and all clouds. On the basis of the single scattering approximation, we propose an iterative method for effectively removing Rayleigh scattering contributions from the measured radiance signal in cloud optical thickness retrievals. The proposed correction algorithm works very well and can easily be incorporated into any cloud retrieval algorithm. The Rayleigh correction method is applicable to cloud at any pressure, providing that the cloud top pressure is known to within +/- 100 bPa. With the Rayleigh correction the errors in retrieved cloud optical thickness are usually reduced to within 3%. In cases of both thin cloud layers and thick ,clouds with large solar zenith angles, the errors are usually reduced by a factor of about 2 to over 10. The Rayleigh correction algorithm has been tested with simulations for realistic cloud optical and microphysical properties with different solar and viewing geometries. We apply the Rayleigh correction algorithm to the cloud optical thickness retrievals from experimental data obtained during the Atlantic Stratocumulus Transition Experiment (ASTEX) conducted near the Azores in June 1992 and compare these results to corresponding retrievals obtained using 0.88 Am. These results provide an example of the Rayleigh scattering effects on thin clouds and further test the Rayleigh correction scheme. Using a nonabsorbing near-infrared wavelength lambda (0.88 Am) in retrieving cloud optical thickness is only applicable over oceans, however, since most land surfaces are highly reflective at 0.88 Am. Hence successful global retrievals of cloud optical thickness should remove Rayleigh scattering effects when using reflectance measurements at 0.66 Am.

When Practice Doesn't Lead to Retrieval: An Analysis of Children's Errors with Simple Addition

ERIC Educational Resources Information Center

de Villiers, Celéste; Hopkins, Sarah

2013-01-01

Counting strategies initially used by young children to perform simple addition are often replaced by more efficient counting strategies, decomposition strategies and rule-based strategies until most answers are encoded in memory and can be directly retrieved. Practice is thought to be the key to developing fluent retrieval of addition facts. This…

Evaluating the design of an earth radiation budget instrument with system simulations. Part 2: Minimization of instantaneous sampling errors for CERES-I

NASA Technical Reports Server (NTRS)

Stowe, Larry; Hucek, Richard; Ardanuy, Philip; Joyce, Robert

1994-01-01

Much of the new record of broadband earth radiation budget satellite measurements to be obtained during the late 1990s and early twenty-first century will come from the dual-radiometer Clouds and Earth's Radiant Energy System Instrument (CERES-I) flown aboard sun-synchronous polar orbiters. Simulation studies conducted in this work for an early afternoon satellite orbit indicate that spatial root-mean-square (rms) sampling errors of instantaneous CERES-I shortwave flux estimates will range from about 8.5 to 14.0 W/m on a 2.5 deg latitude and longitude grid resolution. Rms errors in longwave flux estimates are only about 20% as large and range from 1.5 to 3.5 W/sq m. These results are based on an optimal cross-track scanner design that includes 50% footprint overlap to eliminate gaps in the top-of-the-atmosphere coverage, and a 'smallest' footprint size to increase the ratio in the number of observations lying within to the number of observations lying on grid area boundaries. Total instantaneous measurement error also depends on the variability of anisotropic reflectance and emission patterns and on retrieval methods used to generate target area fluxes. Three retrieval procedures from both CERES-I scanners (cross-track and rotating azimuth plane) are used. (1) The baseline Earth Radiaton Budget Experiment (ERBE) procedure, which assumes that errors due to the use of mean angular dependence models (ADMs) in the radiance-to-flux inversion process nearly cancel when averaged over grid areas. (2) To estimate N, instantaneous ADMs are estimated from the multiangular, collocated observations of the two scanners. These observed models replace the mean models in computation of satellite flux estimates. (3) The scene flux approach, conducts separate target-area retrievals for each ERBE scene category and combines their results using area weighting by scene type. The ERBE retrieval performs best when the simulated radiance field departs from the ERBE mean models by less than 10%. For larger perturbations, both the scene flux and collocation methods produce less error than the ERBE retrieval. The scene flux technique is preferable, however, because it involves fewer restrictive assumptions.

GOCI Yonsei aerosol retrieval version 2 products: an improved algorithm and error analysis with uncertainty estimation from 5-year validation over East Asia

NASA Astrophysics Data System (ADS)

Choi, Myungje; Kim, Jhoon; Lee, Jaehwa; Kim, Mijin; Park, Young-Je; Holben, Brent; Eck, Thomas F.; Li, Zhengqiang; Song, Chul H.

2018-01-01

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed to retrieve hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD had accuracy comparable to ground-based and other satellite-based observations but still had errors because of uncertainties in surface reflectance and simple cloud masking. In addition, near-real-time (NRT) processing was not possible because a monthly database for each year encompassing the day of retrieval was required for the determination of surface reflectance. This study describes the improved GOCI YAER algorithm version 2 (V2) for NRT processing with improved accuracy based on updates to the cloud-masking and surface-reflectance calculations using a multi-year Rayleigh-corrected reflectance and wind speed database, and inversion channels for surface conditions. The improved GOCI AOD τG is closer to that of the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD than was the case for AOD from the YAER V1 algorithm. The V2 τG has a lower median bias and higher ratio within the MODIS expected error range (0.60 for land and 0.71 for ocean) compared with V1 (0.49 for land and 0.62 for ocean) in a validation test against Aerosol Robotic Network (AERONET) AOD τA from 2011 to 2016. A validation using the Sun-Sky Radiometer Observation Network (SONET) over China shows similar results. The bias of error (τG - τA) is within -0.1 and 0.1, and it is a function of AERONET AOD and Ångström exponent (AE), scattering angle, normalized difference vegetation index (NDVI), cloud fraction and homogeneity of retrieved AOD, and observation time, month, and year. In addition, the diagnostic and prognostic expected error (PEE) of τG are estimated. The estimated PEE of GOCI V2 AOD is well correlated with the actual error over East Asia, and the GOCI V2 AOD over South Korea has a higher ratio within PEE than that over China and Japan.

Error-correcting pairs for a public-key cryptosystem

NASA Astrophysics Data System (ADS)

Pellikaan, Ruud; Márquez-Corbella, Irene

2017-06-01

Code-based Cryptography (CBC) is a powerful and promising alternative for quantum resistant cryptography. Indeed, together with lattice-based cryptography, multivariate cryptography and hash-based cryptography are the principal available techniques for post-quantum cryptography. CBC was first introduced by McEliece where he designed one of the most efficient Public-Key encryption schemes with exceptionally strong security guarantees and other desirable properties that still resist to attacks based on Quantum Fourier Transform and Amplitude Amplification. The original proposal, which remains unbroken, was based on binary Goppa codes. Later, several families of codes have been proposed in order to reduce the key size. Some of these alternatives have already been broken. One of the main requirements of a code-based cryptosystem is having high performance t-bounded decoding algorithms which is achieved in the case the code has a t-error-correcting pair (ECP). Indeed, those McEliece schemes that use GRS codes, BCH, Goppa and algebraic geometry codes are in fact using an error-correcting pair as a secret key. That is, the security of these Public-Key Cryptosystems is not only based on the inherent intractability of bounded distance decoding but also on the assumption that it is difficult to retrieve efficiently an error-correcting pair. In this paper, the class of codes with a t-ECP is proposed for the McEliece cryptosystem. Moreover, we study the hardness of distinguishing arbitrary codes from those having a t-error correcting pair.

Statistical retrieval of thin liquid cloud microphysical properties using ground-based infrared and microwave observations

NASA Astrophysics Data System (ADS)

Marke, Tobias; Ebell, Kerstin; Löhnert, Ulrich; Turner, David D.

2016-12-01

In this article, liquid water cloud microphysical properties are retrieved by a combination of microwave and infrared ground-based observations. Clouds containing liquid water are frequently occurring in most climate regimes and play a significant role in terms of interaction with radiation. Small perturbations in the amount of liquid water contained in the cloud can cause large variations in the radiative fluxes. This effect is enhanced for thin clouds (liquid water path, LWP <100 g/m2), which makes accurate retrieval information of the cloud properties crucial. Due to large relative errors in retrieving low LWP values from observations in the microwave domain and a high sensitivity for infrared methods when the LWP is low, a synergistic retrieval based on a neural network approach is built to estimate both LWP and cloud effective radius (reff). These statistical retrievals can be applied without high computational demand but imply constraints like prior information on cloud phase and cloud layering. The neural network retrievals are able to retrieve LWP and reff for thin clouds with a mean relative error of 9% and 17%, respectively. This is demonstrated using synthetic observations of a microwave radiometer (MWR) and a spectrally highly resolved infrared interferometer. The accuracy and robustness of the synergistic retrievals is confirmed by a low bias in a radiative closure study for the downwelling shortwave flux, even for marginally invalid scenes. Also, broadband infrared radiance observations, in combination with the MWR, have the potential to retrieve LWP with a higher accuracy than a MWR-only retrieval.

Retrieval and Validation of Precipitable Water Vapor using GPS Datasets of Mobile Observation Vehicle in the Eastern Coast of Korea

NASA Astrophysics Data System (ADS)

Kim, Y. J.; Kim, S. J.; Kim, G. T.; Choi, B. C.; Shim, J.; Kim, B. G.

2015-12-01

The results from the global positioning system (GPS) measurements of mobile observation vehicle (MOVE) in the eastern coast of Korea have been compared with a fixed observation reference (REF) values from the fixed GPS sites to assess performance of precipitable water vapor (PWV) retrievals in a kinematic environment. MOVE-PWV retrievals have comparatively similar trends and reasonable agreement with REF-PWV with a root mean square error (RMSE) of 7.4 mm and R2 of 0.61 indicating a statistical significance at the 1% level (p-value of 0.01). Especially PWV retrievals from the June cases showed better agreement (mean bias of 2.1 mm and RMSE of 3.8 mm) with the other cases. We further investigated the relationships of determinant factors of GPS signals with the PWV retrievals for the detailed error analysis. As a result, both multipath (MP) errors of L1 and L2 pseudo-range had the best indices (0.75~0.99 m) for the June cases. We also found that both position dilution of precision (PDOP) and signal to noise ratio (SNR) values in June cases during the 1st period (0000~0100 UTC) are better (lower and higher) than those in Non-June cases, which is strongly associated with good accuracy (RMSE of 3.5 mm) of PWV in June cases. These results clearly demonstrate those effects on PWV accuracy, that is, analytic results of the key factors (MP errors, PDOP, and SNR) that could affect GPS signals should be considered for obtaining more stable performance. Taking advantage of MOVE, we would provide water vapor information with high spatial and temporal resolutions in case that weather dramatically changes such as in Korean Peninsula.

Altitude registration of limb-scattered radiation

NASA Astrophysics Data System (ADS)

Moy, Leslie; Bhartia, Pawan K.; Jaross, Glen; Loughman, Robert; Kramarova, Natalya; Chen, Zhong; Taha, Ghassan; Chen, Grace; Xu, Philippe

2017-01-01

One of the largest constraints to the retrieval of accurate ozone profiles from UV backscatter limb sounding sensors is altitude registration. Two methods, the Rayleigh scattering attitude sensing (RSAS) and absolute radiance residual method (ARRM), are able to determine altitude registration to the accuracy necessary for long-term ozone monitoring. The methods compare model calculations of radiances to measured radiances and are independent of onboard tracking devices. RSAS determines absolute altitude errors, but, because the method is susceptible to aerosol interference, it is limited to latitudes and time periods with minimal aerosol contamination. ARRM, a new technique introduced in this paper, can be applied across all seasons and altitudes. However, it is only appropriate for relative altitude error estimates. The application of RSAS to Limb Profiler (LP) measurements from the Ozone Mapping and Profiler Suite (OMPS) on board the Suomi NPP (SNPP) satellite indicates tangent height (TH) errors greater than 1 km with an absolute accuracy of ±200 m. Results using ARRM indicate a ˜ 300 to 400 m intra-orbital TH change varying seasonally ±100 m, likely due to either errors in the spacecraft pointing or in the geopotential height (GPH) data that we use in our analysis. ARRM shows a change of ˜ 200 m over ˜ 5 years with a relative accuracy (a long-term accuracy) of ±100 m outside the polar regions.

Integrating uncertainty propagation in GNSS radio occultation retrieval: from excess phase to atmospheric bending angle profiles

NASA Astrophysics Data System (ADS)

Schwarz, Jakob; Kirchengast, Gottfried; Schwaerz, Marc

2018-05-01

Global Navigation Satellite System (GNSS) radio occultation (RO) observations are highly accurate, long-term stable data sets and are globally available as a continuous record from 2001. Essential climate variables for the thermodynamic state of the free atmosphere - such as pressure, temperature, and tropospheric water vapor profiles (involving background information) - can be derived from these records, which therefore have the potential to serve as climate benchmark data. However, to exploit this potential, atmospheric profile retrievals need to be very accurate and the remaining uncertainties quantified and traced throughout the retrieval chain from raw observations to essential climate variables. The new Reference Occultation Processing System (rOPS) at the Wegener Center aims to deliver such an accurate RO retrieval chain with integrated uncertainty propagation. Here we introduce and demonstrate the algorithms implemented in the rOPS for uncertainty propagation from excess phase to atmospheric bending angle profiles, for estimated systematic and random uncertainties, including vertical error correlations and resolution estimates. We estimated systematic uncertainty profiles with the same operators as used for the basic state profiles retrieval. The random uncertainty is traced through covariance propagation and validated using Monte Carlo ensemble methods. The algorithm performance is demonstrated using test day ensembles of simulated data as well as real RO event data from the satellite missions CHAllenging Minisatellite Payload (CHAMP); Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC); and Meteorological Operational Satellite A (MetOp). The results of the Monte Carlo validation show that our covariance propagation delivers correct uncertainty quantification from excess phase to bending angle profiles. The results from the real RO event ensembles demonstrate that the new uncertainty estimation chain performs robustly. Together with the other parts of the rOPS processing chain this part is thus ready to provide integrated uncertainty propagation through the whole RO retrieval chain for the benefit of climate monitoring and other applications.

Phase Retrieval System for Assessing Diamond Turning and Optical Surface Defects

NASA Technical Reports Server (NTRS)

Dean, Bruce; Maldonado, Alex; Bolcar, Matthew

2011-01-01

An optical design is presented for a measurement system used to assess the impact of surface errors originating from diamond turning artifacts. Diamond turning artifacts are common by-products of optical surface shaping using the diamond turning process (a diamond-tipped cutting tool used in a lathe configuration). Assessing and evaluating the errors imparted by diamond turning (including other surface errors attributed to optical manufacturing techniques) can be problematic and generally requires the use of an optical interferometer. Commercial interferometers can be expensive when compared to the simple optical setup developed here, which is used in combination with an image-based sensing technique (phase retrieval). Phase retrieval is a general term used in optics to describe the estimation of optical imperfections or aberrations. This turnkey system uses only image-based data and has minimal hardware requirements. The system is straightforward to set up, easy to align, and can provide nanometer accuracy on the measurement of optical surface defects.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-02-16

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m −2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m −2.« less

MODIS 3km Aerosol Product: Algorithm and Global Perspective

NASA Technical Reports Server (NTRS)

Remer, L. A.; Mattoo, S.; Levy, R. C.; Munchak, L.

2013-01-01

After more than a decade of producing a nominal 10 km aerosol product based on the dark target method, the MODIS aerosol team will be releasing a nominal 3 km product as part of their Collection 6 release. The new product differs from the original 10 km product only in the manner in which reflectance pixels are ingested, organized and selected by the aerosol algorithm. Overall, the 3 km product closely mirrors the 10 km product. However, the finer resolution product is able to retrieve over ocean closer to islands and coastlines, and is better able to resolve fine aerosol features such as smoke plumes over both ocean and land. In some situations, it provides retrievals over entire regions that the 10 km product barely samples. In situations traditionally difficult for the dark target algorithm, such as over bright or urban surfaces the 3 km product introduces isolated spikes of artificially high aerosol optical depth (AOD) that the 10 km algorithm avoids. Over land, globally, the 3 km product appears to be 0.01 to 0.02 higher than the 10 km product, while over ocean, the 3 km algorithm is retrieving a proportionally greater number of very low aerosol loading situations. Based on collocations with ground-based observations for only six months, expected errors associated with the 3 km land product are determined to be greater than for the 10 km product: 0.05 0.25 AOD. Over ocean, the suggestion is for expected errors to be the same as the 10 km product: 0.03 0.05 AOD. The advantage of the product is on the local scale, which will require continued evaluation not addressed here. Nevertheless, the new 3 km product is expected to provide important information complementary to existing satellite-derived products and become an important tool for the aerosol community.

Model studies of the beam-filling error for rain-rate retrieval with microwave radiometers

NASA Technical Reports Server (NTRS)

Ha, Eunho; North, Gerald R.

1995-01-01

Low-frequency (less than 20 GHz) single-channel microwave retrievals of rain rate encounter the problem of beam-filling error. This error stems from the fact that the relationship between microwave brightness temperature and rain rate is nonlinear, coupled with the fact that the field of view is large or comparable to important scales of variability of the rain field. This means that one may not simply insert the area average of the brightness temperature into the formula for rain rate without incurring both bias and random error. The statistical heterogeneity of the rain-rate field in the footprint of the instrument is key to determining the nature of these errors. This paper makes use of a series of random rain-rate fields to study the size of the bias and random error associated with beam filling. A number of examples are analyzed in detail: the binomially distributed field, the gamma, the Gaussian, the mixed gamma, the lognormal, and the mixed lognormal ('mixed' here means there is a finite probability of no rain rate at a point of space-time). Of particular interest are the applicability of a simple error formula due to Chiu and collaborators and a formula that might hold in the large field of view limit. It is found that the simple formula holds for Gaussian rain-rate fields but begins to fail for highly skewed fields such as the mixed lognormal. While not conclusively demonstrated here, it is suggested that the notionof climatologically adjusting the retrievals to remove the beam-filling bias is a reasonable proposition.

Combining Passive Microwave Sounders with CYGNSS information for improved retrievals: Observations during Hurricane Harvey

NASA Astrophysics Data System (ADS)

Schreier, M. M.

2017-12-01

The launch of CYGNSS (Cyclone Global Navigation Satellite System) has added an interesting component to satellite observations: it can provide wind speeds in the tropical area with a high repetition rate. Passive microwave sounders that are overpassing the same region can benefit from this information, when it comes to the retrieval of temperature or water profiles: the uncertainty about wind speeds has a strong impact on emissivity and reflectivity calculations with respect to surface temperature. This has strong influences on the uncertainty of retrieval of temperature and water content, especially under extreme weather conditions. Adding CYGNSS information to the retrieval can help to reduce errors and provide a significantly better sounder retrieval. Based on observations during Hurricane Harvey, we want to show the impact of CYGNSS data on the retrieval of passive microwave sensors. We will show examples on the impact on the retrieval from polar orbiting instruments, like the Advanced Technology Microwave Sounder (ATMS) and AMSU-A/B on NOAA-18 and 19. In addition we will also show the impact on retrievals from HAMSR (High Altitude MMIC Sounding Radiometer), which was flying on the Global Hawk during the EPOCH campaign. We will compare the results with other observations and estimate the impact of additional CYGNSS information on the microwave retrieval, especially on the impact in error and uncertainty reduction. We think, that a synergetic use of these different data sources could significantly help to produce better assimilation products for forecast assimilation.

Ground-based remote sensing of thin clouds in the Arctic

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Zhao, C.

2013-05-01

This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" at 862.5 cm-1, 935.8 cm-1, and 988.4 cm-1 where absorption by water vapour is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in the first two of these micro-windows, constrained by the transmission through clouds of primarily stratospheric ozone emission at 1040 cm-1. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius re, visible optical depth τ, number concentration N, and water path WP are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement programme (ARM) North Slope of Alaska - Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with both ground-based microwave radiometer measurements of liquid water path and a method that uses combined shortwave and microwave measurements to retrieve re, τ and N. Compared to other retrieval methods, advantages of this technique include its ability to characterise thin clouds year round, that water vapour is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies and that it relies on a fairly comprehensive suite of ground based measurements.

Improved Soundings and Error Estimates using AIRS/AMSU Data

NASA Technical Reports Server (NTRS)

Susskind, Joel

2006-01-01

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1 K, and layer precipitable water with an rms error of 20 percent, in cases with up to 80 percent effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the at-launch algorithm, and a post-launch algorithm which differed only in the minor details from the at-launch algorithm, have been described previously. The post-launch algorithm, referred to as AIRS Version 4.0, has been used by the Goddard DAAC to analyze and distribute AIRS retrieval products. In this paper we show progress made toward the AIRS Version 5.0 algorithm which will be used by the Goddard DAAC starting late in 2006. A new methodology has been developed to provide accurate case by case error estimates for retrieved geophysical parameters and for the channel by channel cloud cleared radiances used to derive the geophysical parameters from the AIRS/AMSU observations. These error estimates are in turn used for quality control of the derived geophysical parameters and clear column radiances. Improvements made to the retrieval algorithm since Version 4.0 are described as well as results comparing Version 5.0 retrieval accuracy and spatial coverage with those obtained using Version 4.0.

Land Surface Temperature Measurements form EOS MODIS Data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1996-01-01

We have developed a physics-based land-surface temperature (LST) algorithm for simultaneously retrieving surface band-averaged emissivities and temperatures from day/night pairs of MODIS (Moderate Resolution Imaging Spectroradiometer) data in seven thermal infrared bands. The set of 14 nonlinear equations in the algorithm is solved with the statistical regression method and the least-squares fit method. This new LST algorithm was tested with simulated MODIS data for 80 sets of band-averaged emissivities calculated from published spectral data of terrestrial materials in wide ranges of atmospheric and surface temperature conditions. Comprehensive sensitivity and error analysis has been made to evaluate the performance of the new LST algorithm and its dependence on variations in surface emissivity and temperature, upon atmospheric conditions, as well as the noise-equivalent temperature difference (NE(Delta)T) and calibration accuracy specifications of the MODIS instrument. In cases with a systematic calibration error of 0.5%, the standard deviations of errors in retrieved surface daytime and nighttime temperatures fall between 0.4-0.5 K over a wide range of surface temperatures for mid-latitude summer conditions. The standard deviations of errors in retrieved emissivities in bands 31 and 32 (in the 10-12.5 micrometer IR spectral window region) are 0.009, and the maximum error in retrieved LST values falls between 2-3 K. Several issues related to the day/night LST algorithm (uncertainties in the day/night registration and in surface emissivity changes caused by dew occurrence, and the cloud cover) have been investigated. The LST algorithms have been validated with MODIS Airborne Simulator (MAS) dada and ground-based measurement data in two field campaigns conducted in Railroad Valley playa, NV in 1995 and 1996. The MODIS LST version 1 software has been delivered.

Evaluating Light Rain Drop Size Estimates from Multiwavelength Micropulse Lidar Network Profiling

NASA Technical Reports Server (NTRS)

Lolli, Simone; Welton, Ellsworth J.; Campbell, James R.

2013-01-01

This paper investigates multiwavelength retrievals of median equivolumetric drop diameter D(sub 0) suitable for drizzle and light rain, through collocated 355-/527-nm Micropulse Lidar Network (MPLNET) observations collected during precipitation occurring 9 May 2012 at the Goddard Space Flight Center (GSFC) project site. By applying a previously developed retrieval technique for infrared bands, the method exploits the differential backscatter by liquid water at 355 and 527 nm for water drops larger than approximately 50 micrometers. In the absence of molecular and aerosol scattering and neglecting any transmission losses, the ratio of the backscattering profiles at the two wavelengths (355 and 527 nm), measured from light rain below the cloud melting layer, can be described as a color ratio, which is directly related to D(sub 0). The uncertainty associated with this method is related to the unknown shape of the drop size spectrum and to the measurement error. Molecular and aerosol scattering contributions and relative transmission losses due to the various atmospheric constituents should be evaluated to derive D(sub 0) from the observed color ratio profiles. This process is responsible for increasing the uncertainty in the retrieval. Multiple scattering, especially for UV lidar, is another source of error, but it exhibits lower overall uncertainty with respect to other identified error sources. It is found that the total error upper limit on D(sub 0) approaches 50%. The impact of this retrieval for long-term MPLNET monitoring and its global data archive is discussed.

Orbiting Carbon Observatory-2 (OCO-2) Cloud Screening; Validation Against Collocated MODIS and Initial Comparison to CALIOP Data

NASA Technical Reports Server (NTRS)

Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip; Cronk, Heather W.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert; Crisp, David;

An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database

NASA Astrophysics Data System (ADS)

Zhang, Hai; Kondragunta, Shobha; Laszlo, Istvan; Liu, Hongqing; Remer, Lorraine A.; Huang, Jingfeng; Superczynski, Stephen; Ciren, Pubu

2016-09-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has been retrieving aerosol optical thickness (AOT), operationally and globally, over ocean and land since shortly after S-NPP launch in 2011. However, the current operational VIIRS AOT retrieval algorithm over land has two limitations in its assumptions for land surfaces: (1) it only retrieves AOT over the dark surfaces and (2) it assumes that the global surface reflectance ratios between VIIRS bands are constants. In this work, we develop a surface reflectance ratio database over land with a spatial resolution 0.1° × 0.1° using 2 years of VIIRS top of atmosphere reflectances. We enhance the current operational VIIRS AOT retrieval algorithm by applying the surface reflectance ratio database in the algorithm. The enhanced algorithm is able to retrieve AOT over both dark and bright surfaces. Over bright surfaces, the VIIRS AOT retrievals from the enhanced algorithm have a correlation of 0.79, mean bias of -0.008, and standard deviation (STD) of error of 0.139 when compared against the ground-based observations at the global AERONET (Aerosol Robotic Network) sites. Over dark surfaces, the VIIRS AOT retrievals using the surface reflectance ratio database improve the root-mean-square error from 0.150 to 0.123. The use of the surface reflectance ratio database also increases the data coverage of more than 20% over dark surfaces. The AOT retrievals over bright surfaces are comparable to MODIS Deep Blue AOT retrievals.

Errorless learning and spaced retrieval: how do these methods fare in healthy and clinical populations?

PubMed

Haslam, Catherine; Hodder, Kathryn I; Yates, Philip J

2011-04-01

While errorless learning and spaced retrieval have both proved effective in helping many patients with acquired brain injury (ABI) and dementia learn novel information, it is not clear which of these principles we should apply to target treatment most effectively. To address this issue we conducted a systematic comparison of these principles in three experiments, comparing their effectiveness in healthy controls (N = 60), patients with ABI (N = 30), and patients with dementia (N = 15). Participants were asked to learn face-name associations, and the relative effectiveness of the principles over and above trial-and-error learning was investigated. The results were remarkably consistent across experiments: Both errorless learning and spaced retrieval produced greater accuracy in name recall than did trial-and-error learning, but recall under conditions of spaced retrieval was significantly better than that under errorless learning. We discuss the implications of these findings and suggest that spaced retrieval may be the stronger memory rehabilitation principle when it comes to learning face-name associations in people with mild to moderate memory impairment.

Citation Help in Databases: The More Things Change, the More They Stay the Same

ERIC Educational Resources Information Center

Van Ullen, Mary; Kessler, Jane

2012-01-01

In 2005, the authors reviewed citation help in databases and found an error rate of 4.4 errors per citation. This article describes a follow-up study that revealed a modest improvement in the error rate to 3.4 errors per citation, still unacceptably high. The most problematic area was retrieval statements. The authors conclude that librarians…

Monthly mean global satellite data sets available in CCM history tape format

NASA Technical Reports Server (NTRS)

Hurrell, James W.; Campbell, G. Garrett

1992-01-01

Satellite data for climate monitoring have become increasingly important over the past decade, especially with increasing concern for inadvertent antropogenic climate change. Although most satellite based data are of short record, satellites can provide the global coverage that traditional meteorological observations network lack. In addition, satellite data are invaluable for the validation of climate models, and they are useful for many diagnostic studies. Herein, several satellite data sets were processed and transposed into 'history tape' format for use with the Community Climate Model (CCM) modular processor. Only a few of the most widely used and best documented data sets were selected at this point, although future work will expand the number of data sets examined as well as update the archived data sets. An attempt was made to include data of longer record and only monthly averaged data were processed. For studies using satellite data over an extended period, it is important to recognize the impact of changes in instrumentation, drift in instrument calibration, errors introduced by retrieval algorithms and other sources of errors such as those resulting from insufficient space and/or time sampling.

A Physical Validation Program for the GPM Mission

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2003-01-01

The GPM mission is currently planned for start in the late 2007 - early 2008 time frame. Its main scientific goal is to help answer pressing scientific problems arising within the context of global and regional water cycling. These problems cut across a hierarchy of scales and include climate-water cycle interactions, techniques for improving weather and climate predictions, and better methods for combining observed precipitation with hydrometeorological prediction models for applications to hazardous flood-producing storms, seasonal flood draught conditions, and fresh water resource assessments. The GPM mission will expand the scope of precipitation measurement through the use of a constellation of some 9 satellites, one of which will be an advanced TRMM-like core satellite carrying a dual-frequency Ku-Ka band precipitation radar and an advanced, multifrequency passive microwave radiometer with vertical-horizontal polarization discrimination. The other constellation members will include new dedicated satellites and co-existing operational/research satellites carrying similar (but not identical) passive microwave radiometers. The goal of the constellation is to achieve approximately 3-hour sampling at any spot on the globe -- continuously. The constellation's orbit architecture will consist of a mix of sun-synchronous and non-sun-synchronous satellites with the core satellite providing measurements of cloud-precipitation microphysical processes plus calibration-quality rainrate retrievals to be used with the other retrieval information to ensure bias-free constellation coverage. A major requirement before the retrieved rainfall information generated by the GPM mission can be used effectively by prognostic models to improve weather forecasts, hydrometeorological forecasts, and climate model reanalysis simulations is a capability to quantify the error characteristics of the retrievals. A solution for this problem has been upheld in past precipitation missions because of the lack of suitable error modeling systems incorporated into the validation programs and data distribution systems. An overview of how NASA intends to overcome this problem for the GPM mission using a physically-based error modeling approach within a multi-faceted validation program is described. The solution is to first identify specific user requirements and then determine the most stringent of these requirements that embodies all essential error characterization information needed by the entire user community. In the context of NASA s scientific agenda for the GPM mission, the most stringent user requirement is found within the data assimilation community. The fundamental theory of data assimilation vis-a-vis ingesting satellite precipitation information into the pre-forecast initializations is based on quantifying the conditional bias and precision errors of individual rain retrievals, and the space-time structure of the precision error (i.e., the spatial-temporal error covariance). By generating the hardware and software capability to produce this information in a near real-time fashion, and to couple the derived quantitative error properties to the actual retrieved rainrates, all key validation users can be satisfied. The talk will describe the essential components of the hardware and software systems needed to generate such near real-time error properties, as well as the various paradigm shifts needed within the validation community to produce a validation program relevant to the precipitation user community.

The Effects of Rainfall Inhomogeneity on Climate Variability of Rainfall Estimated from Passive Microwave Sensors

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Poyner, Philip; Berg, Wesley; Thomas-Stahle, Jody

2007-01-01

Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (T(sub b)) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the oblique incidence of current radiometers. Because of the horizontal averaging that occurs away from the nadir direction, the beam-filling error is found to be only a fraction of what has been reported previously in the literature based upon plane-parallel calculations. For a FOV representative of the 19-GHz radiometer channel (18 km X 28 km) aboard the Tropical Rainfall Measuring Mission (TRMM), the mean beam-filling correction computed in this study for tropical atmospheres is 1.26 instead of 1.52 computed from plane-parallel techniques. The slant-path solution is also less sensitive to finescale rainfall inhomogeneity and is, thus, able to make use of 4-km radar data from the TRMM Precipitation Radar (PR) in order to map regional and seasonal distributions of observed rainfall inhomogeneity in the Tropics. The data are examined to assess the expected errors introduced into climate rainfall records by unresolved changes in rainfall inhomogeneity. Results show that global mean monthly errors introduced by not explicitly accounting for rainfall inhomogeneity do not exceed 0.5% if the beam-filling error is allowed to be a function of rainfall rate and freezing level and does not exceed 2% if a universal beam-filling correction is applied that depends only upon the freezing level. Monthly regional errors can be significantly larger. Over the Indian Ocean, errors as large as 8% were found if the beam-filling correction is allowed to vary with rainfall rate and freezing level while errors of 15% were found if a universal correction is used.

Note: Focus error detection device for thermal expansion-recovery microscopy (ThERM).

PubMed

Domené, E A; Martínez, O E

2013-01-01

An innovative focus error detection method is presented that is only sensitive to surface curvature variations, canceling both thermoreflectance and photodefelection effects. The detection scheme consists of an astigmatic probe laser and a four-quadrant detector. Nonlinear curve fitting of the defocusing signal allows the retrieval of a cutoff frequency, which only depends on the thermal diffusivity of the sample and the pump beam size. Therefore, a straightforward retrieval of the thermal diffusivity of the sample is possible with microscopic lateral resolution and high axial resolution (~100 pm).

Flash-Type Discrimination

NASA Technical Reports Server (NTRS)

Koshak, William J.

2010-01-01

This viewgraph presentation describes the significant progress made in the flash-type discrimination algorithm development. The contents include: 1) Highlights of Progress for GLM-R3 Flash-Type discrimination Algorithm Development; 2) Maximum Group Area (MGA) Data; 3) Retrieval Errors from Simulations; and 4) Preliminary Global-scale Retrieval.

SMOS salinity retrieval by using Support Vector Regression (SVR)

NASA Astrophysics Data System (ADS)

Katagis, Thomas; Fernández-Prieto, Diego; Marconcini, Mattia; Sabia, Roberto; Martinez, Justino

2013-04-01

The Soil Moisture and Ocean Salinity (SMOS) mission was launched in November 2009 within the framework of the European Space Agency (ESA) Living Planet programme. Over the oceans, it aims at providing Sea Surface Salinity (SSS) maps with spatial and temporal coverage adequate for large scale oceanography. A comprehensive inversion scheme has been defined and implemented in the operational retrieval chain to allow proper SSS estimates in a single satellite overpass (L2 product) from the multi-angular brightness temperatures (TBs) measured by SMOS. Such SMOS operational L2 salinity processor minimizes the difference between the measured and modeled TBs, including additional constraints on Sea Surface Temperature (SST) and wind speed auxiliary fields. In particular, by adopting a maximum-likelihood Bayesian approach, the inversion scheme retrieves salinity under an iterative convergence loop. However, despite the implemented iterative technique is well established and robust, it is still prone to limitations; for instance, the presence of local minima in the cost function cannot be excluded. Moreover, previous studies have demonstrated that the background and observational terms of the cost function are not properly balanced and this is likely to introduce errors in the retrieval procedure. In order to overcome such potential drawbacks, in this study it is proposed a novel approach for the SSS estimation based on the ɛ-insensitive Support Vector Regression (SVR), where both SMOS L1 measurements and auxiliary parameters are used as input. The SVR technique already proved capable of high generalization and robustness in a variety of different applications, with a limited complexity in handling the learning phase. Notably, instead of minimizing the observed training error, it attempts to minimize the generalization error bound so as to achieve generalized performance. For this purpose, the original input domain is mapped into a higher dimensionality space (where the function underlying the data is supposed to have increased flatness) and linear regression is performed. The SVR training is performed using suitable in situ SSS data (i.e., ARGO buoys data) collected in a representative region of the ocean. So far, in situ data coming from a match-up ARGO database in November 2010 over the South Pacific constitute the preliminary benchmark of the study. Ongoing activities point at extending this spatial and temporal frame to assess the robustness of the method. The in situ data have been collocated with SMOS TB measurements and additional parameters (e.g., SST and wind speed) in the learning phase of the SVR under various training/testing configurations. Afterwards, the SSS regression has been performed out of the SMOS TBs or emissivities. Estimated SVR salinity fields are in general (very) well correlated with ARGO data. The analysis of the different impact of the various features has been performed once a rigorous data filtering/flagging is applied, and misfit (SSSSVR-SSSARGO) statistics have been computed. For assessing the effectiveness of the proposed method, final results will be compared to those obtained using the official SMOS SSS retrieval algorithm.

Adaptive correction of ensemble forecasts

NASA Astrophysics Data System (ADS)

Pelosi, Anna; Battista Chirico, Giovanni; Van den Bergh, Joris; Vannitsem, Stephane

2017-04-01

Forecasts from numerical weather prediction (NWP) models often suffer from both systematic and non-systematic errors. These are present in both deterministic and ensemble forecasts, and originate from various sources such as model error and subgrid variability. Statistical post-processing techniques can partly remove such errors, which is particularly important when NWP outputs concerning surface weather variables are employed for site specific applications. Many different post-processing techniques have been developed. For deterministic forecasts, adaptive methods such as the Kalman filter are often used, which sequentially post-process the forecasts by continuously updating the correction parameters as new ground observations become available. These methods are especially valuable when long training data sets do not exist. For ensemble forecasts, well-known techniques are ensemble model output statistics (EMOS), and so-called "member-by-member" approaches (MBM). Here, we introduce a new adaptive post-processing technique for ensemble predictions. The proposed method is a sequential Kalman filtering technique that fully exploits the information content of the ensemble. One correction equation is retrieved and applied to all members, however the parameters of the regression equations are retrieved by exploiting the second order statistics of the forecast ensemble. We compare our new method with two other techniques: a simple method that makes use of a running bias correction of the ensemble mean, and an MBM post-processing approach that rescales the ensemble mean and spread, based on minimization of the Continuous Ranked Probability Score (CRPS). We perform a verification study for the region of Campania in southern Italy. We use two years (2014-2015) of daily meteorological observations of 2-meter temperature and 10-meter wind speed from 18 ground-based automatic weather stations distributed across the region, comparing them with the corresponding COSMO-LEPS ensemble forecasts. Deterministic verification scores (e.g., mean absolute error, bias) and probabilistic scores (e.g., CRPS) are used to evaluate the post-processing techniques. We conclude that the new adaptive method outperforms the simpler running bias-correction. The proposed adaptive method often outperforms the MBM method in removing bias. The MBM method has the advantage of correcting the ensemble spread, although it needs more training data.

Improved Stratospheric Temperature Retrievals for Climate Reanalysis

NASA Technical Reports Server (NTRS)

Rokke, L.; Joiner, J.

1999-01-01

The Data Assimilation Office (DAO) is embarking on plans to generate a twenty year reanalysis data set of climatic atmospheric variables. One of the focus points will be in the evaluation of the dynamics of the stratosphere. The Stratospheric Sounding Unit (SSU), flown as part of the TIROS Operational Vertical Sounder (TOVS), is one of the primary stratospheric temperature sensors flown consistently throughout the reanalysis period. Seven unique sensors made the measurements over time, with individual instrument characteristics that need to be addressed. The stratospheric temperatures being assimilated across satellite platforms will profoundly impact the reanalysis dynamical fields. To attempt to quantify aspects of instrument and retrieval bias we are carefully collecting and analyzing all available information on the sensors, their instrument anomalies, forward model errors and retrieval biases. For the retrieval of stratospheric temperatures, we adapted the minimum variance approach of Jazwinski (1970) and Rodgers (1976) and applied it to the SSU soundings. In our algorithm, the state vector contains an initial guess of temperature from a model six hour forecast provided by the Goddard EOS Data Assimilation System (GEOS/DAS). This is combined with an a priori covariance matrix, a forward model parameterization, and specifications of instrument noise characteristics. A quasi-Newtonian iteration is used to obtain convergence of the retrieved state to the measurement vector. This algorithm also enables us to analyze and address the systematic errors associated with the unique characteristics of the cell pressures on the individual SSU instruments and the resolving power of the instruments to vertical gradients in the stratosphere. The preliminary results of the improved retrievals and their assimilation as well as baseline calculations of bias and rms error between the NESDIS operational product and col-located ground measurements will be presented.

An improved triple collocation algorithm for decomposing autocorrelated and white soil moisture retrieval errors

USDA-ARS?s Scientific Manuscript database

If not properly account for, auto-correlated errors in observations can lead to inaccurate results in soil moisture data analysis and reanalysis. Here, we propose a more generalized form of the triple collocation algorithm (GTC) capable of decomposing the total error variance of remotely-sensed surf...

Some Insights of Spectral Optimization in Ocean Color Inversion

NASA Technical Reports Server (NTRS)

Lee, Zhongping; Franz, Bryan; Shang, Shaoling; Dong, Qiang; Arnone, Robert

2011-01-01

In the past decades various algorithms have been developed for the retrieval of water constituents from the measurement of ocean color radiometry, and one of the approaches is spectral optimization. This approach defines an error target (or error function) between the input remote sensing reflectance and the output remote sensing reflectance, with the latter modeled with a few variables that represent the optically active properties (such as the absorption coefficient of phytoplankton and the backscattering coefficient of particles). The values of the variables when the error reach a minimum (optimization is achieved) are considered the properties that form the input remote sensing reflectance; or in other words, the equations are solved numerically. The applications of this approach implicitly assume that the error is a monotonic function of the various variables. Here, with data from numerical simulation and field measurements, we show the shape of the error surface, in a way to justify the possibility of finding a solution of the various variables. In addition, because the spectral properties could be modeled differently, impacts of such differences on the error surface as well as on the retrievals are also presented.

Retrieval of the aerosol optical thickness from UV global irradiance measurements

NASA Astrophysics Data System (ADS)

Costa, M. J.; Salgueiro, V.; Bortoli, D.; Obregón, M. A.; Antón, M.; Silva, A. M.

2015-12-01

The UV irradiance is measured at Évora since several years, where a CIMEL sunphotometer integrated in AERONET is also installed. In the present work, measurements of UVA (315 - 400 nm) irradiances taken with Kipp&Zonen radiometers, as well as satellite data of ozone total column values, are used in combination with radiative transfer calculations, to estimate the aerosol optical thickness (AOT) in the UV. The retrieved UV AOT in Évora is compared with AERONET AOT (at 340 and 380 nm) and a fairly good agreement is found with a root mean square error of 0.05 (normalized root mean square error of 8.3%) and a mean absolute error of 0.04 (mean percentage error of 2.9%). The methodology is then used to estimate the UV AOT in Sines, an industrialized site on the Atlantic western coast, where the UV irradiance is monitored since 2013 but no aerosol information is available.

Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method

PubMed Central

Zhong, Xinke; Huo, Xing; Ren, Chao; Labed, Jelila; Li, Zhao-Liang

2016-01-01

Land Surface Temperature (LST) is a key parameter in climate systems. The methods for retrieving LST from hyperspectral thermal infrared data either require accurate atmospheric profile data or require thousands of continuous channels. We aim to retrieve LST for natural land surfaces from hyperspectral thermal infrared data using an adapted multi-channel method taking Land Surface Emissivity (LSE) properly into consideration. In the adapted method, LST can be retrieved by a linear function of 36 brightness temperatures at Top of Atmosphere (TOA) using channels where LSE has high values. We evaluated the adapted method using simulation data at nadir and satellite data near nadir. The Root Mean Square Error (RMSE) of the LST retrieved from the simulation data is 0.90 K. Compared with an LST product from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat, the error in the LST retrieved from the Infared Atmospheric Sounding Interferometer (IASI) is approximately 1.6 K. The adapted method can be used for the near-real-time production of an LST product and to provide the physical method to simultaneously retrieve atmospheric profiles, LST, and LSE with a first-guess LST value. The limitations of the adapted method are that it requires the minimum LSE in the spectral interval of 800–950 cm−1 larger than 0.95 and it has not been extended for off-nadir measurements. PMID:27187408

Web Image Retrieval Using Self-Organizing Feature Map.

ERIC Educational Resources Information Center

Wu, Qishi; Iyengar, S. Sitharama; Zhu, Mengxia

2001-01-01

Provides an overview of current image retrieval systems. Describes the architecture of the SOFM (Self Organizing Feature Maps) based image retrieval system, discussing the system architecture and features. Introduces the Kohonen model, and describes the implementation details of SOFM computation and its learning algorithm. Presents a test example…

GOCI Yonsei aerosol retrieval version 2 aerosol products: improved algorithm description and error analysis with uncertainty estimation from 5-year validation over East Asia

NASA Astrophysics Data System (ADS)

Choi, M.; Kim, J.; Lee, J.; KIM, M.; Park, Y. J.; Holben, B. N.; Eck, T. F.; Li, Z.; Song, C. H.

2017-12-01

The Geostationary Ocean Color Imager (GOCI) Yonsei aerosol retrieval (YAER) version 1 algorithm was developed for retrieving hourly aerosol optical depth at 550 nm (AOD) and other subsidiary aerosol optical properties over East Asia. The GOCI YAER AOD showed comparable accuracy compared to ground-based and other satellite-based observations, but still had errors due to uncertainties in surface reflectance and simple cloud masking. Also, it was not capable of near-real-time (NRT) processing because it required a monthly database of each year encompassing the day of retrieval for the determination of surface reflectance. This study describes the improvement of GOCI YAER algorithm to the version 2 (V2) for NRT processing with improved accuracy from the modification of cloud masking, surface reflectance determination using multi-year Rayleigh corrected reflectance and wind speed database, and inversion channels per surface conditions. Therefore, the improved GOCI AOD ( ) is similar with those of Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) AOD compared to V1 of the YAER algorithm. The shows reduced median bias and increased ratio within range (i.e. absolute expected error range of MODIS AOD) compared to V1 in the validation results using Aerosol Robotic Network (AERONET) AOD ( ) from 2011 to 2016. The validation using the Sun-Sky Radiometer Observation Network (SONET) over China also shows similar results. The bias of error ( is within -0.1 and 0.1 range as a function of AERONET AOD and AE, scattering angle, NDVI, cloud fraction and homogeneity of retrieved AOD, observation time, month, and year. Also, the diagnostic and prognostic expected error (DEE and PEE, respectively) of are estimated. The estimated multiple PEE of GOCI V2 AOD is well matched with actual error over East Asia, and the GOCI V2 AOD over Korea shows higher ratio within PEE compared to over China and Japan. Hourly AOD products based on the improved GOCI YAER AOD could contribute to better understandings of aerosols in terms of long-term climate changes and short-term air quality monitoring and forecasting perspectives over East Asia, especially rapid diurnal variation and transboundary transport.

Validation of high-resolution MAIAC aerosol product over South America

NASA Astrophysics Data System (ADS)

Martins, V. S.; Lyapustin, A.; de Carvalho, L. A. S.; Barbosa, C. C. F.; Novo, E. M. L. M.

2017-07-01

Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD550 was performed using ground-truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground-based measurements, with a correlation coefficient (R) close to unity (RTerra:0.956 and RAqua: 0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 ( 66%) of retrievals are within the expected error (EE = ±(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset 0.006). Additionally, MAIAC CWV presents quantitative information with R 0.97 and more than 70% of retrievals within error (±15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.

Preparation breeds success: Brain activity predicts remembering.

PubMed

Herron, Jane E; Evans, Lisa H

2018-05-09

Successful retrieval of episodic information is thought to involve the adoption of memory states that ensure that stimulus events are treated as episodic memory cues (retrieval mode) and which can bias retrieval toward specific memory contents (retrieval orientation). The neural correlates of these memory states have been identified in many neuroimaging studies, yet critically there is no direct evidence that they facilitate retrieval success. We cued participants before each test item to prepare to complete an episodic (retrieve the encoding task performed on the item at study) or a non-episodic task. Our design allowed us to separate event-related potentials (ERPs) elicited by the preparatory episodic cue according to the accuracy of the subsequent memory judgment. We predicted that a correlate of retrieval orientation should be larger in magnitude preceding correct source judgments than that preceding source errors. This hypothesis was confirmed. Preparatory ERPs at bilateral frontal sites were significantly more positive-going when preceding correct source judgments than when preceding source errors or correct responses in a non-episodic baseline task. Furthermore this effect was not evident prior to recognized items associated with incorrect source judgments. This pattern of results indicates a direct contribution of retrieval orientation to the recovery of task-relevant information and highlights the value of separating preparatory neural activity at retrieval according to subsequent memory accuracy. Moreover, at a more general level this work demonstrates the important role of pre-stimulus processing in ecphory, which has remained largely neglected to date. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Direct Retrieval of Sulfur Dioxide Amount and Altitude from Spaceborne Hyperspectral UV Measurements: Theory and Application

NASA Technical Reports Server (NTRS)

Yang, Kau; Liu, Xiong; Bhartia, Pawan K.; Krotkov, Nickolay A.; Carn, Simon A.; Hughes, Eric J.; Krueger, Arlin J.; Spurr, Robert D.; Trahan, Samuel G.

2010-01-01

We describe the physical processes by which a vertically localized absorber perturbs the top-of-atmosphere solar backscattered ultraviolet (UV) radiance. The distinct spectral responses to perturbations of an absorber in its column amount and layer altitude provide the basis for a practical satellite retrieval technique, the Extended Iterative Spectral Fitting (EISF) algorithm, for the simultaneous retrieval of these quantities of a SO2 plume. In addition, the EISF retrieval provides an improved UV aerosol index for quantifying the spectral contrast of apparent scene reflectance at the bottom of atmosphere bounded by the surface and/or cloud; hence it can be used for detection of the presence or absence of UV absorbing aerosols. We study the performance and characterize the uncertainties of the EISF algorithm using synthetic backscattered UV radiances, retrievals from which can be compared with those used in the simulation. Our findings indicate that the presence of aerosols (both absorbing and nonabsorbing) does not cause large errors in EISF retrievals under most observing conditions when they are located below the SO2 plume. The EISF retrievals assuming a homogeneous field of view can provide accurate column amounts for inhomogeneous scenes, but they always underestimate the plume altitudes. The EISF algorithm reduces systematic errors present in existing linear retrieval algorithms that use prescribed SO2 plume heights. Applying the EISF algorithm to Ozone Monitoring Instrument satellite observations of the recent Kasatochi volcanic eruption, we demonstrate the successful retrieval of effective plume altitude of volcanic SO2, and we also show the improvement in accuracy in the corresponding SO2 columns.

Recent study, but not retrieval, of knowledge protects against learning errors.

PubMed

Mullet, Hillary G; Umanath, Sharda; Marsh, Elizabeth J

2014-11-01

Surprisingly, people incorporate errors into their knowledge bases even when they have the correct knowledge stored in memory (e.g., Fazio, Barber, Rajaram, Ornstein, & Marsh, 2013). We examined whether heightening the accessibility of correct knowledge would protect people from later reproducing misleading information that they encountered in fictional stories. In Experiment 1, participants studied a series of target general knowledge questions and their correct answers either a few minutes (high accessibility of knowledge) or 1 week (low accessibility of knowledge) before exposure to misleading story references. In Experiments 2a and 2b, participants instead retrieved the answers to the target general knowledge questions either a few minutes or 1 week before the rest of the experiment. Reading the relevant knowledge directly before the story-reading phase protected against reproduction of the misleading story answers on a later general knowledge test, but retrieving that same correct information did not. Retrieving stored knowledge from memory might actually enhance the encoding of relevant misinformation.

Phase Retrieval Using a Genetic Algorithm on the Systematic Image-Based Optical Alignment Testbed

NASA Technical Reports Server (NTRS)

Taylor, Jaime R.

2003-01-01

NASA s Marshall Space Flight Center s Systematic Image-Based Optical Alignment (SIBOA) Testbed was developed to test phase retrieval algorithms and hardware techniques. Individuals working with the facility developed the idea of implementing phase retrieval by breaking the determination of the tip/tilt of each mirror apart from the piston motion (or translation) of each mirror. Presented in this report is an algorithm that determines the optimal phase correction associated only with the piston motion of the mirrors. A description of the Phase Retrieval problem is first presented. The Systematic Image-Based Optical Alignment (SIBOA) Testbeb is then described. A Discrete Fourier Transform (DFT) is necessary to transfer the incoming wavefront (or estimate of phase error) into the spatial frequency domain to compare it with the image. A method for reducing the DFT to seven scalar/matrix multiplications is presented. A genetic algorithm is then used to search for the phase error. The results of this new algorithm on a test problem are presented.

Comparisons of the error budgets associated with ground-based FTIR measurements of atmospheric CH4 profiles at Île de la Réunion and Jungfraujoch.

NASA Astrophysics Data System (ADS)

Vanhaelewyn, Gauthier; Duchatelet, Pierre; Vigouroux, Corinne; Dils, Bart; Kumps, Nicolas; Hermans, Christian; Demoulin, Philippe; Mahieu, Emmanuel; Sussmann, Ralf; de Mazière, Martine

2010-05-01

The Fourier Transform Infra Red (FTIR) remote measurements of atmospheric constituents at the observatories at Saint-Denis (20.90°S, 55.48°E, 50 m a.s.l., Île de la Réunion) and Jungfraujoch (46.55°N, 7.98°E, 3580 m a.s.l., Switzerland) are affiliated to the Network for the Detection of Atmospheric Composition Change (NDACC). The European NDACC FTIR data for CH4 were improved and homogenized among the stations in the EU project HYMN. One important application of these data is their use for the validation of satellite products, like the validation of SCIAMACHY or IASI CH4 columns. Therefore, it is very important that errors and uncertainties associated to the ground-based FTIR CH4 data are well characterized. In this poster we present a comparison of errors on retrieved vertical concentration profiles of CH4 between Saint-Denis and Jungfraujoch. At both stations, we have used the same retrieval algorithm, namely SFIT2 v3.92 developed jointly at the NASA Langley Research Center, the National Center for Atmospheric Research (NCAR) and the National Institute of Water and Atmosphere Research (NIWA) at Lauder, New Zealand, and error evaluation tools developed at the Belgian Institute for Space Aeronomy (BIRA-IASB). The error components investigated in this study are: smoothing, noise, temperature, instrumental line shape (ILS) (in particular the modulation amplitude and phase), spectroscopy (in particular the pressure broadening and intensity), interfering species and solar zenith angle (SZA) error. We will determine if the characteristics of the sites in terms of altitude, geographic locations and atmospheric conditions produce significant differences in the error budgets for the retrieved CH4 vertical profiles

Connecting Satellite-Based Precipitation Estimates to Users

NASA Technical Reports Server (NTRS)

Huffman, George J.; Bolvin, David T.; Nelkin, Eric

2018-01-01

Beginning in 1997, the Merged Precipitation Group at NASA Goddard has distributed gridded global precipitation products built by combining satellite and surface gauge data. This started with the Global Precipitation Climatology Project (GPCP), then the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), and recently the Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG). This 20+-year (and on-going) activity has yielded an important set of insights and lessons learned for making state-of-the-art precipitation data accessible to the diverse communities of users. Merged-data products critically depend on the input sensors and the retrieval algorithms providing accurate, reliable estimates, but it is also important to provide ancillary information that helps users determine suitability for their application. We typically provide fields of estimated random error, and recently reintroduced the quality index concept at user request. Also at user request we have added a (diagnostic) field of estimated precipitation phase. Over time, increasingly more ancillary fields have been introduced for intermediate products that give expert users insight into the detailed performance of the combination algorithm, such as individual merged microwave and microwave-calibrated infrared estimates, the contributing microwave sensor types, and the relative influence of the infrared estimate.

Theoretical evaluation of errors in aerosol optical depth retrievals from ground-based direct-sun measurements due to circumsolar and related effects

NASA Astrophysics Data System (ADS)

Kocifaj, Miroslav; Gueymard, Christian A.

2011-02-01

Aerosol optical depth (AOD) has a crucial importance for estimating the optical properties of the atmosphere, and is constantly present in optical models of aerosol systems. Any error in aerosol optical depth (∂AOD) has direct and indirect consequences. On the one hand, such errors affect the accuracy of radiative transfer models (thus implying, e.g., potential errors in the evaluation of radiative forcing by aerosols). Additionally, any error in determining AOD is reflected in the retrieved microphysical properties of aerosol particles, which might therefore be inaccurate. Three distinct effects (circumsolar radiation, optical mass, and solar disk's brightness distribution) affecting ∂AOD are qualified and quantified in the present study. The contribution of circumsolar (CS) radiation to the measured flux density of direct solar radiation has received more attention than the two other effects in the literature. It varies rapidly with meteorological conditions and size distribution of the aerosol particles, but also with instrument field of view. Numerical simulations of the three effects just mentioned were conducted, assuming otherwise "perfect" experimental conditions. The results show that CS is responsible for the largest error in AOD, while the effect of brightness distribution (BD) has only a negligible impact. The optical mass (OM) effect yields negligible errors in AOD generally, but noticeable errors for low sun (within 10° of the horizon). In general, the OM and BD effects result in negative errors in AOD (i.e. the true AOD is smaller than that of the experimental determination), conversely to CS. Although the rapid increase in optical mass at large zenith angles can change the sign of ∂AOD, the CS contribution frequently plays the leading role in ∂AOD. To maximize the accuracy in AOD retrievals, the CS effect should not be ignored. In practice, however, this effect can be difficult to evaluate correctly unless the instantaneous aerosols size distribution is known from, e.g., inversion techniques.

Expected trace gas and aerosol retrieval accuracy of the Geostationary Environment Monitoring Spectrometer

NASA Astrophysics Data System (ADS)

Jeong, U.; Kim, J.; Liu, X.; Lee, K. H.; Chance, K.; Song, C. H.

2015-12-01

The predicted accuracy of the trace gases and aerosol retrievals from the geostationary environment monitoring spectrometer (GEMS) was investigated. The GEMS is one of the first sensors to monitor NO2, SO2, HCHO, O3, and aerosols onboard geostationary earth orbit (GEO) over Asia. Since the GEMS is not launched yet, the simulated measurements and its precision were used in this study. The random and systematic component of the measurement error was estimated based on the instrument design. The atmospheric profiles were obtained from Model for Ozone And Related chemical Tracers (MOZART) simulations and surface reflectances were obtained from climatology of OMI Lambertian equivalent reflectance. The uncertainties of the GEMS trace gas and aerosol products were estimated based on the OE method using the atmospheric profile and surface reflectance. Most of the estimated uncertainties of NO2, HCHO, stratospheric and total O3 products satisfied the user's requirements with sufficient margin. However, about 26% of the estimated uncertainties of SO2 and about 30% of the estimated uncertainties of tropospheric O3 do not meet the required precision. Particularly the estimated uncertainty of SO2 is high in winter, when the emission is strong in East Asia. Further efforts are necessary in order to improve the retrieval accuracy of SO2 and tropospheric O3 in order to reach the scientific goal of GEMS. Random measurement error of GEMS was important for the NO2, SO2, and HCHO retrieval, while both the random and systematic measurement errors were important for the O3 retrievals. The degree of freedom for signal of tropospheric O3 was 0.8 ± 0.2 and that for stratospheric O3 was 2.9 ± 0.5. The estimated uncertainties of the aerosol retrieval from GEMS measurements were predicted to be lower than the required precision for the SZA range of the trace gas retrievals.

Coherent Doppler Lidar for Boundary Layer Studies and Wind Energy

NASA Astrophysics Data System (ADS)

Choukulkar, Aditya

This thesis outlines the development of a vector retrieval technique, based on data assimilation, for a coherent Doppler LIDAR (Light Detection and Ranging). A detailed analysis of the Optimal Interpolation (OI) technique for vector retrieval is presented. Through several modifications to the OI technique, it is shown that the modified technique results in significant improvement in velocity retrieval accuracy. These modifications include changes to innovation covariance portioning, covariance binning, and analysis increment calculation. It is observed that the modified technique is able to make retrievals with better accuracy, preserves local information better, and compares well with tower measurements. In order to study the error of representativeness and vector retrieval error, a lidar simulator was constructed. Using the lidar simulator a thorough sensitivity analysis of the lidar measurement process and vector retrieval is carried out. The error of representativeness as a function of scales of motion and sensitivity of vector retrieval to look angle is quantified. Using the modified OI technique, study of nocturnal flow in Owens' Valley, CA was carried out to identify and understand uncharacteristic events on the night of March 27th 2006. Observations from 1030 UTC to 1230 UTC (0230 hr local time to 0430 hr local time) on March 27 2006 are presented. Lidar observations show complex and uncharacteristic flows such as sudden bursts of westerly cross-valley wind mixing with the dominant up-valley wind. Model results from Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS RTM) and other in-situ instrumentations are used to corroborate and complement these observations. The modified OI technique is used to identify uncharacteristic and extreme flow events at a wind development site. Estimates of turbulence and shear from this technique are compared to tower measurements. A formulation for equivalent wind speed in the presence of variations in wind speed and direction, combined with shear is developed and used to determine wind energy content in presence of turbulence.

Trait dissociation and commission errors in memory reports of emotional events.

PubMed

Merckelbach, Harald; Zeles, Gwen; Van Bergen, Saskia; Giesbrecht, Timo

2007-01-01

In 2 studies we examined whether trait dissociation is related to spontaneous commission errors (reports of events that did not occur) in free recall of emotional events. We also explored whether the functional locus of the dissociation-commission link is related to repeated retrieval or shallow encoding. In Experiment 1 participants were exposed to a staged incident and were repeatedly asked to add more information to their written accounts of the event. Dissociation levels were related to commission errors, indicating that people who report many dissociative experiences tend to make more commission errors. However, it was not the case that the overall increase in commission errors over successive retrieval attempts was typical for high dissociative participants. In Experiment 2 participants saw a video fragment of a severe car accident. During the video, half the participants performed a dual task, and the other half did not. Participants performing the dual task made more commission errors than controls, but this effect was not more pronounced in those with high trait dissociation scores. These studies show that there is a link between dissociation and spontaneous commission errors in memory reports of emotional events, but the functional locus of this link remains unclear.

Error analysis of the crystal orientations obtained by the dictionary approach to EBSD indexing.

PubMed

Ram, Farangis; Wright, Stuart; Singh, Saransh; De Graef, Marc

2017-10-01

The efficacy of the dictionary approach to Electron Back-Scatter Diffraction (EBSD) indexing was evaluated through the analysis of the error in the retrieved crystal orientations. EBSPs simulated by the Callahan-De Graef forward model were used for this purpose. Patterns were noised, distorted, and binned prior to dictionary indexing. Patterns with a high level of noise, with optical distortions, and with a 25 × 25 pixel size, when the error in projection center was 0.7% of the pattern width and the error in specimen tilt was 0.8°, were indexed with a 0.8° mean error in orientation. The same patterns, but 60 × 60 pixel in size, were indexed by the standard 2D Hough transform based approach with almost the same orientation accuracy. Optimal detection parameters in the Hough space were obtained by minimizing the orientation error. It was shown that if the error in detector geometry can be reduced to 0.1% in projection center and 0.1° in specimen tilt, the dictionary approach can retrieve a crystal orientation with a 0.2° accuracy. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantitative, Comparable Coherent Anti-Stokes Raman Scattering (CARS) Spectroscopy: Correcting Errors in Phase Retrieval

PubMed Central

Camp, Charles H.; Lee, Young Jong; Cicerone, Marcus T.

2017-01-01

Coherent anti-Stokes Raman scattering (CARS) microspectroscopy has demonstrated significant potential for biological and materials imaging. To date, however, the primary mechanism of disseminating CARS spectroscopic information is through pseudocolor imagery, which explicitly neglects a vast majority of the hyperspectral data. Furthermore, current paradigms in CARS spectral processing do not lend themselves to quantitative sample-to-sample comparability. The primary limitation stems from the need to accurately measure the so-called nonresonant background (NRB) that is used to extract the chemically-sensitive Raman information from the raw spectra. Measurement of the NRB on a pixel-by-pixel basis is a nontrivial task; thus, reference NRB from glass or water are typically utilized, resulting in error between the actual and estimated amplitude and phase. In this manuscript, we present a new methodology for extracting the Raman spectral features that significantly suppresses these errors through phase detrending and scaling. Classic methods of error-correction, such as baseline detrending, are demonstrated to be inaccurate and to simply mask the underlying errors. The theoretical justification is presented by re-developing the theory of phase retrieval via the Kramers-Kronig relation, and we demonstrate that these results are also applicable to maximum entropy method-based phase retrieval. This new error-correction approach is experimentally applied to glycerol spectra and tissue images, demonstrating marked consistency between spectra obtained using different NRB estimates, and between spectra obtained on different instruments. Additionally, in order to facilitate implementation of these approaches, we have made many of the tools described herein available free for download. PMID:28819335

Estimates of Single Sensor Error Statistics for the MODIS Matchup Database Using Machine Learning

NASA Astrophysics Data System (ADS)

Kumar, C.; Podesta, G. P.; Minnett, P. J.; Kilpatrick, K. A.

2017-12-01

Sea surface temperature (SST) is a fundamental quantity for understanding weather and climate dynamics. Although sensors aboard satellites provide global and repeated SST coverage, a characterization of SST precision and bias is necessary for determining the suitability of SST retrievals in various applications. Guidance on how to derive meaningful error estimates is still being developed. Previous methods estimated retrieval uncertainty based on geophysical factors, e.g. season or "wet" and "dry" atmospheres, but the discrete nature of these bins led to spatial discontinuities in SST maps. Recently, a new approach clustered retrievals based on the terms (excluding offset) in the statistical algorithm used to estimate SST. This approach resulted in over 600 clusters - too many to understand the geophysical conditions that influence retrieval error. Using MODIS and buoy SST matchups (2002 - 2016), we use machine learning algorithms (recursive and conditional trees, random forests) to gain insight into geophysical conditions leading to the different signs and magnitudes of MODIS SST residuals (satellite SSTs minus buoy SSTs). MODIS retrievals were first split into three categories: < -0.4 C, -0.4 C ≤ residual ≤ 0.4 C, and > 0.4 C. These categories are heavily unbalanced, with residuals > 0.4 C being much less frequent. Performance of classification algorithms is affected by imbalance, thus we tested various rebalancing algorithms (oversampling, undersampling, combinations of the two). We consider multiple features for the decision tree algorithms: regressors from the MODIS SST algorithm, proxies for temperature deficit, and spatial homogeneity of brightness temperatures (BTs), e.g., the range of 11 μm BTs inside a 25 km2 area centered on the buoy location. These features and a rebalancing of classes led to an 81.9% accuracy when classifying SST retrievals into the < -0.4 C and -0.4 C ≤ residual ≤ 0.4 C categories. Spatial homogeneity in BTs consistently appears as a very important variable for classification, suggesting that unidentified cloud contamination still is one of the causes leading to negative SST residuals. Precision and accuracy of error estimates from our decision tree classifier are enhanced using this knowledge.

Uncertainties of aerosol retrieval from neglecting non-sphericity of dust aerosols

NASA Astrophysics Data System (ADS)

Li, Chi; Xue, Yong; Yang, Leiku; Guang, Jie

2013-04-01

The Mie theory is conventionally applied to calculate aerosol optical properties in satellite remote sensing applications, while dust aerosols cannot be well modeled by the Mie calculation for their non-sphericity. It has been cited in Mishchenko et al. (1995; 1997) that neglecting non-sphericity can severely influence aerosol optical depth (AOD, ?) retrieval in case of dust aerosols because of large difference of phase functions under spherical and non-spherical assumptions, whereas this uncertainty has not been thoroughly studied. This paper aims at a better understanding of uncertainties on AOD retrieval caused by aerosol non-sphericity. A dust aerosol model with known refractive index and size distribution is generated from long-term AERONET observations since 1999 over China. Then aerosol optical properties, such as the extinction, phase function, single scattering albedo (SSA) are calculated respectively in the assumption of spherical and non-spherical aerosols. Mie calculation is carried out for spherical assumption, meanwhile for non-spherical aerosol modeling, we adopt the pre-calculated scattering kernels and software package presented by Dubovik et al. (2002; 2006), which describes dust as a shape mixture of randomly oriented polydisperse spheroids. Consequently we generate two lookup tables (LUTspheric and LUTspheroid) from simulated satellite received reflectance at top of atmosphere (TOA) under varieties of observing conditions and aerosol loadings using Second Simulation of a Satellite Signal in the Solar Spectrum - Vector (6SV) code. All the simulations are made at 550 nm, and for simplicity the Lambertian surface is assumed. Using the obtained LUTs we examine the differences of TOA reflectance (Δ?TOA = ?spheric - ?spheroid) under different surface reflectance and aerosol loadings. Afterwards AOD is retrieved using LUTspheric from the simulated TOA reflectance by LUTspheroid in order to detect the retrieval errors (Δ? = ?retreived -?input) induced by straightforwardly utilizing Mie theory in dust aerosol retrieval. As expected we find that the uncertainties mainly result from the obvious difference of phase functions (Pspheric and Pspheroid). Errors may be positive or negative, depending on the specific geometry. In scattering angle (θ) regions where Psphericis greater (30°~85° & 145°~180°), we generally get positive Δ?TOA and negative Δ?, and vice versa (85°~145°). For low aerosol loading (? ~0.25) and black surface, |Δ?TOA| could be greater than 0.004 and 0.012 around θ ~120° and θ ~170°, with |Δ?| of ~0.04 and ~0.12 respectively. In most back scattering cases (θ >100°), the magnitude of Δ? is about ten times that of Δ?TOA, while this ratio (|Δ?|/|Δ?TOA|) significantly reduces to as low as ~0.5 for forward scattering, and can reach ~20 at θ ~145°. Moreover, this errors and |Δ?|/|Δ?TOA| can increase more than ten times as aerosol loading gets higher and surface gets brighter. Therefore we conclude that the neglect of non-sphericity introduces substantial errors on radiative transfer simulation and AOD retrieval. As a result of this study, a representative aspheric aerosol model other than Mie calculation is recommended for inversion algorithms related with dust-like non-spherical aerosols. References Dubovik, O., Holben, B. N., Lapyonok, T., Sinyuk, A., Mishchenko, M. I., Yang, P., and Slutsker, I. (2002). Non-spherical aerosol retrieval method employing light scattering by spheroids. Geophyscal Research Letters, 29(10), 1415, doi:10.1029/2001GL014506. Dubovik, O., Sinyuk, A., Lapyonok, T., Holben, B. N., Mishchenko, M., Yang, P., Eck, T. F., Volten, H., Muñoz, O., Veihelmann, B., van der Zande, W. J., Leon, J.-F., Sorokin, M., and Slutsker, I. (2006). Application of spheroid models to account for aerosol particle nonsphericity in remote sensing of desert dust. Journal of Geophysical Research, 111, D11208, doi:10.1029/2005JD006619. Mishchenko, M. I., Lacis, A. A., Carlson, B. E., and Travis, L. D. (1995). Nonsphericity of dust-like aerosols: Implications for aerosol remote sensing and climate modeling, Geophyscal Research Letters, 22, 1077- 1080. Mishchenko, M. I., Travis, L. D., Kahn, R. A., and West, R. A. (1997). Modeling phase functions for dustlike tropospheric aerosols using a shape mixture of randomly oriented polydisperse spheroids, Journal of Geophysical Research, 102, 16831- 16847.

Error Analysis and Selection of Optimal Excitation Parameters for the Sensing of CO2 and O2 from Space for ASCENDS Applications

NASA Technical Reports Server (NTRS)

Pliutau, Denis; Prasad, Narasimha S.

2012-01-01

Simulation studies to optimize sensing of CO2 and O2 from space are described. Uncertainties in line-by-line calculations unaccounted for in previous studies identified. Multivariate methods are employed for measurement wavelengths selection. The Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) recommended by NRC Decadal Survey has a stringent accuracy requirements of 0.5% or better in XCO2 retrievals. NASA LaRC and its partners are investigating the use of the 1.57 m band of CO2 and the 1.26-1.27 m band of oxygen for XCO2 measurements. As part of these efforts, we are carrying out simulation studies using a lidar modeling framework being developed at NASA LaRC to predict the performance of our proposed ASCENDS mission implementation [1]. Our study is aimed at predicting the sources and magnitudes of errors anticipated in XCO2 retrievals for further error minimization through the selection of optimum excitation parameters and development of better retrieval methods.

Memory Retrieval in Parsing and Interpretation

ERIC Educational Resources Information Center

Schlueter, Ananda Lila Zoe

2017-01-01

This dissertation explores the relationship between the parser and the grammar in error-driven retrieval by examining the mechanism underlying the illusory licensing of subject-verb agreement violations ("agreement attraction"). Previous work motivates a two-stage model of agreement attraction in which the parser predicts the verb's…

Performance Metrics for Soil Moisture Retrievals and Applications Requirements

USDA-ARS?s Scientific Manuscript database

Quadratic performance metrics such as root-mean-square error (RMSE) and time series correlation are often used to assess the accuracy of geophysical retrievals and true fields. These metrics are generally related; nevertheless each has advantages and disadvantages. In this study we explore the relat...

A SEMantic and EPisodic Memory Test (SEMEP) Developed within the Embodied Cognition Framework: Application to Normal Aging, Alzheimer's Disease and Semantic Dementia.

PubMed

Vallet, Guillaume T; Hudon, Carol; Bier, Nathalie; Macoir, Joël; Versace, Rémy; Simard, Martine

2017-01-01

Embodiment has highlighted the importance of sensory-motor components in cognition. Perception and memory are thus very tightly bound together, and episodic and semantic memories should rely on the same grounded memory traces. Reduced perception should then directly reduce the ability to encode and retrieve an episodic memory, as in normal aging. Multimodal integration deficits, as in Alzheimer's disease, should lead to more severe episodic memory impairment. The present study introduces a new memory test developed to take into account these assumptions. The SEMEP (SEMantic-Episodic) memory test proposes to assess conjointly semantic and episodic knowledge across multiple tasks: semantic matching, naming, free recall, and recognition. The performance of young adults is compared to healthy elderly adults (HE), patients with Alzheimer's disease (AD), and patients with semantic dementia (SD). The results show specific patterns of performance between the groups. HE commit memory errors only for presented but not to be remembered items. AD patients present the worst episodic memory performance associated with intrusion errors (recall or recognition of items never presented). They were the only group to not benefit from a visual isolation (addition of a yellow background), a method known to increase the distinctiveness of the memory traces. Finally, SD patients suffer from the most severe semantic impairment. To conclude, confusion errors are common across all the elderly groups, whereas AD was the only group to exhibit regular intrusion errors and SD patients to show severe semantic impairment.

Do errors matter? Errorless and errorful learning in anomic picture naming.

PubMed

McKissock, Stephen; Ward, Jamie

2007-06-01

Errorless training methods significantly improve learning in memory-impaired patients relative to errorful training procedures. However, the validity of this technique for acquiring linguistic information in aphasia has rarely been studied. This study contrasts three different treatment conditions over an 8 week period for rehabilitating picture naming in anomia: (1) errorless learning in which pictures are shown and the experimenter provides the name, (2) errorful learning with feedback in which the patient is required to generate a name but the correct name is then supplied by the experimenter, and (3) errorful learning in which no feedback is given. These conditions are compared to an untreated set of matched words. Both errorless and errorful learning with feedback conditions led to significant improvement at a 2-week and 12-14-week retest (errorful without feedback and untreated words were similar). The results suggest that it does not matter whether anomic patients are allowed to make errors in picture naming or not (unlike in memory impaired individuals). What does matter is that a correct response is given as feedback. The results also question the widely held assumption that it is beneficial for a patient to attempt to retrieve a word, given that our errorless condition involved no retrieval effort and had the greatest benefits.

Study of different operational modes of the IAP 2-port-DOAS instrument for atmospheric trace gases investigation during CINDI-2 campaign basing on residual noise analysis

NASA Astrophysics Data System (ADS)

Borovski, A.; Postylyakov, O.; Elokhov, A.; Bruchkovski, I.

2017-11-01

An instrument for measuring atmospheric trace gases by DOAS method using scattered solar radiation was developed in A.M.Obukhov IAP RAS. The instrument layout is based on the lab Shamrock 303i spectrograph supplemented by 2-port radiation input system employing optical fiber. Optical ports may be used with a telescope with fixed field of view or with a scanning MAX-DOAS unit. MAX-DOAS unit port will be used for investigation of gas contents and profiles in the low troposphere. In September 2016 the IAP instrument participated in the CINDI-2 campaign, held in the Netherlands. CINDI 2 (2nd Cabauw Intercomparison of Nitrogen Dioxide Measuring Instruments) involves about 40 instruments quasi-synchronously performing DOAS measurements of NO2 and other trace gases. During the campaign the instrument ports had telescopes A and B with similar field of view of about 0.3°. Telescope A was always directed to the zenith. Telescope B was directed at 5° elevation angle. Two gratings were installed in the spectrometer. They provide different spectral resolution (FWHM 0.4 and 0.8 nm respectively) and spectral window width ( 70 and 140 nm respectively). During CINDI-2 campaign we performed test measurements in UV and visible wavelength ranges to investigate instrument stability and retrieval errors of NO2 and HCHO contents. We perform the preliminary error analysis of retrieval of the NO2 and HCHO differential slant column densities using spectra measured in four modes of the instrument basing on residual noise analysis in this paper. It was found that rotation of grating turret does not significantly affected on quality of NO2 DSCD retrieval from spectra which measured in visible spectral region. Influence of grating turret rotation is much more significant for gas DSCD retrieval from spectra which measured in UV spectral region. Standard deviation of retrieval error points to presence of some systematic error.

Passive Microwave Precipitation Retrieval Uncertainty Characterized based on Field Campaign Data over Complex Terrain

NASA Astrophysics Data System (ADS)

Derin, Y.; Anagnostou, E. N.; Anagnostou, M.; Kalogiros, J. A.; Casella, D.; Marra, A. C.; Panegrossi, G.; Sanò, P.

2017-12-01

Difficulties in representation of high rainfall variability over mountainous areas using ground based sensors make satellite remote sensing techniques attractive for hydrologic studies over these regions. Even though satellite-based rainfall measurements are quasi global and available at high spatial resolution, these products have uncertainties that necessitate use of error characterization and correction procedures based upon more accurate in situ rainfall measurements. Such measurements can be obtained from field campaigns facilitated by research quality sensors such as locally deployed weather radar and in situ weather stations. This study uses such high quality and resolution rainfall estimates derived from dual-polarization X-band radar (XPOL) observations from three field experiments in Mid-Atlantic US East Coast (NASA IPHEX experiment), the Olympic Peninsula of Washington State (NASA OLYMPEX experiment), and the Mediterranean to characterize the error characteristics of multiple passive microwave (PMW) sensor retrievals. The study first conducts an independent error analysis of the XPOL radar reference rainfall fields against in situ rain gauges and disdrometer observations available by the field experiments. Then the study evaluates different PMW precipitation products using the XPOL datasets (GR) over the three aforementioned complex terrain study areas. We extracted matchups of PMW/GR rainfall based on a matching methodology that identifies GR volume scans coincident with PMW field-of-view sampling volumes, and scaled GR parameters to the satellite products' nominal spatial resolution. The following PMW precipitation retrieval algorithms are evaluated: the NASA Goddard PROFiling algorithm (GPROF), standard and climatology-based products (V 3, 4 and 5) from four PMW sensors (SSMIS, MHS, GMI, and AMSR2), and the precipitation products based on the algorithms Cloud Dynamics and Radiation Database (CDRD) for SSMIS and Passive microwave Neural network Precipitation Retrieval (PNPR) for AMSU/MHS, developed at ISAC-CNR within the EUMETSAT H-SAF. We will present error analysis results for the different PMW rainfall retrievals and discuss dependences on precipitation type, elevation and precipitation microphysics (derived from XPOL).

[Design and implementation of medical instrument standard information retrieval system based on APS.NET].

PubMed

Yu, Kaijun

2010-07-01

This paper Analys the design goals of Medical Instrumentation standard information retrieval system. Based on the B /S structure,we established a medical instrumentation standard retrieval system with ASP.NET C # programming language, IIS f Web server, SQL Server 2000 database, in the. NET environment. The paper also Introduces the system structure, retrieval system modules, system development environment and detailed design of the system.

Quantification of model uncertainty in aerosol optical thickness retrieval from Ozone Monitoring Instrument (OMI) measurements

NASA Astrophysics Data System (ADS)

Määttä, A.; Laine, M.; Tamminen, J.; Veefkind, J. P.

2013-09-01

We study uncertainty quantification in remote sensing of aerosols in the atmosphere with top of the atmosphere reflectance measurements from the nadir-viewing Ozone Monitoring Instrument (OMI). Focus is on the uncertainty in aerosol model selection of pre-calculated aerosol models and on the statistical modelling of the model inadequacies. The aim is to apply statistical methodologies that improve the uncertainty estimates of the aerosol optical thickness (AOT) retrieval by propagating model selection and model error related uncertainties more realistically. We utilise Bayesian model selection and model averaging methods for the model selection problem and use Gaussian processes to model the smooth systematic discrepancies from the modelled to observed reflectance. The systematic model error is learned from an ensemble of operational retrievals. The operational OMI multi-wavelength aerosol retrieval algorithm OMAERO is used for cloud free, over land pixels of the OMI instrument with the additional Bayesian model selection and model discrepancy techniques. The method is demonstrated with four examples with different aerosol properties: weakly absorbing aerosols, forest fires over Greece and Russia, and Sahara dessert dust. The presented statistical methodology is general; it is not restricted to this particular satellite retrieval application.

A drifting GPS buoy for retrieving effective riverbed bathymetry

NASA Astrophysics Data System (ADS)

Hostache, R.; Matgen, P.; Giustarini, L.; Teferle, F. N.; Tailliez, C.; Iffly, J.-F.; Corato, G.

2015-01-01

Spatially distributed riverbed bathymetry information are rarely available but mandatory for accurate hydrodynamic modeling. This study aims at evaluating the potential of the Global Navigation Satellite System (GNSS), like for instance Global Positioning System (GPS), for retrieving such data. Drifting buoys equipped with navigation systems such as GPS enable the quasi-continuous measurement of water surface elevation, from virtually any point in the world. The present study investigates the potential of assimilating GNSS-derived water surface elevation measurements into hydraulic models in order to retrieve effective riverbed bathymetry. First tests with a GPS dual-frequency receiver show that the root mean squared error (RMSE) on the elevation measurement equals 30 cm provided that a differential post processing is performed. Next, synthetic observations of a drifting buoy were generated assuming a 30 cm average error of Water Surface Elevation (WSE) measurements. By assimilating the synthetic observation into a 1D-Hydrodynamic model, we show that the riverbed bathymetry can be retrieved with an accuracy of 36 cm. Moreover, the WSEs simulated by the hydrodynamic model using the retrieved bathymetry are in good agreement with the synthetic "truth", exhibiting an RMSE of 27 cm.

Phase Retrieval for Radio Telescope and Antenna Control

NASA Technical Reports Server (NTRS)

Dean, Bruce

2011-01-01

Phase-retrieval is a general term used in optics to describe the estimation of optical imperfections or "aberrations." The purpose of this innovation is to develop the application of phase retrieval to radio telescope and antenna control in the millimeter wave band. Earlier techniques do not approximate the incoherent subtraction process as a coherent propagation. This approximation reduces the noise in the data and allows a straightforward application of conventional phase retrieval techniques for radio telescope and antenna control. The application of iterative-transform phase retrieval to radio telescope and antenna control is made by approximating the incoherent subtraction process as a coherent propagation. Thus, for systems utilizing both positive and negative polarity feeds, this approximation allows both surface and alignment errors to be assessed without the use of additional hardware or laser metrology. Knowledge of the antenna surface profile allows errors to be corrected at a given surface temperature and observing angle. In addition to imperfections of the antenna surface figure, the misalignment of multiple antennas operating in unison can reduce or degrade the signal-to-noise ratio of the received or broadcast signals. This technique also has application to the alignment of antenna array configurations.

Information content of OCO-2 oxygen A-band channels for retrieving marine liquid cloud properties

NASA Astrophysics Data System (ADS)

Richardson, Mark; Stephens, Graeme L.

2018-03-01

Information content analysis is used to select channels for a marine liquid cloud retrieval using the high-spectral-resolution oxygen A-band instrument on NASA's Orbiting Carbon Observatory-2 (OCO-2). Desired retrieval properties are cloud optical depth, cloud-top pressure and cloud pressure thickness, which is the geometric thickness expressed in hectopascals. Based on information content criteria we select a micro-window of 75 of the 853 functioning OCO-2 channels spanning 763.5-764.6 nm and perform a series of synthetic retrievals with perturbed initial conditions. We estimate posterior errors from the sample standard deviations and obtain ±0.75 in optical depth and ±12.9 hPa in both cloud-top pressure and cloud pressure thickness, although removing the 10 % of samples with the highest χ2 reduces posterior error in cloud-top pressure to ±2.9 hPa and cloud pressure thickness to ±2.5 hPa. The application of this retrieval to real OCO-2 measurements is briefly discussed, along with limitations and the greatest caution is urged regarding the assumption of a single homogeneous cloud layer, which is often, but not always, a reasonable approximation for marine boundary layer clouds.

Improved Methodology for Surface and Atmospheric Soundings, Error Estimates, and Quality Control Procedures: the AIRS Science Team Version-6 Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Blaisdell, John; Iredell, Lena

2014-01-01

The AIRS Science Team Version-6 AIRS/AMSU retrieval algorithm is now operational at the Goddard DISC. AIRS Version-6 level-2 products are generated near real-time at the Goddard DISC and all level-2 and level-3 products are available starting from September 2002. This paper describes some of the significant improvements in retrieval methodology contained in the Version-6 retrieval algorithm compared to that previously used in Version-5. In particular, the AIRS Science Team made major improvements with regard to the algorithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the cloud clearing and retrieval procedures; and 3) derive error estimates and use them for Quality Control. Significant improvements have also been made in the generation of cloud parameters. In addition to the basic AIRS/AMSU mode, Version-6 also operates in an AIRS Only (AO) mode which produces results almost as good as those of the full AIRS/AMSU mode. This paper also demonstrates the improvements of some AIRS Version-6 and Version-6 AO products compared to those obtained using Version-5.

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Aires, F.; Prigent, C.; Rossow, W. B.; Rothstein, M.; Hansen, James E. (Technical Monitor)

2000-01-01

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Revealing past memories: proactive interference and ketamine-induced memory deficits.

PubMed

Chrobak, James J; Hinman, James R; Sabolek, Helen R

2008-04-23

Memories of events that occur often are sensitive to interference from memories of similar events. Proactive interference plays an important and often unexamined role in memory testing for spatially and temporally unique events ("episodes"). Ketamine (NMDA receptor antagonist) treatment in humans and other mammals induces a constellation of cognitive deficits, including impairments in working and episodic memory. We examined the effects of the ketamine (2.5-100 mg/kg) on the acquisition, retrieval, and retention of memory in a delayed-match-to-place radial water maze task that can be used to assess proactive interference. Ketamine (2.5-25 mg/kg, i.p.) given 20 min before the sample trial, impaired encoding. The first errors made during the test trial were predominantly to arms located spatially adjacent to the goal arm, suggesting an established albeit weakened representation. Ketamine (25-100 mg/kg) given immediately after the sample trial had no effect on retention. Ketamine given before the test trial impaired retrieval. First errors under the influence of ketamine were predominantly to the goal location of the previous session. Thus, ketamine treatment promoted proactive interference. These memory deficits were not state dependent, because ketamine treatment at both encoding and retrieval only increased the number of errors during the test session. These data demonstrate the competing influence of distinct memory representations during the performance of a memory task in the rat. Furthermore, they demonstrate the subtle disruptive effects of the NMDA antagonist ketamine on both encoding and retrieval. Specifically, ketamine treatment disrupted retrieval by promoting proactive interference from previous episodic representations.

Retrieving the Polar Mixed-Phase Cloud Liquid Water Path by Combining CALIOP and IIR Measurements

NASA Astrophysics Data System (ADS)

Luo, Tao; Wang, Zhien; Li, Xuebin; Deng, Shumei; Huang, Yong; Wang, Yingjian

2018-02-01

Mixed-phase cloud (MC) is the dominant cloud type over the polar region, and there are challenging conditions for remote sensing and in situ measurements. In this study, a new methodology of retrieving the stratiform MC liquid water path (LWP) by combining Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and infrared imaging radiometer (IIR) measurements was developed and evaluated. This new methodology takes the advantage of reliable cloud-phase discrimination by combining lidar and radar measurements. An improved multiple-scattering effect correction method for lidar signals was implemented to provide reliable cloud extinction near cloud top. Then with the adiabatic cloud assumption, the MC LWP can be retrieved by a lookup-table-based method. Simulations with error-free inputs showed that the mean bias and the root mean squared error of the LWP derived from the new method are -0.23 ± 2.63 g/m2, with the mean absolute relative error of 4%. Simulations with erroneous inputs suggested that the new methodology could provide reliable retrieval of LWP to support the statistical or climatology analysis. Two-month A-train satellite retrievals over Arctic region showed that the new method can produce very similar cloud top temperature (CTT) dependence of LWP to the ground-based microwave radiometer measurements, with a bias of -0.78 g/m2 and a correlation coefficient of 0.95 between the two mean CTT-LWP relationships. The new approach can also produce reasonable pattern and value of LWP in spatial distribution over the Arctic region.

A method to account for the temperature sensitivity of TCCON total column measurements

NASA Astrophysics Data System (ADS)

Niebling, Sabrina G.; Wunch, Debra; Toon, Geoffrey C.; Wennberg, Paul O.; Feist, Dietrich G.

2014-05-01

The Total Carbon Column Observing Network (TCCON) consists of ground-based Fourier Transform Spectrometer (FTS) systems all around the world. It achieves better than 0.25% precision and accuracy for total column measurements of CO2 [Wunch et al. (2011)]. In recent years, the TCCON data processing and retrieval software (GGG) has been improved to achieve better and better results (e. g. ghost correction, improved a priori profiles, more accurate spectroscopy). However, a small error is also introduced by the insufficent knowledge of the true temperature profile in the atmosphere above the individual instruments. This knowledge is crucial to retrieve highly precise gas concentrations. In the current version of the retrieval software, we use six-hourly NCEP reanalysis data to produce one temperature profile at local noon for each measurement day. For sites in the mid latitudes which can have a large diurnal variation of the temperature in the lowermost kilometers of the atmosphere, this approach can lead to small errors in the final gas concentration of the total column. Here, we present and describe a method to account for the temperature sensitivity of the total column measurements. We exploit the fact that H2O is most abundant in the lowermost kilometers of the atmosphere where the largest diurnal temperature variations occur. We use single H2O absorption lines with different temperature sensitivities to gain information about the temperature variations over the course of the day. This information is used to apply a posteriori correction of the retrieved gas concentration of total column. In addition, we show that the a posteriori temperature correction is effective by applying it to data from Lamont, Oklahoma, USA (36,6°N and 97,5°W). We chose this site because regular radiosonde launches with a time resolution of six hours provide detailed information of the real temperature in the atmosphere and allow us to test the effectiveness of our correction. References: Wunch, D., Toon, G. C., Blavier, J.-F. L., Washenfelder, R. A., Notholt, J., Connor, B. J., Griffith, D. W. T., Sherlock, V., and Wennberg, P. O.: The Total Carbon Column Observing Network, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369, 2087-2112, 2011.

What is the evidence for retrieval problems in the elderly?

PubMed

White, N; Cunningham, W R

1982-01-01

To determine whether older adults experience particular problems with retrieval, groups of young and elderly adults were given free recall and recognition tests of supraspan lists of unrelated words. Analysis of number of words correctly recalled and recognized yielded a significant age by retention test interaction: greater age differences were observed for recall than for recognition. In a second analysis of words recalled and recognized, corrected for guessing, the interaction disappeared. It was concluded that previous interpretations that age by retention test interactions are indicative of retrieval problems of the elderly may have been confounded by methodological problems. Furthermore, it was suggested that researchers in aging and memory need to be explicit in identifying their underlying models of error processes when analyzing recognition scores: different error models may lead to different results and interpretations.

Retrieval Enhances Route Knowledge Acquisition, but Only When Movement Errors Are Prevented

ERIC Educational Resources Information Center

Kelly, Jonathan W.; Carpenter, Shana K.; Sjolund, Lori A.

2015-01-01

Studies of the "testing effect" have shown that retrieval significantly improves learning. However, most of these studies have been restricted to simple types of declarative verbal knowledge. Five experiments were designed to explore whether testing improves acquisition of route knowledge, which has a procedural component consisting of…

Cross-Language Information Retrieval: An Analysis of Errors.

ERIC Educational Resources Information Center

Ruiz, Miguel E.; Srinivasan, Padmini

1998-01-01

Investigates an automatic method for Cross Language Information Retrieval (CLIR) that utilizes the multilingual Unified Medical Language System (UMLS) Metathesaurus to translate Spanish natural-language queries into English. Results indicate that for Spanish, the UMLS Metathesaurus-based CLIR method is at least equivalent to if not better than…

Features and Feedback: Enhancing Metamnemonic Knowledge at Retrieval Reduces Source-Monitoring Errors

ERIC Educational Resources Information Center

Lane, Sean M.; Roussel, Cristine C.; Villa, Diane; Morita, Shelby K.

2007-01-01

Three experiments explored the issue of whether enhanced metamnemonic knowledge at retrieval can improve participants' ability to make difficult source discriminations in the context of the eyewitness suggestibility paradigm. The 1st experiment documented differences in phenomenal experience between veridical and false memories. Experiment 2…

ASSOCIATIVE ADJUSTMENTS TO REDUCE ERRORS IN DOCUMENT SEARCHING.

ERIC Educational Resources Information Center

BRYANT, EDWARD C.; AND OTHERS

ASSOCIATIVE ADJUSTMENTS TO A DOCUMENT FILE ARE CONSIDERED AS A MEANS FOR IMPROVING RETRIEVAL. A THEORETICAL INVESTIGATION OF THE STATISTICAL PROPERTIES OF A GENERALIZED MISMATCH MEASURE WAS CARRIED OUT AND IMPROVEMENTS IN RETRIEVAL RESULTING FROM PERFORMING ASSOCIATIVE REGRESSION ADJUSTMENTS ON DATA FILE WERE EXAMINED BOTH FROM THE THEORETICAL AND…

Utilization of all Spectral Channels of IASI for the Retrieval of the Atmospheric State

NASA Astrophysics Data System (ADS)

Del Bianco, S.; Cortesi, U.; Carli, B.

2010-12-01

The retrieval of atmospheric state parameters from broadband measurements acquired by high spectral resolution sensors, such as the Infrared Atmospheric Sounding Interferometer (IASI) onboard the Meteorological Operational (MetOp) platform, generally requires to deal with a prohibitively large number of spectral elements available from a single observation (8461 samples in the case of IASI, covering the 645-2760 cm-1 range with a resolution of 0.5 cm-1 and a spectral sampling of 0.25 cm-1). Most inversion algorithms developed for both operational and scientific analysis of IASI spectra perform a reduction of the data - typically based on channel selection, super-channel clustering or Principal Component Analysis (PCA) techniques - in order to handle the high dimensionality of the problem. Accordingly, simultaneous processing of all IASI channels received relatively low attention. Here we prove the feasibility of a retrieval approach exploiting all spectral channels of IASI, to extract information on water vapor, temperature and ozone profiles. This multi-target retrieval removes the systematic errors due to interfering parameters and makes the channel selection no longer necessary. The challenging computation is made possible by the use of a coarse spectral grid for the forward model calculation and by the abatement of the associated modeling errors through the use of a variance-covariance matrix of the residuals that takes into account all the forward model errors.

Satellite-based emission constraint for nitrogen oxides: Capability and uncertainty

NASA Astrophysics Data System (ADS)

Lin, J.; McElroy, M. B.; Boersma, F.; Nielsen, C.; Zhao, Y.; Lei, Y.; Liu, Y.; Zhang, Q.; Liu, Z.; Liu, H.; Mao, J.; Zhuang, G.; Roozendael, M.; Martin, R.; Wang, P.; Spurr, R. J.; Sneep, M.; Stammes, P.; Clemer, K.; Irie, H.

2013-12-01

Vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) retrieved from satellite remote sensing have been employed widely to constrain emissions of nitrogen oxides (NOx). A major strength of satellite-based emission constraint is analysis of emission trends and variability, while a crucial limitation is errors both in satellite NO2 data and in model simulations relating NOx emissions to NO2 columns. Through a series of studies, we have explored these aspects over China. We separate anthropogenic from natural sources of NOx by exploiting their different seasonality. We infer trends of NOx emissions in recent years and effects of a variety of socioeconomic events at different spatiotemporal scales including the general economic growth, global financial crisis, Chinese New Year, and Beijing Olympics. We further investigate the impact of growing NOx emissions on particulate matter (PM) pollution in China. As part of recent developments, we identify and correct errors in both satellite NO2 retrieval and model simulation that ultimately affect NOx emission constraint. We improve the treatments of aerosol optical effects, clouds and surface reflectance in the NO2 retrieval process, using as reference ground-based MAX-DOAS measurements to evaluate the improved retrieval results. We analyze the sensitivity of simulated NO2 to errors in the model representation of major meteorological and chemical processes with a subsequent correction of model bias. Future studies will implement these improvements to re-constrain NOx emissions.

Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium).

NASA Astrophysics Data System (ADS)

di Diodato, A.; de Leonibus, L.; Zauli, F.; Biron, D.; Melfi, D.

2009-04-01

Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium). Cap. Attilio DI DIODATO(*), T.Col. Luigi DE LEONIBUS(*), T.Col Francesco ZAULI(*), Cap. Daniele BIRON(*), Ten. Davide Melfi(*) Satellite Application Facilities (SAFs) are specialised development and processing centres of the EUMETSAT Distributed Ground Segment. SAFs process level 1b data from meteorological satellites (geostationary and polar ones) in conjunction with all other relevant sources of data and appropriate models to generate services and level 2 products. Each SAF is a consortium of EUMETSAT European partners lead by a host institute responsible for the management of the complete SAF project. The Meteorological Service of Italian Air Force is the host Institute for the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF). HSAF has the commitment to develop and to provide, operationally after 2010, products regarding precipitation, soil moisture and snow. HSAF is going to provide information on error structure of its products and validation of the products via their impacts into Hydrological models. To that purpose it has been structured a specific subgroups. Accumulated precipitation is computed by temporal integration of the instantaneous rain rate achieved by the blended LEO/MW and GEO/IR precipitation rate products generated by Rapid Update method available every 15 minutes. The algorithm provides four outputs, consisting in accumulated precipitation in 3, 6, 12 and 24 hours, delivered every 3 hours at the synoptic hours. These outputs are our precipitation background fields. Satellite estimates can cover most of the globe, however, they suffer from errors due to lack of a direct relationship between observation parameters and precipitation, the poor sampling and algorithm imperfections. For this reason the 3 hours accumulated precipitation is compared by climatic thresholds got, basically, by the project "Climate Atlas of Europe" led by Meteo France inside the project ECSN (European Climate Support Network) of EUMETNET. To reduce the bias errors introduced by satellite estimates the rain gauge data are used to make an intercalibration with the satellite estimates, using information achieved by GTS network. Precipitation increments are estimated at each observation location from the observation and the interpolated background field. A field of the increments is carried out by standard Kriging method. The final precipitation analysis is achieved by the sum of the increments and the precipitation estimation at each grid points. It is also considered that major error sources in retrieval 15 minutes instantaneous precipitation from cloud top temperature comes from high (cold) non precipitating clouds and the use of same regression coefficients both for warm clouds (stratus) and cold clouds (convective). As that error is intrinsic in the blending technique applied, we are going to improve performances making use of cloud type specified retrievals. To apply such scheme on the products, we apply a discrimination from convective and stratified clouds, then we retrieve precipitation in parallel for the two clouds classes; the two outputs are merged again into one products, solving the double retrieval pixels keeping the convection retrieval. Basic tools for that is the computation of two different lookup tables to associate precipitation at a brightness temperature for the two kinds of cloudiness. The clouds discrimination will be done by the NWC-SAF product named "cloud type" for the stratified clouds and with an application, running operationally at Italian Met Service, named NEFODINA for automatic detection of convective phenomena. Results of studies to improve the accumulated precipitation as well are presented. The studies exploit the potential to use other source of information like quantitative precipitation forecast (QPF) got by numerical weather prediction model to improve the algorithm where the density of ground observations is low, or using it as a background field to generate a precipitation analysis by an optimal interpolation technique. (*) Centro Nazionale Meteorologia e Climatologia Aeronautica - CNMCA

PID-based error signal modeling

NASA Astrophysics Data System (ADS)

Yohannes, Tesfay

1997-10-01

This paper introduces a PID based signal error modeling. The error modeling is based on the betterment process. The resulting iterative learning algorithm is introduced and a detailed proof is provided for both linear and nonlinear systems.

Developing an A Priori Database for Passive Microwave Snow Water Retrievals Over Ocean

NASA Astrophysics Data System (ADS)

Yin, Mengtao; Liu, Guosheng

2017-12-01

A physically optimized a priori database is developed for Global Precipitation Measurement Microwave Imager (GMI) snow water retrievals over ocean. The initial snow water content profiles are derived from CloudSat Cloud Profiling Radar (CPR) measurements. A radiative transfer model in which the single-scattering properties of nonspherical snowflakes are based on the discrete dipole approximate results is employed to simulate brightness temperatures and their gradients. Snow water content profiles are then optimized through a one-dimensional variational (1D-Var) method. The standard deviations of the difference between observed and simulated brightness temperatures are in a similar magnitude to the observation errors defined for observation error covariance matrix after the 1D-Var optimization, indicating that this variational method is successful. This optimized database is applied in a Bayesian retrieval snow water algorithm. The retrieval results indicated that the 1D-Var approach has a positive impact on the GMI retrieved snow water content profiles by improving the physical consistency between snow water content profiles and observed brightness temperatures. Global distribution of snow water contents retrieved from the a priori database is compared with CloudSat CPR estimates. Results showed that the two estimates have a similar pattern of global distribution, and the difference of their global means is small. In addition, we investigate the impact of using physical parameters to subset the database on snow water retrievals. It is shown that using total precipitable water to subset the database with 1D-Var optimization is beneficial for snow water retrievals.

Validation of High-Resolution MAIAC Aerosol Product over South America

NASA Technical Reports Server (NTRS)

Martins, V. S.; Lyapustin, A.; de Carvalho, L. A. S.; Barbosa, C. C. F.; Novo, E. M. L. M.

2017-01-01

Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD(sub 550) was performed using ground-truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground-based measurements, with a correlation coefficient (R) close to unity (R(sub Terra):0.956 and R(sub Aqua):0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 (approximately 66%) of retrievals are within the expected error (EE = +/-(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset approximately 0.006). Additionally, MAIAC CWV presents quantitative information with R approximatley 0.97 and more than 70% of retrievals within error (+/-15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.

Algorithms and sensitivity analyses for Stratospheric Aerosol and Gas Experiment II water vapor retrieval

NASA Technical Reports Server (NTRS)

Chu, W. P.; Chiou, E. W.; Larsen, J. C.; Thomason, L. W.; Rind, D.; Buglia, J. J.; Oltmans, S.; Mccormick, M. P.; Mcmaster, L. M.

1993-01-01

The operational inversion algorithm used for the retrieval of the water-vapor vertical profiles from the Stratospheric Aerosol and Gas Experiment II (SAGE II) occultation data is presented. Unlike the algorithm used for the retrieval of aerosol, O3, and NO2, the water-vapor retrieval algorithm accounts for the nonlinear relationship between the concentration versus the broad-band absorption characteristics of water vapor. Problems related to the accuracy of the computational scheme, the accuracy of the removal of other interfering species, and the expected uncertainty of the retrieved profile are examined. Results are presented on the error analysis of the SAGE II water vapor retrieval, indicating that the SAGE II instrument produced good quality water vapor data.

Combining approaches to on-line handwriting information retrieval

NASA Astrophysics Data System (ADS)

Peña Saldarriaga, Sebastián; Viard-Gaudin, Christian; Morin, Emmanuel

2010-01-01

In this work, we propose to combine two quite different approaches for retrieving handwritten documents. Our hypothesis is that different retrieval algorithms should retrieve different sets of documents for the same query. Therefore, significant improvements in retrieval performances can be expected. The first approach is based on information retrieval techniques carried out on the noisy texts obtained through handwriting recognition, while the second approach is recognition-free using a word spotting algorithm. Results shows that for texts having a word error rate (WER) lower than 23%, the performances obtained with the combined system are close to the performances obtained on clean digital texts. In addition, for poorly recognized texts (WER > 52%), an improvement of nearly 17% can be observed with respect to the best available baseline method.

Retrievals of aerosol optical and microphysical properties from Imaging Polar Nephelometer scattering measurements

NASA Astrophysics Data System (ADS)

Reed Espinosa, W.; Remer, Lorraine A.; Dubovik, Oleg; Ziemba, Luke; Beyersdorf, Andreas; Orozco, Daniel; Schuster, Gregory; Lapyonok, Tatyana; Fuertes, David; Vanderlei Martins, J.

2017-03-01

A method for the retrieval of aerosol optical and microphysical properties from in situ light-scattering measurements is presented and the results are compared with existing measurement techniques. The Generalized Retrieval of Aerosol and Surface Properties (GRASP) is applied to airborne and laboratory measurements made by a novel polar nephelometer. This instrument, the Polarized Imaging Nephelometer (PI-Neph), is capable of making high-accuracy field measurements of phase function and degree of linear polarization, at three visible wavelengths, over a wide angular range of 3 to 177°. The resulting retrieval produces particle size distributions (PSDs) that agree, within experimental error, with measurements made by commercial optical particle counters (OPCs). Additionally, the retrieved real part of the refractive index is generally found to be within the predicted error of 0.02 from the expected values for three species of humidified salt particles, with a refractive index that is well established. The airborne measurements used in this work were made aboard the NASA DC-8 aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field campaign, and the inversion of this data represents the first aerosol retrievals of airborne polar nephelometer data. The results provide confidence in the real refractive index product, as well as in the retrieval's ability to accurately determine PSD, without assumptions about refractive index that are required by the majority of OPCs.

Flexible Retrieval: When True Inferences Produce False Memories

PubMed Central

Carpenter, Alexis C.; Schacter, Daniel L.

2016-01-01

Episodic memory involves flexible retrieval processes that allow us to link together distinct episodes, make novel inferences across overlapping events, and recombine elements of past experiences when imagining future events. However, the same flexible retrieval and recombination processes that underpin these adaptive functions may also leave memory prone to error or distortion, such as source misattributions in which details of one event are mistakenly attributed to another related event. To determine whether the same recombination-related retrieval mechanism supports both successful inference and source memory errors, we developed a modified version of an associative inference paradigm in which participants encoded everyday scenes comprised of people, objects, and other contextual details. These scenes contained overlapping elements (AB, BC) that could later be linked to support novel inferential retrieval regarding elements that had not appeared together previously (AC). Our critical experimental manipulation concerned whether contextual details were probed before or after the associative inference test, thereby allowing us to assess whether a) false memories increased for successful versus unsuccessful inferences, and b) any such effects were specific to after as compared to before participants received the inference test. In each of four experiments that used variants of this paradigm, participants were more susceptible to false memories for contextual details after successful than unsuccessful inferential retrieval, but only when contextual details were probed after the associative inference test. These results suggest that the retrieval-mediated recombination mechanism that underlies associative inference also contributes to source misattributions that result from combining elements of distinct episodes. PMID:27918169

Evaluation of snow cover and snow depth on the Qinghai-Tibetan Plateau derived from passive microwave remote sensing

NASA Astrophysics Data System (ADS)

Dai, Liyun; Che, Tao; Ding, Yongjian; Hao, Xiaohua

2017-08-01

Snow cover on the Qinghai-Tibetan Plateau (QTP) plays a significant role in the global climate system and is an important water resource for rivers in the high-elevation region of Asia. At present, passive microwave (PMW) remote sensing data are the only efficient way to monitor temporal and spatial variations in snow depth at large scale. However, existing snow depth products show the largest uncertainties across the QTP. In this study, MODIS fractional snow cover product, point, line and intense sampling data are synthesized to evaluate the accuracy of snow cover and snow depth derived from PMW remote sensing data and to analyze the possible causes of uncertainties. The results show that the accuracy of snow cover extents varies spatially and depends on the fraction of snow cover. Based on the assumption that grids with MODIS snow cover fraction > 10 % are regarded as snow cover, the overall accuracy in snow cover is 66.7 %, overestimation error is 56.1 %, underestimation error is 21.1 %, commission error is 27.6 % and omission error is 47.4 %. The commission and overestimation errors of snow cover primarily occur in the northwest and southeast areas with low ground temperature. Omission error primarily occurs in cold desert areas with shallow snow, and underestimation error mainly occurs in glacier and lake areas. With the increase of snow cover fraction, the overestimation error decreases and the omission error increases. A comparison between snow depths measured in field experiments, measured at meteorological stations and estimated across the QTP shows that agreement between observation and retrieval improves with an increasing number of observation points in a PMW grid. The misclassification and errors between observed and retrieved snow depth are associated with the relatively coarse resolution of PMW remote sensing, ground temperature, snow characteristics and topography. To accurately understand the variation in snow depth across the QTP, new algorithms should be developed to retrieve snow depth with higher spatial resolution and should consider the variation in brightness temperatures at different frequencies emitted from ground with changing ground features.

Evaluation of assumptions in soil moisture triple collocation analysis

USDA-ARS?s Scientific Manuscript database

Triple collocation analysis (TCA) enables estimation of error variances for three or more products that retrieve or estimate the same geophysical variable using mutually-independent methods. Several statistical assumptions regarding the statistical nature of errors (e.g., mutual independence and ort...

Cirrus cloud retrieval with MSG/SEVIRI using artificial neural networks

NASA Astrophysics Data System (ADS)

Strandgren, Johan; Bugliaro, Luca; Sehnke, Frank; Schröder, Leon

2017-09-01

Cirrus clouds play an important role in climate as they tend to warm the Earth-atmosphere system. Nevertheless their physical properties remain one of the largest sources of uncertainty in atmospheric research. To better understand the physical processes of cirrus clouds and their climate impact, enhanced satellite observations are necessary. In this paper we present a new algorithm, CiPS (Cirrus Properties from SEVIRI), that detects cirrus clouds and retrieves the corresponding cloud top height, ice optical thickness and ice water path using the SEVIRI imager aboard the geostationary Meteosat Second Generation satellites. CiPS utilises a set of artificial neural networks trained with SEVIRI thermal observations, CALIOP backscatter products, the ECMWF surface temperature and auxiliary data. CiPS detects 71 and 95 % of all cirrus clouds with an optical thickness of 0.1 and 1.0, respectively, that are retrieved by CALIOP. Among the cirrus-free pixels, CiPS classifies 96 % correctly. With respect to CALIOP, the cloud top height retrieved by CiPS has a mean absolute percentage error of 10 % or less for cirrus clouds with a top height greater than 8 km. For the ice optical thickness, CiPS has a mean absolute percentage error of 50 % or less for cirrus clouds with an optical thickness between 0.35 and 1.8 and of 100 % or less for cirrus clouds with an optical thickness down to 0.07 with respect to the optical thickness retrieved by CALIOP. The ice water path retrieved by CiPS shows a similar performance, with mean absolute percentage errors of 100 % or less for cirrus clouds with an ice water path down to 1.7 g m-2. Since the training reference data from CALIOP only include ice water path and optical thickness for comparably thin clouds, CiPS also retrieves an opacity flag, which tells us whether a retrieved cirrus is likely to be too thick for CiPS to accurately derive the ice water path and optical thickness. By retrieving CALIOP-like cirrus properties with the large spatial coverage and high temporal resolution of SEVIRI during both day and night, CiPS is a powerful tool for analysing the temporal evolution of cirrus clouds including their optical and physical properties. To demonstrate this, the life cycle of a thin cirrus cloud is analysed.

Ultra-fast quantitative imaging using ptychographic iterative engine based digital micro-mirror device

NASA Astrophysics Data System (ADS)

Sun, Aihui; Tian, Xiaolin; Kong, Yan; Jiang, Zhilong; Liu, Fei; Xue, Liang; Wang, Shouyu; Liu, Cheng

2018-01-01

As a lensfree imaging technique, ptychographic iterative engine (PIE) method can provide both quantitative sample amplitude and phase distributions avoiding aberration. However, it requires field of view (FoV) scanning often relying on mechanical translation, which not only slows down measuring speed, but also introduces mechanical errors decreasing both resolution and accuracy in retrieved information. In order to achieve high-accurate quantitative imaging with fast speed, digital micromirror device (DMD) is adopted in PIE for large FoV scanning controlled by on/off state coding by DMD. Measurements were implemented using biological samples as well as USAF resolution target, proving high resolution in quantitative imaging using the proposed system. Considering its fast and accurate imaging capability, it is believed the DMD based PIE technique provides a potential solution for medical observation and measurements.

Adult age differences in unconscious transference: source confusion or identity blending?

PubMed

Perfect, Timothy J; Harris, Lucy J

2003-06-01

Eyewitnesses are known often to falsely identify a familiar but innocent bystander when asked to pick out a perpetrator from a lineup. Such unconscious transference errors have been attributed to either identity confusions at encoding or source retrieval errors. Three experiments contrasted younger and older adults in their susceptibility to such misidentifications. Participants saw photographs of perpetrators, then a series of mug shots of innocent bystanders. A week later, they saw lineups containing bystanders (and others containing perpetrators in Experiment 3) and were asked whether any of the perpetrators were present. When younger faces were used as stimuli (Experiments 1 and 3), older adults showed higher rates of transference errors. When older faces were used as stimuli (Experiments 2 and 3), no such age effects in rates of unconscious transference were apparent. In addition, older adults in Experiment 3 showed an own-age bias effect for correct identification of targets. Unconscious transference errors were found to be due to both source retrieval errors and identity confusions, but age-related increases were found only in the latter.

A radiative transfer model for sea surface temperature retrieval for the along-track scanning radiometer

NASA Astrophysics Data System (ADS)

ZáVody, A. M.; Mutlow, C. T.; Llewellyn-Jones, D. T.

1995-01-01

The measurements made by the along-track scanning radiometer are now converted routinely into sea surface temperature (SST). The details of the atmospheric model which had been used for deriving the SST algorithms are given, together with tables of the coefficients in the algorithms for the different SST products. The accuracy of the retrieval under normal conditions and the effect of errors in the model on the retrieved SST are briefly discussed.

Sampling Analysis of Aerosol Retrievals by Single-track Spaceborne Instrument for Climate Research

NASA Astrophysics Data System (ADS)

Geogdzhayev, I. V.; Cairns, B.; Alexandrov, M. D.; Mishchenko, M. I.

2012-12-01

We examine to what extent the reduced sampling of along-track instruments such as Cloud-Aerosol LIdar with Orthogonal Polarisation (CALIOP) and Aerosol Polarimetry Sensor (APS) affects the statistical accuracy of a satellite climatology of retrieved aerosol optical thickness (AOT) by sub-sampling the retrievals from a wide-swath imaging instrument (MODerate resolution Imaging Spectroradiometer (MODIS)). Owing to its global coverage, longevity, and extensive characterization versus ground based data, the MODIS level-2 aerosol product is an instructive testbed for assessing sampling effects on climatic means derived from along-track instrument data. The advantage of using daily pixel-level aerosol retrievals from MODIS is that limitations caused by the presence of clouds are implicit in the sample, so that their seasonal and regional variations are captured coherently. However, imager data can exhibit cross-track variability of monthly global mean AOTs caused by a scattering-angle dependence. We found that single along-track values can deviate from the imager mean by 15% over land and by more than 20% over ocean. This makes it difficult to separate natural variability from viewing-geometry artifacts complicating direct comparisons of an along-track sub-sample with the full imager data. To work around this problem, we introduce "flipped-track" sampling which, by design, is statistically equivalent to along-track sampling and while closely approximating the imager in terms of angular artifacts. We show that the flipped-track variability of global monthly mean AOT is much smaller than the cross-track one for the 7-year period considered. Over the ocean flipped-track standard error is 85% less than the cross-track one (absolute values 0.0012 versus 0.0079), and over land it is about one third of the cross-track value (0.0054 versus 0.0188) on average. This allows us to attribute the difference between the two errors to the viewing-geometry artifacts and obtain an upper limit on AOT errors caused by along-track sampling. Our results show that using along-track subsets of MODIS aerosol data directly to analyze the sampling adequacy of single-track instruments can lead to false conclusions owing to the apparent enhancement of natural aerosol variability by the track-to-track artifacts. The analysis based on the statistics of the flipped-track means yields better estimates because it allows for better separation of the viewing-geometry artifacts and true natural variability. Published assessments estimate that a global AOT change of 0.01 would yield a climatically important flux change of 0.25 W/m2. Since the standard error estimates that we have obtained are comfortably below 0.01, we conclude that along-track instruments flown on a sun-synchronous orbiting platform have sufficient spatial sampling for estimating aerosol effects on climate. Since AOT is believed to be the most variable characteristic of tropospheric aerosols, our results imply that pixel-wide along-track coverage also provides adequate statistical representation of the global distribution of aerosol microphysical parameters.

Regression techniques for oceanographic parameter retrieval using space-borne microwave radiometry

NASA Technical Reports Server (NTRS)

Hofer, R.; Njoku, E. G.

1981-01-01

Variations of conventional multiple regression techniques are applied to the problem of remote sensing of oceanographic parameters from space. The techniques are specifically adapted to the scanning multichannel microwave radiometer (SMRR) launched on the Seasat and Nimbus 7 satellites to determine ocean surface temperature, wind speed, and atmospheric water content. The retrievals are studied primarily from a theoretical viewpoint, to illustrate the retrieval error structure, the relative importances of different radiometer channels, and the tradeoffs between spatial resolution and retrieval accuracy. Comparisons between regressions using simulated and actual SMMR data are discussed; they show similar behavior.

High Spectral Resolution Lidar and MPLNET Micro Pulse Lidar Aerosol Optical Property Retrieval Intercomparison During the 2012 7-SEAS Field Campaign at Singapore

NASA Technical Reports Server (NTRS)

Lolli, Simone; Welton, Ellsworth J.; Campbell, James R.; Eloranta, Edwin; Holben, Brent N.; Chew, Boon Ning; Salinas, Santo V.

2014-01-01

From August 2012 to February 2013 a High Resolution Spectral Lidar (HSRL; 532 nm) was deployed at that National University of Singapore near a NASA Micro Pulse Lidar NETwork (MPLNET; 527 nm) site. A primary objective of the MPLNET lidar project is the production and dissemination of reliable Level 1 measurements and Level 2 retrieval products. This paper characterizes and quantifies error in Level 2 aerosol optical property retrievals conducted through inversion techniques that derive backscattering and extinction coefficients from MPLNET elastic single-wavelength datasets. MPLNET Level 2 retrievals for aerosol optical depth and extinction/backscatter coefficient profiles are compared with corresponding HSRL datasets, for which the instrument collects direct measurements of each using a unique optical configuration that segregates aerosol and cloud backscattered signal from molecular signal. The intercomparison is performed, and error matrices reported, for lower (0-5km) and the upper (>5km) troposphere, respectively, to distinguish uncertainties observed within and above the MPLNET instrument optical overlap regime.

A climate index indicative of cloudiness derived from satellite infrared sounder data

NASA Technical Reports Server (NTRS)

Abel, M. D.; Cox, S. K.

1981-01-01

In many current studies conducted to enhance the usefulness of meteorological satellite radiance data, one common objective is to infer conventional weather variables. The present investigation, on the other hand, is mainly concerned with the efficient retrieval (minimization of errors) of a nonstandard atmospheric descriptor. The atmosphere's Vertical Infrared Radiative Emitting Structure (VIRES) is retrieved. VIRES is described by the broadband infrared weighting function curve. The shapes of these weighting curves are primarily a function of the three-dimensional cloud structure. The weighting curves are retrieved by a method which uses satellite spectral radiance data. The basic theory involved in the VIRES retrieval procedure parallels the technique used to retrieve temperature soundings.

Sea ice motion from low-resolution satellite sensors: An alternative method and its validation in the Arctic

NASA Astrophysics Data System (ADS)

Lavergne, T.; Eastwood, S.; Teffah, Z.; Schyberg, H.; Breivik, L.-A.

2010-10-01

The retrieval of sea ice motion with the Maximum Cross-Correlation (MCC) method from low-resolution (10-15 km) spaceborne imaging sensors is challenged by a dominating quantization noise as the time span of displacement vectors is shortened. To allow investigating shorter displacements from these instruments, we introduce an alternative sea ice motion tracking algorithm that builds on the MCC method but relies on a continuous optimization step for computing the motion vector. The prime effect of this method is to effectively dampen the quantization noise, an artifact of the MCC. It allows for retrieving spatially smooth 48 h sea ice motion vector fields in the Arctic. Strategies to detect and correct erroneous vectors as well as to optimally merge several polarization channels of a given instrument are also described. A test processing chain is implemented and run with several active and passive microwave imagers (Advanced Microwave Scanning Radiometer-EOS (AMSR-E), Special Sensor Microwave Imager, and Advanced Scatterometer) during three Arctic autumn, winter, and spring seasons. Ice motion vectors are collocated to and compared with GPS positions of in situ drifters. Error statistics are shown to be ranging from 2.5 to 4.5 km (standard deviation for components of the vectors) depending on the sensor, without significant bias. We discuss the relative contribution of measurement and representativeness errors by analyzing monthly validation statistics. The 37 GHz channels of the AMSR-E instrument allow for the best validation statistics. The operational low-resolution sea ice drift product of the EUMETSAT OSI SAF (European Organisation for the Exploitation of Meteorological Satellites Ocean and Sea Ice Satellite Application Facility) is based on the algorithms presented in this paper.

Processing TES Level-2 Data

NASA Technical Reports Server (NTRS)

Poosti, Sassaneh; Akopyan, Sirvard; Sakurai, Regina; Yun, Hyejung; Saha, Pranjit; Strickland, Irina; Croft, Kevin; Smith, Weldon; Hoffman, Rodney; Koffend, John;

A multisensor approach to sea ice classification for the validation of DMSP-SSM/I passive microwave derived sea ice products

NASA Technical Reports Server (NTRS)

Steffen, K.; Schweiger, A. J.

1990-01-01

The validation of sea ice products derived from the Special Sensor Microwave Imager (SSM/I) on board a DMSP platform is examined using data from the Landsat MSS and NOAA-AVHRR sensors. Image processing techniques for retrieving ice concentrations from each type of imagery are developed and results are intercompared to determine the ice parameter retrieval accuracy of the SSM/I NASA-Team algorithm. For case studies in the Beaufort Sea and East Greenland Sea, average retrieval errors of the SSM/I algorithm are between 1.7 percent for spring conditions and 4.3 percent during freeze up in comparison with Landsat derived ice concentrations. For a case study in the East Greenland Sea, SSM/I derived ice concentration in comparison with AVHRR imagery display a mean error of 9.6 percent.

Visual Typo Correction by Collocative Optimization: A Case Study on Merchandize Images.

PubMed

Wei, Xiao-Yong; Yang, Zhen-Qun; Ngo, Chong-Wah; Zhang, Wei

2014-02-01

Near-duplicate retrieval (NDR) in merchandize images is of great importance to a lot of online applications on e-Commerce websites. In those applications where the requirement of response time is critical, however, the conventional techniques developed for a general purpose NDR are limited, because expensive post-processing like spatial verification or hashing is usually employed to compromise the quantization errors among the visual words used for the images. In this paper, we argue that most of the errors are introduced because of the quantization process where the visual words are considered individually, which has ignored the contextual relations among words. We propose a "spelling or phrase correction" like process for NDR, which extends the concept of collocations to visual domain for modeling the contextual relations. Binary quadratic programming is used to enforce the contextual consistency of words selected for an image, so that the errors (typos) are eliminated and the quality of the quantization process is improved. The experimental results show that the proposed method can improve the efficiency of NDR by reducing vocabulary size by 1000% times, and under the scenario of merchandize image NDR, the expensive local interest point feature used in conventional approaches can be replaced by color-moment feature, which reduces the time cost by 9202% while maintaining comparable performance to the state-of-the-art methods.

Comparison between two lidar methods to retrieve microphysical properties of liquid-water clouds

NASA Astrophysics Data System (ADS)

Jimenez, Cristofer; Ansmann, Albert; Donovan, David; Engelmann, Ronny; Schmidt, Jörg; Wandinger, Ulla

2018-04-01

Since 2010, the Raman dual-FOV lidar system permits the retrieval of microphysical properties of liquid-water clouds during nighttime. A new robust lidar depolarization approach was recently introduced, which permits the retrieval of these properties as well, with high temporal resolution and during daytime. To implement this approach, the lidar system was upgraded, by adding a three channel depolarization receiver. The first preliminary retrieval results and a comparison between both methods is presented.

Development and application of a probability distribution retrieval scheme to the remote sensing of clouds and precipitation

NASA Astrophysics Data System (ADS)

McKague, Darren Shawn

2001-12-01

The statistical properties of clouds and precipitation on a global scale are important to our understanding of climate. Inversion methods exist to retrieve the needed cloud and precipitation properties from satellite data pixel-by-pixel that can then be summarized over large data sets to obtain the desired statistics. These methods can be quite computationally expensive, and typically don't provide errors on the statistics. A new method is developed to directly retrieve probability distributions of parameters from the distribution of measured radiances. The method also provides estimates of the errors on the retrieved distributions. The method can retrieve joint distributions of parameters that allows for the study of the connection between parameters. A forward radiative transfer model creates a mapping from retrieval parameter space to radiance space. A Monte Carlo procedure uses the mapping to transform probability density from the observed radiance histogram to a two- dimensional retrieval property probability distribution function (PDF). An estimate of the uncertainty in the retrieved PDF is calculated from random realizations of the radiance to retrieval parameter PDF transformation given the uncertainty of the observed radiances, the radiance PDF, the forward radiative transfer, the finite number of prior state vectors, and the non-unique mapping to retrieval parameter space. The retrieval method is also applied to the remote sensing of precipitation from SSM/I microwave data. A method of stochastically generating hydrometeor fields based on the fields from a numerical cloud model is used to create the precipitation parameter radiance space transformation. The impact of vertical and horizontal variability within the hydrometeor fields has a significant impact on algorithm performance. Beamfilling factors are computed from the simulated hydrometeor fields. The beamfilling factors vary quite a bit depending upon the horizontal structure of the rain. The algorithm is applied to SSM/I images from the eastern tropical Pacific and is compared to PDFs of rain rate computed using pixel-by-pixel retrievals from Wilheit and from Liu and Curry. Differences exist between the three methods, but good general agreement is seen between the PDF retrieval algorithm and the algorithm of Liu and Curry. (Abstract shortened by UMI.)

Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

NASA Astrophysics Data System (ADS)

Poulsen, C. A.; Siddans, R.; Thomas, G. E.; Sayer, A. M.; Grainger, R. G.; Campmany, E.; Dean, S. M.; Arnold, C.; Watts, P. D.

2012-08-01

Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud) which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase. The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick, greater than 50 optical depths, where the cloud begins to saturate. The cost proved a good indicator of multi-layer scenarios. Both the retrieval cost and the error need to be considered together in order to evaluate the quality of the retrieval. This algorithm in the configuration described here has been applied to both ATSR-2 and AATSR visible and infrared measurements in the context of the GRAPE (Global Retrieval and cloud Product Evaluation) project to produce a 14 yr consistent record for climate research.

Characterizing the Retrieval of Cloud Optical Thickness and Droplet Effective Radius to Overlying Aerosols Using a General Inverse Theory Approach

NASA Astrophysics Data System (ADS)

Coddington, O.; Pilewskie, P.; Schmidt, S.

2013-12-01

The upwelling shortwave irradiance measured by the airborne Solar Spectral Flux Radiometer (SSFR) flying above a cloud and aerosol layer is influenced by the properties of the cloud and aerosol particles below, just as would the radiance measured from satellite. Unlike satellite measurements, those from aircraft provide the unique capability to fly a lower-level leg above the cloud, yet below the aerosol layer, to characterize the extinction of the aerosol layer and account for its impact on the measured cloud albedo. Previous work [Coddington et al., 2010] capitalized on this opportunity to test the effects of aerosol particles (or more appropriately, the effects of neglecting aerosols in forward modeling calculations) on cloud retrievals using data obtained during the Intercontinental Chemical Transport Experiment/Intercontinental Transport and Chemical Transformation of anthropogenic pollution (INTEX-A/ITCT) study. This work showed aerosols can cause a systematic bias in the cloud retrieval and that such a bias would need to be distinguished from a true aerosol indirect effect (i.e. the brightening of a cloud due to aerosol effects on cloud microphysics) as theorized by Haywood et al., [2004]. The effects of aerosols on clouds are typically neglected in forward modeling calculations because their pervasiveness, variable microphysical properties, loading, and lifetimes makes forward modeling calculations under all possible combinations completely impractical. Using a general inverse theory technique, which propagates separate contributions from measurement and forward modeling errors into probability distributions of retrieved cloud optical thickness and droplet effective radius, we have demonstrated how the aerosol presence can be introduced as a spectral systematic error in the distributions of the forward modeling solutions. The resultant uncertainty and bias in cloud properties induced by the aerosols is identified by the shape and peak of the posteriori retrieval distributions. In this work, we apply this general inverse theory approach to extend our analysis of the spectrally-dependent impacts of overlying aerosols on cloud properties over a broad range in cloud optical thickness and droplet effective radius. We investigate the relative impacts of this error source and compare and contrast results to biases and uncertainties in cloud properties induced by varying surface conditions (ocean, land, snow). We perform the analysis for two different measurement accuracies (3% and 0.3%) that are typical of current passive imagers, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) [Platnick et al., 2003], and that are expected for future passive imagers, such as the HyperSpectral Imager for Climate Science (HySICS) [Kopp et al., 2010]. Coddington, O., P. Pilewskie, et al., 2010, J. Geophys. Res., 115, doi: 10.1029/2009JD012829. Haywood, J. M., S. R. Osborne, and S. J. Abel, 2004, Q. J. R. Meteorol. Soc., 130, 779-800. Kopp, G., et al., 2010, Hyperspectral Imagery Radiometry Improvements for Visible and Near-Infrared Climate Studies, paper presented at 2010 Earth Science Technology Forum, Arlington, VA, USA. Platnick, S., et al., 2003, IEEE Trans. Geosci. Remote Sens., 41(2), 459- 473.

Improved track forecasting of a typhoon reaching landfall from four-dimensional variational data assimilation of AMSU-A retrieved data

NASA Astrophysics Data System (ADS)

Zhao, Ying; Wang, Bin; Ji, Zhongzhen; Liang, Xudong; Deng, Guo; Zhang, Xin

2005-07-01

In this study, an attempt to improve typhoon forecasts is made by incorporating three-dimensional Advanced Microwave Sounding Unit-A (AMSU-A) retrieved wind and temperature and the central sea level pressure of cyclones from typhoon reports or bogus surface low data into initial conditions, on the basis of the Fifth-Generation National Center for Atmospheric Research/Pennsylvania State University Mesoscale Model (MM5) four-dimensional variational data assimilation (4DVar) system with a full-physics adjoint model. All the above-mentioned data are found to be useful for improvement of typhoon forecasts in this mesoscale data assimilation experiment. The comparison tests showed the following results: (1) The assimilation of the satellite-retrieved data was found to have a positive impact on the typhoon track forecast, but the landing position error is ˜150 km. (2) The assimilation of both the satellite-retrieved data and moving information of the typhoon center dramatically improved the track forecast and captured the recurvature and landfall. The mean track error during the 72-hour forecast is 69 km. The predicted typhoon intensity, however, is much weaker than that from observations. (3) The assimilation of both the satellite-retrieved data and the bogus surface low data improved the intensity and track forecasts more significantly than the assimilation of only bogus surface low data (bogus data assimilation) did. The mean errors during the 72-hour forecast are 2.6 hPa for the minimum sea level pressure and 87 km for track position. However, the forecasted landing time is ˜6 hours earlier than the observed one.

Integrated Active Fire Retrievals and Biomass Burning Emissions Using Complementary Near-Coincident Ground, Airborne and Spaceborne Sensor Data

NASA Technical Reports Server (NTRS)

Schroeder, Wilfrid; Ellicott, Evan; Ichoku, Charles; Ellison, Luke; Dickinson, Matthew B.; Ottmar, Roger D.; Clements, Craig; Hall, Dianne; Ambrosia, Vincent; Kremens, Robert

2013-01-01

Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

Single-lens 3D digital image correlation system based on a bilateral telecentric lens and a bi-prism: Systematic error analysis and correction

NASA Astrophysics Data System (ADS)

Wu, Lifu; Zhu, Jianguo; Xie, Huimin; Zhou, Mengmeng

2016-12-01

Recently, we proposed a single-lens 3D digital image correlation (3D DIC) method and established a measurement system on the basis of a bilateral telecentric lens (BTL) and a bi-prism. This system can retrieve the 3D morphology of a target and measure its deformation using a single BTL with relatively high accuracy. Nevertheless, the system still suffers from systematic errors caused by manufacturing deficiency of the bi-prism and distortion of the BTL. In this study, in-depth evaluations of these errors and their effects on the measurement results are performed experimentally. The bi-prism deficiency and the BTL distortion are characterized by two in-plane rotation angles and several distortion coefficients, respectively. These values are obtained from a calibration process using a chessboard placed into the field of view of the system; this process is conducted after the measurement of tested specimen. A modified mathematical model is proposed, which takes these systematic errors into account and corrects them during 3D reconstruction. Experiments on retrieving the 3D positions of the chessboard grid corners and the morphology of a ceramic plate specimen are performed. The results of the experiments reveal that ignoring the bi-prism deficiency will induce attitude error to the retrieved morphology, and the BTL distortion can lead to its pseudo out-of-plane deformation. Correcting these problems can further improve the measurement accuracy of the bi-prism-based single-lens 3D DIC system.

How Well Will MODIS Measure Top of Atmosphere Aerosol Direct Radiative Forcing?

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Kaufman, Yoram J.; Levin, Zev; Ghan, Stephen; Einaudi, Franco (Technical Monitor)

2000-01-01

The new generation of satellite sensors such as the Moderate Resolution Imaging Spectroradiometer (MODIS) will be able to detect and characterize global aerosols with an unprecedented accuracy. The question remains whether this accuracy will be sufficient to narrow the uncertainties in our estimates of aerosol radiative forcing at the top of the atmosphere. Satellite remote sensing detects aerosol optical thickness with the least amount of relative error when aerosol loading is high. Satellites are less effective when aerosol loading is low. We use the monthly mean results of two global aerosol transport models to simulate the spatial distribution of smoke aerosol in the Southern Hemisphere during the tropical biomass burning season. This spatial distribution allows us to determine that 87-94% of the smoke aerosol forcing at the top of the atmosphere occurs in grid squares with sufficient signal to noise ratio to be detectable from space. The uncertainty of quantifying the smoke aerosol forcing in the Southern Hemisphere depends on the uncertainty introduced by errors in estimating the background aerosol, errors resulting from uncertainties in surface properties and errors resulting from uncertainties in assumptions of aerosol properties. These three errors combine to give overall uncertainties of 1.5 to 2.2 Wm-2 (21-56%) in determining the Southern Hemisphere smoke aerosol forcing at the top of the atmosphere. The range of values depend on which estimate of MODIS retrieval uncertainty is used, either the theoretical calculation (upper bound) or the empirical estimate (lower bound). Strategies that use the satellite data to derive flux directly or use the data in conjunction with ground-based remote sensing and aerosol transport models can reduce these uncertainties.

Amphetamine increases errors during episodic memory retrieval.

PubMed

Ballard, Michael Edward; Gallo, David A; de Wit, Harriet

2014-02-01

Moderate doses of stimulant drugs are known to enhance memory encoding and consolidation, but their effects on memory retrieval have not been explored in depth. In laboratory animals, stimulants seem to improve retrieval of emotional memories, but comparable studies have not been carried out in humans. In the present study, we examined the effects of dextroamphetamine (AMP) on retrieval of emotional and unemotional stimuli in healthy young adults, using doses that enhanced memory formation when administered before encoding in our previous study. During 3 sessions, healthy volunteers (n = 31) received 2 doses of AMP (10 and 20 mg) and placebo in counterbalanced order under double-blind conditions. During each session, they first viewed emotional and unemotional pictures and words in a drug-free state, and then 2 days later their memory was tested, 1 hour after AMP or placebo administration. Dextroamphetamine did not affect the number of emotional or unemotional stimuli remembered, but both doses increased recall intrusions and false recognition. Dextroamphetamine (20 mg) also increased the number of positively rated picture descriptions and words generated during free recall. These data provide the first evidence that therapeutic range doses of stimulant drugs can increase memory retrieval errors. The ability of AMP to positively bias recollection of prior events could contribute to its potential for abuse.

Amphetamine Increases Errors During Episodic Memory Retrieval

PubMed Central

Ballard, Michael Edward; Gallo, David A.; de Wit, Harriet

2014-01-01

Moderate doses of stimulant drugs are known to enhance memory encoding and consolidation, but their effects on memory retrieval have not been explored in depth. In laboratory animals, stimulants seem to improve retrieval of emotional memories, but comparable studies have not been carried out in humans. In the present study, we examined the effects of dextroamphetamine (AMP) on retrieval of emotional and unemotional stimuli in healthy young adults, using doses that enhanced memory formation when administered before encoding in our previous study. During 3 sessions, healthy volunteers (n = 31) received 2 doses of AMP (10 and 20 mg) and placebo in counter-balanced order under double-blind conditions. During each session, they first viewed emotional and unemotional pictures and words in a drug-free state, and then 2 days later their memory was tested, 1 hour after AMP or placebo administration. Dextroamphetamine did not affect the number of emotional or unemotional stimuli remembered, but both doses increased recall intrusions and false recognition. Dextroamphetamine (20 mg) also increased the number of positively rated picture descriptions and words generated during free recall. These data provide the first evidence that therapeutic range doses of stimulant drugs can increase memory retrieval errors. The ability of AMP to positively bias recollection of prior events could contribute to its potential for abuse. PMID:24135845

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-07-02

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m -2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m -2.« less

Aircraft electric field measurements: Calibration and ambient field retrieval

NASA Technical Reports Server (NTRS)

Koshak, William J.; Bailey, Jeff; Christian, Hugh J.; Mach, Douglas M.

1994-01-01

An aircraft locally distorts the ambient thundercloud electric field. In order to determine the field in the absence of the aircraft, an aircraft calibration is required. In this work a matrix inversion method is introduced for calibrating an aircraft equipped with four or more electric field sensors and a high-voltage corona point that is capable of charging the aircraft. An analytic, closed form solution for the estimate of a (3 x 3) aircraft calibration matrix is derived, and an absolute calibration experiment is used to improve the relative magnitudes of the elements of this matrix. To demonstrate the calibration procedure, we analyze actual calibration date derived from a Lear jet 28/29 that was equipped with five shutter-type field mill sensors (each with sensitivities of better than 1 V/m) located on the top, bottom, port, starboard, and aft positions. As a test of the calibration method, we analyze computer-simulated calibration data (derived from known aircraft and ambient fields) and explicitly determine the errors involved in deriving the variety of calibration matrices. We extend our formalism to arrive at an analytic solution for the ambient field, and again carry all errors explicitly.

Pixel-super-resolved lensfree holography using adaptive relaxation factor and positional error correction

NASA Astrophysics Data System (ADS)

Zhang, Jialin; Chen, Qian; Sun, Jiasong; Li, Jiaji; Zuo, Chao

2018-01-01

Lensfree holography provides a new way to effectively bypass the intrinsical trade-off between the spatial resolution and field-of-view (FOV) of conventional lens-based microscopes. Unfortunately, due to the limited sensor pixel-size, unpredictable disturbance during image acquisition, and sub-optimum solution to the phase retrieval problem, typical lensfree microscopes only produce compromised imaging quality in terms of lateral resolution and signal-to-noise ratio (SNR). In this paper, we propose an adaptive pixel-super-resolved lensfree imaging (APLI) method to address the pixel aliasing problem by Z-scanning only, without resorting to subpixel shifting or beam-angle manipulation. Furthermore, an automatic positional error correction algorithm and adaptive relaxation strategy are introduced to enhance the robustness and SNR of reconstruction significantly. Based on APLI, we perform full-FOV reconstruction of a USAF resolution target across a wide imaging area of {29.85 mm2 and achieve half-pitch lateral resolution of 770 nm, surpassing 2.17 times of the theoretical Nyquist-Shannon sampling resolution limit imposed by the sensor pixel-size (1.67 μm). Full-FOV imaging result of a typical dicot root is also provided to demonstrate its promising potential applications in biologic imaging.

NASA GPM GV Science Requirements

NASA Technical Reports Server (NTRS)

Smith, E.

2003-01-01

An important scientific objective of the NASA portion of the GPM Mission is to generate quantitatively-based error characterization information along with the rainrate retrievals emanating from the GPM constellation of satellites. These data must serve four main purposes: (1) they must be of sufficient quality, uniformity, and timeliness to govern the observation weighting schemes used in the data assimilation modules of numerical weather prediction models; (2) they must extend over that portion of the globe accessible by the GPM core satellite to which the NASA GV program is focused - (approx.65 degree inclination); (3) they must have sufficient specificity to enable detection of physically-formulated microphysical and meteorological weaknesses in the standard physical level 2 rainrate algorithms to be used in the GPM Precipitation Processing System (PPS), i.e., algorithms which will have evolved from the TRMM standard physical level 2 algorithms; and (4) they must support the use of physical error modeling as a primary validation tool and as the eventual replacement of the conventional GV approach of statistically intercomparing surface rainrates fiom ground and satellite measurements. This approach to ground validation research represents a paradigm shift vis-&-vis the program developed for the TRMM mission, which conducted ground validation largely as a statistical intercomparison process between raingauge-derived or radar-derived rainrates and the TRMM satellite rainrate retrievals -- long after the original satellite retrievals were archived. This approach has been able to quantify averaged rainrate differences between the satellite algorithms and the ground instruments, but has not been able to explain causes of algorithm failures or produce error information directly compatible with the cost functions of data assimilation schemes. These schemes require periodic and near-realtime bias uncertainty (i.e., global space-time distributed conditional accuracy of the retrieved rainrates) and local error covariance structure (i.e., global space-time distributed error correlation information for the local 4-dimensional space-time domain -- or in simpler terms, the matrix form of precision error). This can only be accomplished by establishing a network of high quality-heavily instrumented supersites selectively distributed at a few oceanic, continental, and coastal sites. Economics and pragmatics dictate that the network must be made up of a relatively small number of sites (6-8) created through international cooperation. This presentation will address some of the details of the methodology behind the error characterization approach, some proposed solutions for expanding site-developed error properties to regional scales, a data processing and communications concept that would enable rapid implementation of algorithm improvement by the algorithm developers, and the likely available options for developing the supersite network.

An evaluation of satellite-derived humidity and its relationship to convective development

NASA Technical Reports Server (NTRS)

Fuelberg, Henry E.

1993-01-01

An aircraft prototype of the High-Resolution Interferometer Sounder (HIS) was flown over Tennessee and northern Alabama during summer 1986. The HIS temperature and dewpoint soundings were examined on two flight days to determine their error characteristics and utility in mesoscale analyses. Random errors were calculated from structure functions while total errors were obtained by pairing the HIS soundings with radiosonde-derived profiles. Random temperature errors were found to be less than 1 C at most levels, but random dewpoint errors ranged from 1 to 5 C. Total errors of both parameters were considerably greater, with dewpoint errors especially large on the day having a pronounced subsidence inversion. Cumulus cloud cover on 15 June limited HIS mesoscale analyses on that day. Previously undetected clouds were found in many HIS fields of view, and these probably produced the low-level horizontal temperature and dewpoint variations observed in the retrievals. HIS dewpoints at 300 mb indicated a strong moisture gradient that was confirmed by GOES 6.7-micron imagery. HIS mesoscale analyses on 19 June revealed a tongue of humid air stretching across the study area. The moist region was confirmed by radiosonde data and imagery from the Multispectral Atmospheric Mapping Sensor (MAMS). Convective temperatures derived from HIS retrievals helped explain the cloud formation that occurred after the HIS overflights. Crude estimates of Bowen ratio were obtained from HIS data using a mixing-line approach. Values indicated that areas of large sensible heat flux were the areas of first cloud development. These locations were also suggested by GOES visible and infrared imagery. The HIS retrievals indicated that areas of thunderstorm formation were regions of greatest instability. Local landscape variability and atmospheric temperature and humidity fluctuations were found to be important factors in producing the cumulus clouds on 19 June. HIS soundings were capable of detecting some of this variability. The authors were impressed by HIS's performance on the two study days.

Combining ground-based microwave radiometer and the AROME convective scale model through 1DVAR retrievals in complex terrain: an Alpine valley case study

NASA Astrophysics Data System (ADS)

Martinet, Pauline; Cimini, Domenico; De Angelis, Francesco; Canut, Guylaine; Unger, Vinciane; Guillot, Remi; Tzanos, Diane; Paci, Alexandre

2017-09-01

A RPG-HATPRO ground-based microwave radiometer (MWR) was operated in a deep Alpine valley during the Passy-2015 field campaign. This experiment aims to investigate how stable boundary layers during wintertime conditions drive the accumulation of pollutants. In order to understand the atmospheric processes in the valley, MWRs continuously provide vertical profiles of temperature and humidity at a high time frequency, providing valuable information to follow the evolution of the boundary layer. A one-dimensional variational (1DVAR) retrieval technique has been implemented during the field campaign to optimally combine an MWR and 1 h forecasts from the French convective scale model AROME. Retrievals were compared to radiosonde data launched at least every 3 h during two intensive observation periods (IOPs). An analysis of the AROME forecast errors during the IOPs has shown a large underestimation of the surface cooling during the strongest stable episode. MWR brightness temperatures were monitored against simulations from the radiative transfer model ARTS2 (Atmospheric Radiative Transfer Simulator) and radiosonde launched during the field campaign. Large errors were observed for most transparent channels (i.e., 51-52 GHz) affected by absorption model and calibration uncertainties while a good agreement was found for opaque channels (i.e., 54-58 GHz). Based on this monitoring, a bias correction of raw brightness temperature measurements was applied before the 1DVAR retrievals. 1DVAR retrievals were found to significantly improve the AROME forecasts up to 3 km but mainly below 1 km and to outperform usual statistical regressions above 1 km. With the present implementation, a root-mean-square error (RMSE) of 1 K through all the atmospheric profile was obtained with values within 0.5 K below 500 m in clear-sky conditions. The use of lower elevation angles (up to 5°) in the MWR scanning and the bias correction were found to improve the retrievals below 1000 m. MWR retrievals were found to catch deep near-surface temperature inversions very well. Larger errors were observed in cloudy conditions due to the difficulty of ground-based MWRs to resolve high level inversions that are still challenging. Finally, 1DVAR retrievals were optimized for the analysis of the IOPs by using radiosondes as backgrounds in the 1DVAR algorithm instead of the AROME forecasts. A significant improvement of the retrievals in cloudy conditions and below 1000 m in clear-sky conditions was observed. From this study, we can conclude that MWRs are expected to bring valuable information into numerical weather prediction models up to 3 km in altitude both in clear-sky and cloudy-sky conditions with the maximum improvement found around 500 m. With an accuracy between 0.5 and 1 K in RMSE, our study has also proven that MWRs are capable of resolving deep near-surface temperature inversions observed in complex terrain during highly stable boundary layer conditions.

Data Assimilation Experiments using Quality Controlled AIRS Version 5 Temperature Soundings

NASA Technical Reports Server (NTRS)

SUsskind, Joel

2008-01-01

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 pm C02 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 pm C02 observations are now used primarily in the generation of cloud cleared radiances Ri. This approach allows for the generation of accurate values of Ri and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by- channel error estimates for Ri. These error estimates are used for quality control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of quality control using the NASA GEOS-5 data assimilation system. Assimilation of quality controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done Operationally by ECMWF and NCEP. Forecasts resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

Flexible retrieval: When true inferences produce false memories.

PubMed

Carpenter, Alexis C; Schacter, Daniel L

2017-03-01

Episodic memory involves flexible retrieval processes that allow us to link together distinct episodes, make novel inferences across overlapping events, and recombine elements of past experiences when imagining future events. However, the same flexible retrieval and recombination processes that underpin these adaptive functions may also leave memory prone to error or distortion, such as source misattributions in which details of one event are mistakenly attributed to another related event. To determine whether the same recombination-related retrieval mechanism supports both successful inference and source memory errors, we developed a modified version of an associative inference paradigm in which participants encoded everyday scenes comprised of people, objects, and other contextual details. These scenes contained overlapping elements (AB, BC) that could later be linked to support novel inferential retrieval regarding elements that had not appeared together previously (AC). Our critical experimental manipulation concerned whether contextual details were probed before or after the associative inference test, thereby allowing us to assess whether (a) false memories increased for successful versus unsuccessful inferences, and (b) any such effects were specific to after compared with before participants received the inference test. In each of 4 experiments that used variants of this paradigm, participants were more susceptible to false memories for contextual details after successful than unsuccessful inferential retrieval, but only when contextual details were probed after the associative inference test. These results suggest that the retrieval-mediated recombination mechanism that underlies associative inference also contributes to source misattributions that result from combining elements of distinct episodes. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Atmospheric Compensation and Surface Temperature and Emissivity Retrieval with LWIR Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Pieper, Michael

Accurate estimation or retrieval of surface emissivity spectra from long-wave infrared (LWIR) or Thermal Infrared (TIR) hyperspectral imaging data acquired by airborne or space-borne sensors is necessary for many scientific and defense applications. The at-aperture radiance measured by the sensor is a function of the ground emissivity and temperature, modified by the atmosphere. Thus the emissivity retrieval process consists of two interwoven steps: atmospheric compensation (AC) to retrieve the ground radiance from the measured at-aperture radiance and temperature-emissivity separation (TES) to separate the temperature and emissivity from the ground radiance. In-scene AC (ISAC) algorithms use blackbody-like materials in the scene, which have a linear relationship between their ground radiances and at-aperture radiances determined by the atmospheric transmission and upwelling radiance. Using a clear reference channel to estimate the ground radiance, a linear fitting of the at-aperture radiance and estimated ground radiance is done to estimate the atmospheric parameters. TES algorithms for hyperspectral imaging data assume that the emissivity spectra for solids are smooth compared to the sharp features added by the atmosphere. The ground temperature and emissivity are found by finding the temperature that provides the smoothest emissivity estimate. In this thesis we develop models to investigate the sensitivity of AC and TES to the basic assumptions enabling their performance. ISAC assumes that there are perfect blackbody pixels in a scene and that there is a clear channel, which is never the case. The developed ISAC model explains how the quality of blackbody-like pixels affect the shape of atmospheric estimates and the clear channel assumption affects their magnitude. Emissivity spectra for solids usually have some roughness. The TES model identifies four sources of error: the smoothing error of the emissivity spectrum, the emissivity error from using the incorrect temperature, and the errors caused by sensor noise and wavelength calibration. The ways these errors interact determines the overall TES performance. Since the AC and TES processes are interwoven, any errors in AC are transferred to TES and the final temperature and emissivity estimates. Combining the two models, shape errors caused by the blackbody assumption are transferred to the emissivity estimates, where magnitude errors from the clear channel assumption are compensated by TES temperature induced emissivity errors. The ability for the temperature induced error to compensate for such atmospheric errors makes it difficult to determine the correct atmospheric parameters for a scene. With these models we are able to determine the expected quality of estimated emissivity spectra based on the quality of blackbody-like materials on the ground, the emissivity of the materials being searched for, and the properties of the sensor. The quality of material emissivity spectra is a key factor in determining detection performance for a material in a scene.

The Design of an Interactive Data Retrieval System for Casual Users.

ERIC Educational Resources Information Center

Radhakrishnan, T.; And Others

1982-01-01

Describes an interactive data retrieval system which was designed and implemented for casual users and which incorporates a user-friendly interface, aids to train beginners in use of the system, versatility in output, and error recovery protocols. A 14-item reference list and two figures illustrating system operation and output are included. (JL)

What Friends Are For: Collaborative Intelligence Analysis and Search

DTIC Science & Technology

2014-06-01

14. SUBJECT TERMS Intelligence Community, information retrieval, recommender systems , search engines, social networks, user profiling, Lucene...improvements over existing search systems . The improvements are shown to be robust to high levels of human error and low similarity between users ...precision NOLH nearly orthogonal Latin hypercubes P@ precision at documents RS recommender systems TREC Text REtrieval Conference USM user

Do age-related word retrieval difficulties appear (or disappear) in connected speech?

PubMed

Kavé, Gitit; Goral, Mira

2017-09-01

We conducted a comprehensive literature review of studies of word retrieval in connected speech in healthy aging and reviewed relevant aphasia research that could shed light on the aging literature. Four main hypotheses guided the review: (1) Significant retrieval difficulties would lead to reduced output in connected speech. (2) Significant retrieval difficulties would lead to a more limited lexical variety in connected speech. (3) Significant retrieval difficulties would lead to an increase in word substitution errors and in pronoun use as well as to greater dysfluency and hesitation in connected speech. (4) Retrieval difficulties on tests of single-word production would be associated with measures of word retrieval in connected speech. Studies on aging did not confirm these four hypotheses, unlike studies on aphasia that generally did. The review suggests that future research should investigate how context facilitates word production in old age.

A Method for Retrieving Ground Flash Fraction from Satellite Lightning Imager Data

NASA Technical Reports Server (NTRS)

Koshak, William J.

2009-01-01

A general theory for retrieving the fraction of ground flashes in N lightning observed by a satellite-based lightning imager is provided. An "exponential model" is applied as a physically reasonable constraint to describe the measured optical parameter distributions, and population statistics (i.e., mean, variance) are invoked to add additional constraints to the retrieval process. The retrieval itself is expressed in terms of a Bayesian inference, and the Maximum A Posteriori (MAP) solution is obtained. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The ability to retrieve ground flash fraction has important benefits to the atmospheric chemistry community. For example, using the method to partition the existing satellite global lightning climatology into separate ground and cloud flash climatologies will improve estimates of lightning nitrogen oxides (NOx) production; this in turn will improve both regional air quality and global chemistry/climate model predictions.

Error sources in passive and active microwave satellite soil moisture over Australia

USDA-ARS?s Scientific Manuscript database

Development of a long-term climate record of soil moisture (SM) involves combining historic and present satellite-retrieved SM data sets. This in turn requires a consistent characterization and deep understanding of the systematic differences and errors in the individual data sets, which vary due to...

Actual daily evapotranspiration estimated from MERIS and AATSR data over the Chinese Loess Plateau

NASA Astrophysics Data System (ADS)

Liu, R.; Wen, J.; Wang, X.; Wang, L.; Tian, H.; Zhang, T. T.; Shi, X. K.; Zhang, J. H.; Lu, Sh. N.

2009-02-01

The Loess Plateau is located in north of China and has a significant impact on the climate and ecosystem evolvement over the East Asian continent. Based on the land surface energy balance theory, the potential of using Medium Resolution Imaging Spectrometer (onboard sensor of the Environmental Satellite) remote sensing data on 7, 11 and 27 June 2005 is explored. The "split-window" algorithm is used to retrieve surface temperature from the Advanced the Along-Track Scanning Radiometer, another onboard senor of the Environmental Satellite. Then the near surface net radiation, sensible heat flux and soil heat flux are estimated by using the developed algorithm. We introduce a simple algorithm to predict the heat flux partitioning between the soil and vegetation. Combining the sunshine hours, air temperature, sunshine duration and wind speed measured by weather stations, a model for estimating daily ET is proposed. The instantaneous ET is also converted to daily value. Comparison of latent heats flux retrieved by remote sensing data with ground observation from eddy covariance flux system during Loess Plateau land surface process field Experiment, the maximum and minimum error of this approach are 10.96% and 4.80% respectively, the cause of the bias is also explored and discussed.

Improving Retrieval Performance by Relevance Feedback.

ERIC Educational Resources Information Center

Salton, Gerard; Buckley, Chris

1990-01-01

Briefly describes the principal relevance feedback methods that have been introduced over the years and evaluates the effectiveness of the methods in producing improved query formulations. Prescriptions are given for conducting text retrieval operations iteratively using relevance feedback. (24 references) (Author/CLB)

Content-based video retrieval by example video clip

NASA Astrophysics Data System (ADS)

Dimitrova, Nevenka; Abdel-Mottaleb, Mohamed

1997-01-01

This paper presents a novel approach for video retrieval from a large archive of MPEG or Motion JPEG compressed video clips. We introduce a retrieval algorithm that takes a video clip as a query and searches the database for clips with similar contents. Video clips are characterized by a sequence of representative frame signatures, which are constructed from DC coefficients and motion information (`DC+M' signatures). The similarity between two video clips is determined by using their respective signatures. This method facilitates retrieval of clips for the purpose of video editing, broadcast news retrieval, or copyright violation detection.

Multi-Angle Implementation of Atmospheric Correction for MODIS (MAIAC). Part 3: Atmospheric Correction

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Hilker, T.; Hall, F.; Sellers, P.; Tucker, J.; Korkin, S.

2012-01-01

This paper describes the atmospheric correction (AC) component of the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) which introduces a new way to compute parameters of the Ross-Thick Li-Sparse (RTLS) Bi-directional reflectance distribution function (BRDF), spectral surface albedo and bidirectional reflectance factors (BRF) from satellite measurements obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS). MAIAC uses a time series and spatial analysis for cloud detection, aerosol retrievals and atmospheric correction. It implements a moving window of up to 16 days of MODIS data gridded to 1 km resolution in a selected projection. The RTLS parameters are computed directly by fitting the cloud-free MODIS top of atmosphere (TOA) reflectance data stored in the processing queue. The RTLS retrieval is applied when the land surface is stable or changes slowly. In case of rapid or large magnitude change (as for instance caused by disturbance), MAIAC follows the MODIS operational BRDF/albedo algorithm and uses a scaling approach where the BRDF shape is assumed stable but its magnitude is adjusted based on the latest single measurement. To assess the stability of the surface, MAIAC features a change detection algorithm which analyzes relative change of reflectance in the Red and NIR bands during the accumulation period. To adjust for the reflectance variability with the sun-observer geometry and allow comparison among different days (view geometries), the BRFs are normalized to the fixed view geometry using the RTLS model. An empirical analysis of MODIS data suggests that the RTLS inversion remains robust when the relative change of geometry-normalized reflectance stays below 15%. This first of two papers introduces the algorithm, a second, companion paper illustrates its potential by analyzing MODIS data over a tropical rainforest and assessing errors and uncertainties of MAIAC compared to conventional MODIS products.

Method for transferring data from an unsecured computer to a secured computer

DOEpatents

Nilsen, Curt A.

1997-01-01

A method is described for transferring data from an unsecured computer to a secured computer. The method includes transmitting the data and then receiving the data. Next, the data is retransmitted and rereceived. Then, it is determined if errors were introduced when the data was transmitted by the unsecured computer or received by the secured computer. Similarly, it is determined if errors were introduced when the data was retransmitted by the unsecured computer or rereceived by the secured computer. A warning signal is emitted from a warning device coupled to the secured computer if (i) an error was introduced when the data was transmitted or received, and (ii) an error was introduced when the data was retransmitted or rereceived.

Phase and Pupil Amplitude Recovery for JWST Space-Optics Control

NASA Technical Reports Server (NTRS)

Dean, B. H.; Zielinski, T. P.; Smith, J. S.; Bolcar, M. R.; Aronstein, D. L.; Fienup, J. R.

2010-01-01

This slide presentation reviews the phase and pupil amplitude recovery for the James Webb Space Telescope (JWST) Near Infrared Camera (NIRCam). It includes views of the Integrated Science Instrument Module (ISIM), the NIRCam, examples of Phase Retrieval Data, Ghost Irradiance, Pupil Amplitude Estimation, Amplitude Retrieval, Initial Plate Scale Estimation using the Modulation Transfer Function (MTF), Pupil Amplitude Estimation vs lambda, Pupil Amplitude Estimation vs. number of Images, Pupil Amplitude Estimation vs Rotation (clocking), and Typical Phase Retrieval Results Also included is information about the phase retrieval approach, Non-Linear Optimization (NLO) Optimized Diversity Functions, and Least Square Error vs. Starting Pupil Amplitude.

Simulating Children's Retrieval Errors in Picture-Naming: A Test of Foygel and Dell's (2000) Semantic/Phonological Model of Speech Production

ERIC Educational Resources Information Center

Budd, Mary-Jane; Hanley, J. Richard; Griffiths, Yvonne

2011-01-01

This study investigated whether Foygel and Dell's (2000) interactive two-step model of speech production could simulate the number and type of errors made in picture-naming by 68 children of elementary-school age. Results showed that the model provided a satisfactory simulation of the mean error profile of children aged five, six, seven, eight and…

Visuoconstructional Impairment in Subtypes of Mild Cognitive Impairment

PubMed Central

Ahmed, Samrah; Brennan, Laura; Eppig, Joel; Price, Catherine C.; Lamar, Melissa; Delano-Wood, Lisa; Bangen, Katherine J.; Edmonds, Emily C.; Clark, Lindsey; Nation, Daniel A.; Jak, Amy; Au, Rhoda; Swenson, Rodney; Bondi, Mark W.; Libon, David J.

2018-01-01

Clock Drawing Test performance was examined alongside other neuropsychological tests in mild cognitive impairment (MCI). We tested the hypothesis that clock-drawing errors are related to executive impairment. The current research examined 86 patients with MCI for whom, in prior research, cluster analysis was used to sort patients into dysexecutive (dMCI, n=22), amnestic (aMCI, n=13), and multi-domain (mMCI, n=51) subtypes. First, principal components analysis (PCA) and linear regression examined relations between clock-drawing errors and neuropsychological test performance independent of MCI subtype. Second, between-group differences were assessed with analysis of variance (ANOVA) where MCI subgroups were compared to normal controls (NC). PCA yielded a 3-group solution. Contrary to expectations, clock-drawing errors loaded with lower performance on naming/lexical retrieval, rather than with executive tests. Regression analyses found increasing clock-drawing errors to command were associated with worse performance only on naming/lexical retrieval tests. ANOVAs revealed no differences in clock-drawing errors between dMCI versus mMCI or aMCI versus NCs. Both the dMCI and mMCI groups generated more clock-drawing errors than the aMCI and NC groups in the command condition. In MCI, language-related skills contribute to clock-drawing impairment. PMID:26397732

Minimization of model representativity errors in identification of point source emission from atmospheric concentration measurements

NASA Astrophysics Data System (ADS)

Sharan, Maithili; Singh, Amit Kumar; Singh, Sarvesh Kumar

2017-11-01

Estimation of an unknown atmospheric release from a finite set of concentration measurements is considered an ill-posed inverse problem. Besides ill-posedness, the estimation process is influenced by the instrumental errors in the measured concentrations and model representativity errors. The study highlights the effect of minimizing model representativity errors on the source estimation. This is described in an adjoint modelling framework and followed in three steps. First, an estimation of point source parameters (location and intensity) is carried out using an inversion technique. Second, a linear regression relationship is established between the measured concentrations and corresponding predicted using the retrieved source parameters. Third, this relationship is utilized to modify the adjoint functions. Further, source estimation is carried out using these modified adjoint functions to analyse the effect of such modifications. The process is tested for two well known inversion techniques, called renormalization and least-square. The proposed methodology and inversion techniques are evaluated for a real scenario by using concentrations measurements from the Idaho diffusion experiment in low wind stable conditions. With both the inversion techniques, a significant improvement is observed in the retrieval of source estimation after minimizing the representativity errors.

Expert system for automatically correcting OCR output

NASA Astrophysics Data System (ADS)

Taghva, Kazem; Borsack, Julie; Condit, Allen

1994-03-01

This paper describes a new expert system for automatically correcting errors made by optical character recognition (OCR) devices. The system, which we call the post-processing system, is designed to improve the quality of text produced by an OCR device in preparation for subsequent retrieval from an information system. The system is composed of numerous parts: an information retrieval system, an English dictionary, a domain-specific dictionary, and a collection of algorithms and heuristics designed to correct as many OCR errors as possible. For the remaining errors that cannot be corrected, the system passes them on to a user-level editing program. This post-processing system can be viewed as part of a larger system that would streamline the steps of taking a document from its hard copy form to its usable electronic form, or it can be considered a stand alone system for OCR error correction. An earlier version of this system has been used to process approximately 10,000 pages of OCR generated text. Among the OCR errors discovered by this version, about 87% were corrected. We implement numerous new parts of the system, test this new version, and present the results.

Adaptive target binarization method based on a dual-camera system

NASA Astrophysics Data System (ADS)

Lei, Jing; Zhang, Ping; Xu, Jiangtao; Gao, Zhiyuan; Gao, Jing

2018-01-01

An adaptive target binarization method based on a dual-camera system that contains two dynamic vision sensors was proposed. First, a preprocessing procedure of denoising is introduced to remove the noise events generated by the sensors. Then, the complete edge of the target is retrieved and represented by events based on an event mosaicking method. Third, the region of the target is confirmed by an event-to-event method. Finally, a postprocessing procedure of image open and close operations of morphology methods is adopted to remove the artifacts caused by event-to-event mismatching. The proposed binarization method has been extensively tested on numerous degraded images with nonuniform illumination, low contrast, noise, or light spots and successfully compared with other well-known binarization methods. The experimental results, which are based on visual and misclassification error criteria, show that the proposed method performs well and has better robustness on the binarization of degraded images.

Blurry-frame detection and shot segmentation in colonoscopy videos

NASA Astrophysics Data System (ADS)

Oh, JungHwan; Hwang, Sae; Tavanapong, Wallapak; de Groen, Piet C.; Wong, Johnny

2003-12-01

Colonoscopy is an important screening procedure for colorectal cancer. During this procedure, the endoscopist visually inspects the colon. Human inspection, however, is not without error. We hypothesize that colonoscopy videos may contain additional valuable information missed by the endoscopist. Video segmentation is the first necessary step for the content-based video analysis and retrieval to provide efficient access to the important images and video segments from a large colonoscopy video database. Based on the unique characteristics of colonoscopy videos, we introduce a new scheme to detect and remove blurry frames, and segment the videos into shots based on the contents. Our experimental results show that the average precision and recall of the proposed scheme are over 90% for the detection of non-blurry images. The proposed method of blurry frame detection and shot segmentation is extensible to the videos captured from other endoscopic procedures such as upper gastrointestinal endoscopy, enteroscopy, cystoscopy, and laparoscopy.

Optimal estimation retrieval of aerosol microphysical properties from SAGE~II satellite observations in the volcanically unperturbed lower stratosphere

NASA Astrophysics Data System (ADS)

Wurl, D.; Grainger, R. G.; McDonald, A. J.; Deshler, T.

2010-05-01

Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003). An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE) method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths) with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities), even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal) size distributions naturally differ from the correct bimodal values, the associated surface area (A) and volume densities (V) are, nevertheless, fairly accurately retrieved, except at values larger than 1.0 μm2 cm-3 (A) and 0.05 μm3 cm-3 (V), where they tend to underestimate the true bimodal values. Due to the limited information content in the SAGE II spectral extinction measurements this kind of forward model error cannot be avoided here. Nevertheless, the retrieved uncertainties are a good estimate of the true errors in the retrieved integrated properties, except where the surface area density exceeds the 1.0 μm2 cm-3 threshold. When applied to near-global SAGE II satellite extinction measured in 1999 the retrieved OE surface area and volume densities are observed to be larger by, respectively, 20-50% and 10-40% compared to those estimates obtained by the SAGE~II operational retrieval algorithm. An examination of the OE algorithm biases with in situ data indicates that the new OE aerosol property estimates tend to be more realistic than previous estimates obtained from remotely sensed data through other retrieval techniques. Based on the results of this study we therefore suggest that the new Optimal Estimation retrieval algorithm is able to contribute to an advancement in aerosol research by considerably improving current estimates of aerosol properties in the lower stratosphere under low aerosol loading conditions.

An architecture for diversity-aware search for medical web content.

PubMed

Denecke, K

2012-01-01

The Web provides a huge source of information, also on medical and health-related issues. In particular the content of medical social media data can be diverse due to the background of an author, the source or the topic. Diversity in this context means that a document covers different aspects of a topic or a topic is described in different ways. In this paper, we introduce an approach that allows to consider the diverse aspects of a search query when providing retrieval results to a user. We introduce a system architecture for a diversity-aware search engine that allows retrieving medical information from the web. The diversity of retrieval results is assessed by calculating diversity measures that rely upon semantic information derived from a mapping to concepts of a medical terminology. Considering these measures, the result set is diversified by ranking more diverse texts higher. The methods and system architecture are implemented in a retrieval engine for medical web content. The diversity measures reflect the diversity of aspects considered in a text and its type of information content. They are used for result presentation, filtering and ranking. In a user evaluation we assess the user satisfaction with an ordering of retrieval results that considers the diversity measures. It is shown through the evaluation that diversity-aware retrieval considering diversity measures in ranking could increase the user satisfaction with retrieval results.

Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications

NASA Astrophysics Data System (ADS)

Minnis, P.; Bedka, K. M.; Smith, W., Jr.; Yost, C. R.; Bedka, S. T.; Palikonda, R.; Spangenberg, D.; Sun-Mack, S.; Trepte, Q.; Dong, X.; Xi, B.

2014-12-01

Cloud properties determined from satellite imager radiances are increasingly used in weather and climate applications, particularly in nowcasting, model assimilation and validation, trend monitoring, and precipitation and radiation analyses. The value of using the satellite-derived cloud parameters is determined by the accuracy of the particular parameter for a given set of conditions, such as viewing and illumination angles, surface background, and cloud type and structure. Because of the great variety of those conditions and of the sensors used to monitor clouds, determining the accuracy or uncertainties in the retrieved cloud parameters is a daunting task. Sensitivity studies of the retrieved parameters to the various inputs for a particular cloud type are helpful for understanding the errors associated with the retrieval algorithm relative to the plane-parallel world assumed in most of the model clouds that serve as the basis for the retrievals. Real world clouds, however, rarely fit the plane-parallel mold and generate radiances that likely produce much greater errors in the retrieved parameter than can be inferred from sensitivity analyses. Thus, independent, empirical methods are used to provide a more reliable uncertainty analysis. At NASA Langley, cloud properties are being retrieved from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for climate monitoring and model validation as part of the NASA CERES project since 2000 and from AVHRR data since 1978 as part of the NOAA CDR program. Cloud properties are also being retrieved in near-real time globally from both GEO and LEO satellites for weather model assimilation and nowcasting for hazards such as aircraft icing. This paper discusses the various independent datasets and approaches that are used to assessing the imager-based satellite cloud retrievals. These include, but are not limited to data from ARM sites, CloudSat, and CALIPSO. This paper discusses the use of the various datasets available, the methods employed to utilize them in the cloud property retrieval validation process, and the results and how they aid future development of the retrieval algorithms. Future needs are also discussed.

Exploring the Retrieval Dynamics of Delayed and Final Free Recall: Further Evidence for Temporal-Contextual Search

ERIC Educational Resources Information Center

Unsworth, Nash

2008-01-01

Retrieval dynamics in free recall were explored based on a two-stage search model that relies on temporal-contextual cues. Participants were tested on both delayed and final free recall and correct recalls, errors, and latency measures were examined. In delayed free recall, participants began recall with the first word presented and tended to…

Neural network cloud top pressure and height for MODIS

NASA Astrophysics Data System (ADS)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found to give the most useful information of the spread of the errors. For all descriptive statistics presented MAE, IQR, RMSE (root mean square error), SD, mode, median, bias and percentage of absolute errors above 0.25, 0.5, 1 and 2 km the neural network perform better than the reference algorithms both validated with CALIOP and CPR (CloudSat). The neural networks using the brightness temperatures at 11 and 12 µm show at least 32 % (or 623 m) lower MAE compared to the two operational reference algorithms when validating with CALIOP height. Validation with CPR (CloudSat) height gives at least 25 % (or 430 m) reduction of MAE.

Retrieval of Boundary Layer 3D Cloud Properties Using Scanning Cloud Radar and 3D Radiative Transfer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marchand, Roger

Retrievals of cloud optical and microphysical properties for boundary layer clouds, including those widely used by ASR investigators, frequently assume that clouds are sufficiently horizontally homogeneous that scattering and absorption (at all wavelengths) can be treated using one dimensional (1D) radiative transfer, and that differences in the field-of-view of different sensors are unimportant. Unfortunately, most boundary layer clouds are far from horizontally homogeneous, and numerous theoretical and observational studies show that the assumption of horizontal homogeneity leads to significant errors. The introduction of scanning cloud and precipitation radars at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) programmore » sites presents opportunities to move beyond the horizontally homogeneous assumption. The primary objective of this project was to develop a 3D retrieval for warm-phase (liquid only) boundary layer cloud microphysical properties, and to assess errors in current 1D (non-scanning) approaches. Specific research activities also involved examination of the diurnal cycle of hydrometeors as viewed by ARM cloud radar, and continued assessment of precipitation impacts on retrievals of cloud liquid water path using passive microwaves.« less

A Quality Control study of the distribution of NOAA MIRS Cloudy retrievals during Hurricane Sandy

NASA Astrophysics Data System (ADS)

Fletcher, S. J.

2013-12-01

Cloudy radiance present a difficult challenge to data assimilation (DA) systems, through both the radiative transfer system as well the hydrometers required to resolve the cloud and precipitation. In most DA systems the hydrometers are not control variables due to many limitations. The National Oceanic and Atmospheric Administration's (NOAA) Microwave Integrated Retrieval System (MIRS) is producing products from the NPP-ATMS satellite where the scene is cloud and precipitation affected. The test case that we present here is the life time of Hurricane and then Superstorm Sandy in October 2012. As a quality control study we shall compare the retrieved water vapor content during the lifetime of Sandy with the first guess and the analysis from the NOAA Gridpoint Statistical Interpolation (GSI) system. The assessment involves the gross error check system against the first guess with different values for the observational error's variance to see if the difference is within three standard deviations. We shall also compare against the final analysis at the relevant cycles to see if the products which have been retrieved through a cloudy radiance are similar, given that the DA system does not assimilate cloudy radiances yet.

Ozone Climatological Profiles for Version 8 TOMS and SBUV Retrievals

NASA Technical Reports Server (NTRS)

McPeters, R. D.; Logan, J. A.; Labow, G. J.

2003-01-01

A new altitude dependent ozone climatology has been produced for use with the latest Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet (SBUV) retrieval algorithms. The climatology consists of monthly average profiles for ten degree latitude zones covering from 0 to 60 km. The climatology was formed by combining data from SAGE II (1988 to 2000) and MLS (1991-1999) with data from balloon sondes (1988-2002). Ozone below about 20 km is based on balloons sondes, while ozone above 30 km is based on satellite measurements. The profiles join smoothly between 20 and 30 km. The ozone climatology in the southern hemisphere and tropics has been greatly enhanced in recent years by the addition of balloon sonde stations under the SHADOZ (Southern Hemisphere Additional Ozonesondes) program. A major source of error in the TOMS and SBUV retrieval of total column ozone comes from their reduced sensitivity to ozone in the lower troposphere. An accurate climatology for the retrieval a priori is important for reducing this error on the average. The new climatology follows the seasonal behavior of tropospheric ozone and reflects its hemispheric asymmetry. Comparisons of TOMS version 8 ozone with ground stations show an improvement due in part to the new climatology.

A multi-spectral approach to simultaneously retrieve above-cloud smoke optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds using MODIS

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2013-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into the standard MODIS cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 μm (effective particle size retrievals are derived from the short and mid-wave IR channels at 1.6, 2.1, and 3.7 μm). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple MODIS spectral channels in the visible and near- and shortwave-infrared. Preliminary retrieval results are shown, as are comparisons with other A-Train sensors.

An imager-based multispectral retrieval of above-cloud absorbing aerosol optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2014-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into imager-based cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced for cloud optical thickness retrievals, which are typically derived from the visible or near-IR wavelength channels (effective particle size retrievals are derived from short and mid-wave IR channels that are less affected by aerosol absorption). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple spectral channels in the visible and near- and shortwave-IR. The technique has been applied to MODIS, and retrieval results and statistics, as well as comparisons with other A-Train sensors, are shown.

MOPITT V7 Level 1 & Level 2 Release Announcement

Atmospheric Science Data Center

2016-08-02

...  - MOPITT Level 1 Radiances   Several significant retrieval algorithm and product format changes are introduced in the V7 ... in the V7 User's Guide available on the MOPITT Data and Information landing pages. Featured improvements in the V7 retrieval products ...

Introducing Chemistry Undergraduate Students to Online Chemical Information Retrieval.

ERIC Educational Resources Information Center

Wolman, Yecheskel

1985-01-01

The results of manual and online searching are compared during a unit on online chemical information retrieval taught at Hebrew University. Strategies and results obtained are provided for student searches on the synthesis of vitamin K(3) from 2-methylnaphthalene and polywater. (JN)

A Generalized Process Model of Human Action Selection and Error and its Application to Error Prediction

DTIC Science & Technology

2014-07-01

Macmillan & Creelman , 2005). This is a quite high degree of discriminability and it means that when the decision model predicts a probability of...ROC analysis. Pattern Recognition Letters, 27(8), 861-874. Retrieved from Google Scholar. Macmillan, N. A., & Creelman , C. D. (2005). Detection

Effects of OCR Errors on Ranking and Feedback Using the Vector Space Model.

ERIC Educational Resources Information Center

Taghva, Kazem; And Others

1996-01-01

Reports on the performance of the vector space model in the presence of OCR (optical character recognition) errors in information retrieval. Highlights include precision and recall, a full-text test collection, smart vector representation, impact of weighting parameters, ranking variability, and the effect of relevance feedback. (Author/LRW)

Error Characterisation and Merging of Active and Passive Microwave Soil Moisture Data Sets

NASA Astrophysics Data System (ADS)

Wagner, Wolfgang; Gruber, Alexander; de Jeu, Richard; Parinussa, Robert; Chung, Daniel; Dorigo, Wouter; Reimer, Christoph; Kidd, Richard

2015-04-01

As part of the Climate Change Initiative (CCI) programme of the European Space Agency (ESA) a data fusion system has been developed which is capable of ingesting surface soil moisture data derived from active and passive microwave sensors (ASCAT, AMSR-E, etc.) flown on different satellite platforms and merging them to create long and consistent time series of soil moisture suitable for use in climate change studies. The so-created soil moisture data records (latest version: ESA CCI SM v02.1 released on 5/12/2014) are freely available and can be obtained from http://www.esa-soilmoisture-cci.org/. As described by Wagner et al. (2012) the principle steps of the data fusion process are: 1) error characterisation, 2) matching to account for data set specific biases, and 3) merging. In this presentation we present the current data fusion process and discuss how new error characterisation methods, such as the increasingly popular triple collocation method as discussed for example by Zwieback et al. (2012) may be used to improve it. The main benefit of an improved error characterisation would be a more reliable identification of the best performing microwave soil moisture retrieval(s) for each grid point and each point in time. In case that two or more satellite data sets provides useful information, the estimated errors can be used to define the weights with which each satellite data set are merged, i.e. the lower its error the higher its weight. This is expected to bring a significant improvement over the current data fusion scheme which is not yet based on quantitative estimates of the retrieval errors but on a proxy measure, namely the vegetation optical depth (Dorigo et al., 2015): over areas with low vegetation passive soil moisture retrievals are used, while over areas with moderate vegetation density active retrievals are used. In transition areas, where both products correlate well, both products are being used in a synergistic way: on time steps where only one of the products is available, the estimate of the respective product is used, while on days where both active and passive sensors provide an estimate, their observations are averaged. REFERENCES Dorigo, W.A., A. Gruber, R. de Jeu, W. Wagner, T. Stacke, A. Löw, C. Albergel, L. Brocca, D. Chung, R. Parinussa, R. Kidd (2015) Evaluation of the ESA CCI soil moisture product using ground-based observations, Remote Sensing of Environment, in press. Wagner, W., W. Dorigo, R. de Jeu, D. Fernandez, J. Benveniste, E. Haas, M. Ertl (2012) Fusion of active and passive microwave observations to create an Essential Climate Variable data record on soil moisture, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Annals), Volume I-7, XXII ISPRS Congress, Melbourne, Australia, 25 August-1 September 2012, 315-321. Zwieback, S., K. Scipal, W. Dorigo, W. Wagner (2012) Structural and statistical properties of the collocation technique for error characterization, Nonlinear Processes in Geophysics, 19, 69-80.

Garbage in, Garbage Out: Data Collection, Quality Assessment and Reporting Standards for Social Media Data Use in Health Research, Infodemiology and Digital Disease Detection.

PubMed

Kim, Yoonsang; Huang, Jidong; Emery, Sherry

2016-02-26

Social media have transformed the communications landscape. People increasingly obtain news and health information online and via social media. Social media platforms also serve as novel sources of rich observational data for health research (including infodemiology, infoveillance, and digital disease detection detection). While the number of studies using social data is growing rapidly, very few of these studies transparently outline their methods for collecting, filtering, and reporting those data. Keywords and search filters applied to social data form the lens through which researchers may observe what and how people communicate about a given topic. Without a properly focused lens, research conclusions may be biased or misleading. Standards of reporting data sources and quality are needed so that data scientists and consumers of social media research can evaluate and compare methods and findings across studies. We aimed to develop and apply a framework of social media data collection and quality assessment and to propose a reporting standard, which researchers and reviewers may use to evaluate and compare the quality of social data across studies. We propose a conceptual framework consisting of three major steps in collecting social media data: develop, apply, and validate search filters. This framework is based on two criteria: retrieval precision (how much of retrieved data is relevant) and retrieval recall (how much of the relevant data is retrieved). We then discuss two conditions that estimation of retrieval precision and recall rely on--accurate human coding and full data collection--and how to calculate these statistics in cases that deviate from the two ideal conditions. We then apply the framework on a real-world example using approximately 4 million tobacco-related tweets collected from the Twitter firehose. We developed and applied a search filter to retrieve e-cigarette-related tweets from the archive based on three keyword categories: devices, brands, and behavior. The search filter retrieved 82,205 e-cigarette-related tweets from the archive and was validated. Retrieval precision was calculated above 95% in all cases. Retrieval recall was 86% assuming ideal conditions (no human coding errors and full data collection), 75% when unretrieved messages could not be archived, 86% assuming no false negative errors by coders, and 93% allowing both false negative and false positive errors by human coders. This paper sets forth a conceptual framework for the filtering and quality evaluation of social data that addresses several common challenges and moves toward establishing a standard of reporting social data. Researchers should clearly delineate data sources, how data were accessed and collected, and the search filter building process and how retrieval precision and recall were calculated. The proposed framework can be adapted to other public social media platforms.

Document image database indexing with pictorial dictionary

NASA Astrophysics Data System (ADS)

Akbari, Mohammad; Azimi, Reza

2010-02-01

In this paper we introduce a new approach for information retrieval from Persian document image database without using Optical Character Recognition (OCR).At first an attribute called subword upper contour label is defined then, a pictorial dictionary is constructed based on this attribute for the subwords. By this approach we address two issues in document image retrieval: keyword spotting and retrieval according to the document similarities. The proposed methods have been evaluated on a Persian document image database. The results have proved the ability of this approach in document image information retrieval.

Multi-Decadal Pathfinder Data Sets of Global Land Biophysical Variables from AVHRR and MODIS and their Use in GCM Studies of Biogeophysics and Biogeochemistry

NASA Technical Reports Server (NTRS)

Myneni, Ranga

2003-01-01

The problem of how the scale, or spatial resolution, of reflectance data impacts retrievals of vegetation leaf area index (LAI) and fraction absorbed photosynthetically active radiation (PAR) has been investigated. We define the goal of scaling as the process by which it is established that LAI and FPAR values derived from coarse resolution sensor data equal the arithmetic average of values derived independently from fine resolution sensor data. The increasing probability of land cover mixtures with decreasing resolution is defined as heterogeneity, which is a key concept in scaling studies. The effect of pixel heterogeneity on spectral reflectances and LAI/FPAR retrievals is investigated with 1 km Advanced Very High Resolution Radiometer (AVHRR) data aggregated to different coarse spatial resolutions. It is shown that LAI retrieval errors at coarse resolution are inversely related to the proportion of the dominant land cover in such pixel. Further, large errors in LAI retrievals are incurred when forests are minority biomes in non-forest pixels compared to when forest biomes are mixed with one another, and vice-versa. A physically based technique for scaling with explicit spatial resolution dependent radiative transfer formulation is developed. The successful application of this theory to scaling LAI retrievals from AVHRR data of different resolutions is demonstrated

Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation

NASA Technical Reports Server (NTRS)

Mandrake, Lukas

2013-01-01

Retrieval algorithms like that used by the Orbiting Carbon Observatory (OCO)-2 mission generate massive quantities of data of varying quality and reliability. A computationally efficient, simple method of labeling problematic datapoints or predicting soundings that will fail is required for basic operation, given that only 6% of the retrieved data may be operationally processed. This method automatically obtains a filter designed to reduce scatter based on a small number of input features. Most machine-learning filter construction algorithms attempt to predict error in the CO2 value. By using a surrogate goal of Mean Monthly STDEV, the goal is to reduce the retrieved CO2 scatter rather than solving the harder problem of reducing CO2 error. This lends itself to improved interpretability and performance. This software reduces the scatter of retrieved CO2 values globally based on a minimum number of input features. It can be used as a prefilter to reduce the number of soundings requested, or as a post-filter to label data quality. The use of the MMS (Mean Monthly Standard deviation) provides a much cleaner, clearer filter than the standard ABS(CO2-truth) metrics previously employed by competitor methods. The software's main strength lies in a clearer (i.e., fewer features required) filter that more efficiently reduces scatter in retrieved CO2 rather than focusing on the more complex (and easily removed) bias issues.

Retrieval of aerosol profiles combining sunphotometer and ceilometer measurements in GRASP code

NASA Astrophysics Data System (ADS)

Román, R.; Benavent-Oltra, J. A.; Casquero-Vera, J. A.; Lopatin, A.; Cazorla, A.; Lyamani, H.; Denjean, C.; Fuertes, D.; Pérez-Ramírez, D.; Torres, B.; Toledano, C.; Dubovik, O.; Cachorro, V. E.; de Frutos, A. M.; Olmo, F. J.; Alados-Arboledas, L.

2018-05-01

In this paper we present an approach for the profiling of aerosol microphysical and optical properties combining ceilometer and sun/sky photometer measurements in the GRASP code (General Retrieval of Aerosol and Surface Properties). For this objective, GRASP is used with sun/sky photometer measurements of aerosol optical depth (AOD) and sky radiances, both at four wavelengths and obtained from AErosol RObotic NETwork (AERONET), and ceilometer measurements of range corrected signal (RCS) at 1064 nm. A sensitivity study with synthetic data evidences the capability of the method to retrieve aerosol properties such as size distribution and profiles of volume concentration (VC), especially for coarse particles. Aerosol properties obtained by the mentioned method are compared with airborne in-situ measurements acquired during two flights over Granada (Spain) within the framework of ChArMEx/ADRIMED (Chemistry-Aerosol Mediterranean Experiment/Aerosol Direct Radiative Impact on the regional climate in the MEDiterranean region) 2013 campaign. The retrieved aerosol VC profiles agree well with the airborne measurements, showing a mean bias error (MBE) and a mean absolute bias error (MABE) of 0.3 μm3/cm3 (12%) and 5.8 μm3/cm3 (25%), respectively. The differences between retrieved VC and airborne in-situ measurements are within the uncertainty of GRASP retrievals. In addition, the retrieved VC at 2500 m a.s.l. is shown and compared with in-situ measurements obtained during summer 2016 at a high-atitude mountain station in the framework of the SLOPE I campaign (Sierra Nevada Lidar AerOsol Profiling Experiment). VC from GRASP presents high correlation (r = 0.91) with the in-situ measurements, but overestimates them, MBE and MABE being equal to 23% and 43%.

Validation of MODIS aerosol optical depth product over China using CARSNET measurements

NASA Astrophysics Data System (ADS)

Xie, Yong; Zhang, Yan; Xiong, Xiaoxiong; Qu, John J.; Che, Huizheng

2011-10-01

This study evaluates Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) retrievals with ground measurements collected by the China Aerosol Remote Sensing NETwork (CARSNET). In current stage, the MODIS Collection 5 (C5) AODs are retrieved by two distinct algorithms: the Dark Target (DT) and the Deep Blue (DB). The CARSNET AODs are derived with measurements of Cimel Electronique CE-318, the same instrument deployed by the AEROsol Robotic Network (AEROENT). The collocation is performed by matching each MODIS AOD pixel (10 × 10 km 2) to CARSNET AOD mean within 7.5 min of satellite overpass. Four-year comparisons (2005-2008) of MODIS/CARSNET at ten sites show the performance of MODIS AOD retrieval is highly dependent on the underlying land surface. The MODIS DT AODs are on average lower than the CARSNET AODs by 6-30% over forest and grassland areas, but can be higher by up to 54% over urban area and 95% over desert-like area. More than 50% of the MODIS DT AODs fall within the expected error envelope over forest and grassland areas. The MODIS DT tends to overestimate for small AOD at urban area. At high vegetated area it underestimates for small AOD and overestimates for large AOD. Generally, its quality reduces with the decreasing AOD value. The MODIS DB is capable of retrieving AOD over desert but with a significant underestimation at CARSNET sites. The best retrieval of the MODIS DB is over grassland area with about 70% retrievals within the expected error. The uncertainties of MODIS AOD retrieval from spatial-temporal collocation and instrument calibration are discussed briefly.

Cloud Droplet Size and Liquid Water Path Retrievals From Zenith Radiance Measurements: Examples From the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network

NASA Technical Reports Server (NTRS)

Chiu, J. C.; Marshak, A.; Huang, C.-H.; Varnai, T.; Hogan, R. J.; Giles, D. M.; Holben, B. N.; Knyazikhin, Y.; O'Connor, E. J.; Wiscombe, W. J.

2012-01-01

The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a water-absorbing wavelength (i.e. 1640 nm) with a nonwater-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g/sq m and horizontal resolution of 201m, the retrieval method underestimates the mean effective radius by 0.8 m, with a root-mean-squared error of 1.7 m and a relative deviation of 13 %. For actual observations with a liquid water path less than 450 gm.2 at the ARM Oklahoma site during 2007-2008, our 1.5 min-averaged retrievals are generally larger by around 1 m than those from combined ground-based cloud radar and microwave radiometer at a 5min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 m and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 m. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

Improved Temperature Sounding and Quality Control Methodology Using AIRS/AMSU Data: The AIRS Science Team Version 5 Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Blaisdell, John M.; Iredell, Lena; Keita, Fricky

2009-01-01

This paper describes the AIRS Science Team Version 5 retrieval algorithm in terms of its three most significant improvements over the methodology used in the AIRS Science Team Version 4 retrieval algorithm. Improved physics in Version 5 allows for use of AIRS clear column radiances in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profiles T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of clear column radiances .R(sub i) for all channels. This new approach allows for the generation of more accurate values of .R(sub i) and T(p) under most cloud conditions. Secondly, Version 5 contains a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances. Thresholds of these error estimates are used in a new approach for Quality Control. Finally, Version 5 also contains for the first time an approach to provide AIRS soundings in partially cloudy conditions that does not require use of any microwave data. This new AIRS Only sounding methodology, referred to as AIRS Version 5 AO, was developed as a backup to AIRS Version 5 should the AMSU-A instrument fail. Results are shown comparing the relative performance of the AIRS Version 4, Version 5, and Version 5 AO for the single day, January 25, 2003. The Goddard DISC is now generating and distributing products derived using the AIRS Science Team Version 5 retrieval algorithm. This paper also described the Quality Control flags contained in the DISC AIRS/AMSU retrieval products and their intended use for scientific research purposes.

Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis.

PubMed

Liu, Chuanjun; Xiao, Chengli

2018-01-01

The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one.

Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis

PubMed Central

Liu, Chuanjun; Xiao, Chengli

2018-01-01

The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one. PMID:29467698

The Coplane Analysis Technique for Three-Dimensional Wind Retrieval Using the HIWRAP Airborne Doppler Radar

NASA Technical Reports Server (NTRS)

Didlake, Anthony C., Jr.; Heymsfield, Gerald M.; Tian, Lin; Guimond, Stephen R.

2015-01-01

The coplane analysis technique for mapping the three-dimensional wind field of precipitating systems is applied to the NASA High Altitude Wind and Rain Airborne Profiler (HIWRAP). HIWRAP is a dual-frequency Doppler radar system with two downward pointing and conically scanning beams. The coplane technique interpolates radar measurements to a natural coordinate frame, directly solves for two wind components, and integrates the mass continuity equation to retrieve the unobserved third wind component. This technique is tested using a model simulation of a hurricane and compared to a global optimization retrieval. The coplane method produced lower errors for the cross-track and vertical wind components, while the global optimization method produced lower errors for the along-track wind component. Cross-track and vertical wind errors were dependent upon the accuracy of the estimated boundary condition winds near the surface and at nadir, which were derived by making certain assumptions about the vertical velocity field. The coplane technique was then applied successfully to HIWRAP observations of Hurricane Ingrid (2013). Unlike the global optimization method, the coplane analysis allows for a transparent connection between the radar observations and specific analysis results. With this ability, small-scale features can be analyzed more adequately and erroneous radar measurements can be identified more easily.

A method to correct sampling ghosts in historic near-infrared Fourier transform spectrometer (FTS) measurements

NASA Astrophysics Data System (ADS)

Dohe, S.; Sherlock, V.; Hase, F.; Gisi, M.; Robinson, J.; Sepúlveda, E.; Schneider, M.; Blumenstock, T.

2013-08-01

The Total Carbon Column Observing Network (TCCON) has been established to provide ground-based remote sensing measurements of the column-averaged dry air mole fractions (DMF) of key greenhouse gases. To ensure network-wide consistency, biases between Fourier transform spectrometers at different sites have to be well controlled. Errors in interferogram sampling can introduce significant biases in retrievals. In this study we investigate a two-step scheme to correct these errors. In the first step the laser sampling error (LSE) is estimated by determining the sampling shift which minimises the magnitude of the signal intensity in selected, fully absorbed regions of the solar spectrum. The LSE is estimated for every day with measurements which meet certain selection criteria to derive the site-specific time series of the LSEs. In the second step, this sequence of LSEs is used to resample all the interferograms acquired at the site, and hence correct the sampling errors. Measurements acquired at the Izaña and Lauder TCCON sites are used to demonstrate the method. At both sites the sampling error histories show changes in LSE due to instrument interventions (e.g. realignment). Estimated LSEs are in good agreement with sampling errors inferred from the ratio of primary and ghost spectral signatures in optically bandpass-limited tungsten lamp spectra acquired at Lauder. The original time series of Xair and XCO2 (XY: column-averaged DMF of the target gas Y) at both sites show discrepancies of 0.2-0.5% due to changes in the LSE associated with instrument interventions or changes in the measurement sample rate. After resampling, discrepancies are reduced to 0.1% or less at Lauder and 0.2% at Izaña. In the latter case, coincident changes in interferometer alignment may also have contributed to the residual difference. In the future the proposed method will be used to correct historical spectra at all TCCON sites.

Global distortion of GPS networks associated with satellite antenna model errors

NASA Astrophysics Data System (ADS)

Cardellach, E.; Elósegui, P.; Davis, J. L.

2007-07-01

Recent studies of the GPS satellite phase center offsets (PCOs) suggest that these have been in error by ˜1 m. Previous studies had shown that PCO errors are absorbed mainly by parameters representing satellite clock and the radial components of site position. On the basis of the assumption that the radial errors are equal, PCO errors will therefore introduce an error in network scale. However, PCO errors also introduce distortions, or apparent deformations, within the network, primarily in the radial (vertical) component of site position that cannot be corrected via a Helmert transformation. Using numerical simulations to quantify the effects of PCO errors, we found that these PCO errors lead to a vertical network distortion of 6-12 mm per meter of PCO error. The network distortion depends on the minimum elevation angle used in the analysis of the GPS phase observables, becoming larger as the minimum elevation angle increases. The steady evolution of the GPS constellation as new satellites are launched, age, and are decommissioned, leads to the effects of PCO errors varying with time that introduce an apparent global-scale rate change. We demonstrate here that current estimates for PCO errors result in a geographically variable error in the vertical rate at the 1-2 mm yr-1 level, which will impact high-precision crustal deformation studies.

Global Distortion of GPS Networks Associated with Satellite Antenna Model Errors

NASA Technical Reports Server (NTRS)

Cardellach, E.; Elosequi, P.; Davis, J. L.

2007-01-01

Recent studies of the GPS satellite phase center offsets (PCOs) suggest that these have been in error by approx.1 m. Previous studies had shown that PCO errors are absorbed mainly by parameters representing satellite clock and the radial components of site position. On the basis of the assumption that the radial errors are equal, PCO errors will therefore introduce an error in network scale. However, PCO errors also introduce distortions, or apparent deformations, within the network, primarily in the radial (vertical) component of site position that cannot be corrected via a Helmert transformation. Using numerical simulations to quantify the effects of PC0 errors, we found that these PCO errors lead to a vertical network distortion of 6-12 mm per meter of PCO error. The network distortion depends on the minimum elevation angle used in the analysis of the GPS phase observables, becoming larger as the minimum elevation angle increases. The steady evolution of the GPS constellation as new satellites are launched, age, and are decommissioned, leads to the effects of PCO errors varying with time that introduce an apparent global-scale rate change. We demonstrate here that current estimates for PCO errors result in a geographically variable error in the vertical rate at the 1-2 mm/yr level, which will impact high-precision crustal deformation studies.

Atmospheric Precorrected Differential Absorption technique to retrieve columnar water vapor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schlaepfer, D.; Itten, K.I.; Borel, C.C.

1998-09-01

Differential absorption techniques are suitable to retrieve the total column water vapor contents from imaging spectroscopy data. A technique called Atmospheric Precorrected Differential Absorption (APDA) is derived directly from simplified radiative transfer equations. It combines a partial atmospheric correction with a differential absorption technique. The atmospheric path radiance term is iteratively corrected during the retrieval of water vapor. This improves the results especially over low background albedos. The error of the method for various ground reflectance spectra is below 7% for most of the spectra. The channel combinations for two test cases are then defined, using a quantitative procedure, whichmore » is based on MODTRAN simulations and the image itself. An error analysis indicates that the influence of aerosols and channel calibration is minimal. The APDA technique is then applied to two AVIRIS images acquired in 1991 and 1995. The accuracy of the measured water vapor columns is within a range of {+-}5% compared to ground truth radiosonde data.« less

Phytoplankton pigment concentrations in the Middle Atlantic Bight - Comparison of ship determinations and CZCS estimates. [Coastal Zone Color Scanner

NASA Technical Reports Server (NTRS)

Gordon, H. R.; Brown, J. W.; Clark, D. K.; Brown, O. B.; Evans, R. H.; Broenkow, W. W.

1983-01-01

The processing algorithms used for relating the apparent color of the ocean observed with the Coastal-Zone Color Scanner on Nimbus-7 to the concentration of phytoplankton pigments (principally the pigment responsible for photosynthesis, chlorophyll-a) are developed and discussed in detail. These algorithms are applied to the shelf and slope waters of the Middle Atlantic Bight and also to Sargasso Sea waters. In all, four images are examined, and the resulting pigment concentrations are compared to continuous measurements made along ship tracks. The results suggest that over the 0.08-1.5 mg/cu m range, the error in the retrieved pigment concentration is of the order of 30-40% for a variety of atmospheric turbidities. In three direct comparisons between ship-measured and satellite-retrieved values of the water-leaving radiance, the atmospheric correction algorithm retrieved the water-leaving radiance with an average error of about 10%. This atmospheric correction algorithm does not require any surface measurements for its application.

Optical mass memory investigation

NASA Technical Reports Server (NTRS)

1980-01-01

The MASTER 1 optical mass storage system advanced working model (AWM) was designed to demonstrate recording and playback of imagery data and to enable quantitative data to be derived as to the statistical distribution of raw errors experienced through the system. The AWM consists of two subsystems, the recorder and storage and retrieval. The recorder subsystem utilizes key technologies such as an acoustic travelling wave lens to achieve recording of digital data on fiche at a rate of 30 Mbits/sec, whereas the storage and retrieval reproducer subsystem utilizes a less complex optical system that employs an acousto-optical beam deflector to achieve data readout at a 5 Mbits/sec rate. The system has the built in capability for detecting and collecting error statistics. The recorder and storage and retrieval subsystems operate independent of one another and are each constructed in modular form with each module performing independent functions. The operation of each module and its interface to other modules is controlled by one controller for both subsystems.

Information content of ozone retrieval algorithms

NASA Technical Reports Server (NTRS)

Rodgers, C.; Bhartia, P. K.; Chu, W. P.; Curran, R.; Deluisi, J.; Gille, J. C.; Hudson, R.; Mateer, C.; Rusch, D.; Thomas, R. J.

1989-01-01

The algorithms are characterized that were used for production processing by the major suppliers of ozone data to show quantitatively: how the retrieved profile is related to the actual profile (This characterizes the altitude range and vertical resolution of the data); the nature of systematic errors in the retrieved profiles, including their vertical structure and relation to uncertain instrumental parameters; how trends in the real ozone are reflected in trends in the retrieved ozone profile; and how trends in other quantities (both instrumental and atmospheric) might appear as trends in the ozone profile. No serious deficiencies were found in the algorithms used in generating the major available ozone data sets. As the measurements are all indirect in someway, and the retrieved profiles have different characteristics, data from different instruments are not directly comparable.

Improved Atmospheric Soundings and Error Estimates from Analysis of AIRS/AMSU Data

NASA Technical Reports Server (NTRS)

Susskind, Joel

2007-01-01

The AIRS Science Team Version 5.0 retrieval algorithm became operational at the Goddard DAAC in July 2007 generating near real-time products from analysis of AIRS/AMSU sounding data. This algorithm contains many significant theoretical advances over the AIRS Science Team Version 4.0 retrieval algorithm used previously. Three very significant developments of Version 5 are: 1) the development and implementation of an improved Radiative Transfer Algorithm (RTA) which allows for accurate treatment of non-Local Thermodynamic Equilibrium (non-LTE) effects on shortwave sounding channels; 2) the development of methodology to obtain very accurate case by case product error estimates which are in turn used for quality control; and 3) development of an accurate AIRS only cloud clearing and retrieval system. These theoretical improvements taken together enabled a new methodology to be developed which further improves soundings in partially cloudy conditions, without the need for microwave observations in the cloud clearing step as has been done previously. In this methodology, longwave C02 channel observations in the spectral region 700 cm-' to 750 cm-' are used exclusively for cloud clearing purposes, while shortwave C02 channels in the spectral region 2195 cm-' to 2395 cm-' are used for temperature sounding purposes. The new methodology for improved error estimates and their use in quality control is described briefly and results are shown indicative of their accuracy. Results are also shown of forecast impact experiments assimilating AIRS Version 5.0 retrieval products in the Goddard GEOS 5 Data Assimilation System using different quality control thresholds.

Improving Forecast Skill by Assimilation of Quality Controlled AIRS Version 5 Temperature Soundings

NASA Technical Reports Server (NTRS)

Susskind, Joel; Reale, Oreste

2009-01-01

The AIRS Science Team Version 5 retrieval algorithm has been finalized and is now operational at the Goddard DAAC in the processing (and reprocessing) of all AIRS data. The AIRS Science Team Version 5 retrieval algorithm contains two significant improvements over Version 4: 1) Improved physics allows for use of AIRS observations in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profile T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of cloud cleared radiances R(sub i). This approach allows for the generation of accurate values of R(sub i) and T(p) under most cloud conditions. 2) Another very significant improvement in Version 5 is the ability to generate accurate case-by-case, level-by-level error estimates for the atmospheric temperature profile, as well as for channel-by-channel error estimates for R(sub i). These error estimates are used for Quality Control of the retrieved products. We have conducted forecast impact experiments assimilating AIRS temperature profiles with different levels of Quality Control using the NASA GEOS-5 data assimilation system. Assimilation of Quality Controlled T(p) resulted in significantly improved forecast skill compared to that obtained from analyses obtained when all data used operationally by NCEP, except for AIRS data, is assimilated. We also conducted an experiment assimilating AIRS radiances uncontaminated by clouds, as done operationally by ECMWF and NCEP. Forecast resulting from assimilated AIRS radiances were of poorer quality than those obtained assimilating AIRS temperatures.

Physical Retrieval of Surface Emissivity Spectrum from Hyperspectral Infrared Radiances

NASA Technical Reports Server (NTRS)

Li, Jun; Weisz, Elisabeth; Zhou, Daniel K.

2007-01-01

Retrieval of temperature, moisture profiles and surface skin temperature from hyperspectral infrared (IR) radiances requires spectral information about the surface emissivity. Using constant or inaccurate surface emissivities typically results in large retrieval errors, particularly over semi-arid or arid areas where the variation in emissivity spectrum is large both spectrally and spatially. In this study, a physically based algorithm has been developed to retrieve a hyperspectral IR emissivity spectrum simultaneously with the temperature and moisture profiles, as well as the surface skin temperature. To make the solution stable and efficient, the hyperspectral emissivity spectrum is represented by eigenvectors, derived from the laboratory measured hyperspectral emissivity database, in the retrieval process. Experience with AIRS (Atmospheric InfraRed Sounder) radiances shows that a simultaneous retrieval of the emissivity spectrum and the sounding improves the surface skin temperature as well as temperature and moisture profiles, particularly in the near surface layer.

Surface Reflectance of Mars Observed by CRISM-MRO: 1. Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (mars-reco)

NASA Technical Reports Server (NTRS)

Ceamanos, Xavier; Doute, S.; Fernando, J.; Pinet, P.; Lyapustin, A.

2013-01-01

This article addresses the correction for aerosol effects in near-simultaneous multiangle observations acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter. In the targeted mode, CRISM senses the surface of Mars using 11 viewing angles, which allow it to provide unique information on the scattering properties of surface materials. In order to retrieve these data, however, appropriate strategies must be used to compensate the signal sensed by CRISM for aerosol contribution. This correction is particularly challenging as the photometric curve of these suspended particles is often correlated with the also anisotropic photometric curve of materials at the surface. This article puts forward an innovative radiative transfer based method named Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (MARS-ReCO). The proposed method retrieves photometric curves of surface materials in reflectance units after removing aerosol contribution. MARS-ReCO represents a substantial improvement regarding previous techniques as it takes into consideration the anisotropy of the surface, thus providing more realistic surface products. Furthermore, MARS-ReCO is fast and provides error bars on the retrieved surface reflectance. The validity and accuracy of MARS-ReCO is explored in a sensitivity analysis based on realistic synthetic data. According to experiments, MARS-ReCO provides accurate results (up to 10 reflectance error) under favorable acquisition conditions. In the companion article, photometric properties of Martian materials are retrieved using MARS-ReCO and validated using in situ measurements acquired during the Mars Exploration Rovers mission.

Using satellite observations in performance evaluation for regulatory air quality modeling: Comparison with ground-level measurements

NASA Astrophysics Data System (ADS)

Odman, M. T.; Hu, Y.; Russell, A.; Chai, T.; Lee, P.; Shankar, U.; Boylan, J.

2012-12-01

Regulatory air quality modeling, such as State Implementation Plan (SIP) modeling, requires that model performance meets recommended criteria in the base-year simulations using period-specific, estimated emissions. The goal of the performance evaluation is to assure that the base-year modeling accurately captures the observed chemical reality of the lower troposphere. Any significant deficiencies found in the performance evaluation must be corrected before any base-case (with typical emissions) and future-year modeling is conducted. Corrections are usually made to model inputs such as emission-rate estimates or meteorology and/or to the air quality model itself, in modules that describe specific processes. Use of ground-level measurements that follow approved protocols is recommended for evaluating model performance. However, ground-level monitoring networks are spatially sparse, especially for particulate matter. Satellite retrievals of atmospheric chemical properties such as aerosol optical depth (AOD) provide spatial coverage that can compensate for the sparseness of ground-level measurements. Satellite retrievals can also help diagnose potential model or data problems in the upper troposphere. It is possible to achieve good model performance near the ground, but have, for example, erroneous sources or sinks in the upper troposphere that may result in misleading and unrealistic responses to emission reductions. Despite these advantages, satellite retrievals are rarely used in model performance evaluation, especially for regulatory modeling purposes, due to the high uncertainty in retrievals associated with various contaminations, for example by clouds. In this study, 2007 was selected as the base year for SIP modeling in the southeastern U.S. Performance of the Community Multiscale Air Quality (CMAQ) model, at a 12-km horizontal resolution, for this annual simulation is evaluated using both recommended ground-level measurements and non-traditional satellite retrievals. Evaluation results are assessed against recommended criteria and peer studies in the literature. Further analysis is conducted, based upon these assessments, to discover likely errors in model inputs and potential deficiencies in the model itself. Correlations as well as differences in input errors and model deficiencies revealed by ground-level measurements versus satellite observations are discussed. Additionally, sensitivity analyses are employed to investigate errors in emission-rate estimates using either ground-level measurements or satellite retrievals, and the results are compared against each other considering observational uncertainties. Recommendations are made for how to effectively utilize satellite retrievals in regulatory air quality modeling.

MWR3C physical retrievals of precipitable water vapor and cloud liquid water path

DOE Data Explorer

Cadeddu, Maria

2016-10-12

The data set contains physical retrievals of PWV and cloud LWP retrieved from MWR3C measurements during the MAGIC campaign. Additional data used in the retrieval process include radiosondes and ceilometer. The retrieval is based on an optimal estimation technique that starts from a first guess and iteratively repeats the forward model calculations until a predefined convergence criterion is satisfied. The first guess is a vector of [PWV,LWP] from the neural network retrieval fields in the netcdf file. When convergence is achieved the 'a posteriori' covariance is computed and its square root is expressed in the file as the retrieval 1-sigma uncertainty. The closest radiosonde profile is used for the radiative transfer calculations and ceilometer data are used to constrain the cloud base height. The RMS error between the brightness temperatures is computed at the last iterations as a consistency check and is written in the last column of the output file.

Interfaces and Expert Systems for Online Retrieval.

ERIC Educational Resources Information Center

Kehoe, Cynthia A.

1985-01-01

This paper reviews the history of separate online system interfaces which led to efforts to develop expert systems for searching databases, particularly for end users, and introduces the research on such expert systems. Appended is a bibliography of sources on interfaces and expert systems for online retrieval. (Author/EJS)

Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Reichle, Rolf H.

2016-01-01

Three different data products from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated separately into the Goddard Earth Observing System Model, version 5 (GEOS-5) to improve estimates of surface and root-zone soil moisture. The first product consists of multi-angle, dual-polarization brightness temperature (Tb) observations at the bottom of the atmosphere extracted from Level 1 data. The second product is a derived SMOS Tb product that mimics the data at a 40 degree incidence angle from the Soil Moisture Active Passive (SMAP) mission. The third product is the operational SMOS Level 2 surface soil moisture (SM) retrieval product. The assimilation system uses a spatially distributed ensemble Kalman filter (EnKF) with seasonally varying climatological bias mitigation for Tb assimilation, whereas a time-invariant cumulative density function matching is used for SM retrieval assimilation. All assimilation experiments improve the soil moisture estimates compared to model-only simulations in terms of unbiased root-mean-square differences and anomaly correlations during the period from 1 July 2010 to 1 May 2015 and for 187 sites across the US. Especially in areas where the satellite data are most sensitive to surface soil moisture, large skill improvements (e.g., an increase in the anomaly correlation by 0.1) are found in the surface soil moisture. The domain-average surface and root-zone skill metrics are similar among the various assimilation experiments, but large differences in skill are found locally. The observation-minus-forecast residuals and analysis increments reveal large differences in how the observations add value in the Tb and SM retrieval assimilation systems. The distinct patterns of these diagnostics in the two systems reflect observation and model errors patterns that are not well captured in the assigned EnKF error parameters. Consequently, a localized optimization of the EnKF error parameters is needed to further improve Tb or SM retrieval assimilation.

Retrieval of carbon dioxide vertical profiles from solar occultation observations and associated error budgets for ACE-FTS and CASS-FTS

NASA Astrophysics Data System (ADS)

Sioris, C. E.; Boone, C. D.; Nassar, R.; Sutton, K. J.; Gordon, I. E.; Walker, K. A.; Bernath, P. F.

2014-02-01

An algorithm is developed to retrieve the vertical profile of carbon dioxide in the 5 to 25 km altitude range using mid-infrared solar occultation spectra from the main instrument of the ACE (Atmospheric Chemistry Experiment) mission, namely the Fourier Transform Spectrometer (FTS). The main challenge is to find an atmospheric phenomenon which can be used for accurate tangent height determination in the lower atmosphere, where the tangent heights (THs) calculated from geometric and timing information is not of sufficient accuracy. Error budgets for the retrieval of CO2 from ACE-FTS and the FTS on a potential follow-on mission named CASS (Chemical and Aerosol Sounding Satellite) are calculated and contrasted. Retrieved THs are typically within 60 m of those retrieved using the ACE version 3.x software after revisiting the temperature dependence of the N2 CIA (Collision-Induced Absorption) laboratory measurements and accounting for sulfate aerosol extinction. After correcting for the known residual high bias of ACE version 3.x THs expected from CO2 spectroscopic/isotopic inconsistencies, the remaining bias for tangent heights determined with the N2 CIA is -20m. CO2 in the 5-13 km range in the 2009-2011 time frame is validated against aircraft measurements from CARIBIC, CONTRAIL and HIPPO, yielding typical biases of -1.7 ppm in the 5-13 km range. The standard error of these biases in this vertical range is 0.4 ppm. The multi-year ACE-FTS dataset is valuable in determining the seasonal variation of the latitudinal gradient which arises from the strong seasonal cycle in the Northern Hemisphere troposphere. The annual growth of CO2 in this time frame is determined to be 2.5 ± 0.7 ppm yr-1, in agreement with the currently accepted global growth rate based on ground-based measurements.

Improvement of Aerosol Optical Depth Retrieval over Hong Kong from a Geostationary Meteorological Satellite Using Critical Reflectance with Background Optical Depth Correction

NASA Technical Reports Server (NTRS)

Kim, Mijin; Kim, Jhoon; Wong, Man Sing; Yoon, Jongmin; Lee, Jaehwa; Wu, Dong L.; Chan, P.W.; Nichol, Janet E.; Chung, Chu-Yong; Ou, Mi-Lim

2014-01-01

Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from tMI [basic algorithm] = 0.41tAERONET + 0.16 to tMI [new algorithm] = 0.70tAERONET + 0.01.

Application of the Markov Chain Monte Carlo method for snow water equivalent retrieval based on passive microwave measurements

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Vanderjagt, B. J.

2015-12-01

Markov Chain Monte Carlo (MCMC) method is a retrieval algorithm based on Bayes' rule, which starts from an initial state of snow/soil parameters, and updates it to a series of new states by comparing the posterior probability of simulated snow microwave signals before and after each time of random walk. It is a realization of the Bayes' rule, which gives an approximation to the probability of the snow/soil parameters in condition of the measured microwave TB signals at different bands. Although this method could solve all snow parameters including depth, density, snow grain size and temperature at the same time, it still needs prior information of these parameters for posterior probability calculation. How the priors will influence the SWE retrieval is a big concern. Therefore, in this paper at first, a sensitivity test will be carried out to study how accurate the snow emission models and how explicit the snow priors need to be to maintain the SWE error within certain amount. The synthetic TB simulated from the measured snow properties plus a 2-K observation error will be used for this purpose. It aims to provide a guidance on the MCMC application under different circumstances. Later, the method will be used for the snowpits at different sites, including Sodankyla, Finland, Churchill, Canada and Colorado, USA, using the measured TB from ground-based radiometers at different bands. Based on the previous work, the error in these practical cases will be studied, and the error sources will be separated and quantified.

Syntactic and semantic errors in radiology reports associated with speech recognition software.

PubMed

Ringler, Michael D; Goss, Brian C; Bartholmai, Brian J

2017-03-01

Speech recognition software can increase the frequency of errors in radiology reports, which may affect patient care. We retrieved 213,977 speech recognition software-generated reports from 147 different radiologists and proofread them for errors. Errors were classified as "material" if they were believed to alter interpretation of the report. "Immaterial" errors were subclassified as intrusion/omission or spelling errors. The proportion of errors and error type were compared among individual radiologists, imaging subspecialty, and time periods. In all, 20,759 reports (9.7%) contained errors, of which 3992 (1.9%) were material errors. Among immaterial errors, spelling errors were more common than intrusion/omission errors ( p < .001). Proportion of errors and fraction of material errors varied significantly among radiologists and between imaging subspecialties ( p < .001). Errors were more common in cross-sectional reports, reports reinterpreting results of outside examinations, and procedural studies (all p < .001). Error rate decreased over time ( p < .001), which suggests that a quality control program with regular feedback may reduce errors.

Content-based TV sports video retrieval using multimodal analysis

NASA Astrophysics Data System (ADS)

Yu, Yiqing; Liu, Huayong; Wang, Hongbin; Zhou, Dongru

2003-09-01

In this paper, we propose content-based video retrieval, which is a kind of retrieval by its semantical contents. Because video data is composed of multimodal information streams such as video, auditory and textual streams, we describe a strategy of using multimodal analysis for automatic parsing sports video. The paper first defines the basic structure of sports video database system, and then introduces a new approach that integrates visual stream analysis, speech recognition, speech signal processing and text extraction to realize video retrieval. The experimental results for TV sports video of football games indicate that the multimodal analysis is effective for video retrieval by quickly browsing tree-like video clips or inputting keywords within predefined domain.

Free Recall Enhances Subsequent Learning

PubMed Central

Arnold, Kathleen M.; McDermott, Kathleen B.

2013-01-01

Testing, or retrieval practice, has become a central topic in memory research. One potentially important effect of retrieval practice has received little attention, however: Retrieval practice may enhance, or potentiate, subsequent learning. We introduce a paradigm that can measure the indirect, potentiating effect of free recall tests on subsequent learning, and then test a hypothesis for why tests have this potentiating effect. In two experiments, the benefit of a restudy trial was enhanced when prior free recall tests had been taken. Results from a third correlational study suggest that this effect may be mediated by the effect of testing on organization. Not only do encoding conditions impact later retrievability, but also retrieval attempts impact subsequent encoding effectiveness. PMID:23297100

Optimizing a remote sensing instrument to measure atmospheric surface pressure

NASA Technical Reports Server (NTRS)

Peckham, G. E.; Gatley, C.; Flower, D. A.

1983-01-01

Atmospheric surface pressure can be remotely sensed from a satellite by an active instrument which measures return echoes from the ocean at frequencies near the 60 GHz oxygen absorption band. The instrument is optimized by selecting its frequencies of operation, transmitter powers and antenna size through a new procedure baesd on numerical simulation which maximizes the retrieval accuracy. The predicted standard deviation error in the retrieved surface pressure is 1 mb. In addition the measurements can be used to retrieve water vapor, cloud liquid water and sea state, which is related to wind speed.

Actualities and Development of Heavy-Duty CNC Machine Tool Thermal Error Monitoring Technology

NASA Astrophysics Data System (ADS)

Zhou, Zu-De; Gui, Lin; Tan, Yue-Gang; Liu, Ming-Yao; Liu, Yi; Li, Rui-Ya

2017-09-01

Thermal error monitoring technology is the key technological support to solve the thermal error problem of heavy-duty CNC (computer numerical control) machine tools. Currently, there are many review literatures introducing the thermal error research of CNC machine tools, but those mainly focus on the thermal issues in small and medium-sized CNC machine tools and seldom introduce thermal error monitoring technologies. This paper gives an overview of the research on the thermal error of CNC machine tools and emphasizes the study of thermal error of the heavy-duty CNC machine tool in three areas. These areas are the causes of thermal error of heavy-duty CNC machine tool and the issues with the temperature monitoring technology and thermal deformation monitoring technology. A new optical measurement technology called the "fiber Bragg grating (FBG) distributed sensing technology" for heavy-duty CNC machine tools is introduced in detail. This technology forms an intelligent sensing and monitoring system for heavy-duty CNC machine tools. This paper fills in the blank of this kind of review articles to guide the development of this industry field and opens up new areas of research on the heavy-duty CNC machine tool thermal error.

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

PubMed Central

Tebani, Abdellah; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya

2016-01-01

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era. PMID:27649151

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations.

PubMed

Tebani, Abdellah; Afonso, Carlos; Marret, Stéphane; Bekri, Soumeya

2016-09-14

The rise of technologies that simultaneously measure thousands of data points represents the heart of systems biology. These technologies have had a huge impact on the discovery of next-generation diagnostics, biomarkers, and drugs in the precision medicine era. Systems biology aims to achieve systemic exploration of complex interactions in biological systems. Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations. Precision medicine capitalizes on these conceptual and technological advancements and stands on two main pillars: data generation and data modeling. High-throughput omics technologies allow the retrieval of comprehensive and holistic biological information, whereas computational capabilities enable high-dimensional data modeling and, therefore, accessible and user-friendly visualization. Furthermore, bioinformatics has enabled comprehensive multi-omics and clinical data integration for insightful interpretation. Despite their promise, the translation of these technologies into clinically actionable tools has been slow. In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed. Perspectives regarding the use of multi-omics approaches for inborn errors of metabolism (IEM) are presented by introducing a new paradigm shift in addressing IEM investigations in the post-genomic era.

Measurements of Nitrogen Dioxide Total Column Amounts using a Brewer Double Spectrophotometer in Direct Sun Mode

NASA Technical Reports Server (NTRS)

Cede, Alexander; Herman, Jay; Richter, Andreas; Krotkov, Nickolay; Burrows, John

2006-01-01

NO2 column amounts were measured for the past 2 years at Goddard Space Flight Center, Greenbelt, Maryland, using a Brewer spectrometer in direct Sun mode. A new bootstrap method to calibrate the instrument is introduced and described. This technique selects the cleanest days from the database to obtain the solar reference spectrum. The main advantage for direct Sun measurements is that the conversion uncertainty from slant column to vertical column is negligible compared to the standard scattered light observations where it is typically on the order of 100% (2sigma) at polluted sites. The total 2sigma errors of the direct Sun retrieved column amounts decrease with solar zenith angle and are estimated at 0.2 to 0.6 Dobson units (DU, 1 DU approx. equal to 2.7 10(exp 16) molecules cm(exp -2)), which is more accurate than scattered light measurements for high NO2 amounts. Measured NO2 column amounts, ranging from 0 to 3 DU with a mean of 0.7 DU, show a pronounced daily course and a strong variability from day to day. The NO2 concentration typically increases from sunrise to noon. In the afternoon it decreases in summer and stays constant in winter. As expected from the anthropogenic nature of its source, NO2 amounts on weekends are significantly reduced. The measurements were compared to satellite retrievals from Scanning Image Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). Satellite data give the same average NO2 column and show a seasonal cycle that is similar to the ground data in the afternoon. We show that NO2 must be considered when retrieving aerosol absorption properties, especially for situations with low aerosol optical depth.

Aerosol Extinction Profile Mapping with Lognormal Distribution Based on MPL Data

NASA Astrophysics Data System (ADS)

Lin, T. H.; Lee, T. T.; Chang, K. E.; Lien, W. H.; Liu, G. R.; Liu, C. Y.

2017-12-01

This study intends to challenge the profile mapping of aerosol vertical distribution by mathematical function. With the similarity in distribution pattern, lognormal distribution is examined for mapping the aerosol extinction profile based on MPL (Micro Pulse LiDAR) in situ measurements. The variables of lognormal distribution are log mean (μ) and log standard deviation (σ), which will be correlated with the parameters of aerosol optical depht (AOD) and planetary boundary layer height (PBLH) associated with the altitude of extinction peak (Mode) defined in this study. On the base of 10 years MPL data with single peak, the mapping results showed that the mean error of Mode and σ retrievals are 16.1% and 25.3%, respectively. The mean error of σ retrieval can be reduced to 16.5% under the cases of larger distance between PBLH and Mode. The proposed method is further applied to MODIS AOD product in mapping extinction profile for the retrieval of PM2.5 in terms of satellite observations. The results indicated well agreement between retrievals and ground measurements when aerosols under 525 meters are well-mixed. The feasibility of proposed method to satellite remote sensing is also suggested by the case study. Keyword: Aerosol extinction profile, Lognormal distribution, MPL, Planetary boundary layer height (PBLH), Aerosol optical depth (AOD), Mode

Retrievals of abundances of hydrocarbon and nitrile species in Titan’s upper atmosphere

NASA Astrophysics Data System (ADS)

Yung, Yuk; Fan, Siteng; Shemansky, D. E.; Li, Cheng; Gao, Peter

2017-10-01

We develop an innovative retrieval method for Titan occultation measurements by the Cassini UVIS experiment. The T35 occultation is analyzed to illustrate the methodology. A significant number of occultations observed using the UVIS spectrographs show loss of pointing control required for correction of the spectral vectors. Consequently, only three stellar occultations have been analyzed to date. We use the Markov Chain Monte-Carlo (MCMC) method to retrieve the abundances or upper limits of thirteen hydrocarbon and nitrile species (N2, CH4, C2H2, C2H4, C2H6, HCN, C4H2, C6N2, C6H6, tholin, HC3N, C2N2, NH3) along with the pointing error using the Cassini/UVIS simulator. These numbers are derived for the fast T35 occultation, which has never been analyzed because of large pointing errors. Uncertainty in the retrievals is determined using an intrinsic fitting probability distribution function. The Caltech/JPL photochemical and kinetics model, KINETICS, is used to calculate the atmospheric aforementioned species. Comparisons between model and observations reveal gaps in our current understanding of the chemical kinetics of hydrocarbons and nitrile species, especially for C6H6.

A Conceptual Framework for Predicting Error in Complex Human-Machine Environments

NASA Technical Reports Server (NTRS)

Freed, Michael; Remington, Roger; Null, Cynthia H. (Technical Monitor)

1998-01-01

We present a Goals, Operators, Methods, and Selection Rules-Model Human Processor (GOMS-MHP) style model-based approach to the problem of predicting human habit capture errors. Habit captures occur when the model fails to allocate limited cognitive resources to retrieve task-relevant information from memory. Lacking the unretrieved information, decision mechanisms act in accordance with implicit default assumptions, resulting in error when relied upon assumptions prove incorrect. The model helps interface designers identify situations in which such failures are especially likely.

Aerosol Optical Depths over Oceans: a View from MISR Retrievals and Collocated MAN and AERONET in Situ Observations

NASA Technical Reports Server (NTRS)

Witek, Marcin L.; Garay, Michael J.; Diner, David J.; Smirnov, Alexander

2013-01-01

In this study, aerosol optical depths over oceans are analyzed from satellite and surface perspectives. Multiangle Imaging SpectroRadiometer (MISR) aerosol retrievals are investigated and validated primarily against Maritime Aerosol Network (MAN) observations. Furthermore, AErosol RObotic NETwork (AERONET) data from 19 island and coastal sites is incorporated in this study. The 270 MISRMAN comparison points scattered across all oceans were identified. MISR on average overestimates aerosol optical depths (AODs) by 0.04 as compared to MAN; the correlation coefficient and root-mean-square error are 0.95 and 0.06, respectively. A new screening procedure based on retrieval region characterization is proposed, which is capable of substantially reducing MISR retrieval biases. Over 1000 additional MISRAERONET comparison points are added to the analysis to confirm the validity of the method. The bias reduction is effective within all AOD ranges. Setting a clear flag fraction threshold to 0.6 reduces the bias to below 0.02, which is close to a typical ground-based measurement uncertainty. Twelve years of MISR data are analyzed with the new screening procedure. The average over ocean AOD is reduced by 0.03, from 0.15 to 0.12. The largest AOD decrease is observed in high latitudes of both hemispheres, regions with climatologically high cloud cover. It is postulated that the screening procedure eliminates spurious retrieval errors associated with cloud contamination and cloud adjacency effects. The proposed filtering method can be used for validating aerosol and chemical transport models.

Continental-Scale Mapping of Adelie Penguin Colonies from Landsat Imagery

NASA Technical Reports Server (NTRS)

Schwaller, Mathew R.; Southwell, Colin; Emmerson, Louise

2013-01-01

Breeding distribution of the Adlie penguin, Pygoscelis adeliae, was surveyed with Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data in an area covering approximately 330 of longitude along the coastline of Antarctica.An algorithm was designed to minimize radiometric noise and to retrieve Adlie penguin colony location and spatial extent from the ETM+data. In all, 9143 individual pixels were classified as belonging to an Adlie penguin colony class out of the entire dataset of 195 ETM+ scenes, where the dimension of each pixel is 30 m by 30 m,and each scene is approximately 180 km by 180 km. Pixel clustering identified a total of 187 individual Adlie penguin colonies, ranging in size from a single pixel (900 sq m) to a maximum of 875 pixels (0.788 sq km). Colony retrievals have a very low error of commission, on the order of 1% or less, and the error of omission was estimated to be 3% to 4% by population based on comparisons with direct observations from surveys across east Antarctica. Thus, the Landsat retrievals successfully located Adlie penguin colonies that accounted for 96 to 97% of the regional population used as ground truth. Geographic coordinates and the spatial extent of each colony retrieved from the Landsat data are available publically. Regional analysis found several areas where the Landsat retrievals suggest populations that are significantly larger than published estimates. Six Adlie penguin colonies were found that are believed to be previously unreported in the literature.

Bone age assessment by content-based image retrieval and case-based reasoning

NASA Astrophysics Data System (ADS)

Fischer, Benedikt; Welter, Petra; Grouls, Christoph; Günther, Rolf W.; Deserno, Thomas M.

2011-03-01

Skeletal maturity is assessed visually by comparing hand radiographs to a standardized reference image atlas. Most common are the methods by Greulich & Pyle and Tanner & Whitehouse. For computer-aided diagnosis (CAD), local image regions of interest (ROI) such as the epiphysis or the carpal areas are extracted and evaluated. Heuristic approaches trying to automatically extract, measure and classify bones and distances between bones suffer from the high variability of biological material and the differences in bone development resulting from age, gender and ethnic origin. Content-based image retrieval (CBIR) provides a robust solution without delineating and measuring bones. In this work, epiphyseal ROIs (eROIS) of a hand radiograph are compared to previous cases with known age, mimicking a human observer. Leaving-one-out experiments are conducted on 1,102 left hand radiographs and 15,428 metacarpal and phalangeal eROIs from the publicly available USC hand atlas. The similarity of the eROIs is assessed by a combination of cross-correlation, image distortion model, and Tamura texture features, yielding a mean error rate of 0.97 years and a variance of below 0.63 years. Furthermore, we introduce a publicly available online-demonstration system, where queries on the USC dataset as well as on uploaded radiographs are performed for instant CAD. In future, we plan to evaluate physician with CBIR-CAD against physician without CBIR-CAD rather than physician vs. CBIR-CAD.

Interruption of the Tower of London Task: Support for a Goal-Activation Approach

ERIC Educational Resources Information Center

Hodgetts, Helen M.; Jones, Dylan M.

2006-01-01

Unexpected interruptions introduced during the execution phase of simple Tower of London problems incurred a time cost when the interrupted goal was retrieved, and this cost was exacerbated the longer the goal was suspended. Furthermore, time taken to retrieve goals was greater following a more complex interruption, indicating the processing…

Database Searching for the Service Journalist: Some Theories and Mechanics. An Introduction.

ERIC Educational Resources Information Center

Wendling, Dan

Intended to provide journalism students with an introduction to electronic information retrieval, this guide outlines a few of the 500 online services available to them on the University of Missouri-Columbia campus. The concept of the quality versus the quantity of citations retrieved is introduced and emphasized throughout. Services available at…

Multi-Character Tries for Text Searching.

ERIC Educational Resources Information Center

Cooper, Lorraine K. D.; Tharp, Alan L.

1993-01-01

Introduces the multicharacter trie as an index structure that can improve the time needed for retrieving full-text materials stored on CD-ROMs. The advantages of this structure compared to other structures are described, and experimental results comparing it to the widely used B+ tree and other structures used for full-text retrieval are…

Human Information Behaviour and Design, Development and Evaluation of Information Retrieval Systems

ERIC Educational Resources Information Center

Keshavarz, Hamid

2008-01-01

Purpose: The purpose of this paper is to introduce the concept of human information behaviour and to explore the relationship between information behaviour of users and the existing approaches dominating design and evaluation of information retrieval (IR) systems and also to describe briefly new design and evaluation methods in which extensive…

Garbage in, Garbage Out: Data Collection, Quality Assessment and Reporting Standards for Social Media Data Use in Health Research, Infodemiology and Digital Disease Detection

PubMed Central

Huang, Jidong; Emery, Sherry

2016-01-01

Background Social media have transformed the communications landscape. People increasingly obtain news and health information online and via social media. Social media platforms also serve as novel sources of rich observational data for health research (including infodemiology, infoveillance, and digital disease detection detection). While the number of studies using social data is growing rapidly, very few of these studies transparently outline their methods for collecting, filtering, and reporting those data. Keywords and search filters applied to social data form the lens through which researchers may observe what and how people communicate about a given topic. Without a properly focused lens, research conclusions may be biased or misleading. Standards of reporting data sources and quality are needed so that data scientists and consumers of social media research can evaluate and compare methods and findings across studies. Objective We aimed to develop and apply a framework of social media data collection and quality assessment and to propose a reporting standard, which researchers and reviewers may use to evaluate and compare the quality of social data across studies. Methods We propose a conceptual framework consisting of three major steps in collecting social media data: develop, apply, and validate search filters. This framework is based on two criteria: retrieval precision (how much of retrieved data is relevant) and retrieval recall (how much of the relevant data is retrieved). We then discuss two conditions that estimation of retrieval precision and recall rely on—accurate human coding and full data collection—and how to calculate these statistics in cases that deviate from the two ideal conditions. We then apply the framework on a real-world example using approximately 4 million tobacco-related tweets collected from the Twitter firehose. Results We developed and applied a search filter to retrieve e-cigarette–related tweets from the archive based on three keyword categories: devices, brands, and behavior. The search filter retrieved 82,205 e-cigarette–related tweets from the archive and was validated. Retrieval precision was calculated above 95% in all cases. Retrieval recall was 86% assuming ideal conditions (no human coding errors and full data collection), 75% when unretrieved messages could not be archived, 86% assuming no false negative errors by coders, and 93% allowing both false negative and false positive errors by human coders. Conclusions This paper sets forth a conceptual framework for the filtering and quality evaluation of social data that addresses several common challenges and moves toward establishing a standard of reporting social data. Researchers should clearly delineate data sources, how data were accessed and collected, and the search filter building process and how retrieval precision and recall were calculated. The proposed framework can be adapted to other public social media platforms. PMID:26920122

Recent Improvements in Retrieving Near-Surface Air Temperature and Humidity Using Microwave Remote Sensing

NASA Technical Reports Server (NTRS)

Roberts, J. Brent

2010-01-01

Detailed studies of the energy and water cycles require accurate estimation of the turbulent fluxes of moisture and heat across the atmosphere-ocean interface at regional to basin scale. Providing estimates of these latent and sensible heat fluxes over the global ocean necessitates the use of satellite or reanalysis-based estimates of near surface variables. Recent studies have shown that errors in the surface (10 meter)estimates of humidity and temperature are currently the largest sources of uncertainty in the production of turbulent fluxes from satellite observations. Therefore, emphasis has been placed on reducing the systematic errors in the retrieval of these parameters from microwave radiometers. This study discusses recent improvements in the retrieval of air temperature and humidity through improvements in the choice of algorithms (linear vs. nonlinear) and the choice of microwave sensors. Particular focus is placed on improvements using a neural network approach with a single sensor (Special Sensor Microwave/Imager) and the use of combined sensors from the NASA AQUA satellite platform. The latter algorithm utilizes the unique sampling available on AQUA from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A). Current estimates of uncertainty in the near-surface humidity and temperature from single and multi-sensor approaches are discussed and used to estimate errors in the turbulent fluxes.

Image inversion analysis of the HST OTA (Hubble Space Telescope Optical Telescope Assembly), phase A

NASA Technical Reports Server (NTRS)

Litvak, M. M.

1991-01-01

Technical work during September-December 1990 consisted of: (1) analyzing HST point source images obtained from JPL; (2) retrieving phase information from the images by a direct (noniterative) technique; and (3) characterizing the wavefront aberration due to the errors in the Hubble Space Telescope (HST) mirrors, in a preliminary manner. This work was in support of JPL design of compensating optics for the next generation wide-field planetary camera on HST. This digital technique for phase retrieval from pairs of defocused images, is based on the energy transport equation between these image planes. In addition, an end-to-end wave optics routine, based on the JPL Code 5 prescription of the unaberrated HST and WFPC, was derived for output of the reference phase front when mirror error is absent. Also, the Roddier routine unwrapped the retrieved phase by inserting the required jumps of +/- 2(pi) radians for the sake of smoothness. A least-squares fitting routine, insensitive to phase unwrapping, but nonlinear, was used to obtain estimates of the Zernike polynomial coefficients that describe the aberration. The phase results were close to, but higher than, the expected error in conic constant of the primary mirror suggested by the fossil evidence. The analysis of aberration contributed by the camera itself could be responsible for the small discrepancy, but was not verified by analysis.

Apoplastic water fraction and rehydration techniques introduce significant errors in measurements of relative water content and osmotic potential in plant leaves.

PubMed

Arndt, Stefan K; Irawan, Andi; Sanders, Gregor J

2015-12-01

Relative water content (RWC) and the osmotic potential (π) of plant leaves are important plant traits that can be used to assess drought tolerance or adaptation of plants. We estimated the magnitude of errors that are introduced by dilution of π from apoplastic water in osmometry methods and the errors that occur during rehydration of leaves for RWC and π in 14 different plant species from trees, grasses and herbs. Our data indicate that rehydration technique and length of rehydration can introduce significant errors in both RWC and π. Leaves from all species were fully turgid after 1-3 h of rehydration and increasing the rehydration time resulted in a significant underprediction of RWC. Standing rehydration via the petiole introduced the least errors while rehydration via floating disks and submerging leaves for rehydration led to a greater underprediction of RWC. The same effect was also observed for π. The π values following standing rehydration could be corrected by applying a dilution factor from apoplastic water dilution using an osmometric method but not by using apoplastic water fraction (AWF) from pressure volume (PV) curves. The apoplastic water dilution error was between 5 and 18%, while the two other rehydration methods introduced much greater errors. We recommend the use of the standing rehydration method because (1) the correct rehydration time can be evaluated by measuring water potential, (2) overhydration effects were smallest, and (3) π can be accurately corrected by using osmometric methods to estimate apoplastic water dilution. © 2015 Scandinavian Plant Physiology Society.

On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data

NASA Astrophysics Data System (ADS)

Zhou, Lu; Xu, Shiming; Liu, Jiping; Wang, Bin

2018-03-01

The accurate knowledge of sea ice parameters, including sea ice thickness and snow depth over the sea ice cover, is key to both climate studies and data assimilation in operational forecasts. Large-scale active and passive remote sensing is the basis for the estimation of these parameters. In traditional altimetry or the retrieval of snow depth with passive microwave remote sensing, although the sea ice thickness and the snow depth are closely related, the retrieval of one parameter is usually carried out under assumptions over the other. For example, climatological snow depth data or as derived from reanalyses contain large or unconstrained uncertainty, which result in large uncertainty in the derived sea ice thickness and volume. In this study, we explore the potential of combined retrieval of both sea ice thickness and snow depth using the concurrent active altimetry and passive microwave remote sensing of the sea ice cover. Specifically, laser altimetry and L-band passive remote sensing data are combined using two forward models: the L-band radiation model and the isostatic relationship based on buoyancy model. Since the laser altimetry usually features much higher spatial resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS) satellite, there is potentially covariability between the observed snow freeboard by altimetry and the retrieval target of snow depth on the spatial scale of altimetry samples. Statistically significant correlation is discovered based on high-resolution observations from Operation IceBridge (OIB), and with a nonlinear fitting the covariability is incorporated in the retrieval algorithm. By using fitting parameters derived from large-scale surveys, the retrievability is greatly improved compared with the retrieval that assumes flat snow cover (i.e., no covariability). Verifications with OIB data show good match between the observed and the retrieved parameters, including both sea ice thickness and snow depth. With detailed analysis, we show that the error of the retrieval mainly arises from the difference between the modeled and the observed (SMOS) L-band brightness temperature (TB). The narrow swath and the limited coverage of the sea ice cover by altimetry is the potential source of error associated with the modeling of L-band TB and retrieval. The proposed retrieval methodology can be applied to the basin-scale retrieval of sea ice thickness and snow depth, using concurrent passive remote sensing and active laser altimetry based on satellites such as ICESat-2 and WCOM.

Evaluation of MERIS products from Baltic Sea coastal waters rich in CDOM

NASA Astrophysics Data System (ADS)

Beltrán-Abaunza, J. M.; Kratzer, S.; Brockmann, C.

2013-11-01

In this study, retrievals of the medium resolution imaging spectrometer (MERIS) reflectances and water quality products using 4 different coastal processing algorithms freely available are assessed by comparison against sea-truthing data. The study is based on a pair-wise comparison using processor-dependent quality flags for the retrieval of valid common macro-pixels. This assessment is required in order to ensure the reliability of monitoring systems based on MERIS data, such as the Swedish coastal and lake monitoring system (http.vattenkvalitet.se). The results show that the pre-processing with the Improved Contrast between Ocean and Land (ICOL) processor, correcting for adjacency effects, improve the retrieval of spectral reflectance for all processors, Therefore, it is recommended that the ICOL processor should be applied when Baltic coastal waters are investigated. Chlorophyll was retrieved best using the FUB (Free University of Berlin) processing algorithm, although overestimations in the range 18-26.5%, dependent on the compared pairs, were obtained. At low chlorophyll concentrations (< 2.5 mg m-3), random errors dominated in the retrievals with the MEGS (MERIS ground segment processor) processor. The lowest bias and random errors were obtained with MEGS for suspended particulate matter, for which overestimations in te range of 8-16% were found. Only the FUB retrieved CDOM (Coloured Dissolved Organic Matter) correlate with in situ values. However, a large systematic underestimation appears in the estimates that nevertheless may be corrected for by using a~local correction factor. The MEGS has the potential to be used as an operational processing algorithm for the Himmerfjärden bay and adjacent areas, but it requires further improvement of the atmospheric correction for the blue bands and better definition at relatively low chlorophyll concentrations in presence of high CDOM attenuation.

Aerosol Retrievals from Proposed Satellite Bistatic Lidar Observations: Algorithm and Information Content

NASA Astrophysics Data System (ADS)

Alexandrov, M. D.; Mishchenko, M. I.

2017-12-01

Accurate aerosol retrievals from space remain quite challenging and typically involve solving a severely ill-posed inverse scattering problem. We suggested to address this ill-posedness by flying a bistatic lidar system. Such a system would consist of formation flying constellation of a primary satellite equipped with a conventional monostatic (backscattering) lidar and an additional platform hosting a receiver of the scattered laser light. If successfully implemented, this concept would combine the measurement capabilities of a passive multi-angle multi-spectral polarimeter with the vertical profiling capability of a lidar. Thus, bistatic lidar observations will be free of deficiencies affecting both monostatic lidar measurements (caused by the highly limited information content) and passive photopolarimetric measurements (caused by vertical integration and surface reflection).We present a preliminary aerosol retrieval algorithm for a bistatic lidar system consisting of a high spectral resolution lidar (HSRL) and an additional receiver flown in formation with it at a scattering angle of 165 degrees. This algorithm was applied to synthetic data generated using Mie-theory computations. The model/retrieval parameters in our tests were the effective radius and variance of the aerosol size distribution, complex refractive index of the particles, and their number concentration. Both mono- and bimodal aerosol mixtures were considered. Our algorithm allowed for definitive evaluation of error propagation from measurements to retrievals using a Monte Carlo technique, which involves random distortion of the observations and statistical characterization of the resulting retrieval errors. Our tests demonstrated that supplementing a conventional monostatic HSRL with an additional receiver dramatically increases the information content of the measurements and allows for a sufficiently accurate characterization of tropospheric aerosols.

Application of randomly oriented spheroids for retrieval of dust particle parameters from multiwavelength lidar measurements

NASA Astrophysics Data System (ADS)

Veselovskii, I.; Dubovik, O.; Kolgotin, A.; Lapyonok, T.; di Girolamo, P.; Summa, D.; Whiteman, D. N.; Mishchenko, M.; Tanré, D.

2010-11-01

Multiwavelength (MW) Raman lidars have demonstrated their potential to profile particle parameters; however, until now, the physical models used in retrieval algorithms for processing MW lidar data have been predominantly based on the Mie theory. This approach is applicable to the modeling of light scattering by spherically symmetric particles only and does not adequately reproduce the scattering by generally nonspherical desert dust particles. Here we present an algorithm based on a model of randomly oriented spheroids for the inversion of multiwavelength lidar data. The aerosols are modeled as a mixture of two aerosol components: one composed only of spherical and the second composed of nonspherical particles. The nonspherical component is an ensemble of randomly oriented spheroids with size-independent shape distribution. This approach has been integrated into an algorithm retrieving aerosol properties from the observations with a Raman lidar based on a tripled Nd:YAG laser. Such a lidar provides three backscattering coefficients, two extinction coefficients, and the particle depolarization ratio at a single or multiple wavelengths. Simulations were performed for a bimodal particle size distribution typical of desert dust particles. The uncertainty of the retrieved particle surface, volume concentration, and effective radius for 10% measurement errors is estimated to be below 30%. We show that if the effect of particle nonsphericity is not accounted for, the errors in the retrieved aerosol parameters increase notably. The algorithm was tested with experimental data from a Saharan dust outbreak episode, measured with the BASIL multiwavelength Raman lidar in August 2007. The vertical profiles of particle parameters as well as the particle size distributions at different heights were retrieved. It was shown that the algorithm developed provided substantially reasonable results consistent with the available independent information about the observed aerosol event.

Digital filtering of plume emission spectra

NASA Technical Reports Server (NTRS)

Madzsar, George C.

1990-01-01

Fourier transformation and digital filtering techniques were used to separate the superpositioned spectral phenomena observed in the exhaust plumes of liquid propellant rocket engines. Space shuttle main engine (SSME) spectral data were used to show that extraction of spectral lines in the spatial frequency domain does not introduce error, and extraction of the background continuum introduces only minimal error. Error introduced during band extraction could not be quantified due to poor spectrometer resolution. Based on the atomic and molecular species found in the SSME plume, it was determined that spectrometer resolution must be 0.03 nm for SSME plume spectral monitoring.

Dissociating the two faces of selective memory retrieval.

PubMed

Dobler, Ina M; Bäuml, Karl-Heinz T

2012-07-01

Research in the past four decades has repeatedly shown that selective retrieval of some (non-target) memories can impair subsequent retrieval of other (target) information, a finding known as retrieval-induced forgetting. More recently, however, there is evidence that selective retrieval can both impair and enhance recall of related memories (K-H. T. Bäuml & Samenieh, 2010). To identify possible experimental dissociations between the detrimental and the beneficial effects of memory retrieval, we examined retrieval dynamics in listwise directed forgetting, varying the delay between preceding non-target and subsequent target recall. When target recall immediately followed non-target recall, we replicated the prior work and found detrimental effects of memory retrieval on to-be-remembered items but beneficial effects on to-be-forgotten items. In contrast, when a delay was introduced between non-target and target recall, the detrimental effects were present but the beneficial effects were absent. The results demonstrate a first experimental dissociation between the two effects of memory retrieval. They are consistent with a recent two-factor account of the two faces of selective memory retrieval.

Learning binary code via PCA of angle projection for image retrieval

NASA Astrophysics Data System (ADS)

Yang, Fumeng; Ye, Zhiqiang; Wei, Xueqi; Wu, Congzhong

2018-01-01

With benefits of low storage costs and high query speeds, binary code representation methods are widely researched for efficiently retrieving large-scale data. In image hashing method, learning hashing function to embed highdimensions feature to Hamming space is a key step for accuracy retrieval. Principal component analysis (PCA) technical is widely used in compact hashing methods, and most these hashing methods adopt PCA projection functions to project the original data into several dimensions of real values, and then each of these projected dimensions is quantized into one bit by thresholding. The variances of different projected dimensions are different, and with real-valued projection produced more quantization error. To avoid the real-valued projection with large quantization error, in this paper we proposed to use Cosine similarity projection for each dimensions, the angle projection can keep the original structure and more compact with the Cosine-valued. We used our method combined the ITQ hashing algorithm, and the extensive experiments on the public CIFAR-10 and Caltech-256 datasets validate the effectiveness of the proposed method.

Embedding intensity image into a binary hologram with strong noise resistant capability

NASA Astrophysics Data System (ADS)

Zhuang, Zhaoyong; Jiao, Shuming; Zou, Wenbin; Li, Xia

2017-11-01

A digital hologram can be employed as a host image for image watermarking applications to protect information security. Past research demonstrates that a gray level intensity image can be embedded into a binary Fresnel hologram by error diffusion method or bit truncation coding method. However, the fidelity of the retrieved watermark image from binary hologram is generally not satisfactory, especially when the binary hologram is contaminated with noise. To address this problem, we propose a JPEG-BCH encoding method in this paper. First, we employ the JPEG standard to compress the intensity image into a binary bit stream. Next, we encode the binary bit stream with BCH code to obtain error correction capability. Finally, the JPEG-BCH code is embedded into the binary hologram. By this way, the intensity image can be retrieved with high fidelity by a BCH-JPEG decoder even if the binary hologram suffers from serious noise contamination. Numerical simulation results show that the image quality of retrieved intensity image with our proposed method is superior to the state-of-the-art work reported.

The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm: theoretical basis

NASA Astrophysics Data System (ADS)

Loughman, Robert; Bhartia, Pawan K.; Chen, Zhong; Xu, Philippe; Nyaku, Ernest; Taha, Ghassan

2018-05-01

The theoretical basis of the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm is presented. The algorithm uses an assumed bimodal lognormal aerosol size distribution to retrieve aerosol extinction profiles at 675 nm from OMPS LP radiance measurements. A first-guess aerosol extinction profile is updated by iteration using the Chahine nonlinear relaxation method, based on comparisons between the measured radiance profile at 675 nm and the radiance profile calculated by the Gauss-Seidel limb-scattering (GSLS) radiative transfer model for a spherical-shell atmosphere. This algorithm is discussed in the context of previous limb-scattering aerosol extinction retrieval algorithms, and the most significant error sources are enumerated. The retrieval algorithm is limited primarily by uncertainty about the aerosol phase function. Horizontal variations in aerosol extinction, which violate the spherical-shell atmosphere assumed in the version 1 algorithm, may also limit the quality of the retrieved aerosol extinction profiles significantly.

On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar

PubMed Central

Verhoest, Niko E.C; Lievens, Hans; Wagner, Wolfgang; Álvarez-Mozos, Jesús; Moran, M. Susan; Mattia, Francesco

2008-01-01

Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale. PMID:27879932

Using Ground-Based Measurements and Retrievals to Validate Satellite Data

NASA Technical Reports Server (NTRS)

Dong, Xiquan

2002-01-01

The proposed research is to use the DOE ARM ground-based measurements and retrievals as the ground-truth references for validating satellite cloud results and retrieving algorithms. This validation effort includes four different ways: (1) cloud properties on different satellites, therefore different sensors, TRMM VIRS and TERRA MODIS; (2) cloud properties at different climatic regions, such as DOE ARM SGP, NSA, and TWP sites; (3) different cloud types, low and high level cloud properties; and (4) day and night retrieving algorithms. Validation of satellite-retrieved cloud properties is very difficult and a long-term effort because of significant spatial and temporal differences between the surface and satellite observing platforms. The ground-based measurements and retrievals, only carefully analyzed and validated, can provide a baseline for estimating errors in the satellite products. Even though the validation effort is so difficult, a significant progress has been made during the proposed study period, and the major accomplishments are summarized in the follow.

The absolute radiometric calibration of the advanced very high resolution radiometer

NASA Technical Reports Server (NTRS)

Slater, P. N.; Teillet, P. M.; Ding, Y.

1988-01-01

The need for independent, redundant absolute radiometric calibration methods is discussed with reference to the Thematic Mapper. Uncertainty requirements for absolute calibration of between 0.5 and 4 percent are defined based on the accuracy of reflectance retrievals at an agricultural site. It is shown that even very approximate atmospheric corrections can reduce the error in reflectance retrieval to 0.02 over the reflectance range 0 to 0.4.

An introduction to the theory of ptychographic phase retrieval methods

NASA Astrophysics Data System (ADS)

Konijnenberg, Sander

2017-12-01

An overview of several ptychographic phase retrieval methods and the theory behind them is presented. By looking into the theory behind more basic single-intensity pattern phase retrieval methods, a theoretical framework is provided for analyzing ptychographic algorithms. Extensions of ptychographic algorithms that deal with issues such as partial coherence, thick samples, or uncertainties of the probe or probe positions are also discussed. This introduction is intended for scientists and students without prior experience in the field of phase retrieval or ptychography to quickly get introduced to the theory, so that they can put the more specialized literature in context more easily.

[Study on the effect of solar spectra on the retrieval of atmospheric CO2 concentration using high resolution absorption spectra].

PubMed

Hu, Zhen-Hua; Huang, Teng; Wang, Ying-Ping; Ding, Lei; Zheng, Hai-Yang; Fang, Li

2011-06-01

Taking solar source as radiation in the near-infrared high-resolution absorption spectrum is widely used in remote sensing of atmospheric parameters. The present paper will take retrieval of the concentration of CO2 for example, and study the effect of solar spectra resolution. Retrieving concentrations of CO2 by using high resolution absorption spectra, a method which uses the program provided by AER to calculate the solar spectra at the top of atmosphere as radiation and combine with the HRATS (high resolution atmospheric transmission simulation) to simulate retrieving concentration of CO2. Numerical simulation shows that the accuracy of solar spectrum is important to retrieval, especially in the hyper-resolution spectral retrieavl, and the error of retrieval concentration has poor linear relation with the resolution of observation, but there is a tendency that the decrease in the resolution requires low resolution of solar spectrum. In order to retrieve the concentration of CO2 of atmosphere, the authors' should take full advantage of high-resolution solar spectrum at the top of atmosphere.

Aerosol Retrievals over the Ocean using Channel 1 and 2 AVHRR Data: A Sensitivity Analysis and Preliminary Results

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.; Lacis, Andrew A.

1999-01-01

This paper outlines the methodology of interpreting channel 1 and 2 AVHRR radiance data over the oceans and describes a detailed analysis of the sensitivity of monthly averages of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. The analysis is based on using real AVHRR data and exploiting accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. We show that two-channel algorithms can be expected to provide significantly more accurate and less biased retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening and calibration uncertainties are by far the largest sources of errors in the retrieved aerosol parameters. Both underestimating and overestimating aerosol absorption as well as the potentially strong variability of the real part of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.

Optimal estimation for global ground-level fine particulate matter concentrations

NASA Astrophysics Data System (ADS)

Donkelaar, Aaron; Martin, Randall V.; Spurr, Robert J. D.; Drury, Easan; Remer, Lorraine A.; Levy, Robert C.; Wang, Jun

2013-06-01

We develop an optimal estimation (OE) algorithm based on top-of-atmosphere reflectances observed by the MODIS satellite instrument to retrieve near-surface fine particulate matter (PM2.5). The GEOS-Chem chemical transport model is used to provide prior information for the Aerosol Optical Depth (AOD) retrieval and to relate total column AOD to PM2.5. We adjust the shape of the GEOS-Chem relative vertical extinction profiles by comparison with lidar retrievals from the CALIOP satellite instrument. Surface reflectance relationships used in the OE algorithm are indexed by land type. Error quantities needed for this OE algorithm are inferred by comparison with AOD observations taken by a worldwide network of sun photometers (AERONET) and extended globally based upon aerosol speciation and cross correlation for simulated values, and upon land type for observational values. Significant agreement in PM2.5 is found over North America for 2005 (slope = 0.89; r = 0.82; 1-σ error = 1 µg/m3 + 27%), with improved coverage and correlation relative to previous work for the same region and time period, although certain subregions, such as the San Joaquin Valley of California are better represented by previous estimates. Independently derived error estimates of the OE PM2.5 values at in situ locations over North America (of ±(2.5 µg/m3 + 31%) and Europe of ±(3.5 µg/m3 + 30%) are corroborated by comparison with in situ observations, although globally (error estimates of ±(3.0 µg/m3 + 35%), may be underestimated. Global population-weighted PM2.5 at 50% relative humidity is estimated as 27.8 µg/m3 at 0.1° × 0.1° resolution.

Suomi NPP VIIRS solar diffuser screen transmittance model and its applications.

PubMed

Lei, Ning; Xiong, Xiaoxiong; Mcintire, Jeff

2017-11-01

The visible infrared imaging radiometer suite on the Suomi National Polar-orbiting Partnership satellite calibrates its reflective solar bands through observations of a sunlit solar diffuser (SD) panel. Sunlight passes through a perforated plate, referred to as the SD screen, before reaching the SD. It is critical to know whether the SD screen transmittance measured prelaunch is accurate. Several factors such as misalignments of the SD panel and the measurement apparatus could lead to errors in the measured transmittance and thus adversely impact on-orbit calibration quality through the SD. We develop a mathematical model to describe the transmittance as a function of the angles that incident light makes with the SD screen, and apply the model to fit the prelaunch measured transmittance. The results reveal that the model does not reproduce the measured transmittance unless the size of the apertures in the SD screen is quite different from the design value. We attribute the difference to the orientation alignment errors for the SD panel and the measurement apparatus. We model the alignment errors and apply our transmittance model to fit the prelaunch transmittance to retrieve the "true" transmittance. To use this model correctly, we also examine the finite source size effect on the transmittance. Furthermore, we compare the product of the retrieved "true" transmittance and the prelaunch SD bidirectional reflectance distribution function (BRDF) value to the value derived from on-orbit data to determine whether the prelaunch SD BRDF value is relatively accurate. The model is significant in that it can evaluate whether the SD screen transmittance measured prelaunch is accurate and help retrieve the true transmittance from the transmittance with measurement errors, consequently resulting in a more accurate sensor data product by the same amount.

Error analyses of JEM/SMILES standard products on L2 operational system

NASA Astrophysics Data System (ADS)

Mitsuda, C.; Takahashi, C.; Suzuki, M.; Hayashi, H.; Imai, K.; Sano, T.; Takayanagi, M.; Iwata, Y.; Taniguchi, H.

2009-12-01

SMILES (Superconducting Submillimeter-wave Limb-Emission Sounder) , which has been developed by Japan Aerospace Exploration Agency (JAXA) and National Institute of Information and Communications Technology (NICT), is planned to be launched in September, 2009 and will be on board the Japanese Experiment Module (JEM) of the International Space Station (ISS). The SMILES measures the atmospheric limb emission from stratospheric minor constituents in 640 GHz band. Target species on L2 operational system are O3, ClO, HCl, HNO3, HOCl, CH3CN, HO2, BrO, and O3 isotopes (18OOO, 17OOO and O17OO). The SMILES carries 4 K cooled Superconductor-Insulator-Superconductor mixers to carry out high-sensitivity observations. In sub-millimeter band, water vapor absorption is an important factor to decide the tropospheric and stratospheric brightness temperature. The uncertainty of water vapor absorption influences the accuracy of molecular vertical profiles. Since the SMILES bands are narrow and far from H2O lines, it is a good approximation to assume this uncertainly as linear function of frequency. We include 0th and 1st coefficients of ‘baseline’ function, not water vapor profile, in state vector and retrieve them to remove influence of the water vapor uncertainty. We performed retrieval simulations using spectra computed by L2 operatinal forward model for various H2O conditions (-/+ 5, 10% difference between true profile and a priori profile in the stratosphere and -/+ 10, 20% one in the troposphere). The results show that the incremental errors of molecules are smaller than 10% of measurements errors when height correlation of baseline coefficients and temperature are assumed to be 10 km. In conclusion, the retrieval of the baseline coefficients effectively suppresses profile error due to bias of water vapor profile.

Information storage medium and method of recording and retrieving information thereon

DOEpatents

Marchant, D. D.; Begej, Stefan

1986-01-01

Information storage medium comprising a semiconductor doped with first and second impurities or dopants. Preferably, one of the impurities is introduced by ion implantation. Conductive electrodes are photolithographically formed on the surface of the medium. Information is recorded on the medium by selectively applying a focused laser beam to discrete regions of the medium surface so as to anneal discrete regions of the medium containing lattice defects introduced by the ion-implanted impurity. Information is retrieved from the storage medium by applying a focused laser beam to annealed and non-annealed regions so as to produce a photovoltaic signal at each region.

Simultaneous Retrieval of Effective Refractive Index and Density from Size Distribution and Light Scattering Data: Weakly-Absorbing Aerosol

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kassianov, Evgueni I.; Barnard, James C.; Pekour, Mikhail S.

2014-10-01

We propose here a novel approach for retrieving in parallel the effective density and real refractive index of weakly absorbing aerosol from optical and size distribution measurements. Here we define “weakly absorbing” as aerosol single-scattering albedos that exceed 0.95 at 0.5 um.The required optical measurements are the scattering coefficient and the hemispheric backscatter fraction, obtained in this work from an integrating nephelometer. The required size spectra come from a Scanning Mobility Particle Sizer and an Aerodynamic Particle Sizer. The performance of this approach is first evaluated using a sensitivity study with synthetically generated but measurement-related inputs. The sensitivity study revealsmore » that the proposed approach is robust to random noise; additionally the uncertainties of the retrieval are almost linearly proportional to the measurement errors, and these uncertainties are smaller for the real refractive index than for the effective density. Next, actual measurements are used to evaluate our approach. These measurements include the optical, microphysical, and chemical properties of weakly absorbing aerosol which are representative of a variety of coastal summertime conditions observed during the Two-Column Aerosol Project (TCAP; http://campaign.arm.gov/tcap/). The evaluation includes calculating the root mean square error (RMSE) between the aerosol characteristics retrieved by our approach, and the same quantities calculated using the conventional volume mixing rule for chemical constituents. For dry conditions (defined in this work as relative humidity less than 55%) and sub-micron particles, a very good (RMSE~3%) and reasonable (RMSE~28%) agreement is obtained for the retrieved real refractive index (1.49±0.02) and effective density (1.68±0.21), respectively. Our approach permits discrimination between the retrieved aerosol characteristics of sub-micron and sub-10micron particles. The evaluation results also reveal that the retrieved density and refractive index tend to decrease with an increase of the relative humidity.« less

Recursive Construction of Noiseless Subsystem for Qudits

NASA Astrophysics Data System (ADS)

Güngördü, Utkan; Li, Chi-Kwong; Nakahara, Mikio; Poon, Yiu-Tung; Sze, Nung-Sing

2014-03-01

When the environmental noise acting on the system has certain symmetries, a subsystem of the total system can avoid errors. Encoding information into such a subsystem is advantageous since it does not require any error syndrome measurements, which may introduce further errors to the system. However, utilizing such a subsystem for large systems gets impractical with the increasing number of qudits. A recursive scheme offers a solution to this problem. Here, we review the recursive construct introduced in, which can asymptotically protect 1/d of the qudits in system against collective errors.

Contextual Cues Aid Recovery from Interruption: The Role of Associative Activation

ERIC Educational Resources Information Center

Hodgetts, Helen M.; Jones, Dylan M.

2006-01-01

A series of experiments introduced interruptions to the execution phase of simple Tower of London problems and found that the opportunity for preparation before the break in task reduced the time cost at resumption. Retrieval of the suspended goal was facilitated when participants were given the opportunity to encode retrieval cues during an…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dall'Arno, Michele; ICFO-Institut de Ciencies Fotoniques, E-08860 Castelldefels; Quit Group, Dipartimento di Fisica, via Bassi 6, I-27100 Pavia

We address the problem of quantum reading of optical memories, namely the retrieving of classical information stored in the optical properties of a media with minimum energy. We present optimal strategies for ambiguous and unambiguous quantum reading of unitary optical memories, namely when one's task is to minimize the probability of errors in the retrieved information and when perfect retrieving of information is achieved probabilistically, respectively. A comparison of the optimal strategy with coherent probes and homodyne detection shows that the former saves orders of magnitude of energy when achieving the same performances. Experimental proposals for quantum reading which aremore » feasible with present quantum optical technology are reported.« less

Estimation of liquid water cloud height and fraction using simulated AMSU-A and MHS data. [Advanced Microwave Sounding Unit and Microwave Humidity Sounder

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Diak, George R.

1992-01-01

The rms retrieval errors in cloud top pressure for fully overcast conditions over both land and water surfaces are shown for AMSU-A oxygen channel pair 3 and 5 and MHS water vapor channel pair 4 and 5. For both pairs, the decrease of retrieval skill from high cloud is evident for almost all liquid water contents. For high cloud and medium cloud, the water vapor pair outperforms the oxygen pair. Retrieval accuracy is the best for high and middle clouds and degrades as the cloud top is lower in the atmosphere.

Retrieval of Ice Cloud Properties Using Variable Phase Functions

NASA Astrophysics Data System (ADS)

Heck, Patrick W.; Minnis, Patrick; Yang, Ping; Chang, Fu-Lung; Palikonda, Rabindra; Arduini, Robert F.; Sun-Mack, Sunny

2009-03-01

An enhancement to NASA Langley's Visible Infrared Solar-infrared Split-window Technique (VISST) is developed to identify and account for situations when errors are induced by using smooth ice crystals. The retrieval scheme incorporates new ice cloud phase functions that utilize hexagonal crystals with roughened surfaces. In some situations, cloud optical depths are reduced, hence, cloud height is increased. Cloud effective particle size also changes with the roughened ice crystal models which results in varied effects on the calculation of ice water path. Once validated and expanded, the new approach will be integrated in the CERES MODIS algorithm and real-time retrievals at Langley.

Phase retrieval using regularization method in intensity correlation imaging

NASA Astrophysics Data System (ADS)

Li, Xiyu; Gao, Xin; Tang, Jia; Lu, Changming; Wang, Jianli; Wang, Bin

2014-11-01

Intensity correlation imaging(ICI) method can obtain high resolution image with ground-based low precision mirrors, in the imaging process, phase retrieval algorithm should be used to reconstituted the object's image. But the algorithm now used(such as hybrid input-output algorithm) is sensitive to noise and easy to stagnate. However the signal-to-noise ratio of intensity interferometry is low especially in imaging astronomical objects. In this paper, we build the mathematical model of phase retrieval and simplified it into a constrained optimization problem of a multi-dimensional function. New error function was designed by noise distribution and prior information using regularization method. The simulation results show that the regularization method can improve the performance of phase retrieval algorithm and get better image especially in low SNR condition

Evaluation of Satellite and Model Precipitation Products Over Turkey

NASA Astrophysics Data System (ADS)

Yilmaz, M. T.; Amjad, M.

2017-12-01

Satellite-based remote sensing, gauge stations, and models are the three major platforms to acquire precipitation dataset. Among them satellites and models have the advantage of retrieving spatially and temporally continuous and consistent datasets, while the uncertainty estimates of these retrievals are often required for many hydrological studies to understand the source and the magnitude of the uncertainty in hydrological response parameters. In this study, satellite and model precipitation data products are validated over various temporal scales (daily, 3-daily, 7-daily, 10-daily and monthly) using in-situ measured precipitation observations from a network of 733 gauges from all over the Turkey. Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 version 7 and European Center of Medium-Range Weather Forecast (ECMWF) model estimates (daily, 3-daily, 7-daily and 10-daily accumulated forecast) are used in this study. Retrievals are evaluated for their mean and standard deviation and their accuracies are evaluated via bias, root mean square error, error standard deviation and correlation coefficient statistics. Intensity vs frequency analysis and some contingency table statistics like percent correct, probability of detection, false alarm ratio and critical success index are determined using daily time-series. Both ECMWF forecasts and TRMM observations, on average, overestimate the precipitation compared to gauge estimates; wet biases are 10.26 mm/month and 8.65 mm/month, respectively for ECMWF and TRMM. RMSE values of ECMWF forecasts and TRMM estimates are 39.69 mm/month and 41.55 mm/month, respectively. Monthly correlations between Gauges-ECMWF, Gauges-TRMM and ECMWF-TRMM are 0.76, 0.73 and 0.81, respectively. The model and the satellite error statistics are further compared against the gauges error statistics based on inverse distance weighting (IWD) analysis. Both the model and satellite data have less IWD errors (14.72 mm/month and 10.75 mm/month, respectively) compared to gauges IWD error (21.58 mm/month). These results show that, on average, ECMWF forecast data have higher skill than TRMM observations. Overall, both ECMWF forecast data and TRMM observations show good potential for catchment scale hydrological analysis.

On the Balancing of the SMOS Ocean Salinity Retrieval Cost Function

NASA Astrophysics Data System (ADS)

Sabia, R.; Camps, A.; Portabella, M.; Talone, M.; Ballabrera, J.; Gourrion, J.; Gabarró, C.; Aretxabaleta, A. L.; Font, J.

2009-04-01

The Soil Moisture and Ocean Salinity (SMOS) mission will be launched in mid 2009 to provide synoptic sea surface salinity (SSS) measurements with good temporal resolution [1]. To obtain a proper estimation of the SSS fields derived from the multi-angular brightness temperatures (TB) measured by the Microwave Interferometric Radiometer by Aperture Synthesis (MIRAS) sensor, a comprehensive inversion procedure has been defined [2]. Nevertheless, several salinity retrieval issues remain critical, namely: 1) Scene-dependent bias in the simulated TBs, 2) L-band forward geophysical model function definition, 3) Auxiliary data uncertainties, 4) Constraints in the cost function (inversion), especially in salinity term, and 5) Adequate spatio-temporal averaging. These issues will have to be properly addressed in order to meet the proposed accuracy requirement of the mission: a demanding 0.1 psu (practical salinity units) after averaging in a 30-day and 2°x2° spatio-temporal boxes. The salinity retrieval cost function minimizes the difference between the multi-angular measured SMOS TBs (yet simulated, so far) and the modeled TBs, weighted by the corresponding radiometric noise of the measurements. Furthermore, due to the fact that the minimization problem is both non-linear and ill-posed, background reference terms are needed to nudge the solution and ensuring convergence at the same time [3]. Constraining terms in SSS, sea surface temperature (SST) and wind speed are considered with their respective uncertainties. Moreover, whether SSS constraints have to be included or not as part of the retrieval procedure is still a matter of debate. On one hand, neglecting background reference information on SSS might prevent from retrieving salinity with the prescribed accuracy or at least within reasonable error. Conversely, including constraints in SSS, relying for instance on the climatology, may force the retrieved value to be too close to the reference prior values, thus producing spurious retrievals. In [4] it has been studied the impact of the different auxiliary salinity uncertainties in the accuracy of the retrieval. It has been shown that using physically-consistent salinity field uncertainties of the order of less than 0.5 psu (either as the standard deviation of the considered SSS field or as the standard deviation of the misfit between the original and the auxiliary SSS field) the SSS term turns out to be too constraining. A half-way solution could be envisaged by using empirical weights (regularization factors) which could smooth the overall influence of the SSS term still using the auxiliary fields with their corresponding physically-sounded uncertainties. This operation should be performed for the SST and wind speed term as well. The need for a comprehensive balancing of the different terms included in the cost function is also stressed by recent studies [5], which point out that the even the observational term (TBs) will need to be properly weighted by an effective ratio, taking into account the specific correlation patterns existing in the MIRAS measurements. Simulated data using the SMOS End-to-end Processor Simulator (SEPS), in its full-mode, including the measured antenna patterns for each antenna and all the instrument errors, are used in this study. The salinity retrieval process and the SSS maps (for each satellite overpass) are performed with UPC SMOS-Level 2 Processor Simulator (SMOS-L2PS). The relative weight for each of the terms included in the cost function (observational and background terms) is assessed in different cost function configurations. Regularization factors are introduced to ensure that SMOS information content is fully exploited. Preliminary results on the cost function balancing will be shown at the conference. References [1] Font, J., G. Lagerloef, D. Le Vine, A. Camps, and O.Z. Zanife, The Determination of Surface Salinity with the European SMOS Space Mission, IEEE Trans. Geosci. Remote Sens., 42 (10), 2196-2205, 2004. [2] Zine, S., J. Boutin, J. Font, N. Reul, P. Waldteufel, C. Gabarró, J. Tenerelli, F. Petitcolin, J.L. Vergely, M. Talone, and S. Delwart, Overview of the SMOS Sea Surface Salinity Prototype Processor, IEEE Trans. Geosc. Remote Sens, 46 (3), 621-645, 2008. [3] Gabarró, C., M. Portabella, M. Talone and J. Font, Analysis of the SMOS Ocean Salinity Inversion Algorithm, Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), Barcelona, Spain, 971-974, 2007. [4] Sabia, R, Sea Surface Salinity Retrieval Error Budget within the ESA Soil Moisture and Ocean Salinity Mission, Ph.D. Dissertation, Barcelona, Spain, October 2008. [5] Talone, M., A. Camps, C. Gabarró, R. Sabia, J. Gourrion, M. Vall•llossera, B. Mourre, and J. Font, Contributions to the Improvement of the SMOS Level 2 Retrieval Algorithm: Optimization of the Cost Function, Proceedings of the International Geoscience and Remote Sensing Symposium (IGARSS), Boston, Massachusetts USA, 2008.

Use of In Situ and Airborne Multiangle Data to Assess MODIS- and Landsat-based Estimates of Surface Albedo

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Shuai, Yanmin; Wang, Zhuosen; Gao, Feng; Masek, Jeff; Schaaf, Crystal B.

2012-01-01

The quantification of uncertainty of global surface albedo data and products is a critical part of producing complete, physically consistent, and decadal land property data records for studying ecosystem change. A current challenge in validating satellite retrievals of surface albedo is the ability to overcome the spatial scaling errors that can contribute on the order of 20% disagreement between satellite and field-measured values. Here, we present the results from an uncertain ty analysis of MODerate Resolution Imaging Spectroradiometer (MODIS) and Landsat albedo retrievals, based on collocated comparisons with tower and airborne multi-angular measurements collected at the Atmospheric Radiation Measurement Program s (ARM) Cloud and Radiation Testbed (CART) site during the 2007 Cloud and Land Surface Interaction Campaign (CLAS33 IC 07). Using standard error propagation techniques, airborne measurements obtained by NASA s Cloud Absorption Radiometer (CAR) were used to quantify the uncertainties associated with MODIS and Landsat albedos across a broad range of mixed vegetation and structural types. Initial focus was on evaluating inter-sensor consistency through assessments of temporal stability, as well as examining the overall performance of satellite-derived albedos obtained at all diurnal solar zenith angles. In general, the accuracy of the MODIS and Landsat albedos remained under a 10% margin of error in the SW(0.3 - 5.0 m) domain. However, results reveal a high degree of variability in the RMSE (root mean square error) and bias of albedos in both the visible (0.3 - 0.7 m) and near-infrared (0.3 - 5.0 m) broadband channels; where, in some cases, retrieval uncertainties were found to be in excess of 20%. For the period of CLASIC 07, the primary factors that contributed to uncertainties in the satellite-derived albedo values include: (1) the assumption of temporal stability in the retrieval of 500 m MODIS BRDF values over extended periods of cloud-contaminated observations; and (2) the assumption of spatial 45 and structural uniformity at the Landsat (30 m) pixel scale.

Cirrus cloud retrieval from MSG/SEVIRI during day and night using artificial neural networks

NASA Astrophysics Data System (ADS)

Strandgren, Johan; Bugliaro, Luca

2017-04-01

By covering a large part of the Earth, cirrus clouds play an important role in climate as they reflect incoming solar radiation and absorb outgoing thermal radiation. Nevertheless, the cirrus clouds remain one of the largest uncertainties in atmospheric research and the understanding of the physical processes that govern their life cycle is still poorly understood, as is their representation in climate models. To monitor and better understand the properties and physical processes of cirrus clouds, it's essential that those tenuous clouds can be observed from geostationary spaceborne imagers like SEVIRI (Spinning Enhanced Visible and InfraRed Imager), that possess a high temporal resolution together with a large field of view and play an important role besides in-situ observations for the investigation of cirrus cloud processes. CiPS (Cirrus Properties from Seviri) is a new algorithm targeting thin cirrus clouds. CiPS is an artificial neural network trained with coincident SEVIRI and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations in order to retrieve a cirrus cloud mask along with the cloud top height (CTH), ice optical thickness (IOT) and ice water path (IWP) from SEVIRI. By utilizing only the thermal/IR channels of SEVIRI, CiPS can be used during day and night making it a powerful tool for the cirrus life cycle analysis. Despite the great challenge of detecting thin cirrus clouds and retrieving their properties from a geostationary imager using only the thermal/IR wavelengths, CiPS performs well. Among the cirrus clouds detected by CALIOP, CiPS detects 70 and 95 % of the clouds with an optical thickness of 0.1 and 1.0 respectively. Among the cirrus free pixels, CiPS classify 96 % correctly. For the CTH retrieval, CiPS has a mean absolute percentage error of 10 % or less with respect to CALIOP for cirrus clouds with a CTH greater than 8 km. For the IOT retrieval, CiPS has a mean absolute percentage error of 100 % or less with respect to CALIOP for cirrus clouds with an optical thickness down to 0.07. For such thin cirrus clouds an error of 100 % should be regarded as low from a geostationary imager like SEVIRI. The IWP retrieved by CiPS shows a similar performance, but has larger deviations for the thinner cirrus clouds.

Financial model calibration using consistency hints.

PubMed

Abu-Mostafa, Y S

2001-01-01

We introduce a technique for forcing the calibration of a financial model to produce valid parameters. The technique is based on learning from hints. It converts simple curve fitting into genuine calibration, where broad conclusions can be inferred from parameter values. The technique augments the error function of curve fitting with consistency hint error functions based on the Kullback-Leibler distance. We introduce an efficient EM-type optimization algorithm tailored to this technique. We also introduce other consistency hints, and balance their weights using canonical errors. We calibrate the correlated multifactor Vasicek model of interest rates, and apply it successfully to Japanese Yen swaps market and US dollar yield market.

Smoke Over Haze: Comparative Analysis of Satellite, Surface Radiometer and Airborne In-Situ Measurements of Aerosol Optical Properties and Radiative Forcing Over the Eastern US

NASA Astrophysics Data System (ADS)

vant-Hull, B.; Li, Z.; Taubman, B.; Marufu, L.; Levy, R.; Chang, F.; Doddridge, B.; Dickerson, R.

2004-12-01

In July 2002 Canadian forest fires produced a major smoke episode that blanketed the U.S. East Coast. Properties of the smoke aerosol were measured in-situ from aircraft, complementing operational AERONET and MODIS remote sensed aerosol retrievals. This study compares single scattering albedo and phase function derived from the in-situ measurements and AERONET retrievals in order to evaluate their consistency for application to satellite retrievals of optical depth and radiative forcing. These optical properties were combined with MODIS reflectance observations to calculate optical depth. The use of AERONET optical properties yielded optical depths 2% to 16% lower than those directly measured by AERONET. The use of in-situ derived optical properties resulted in optical depths 22% to 43% higher than AERONET measurements. These higher optical depths are attributed primarily to the higher absorption measured in-situ, which is roughly twice that retrieved by AERONET. The resulting satellite retrieved optical depths were in turn used to calculate integrated radiative forcing at both the surface and TOA. Comparisons to surface (SurfRad and ISIS) and to satellite (CERES) broadband radiometer measurements demonstrate that the use of optical properties derived from the aircraft measurements provided a better broadband forcing estimate (21% error) than those derived from AERONET (33% error). Thus AERONET derived optical properties produced better fits to optical depth measurements, while in-situ properties resulted in better fits to forcing measurements. These apparent inconsistencies underline the significant challenges facing the aerosol community in achieving column closure between narrow and broadband measurements and calculations.

Accuracy of Geophysical Parameters Derived from AIRS/AMSU as a Function of Fractional Cloud Cover

NASA Technical Reports Server (NTRS)

Susskind, Joel; Barnet, Chris; Blaisdell, John; Iredell, Lena; Keita, Fricky; Kouvaris, Lou; Molnar, Gyula; Chahine, Moustafa

2005-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. HSB failed in February 2005, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC in April 2005 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm.

Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

NASA Technical Reports Server (NTRS)

Ghan, Stephen J.; Rissman, Tracey A.; Ellman, Robert; Ferrare, Richard A.; Turner, David; Flynn, Connor; Wang, Jian; Ogren, John; Hudson, James; Jonsson, Haflidi H.;

Determination of wavefront structure for a Hartmann wavefront sensor using a phase-retrieval method.

PubMed

Polo, A; Kutchoukov, V; Bociort, F; Pereira, S F; Urbach, H P

2012-03-26

We apply a phase retrieval algorithm to the intensity pattern of a Hartmann wavefront sensor to measure with enhanced accuracy the phase structure of a Hartmann hole array. It is shown that the rms wavefront error achieved by phase reconstruction is one order of magnitude smaller than the one obtained from a typical centroid algorithm. Experimental results are consistent with a phase measurement performed independently using a Shack-Hartmann wavefront sensor.

Microcomputer system for receiving and processing of satellite TOVS/TIP data for vertical sounding of the atmosphere

NASA Astrophysics Data System (ADS)

Baranski, L. A.; Rozemski, K.

TOVS/TIP digital data transmitted at the VHF-BEACON range from NOAA satellites are receiving and processing at the SDRPC. Receiving station is connected with the microcomputer IBM-PC/AT which process TOVS/TIP data via two states: initial data processing and retrieval of vertical profiles of the temperature, water vapour and ozone mixing ratio in the atmosphere. Receiving and processing equipment, retrieval methods, results and error discussion are presented.

Modeling uncertainties for tropospheric nitrogen dioxide columns affecting satellite-based inverse modeling of nitrogen oxides emissions

NASA Astrophysics Data System (ADS)

Lin, J.-T.; Liu, Z.; Zhang, Q.; Liu, H.; Mao, J.; Zhuang, G.

2012-12-01

Errors in chemical transport models (CTMs) interpreting the relation between space-retrieved tropospheric column densities of nitrogen dioxide (NO2) and emissions of nitrogen oxides (NOx) have important consequences on the inverse modeling. They are however difficult to quantify due to lack of adequate in situ measurements, particularly over China and other developing countries. This study proposes an alternate approach for model evaluation over East China, by analyzing the sensitivity of modeled NO2 columns to errors in meteorological and chemical parameters/processes important to the nitrogen abundance. As a demonstration, it evaluates the nested version of GEOS-Chem driven by the GEOS-5 meteorology and the INTEX-B anthropogenic emissions and used with retrievals from the Ozone Monitoring Instrument (OMI) to constrain emissions of NOx. The CTM has been used extensively for such applications. Errors are examined for a comprehensive set of meteorological and chemical parameters using measurements and/or uncertainty analysis based on current knowledge. Results are exploited then for sensitivity simulations perturbing the respective parameters, as the basis of the following post-model linearized and localized first-order modification. It is found that the model meteorology likely contains errors of various magnitudes in cloud optical depth, air temperature, water vapor, boundary layer height and many other parameters. Model errors also exist in gaseous and heterogeneous reactions, aerosol optical properties and emissions of non-nitrogen species affecting the nitrogen chemistry. Modifications accounting for quantified errors in 10 selected parameters increase the NO2 columns in most areas with an average positive impact of 18% in July and 8% in January, the most important factor being modified uptake of the hydroperoxyl radical (HO2) on aerosols. This suggests a possible systematic model bias such that the top-down emissions will be overestimated by the same magnitude if the model is used for emission inversion without corrections. The modifications however cannot eliminate the large model underestimates in cities and other extremely polluted areas (particularly in the north) as compared to satellite retrievals, likely pointing to underestimates of the a priori emission inventory in these places with important implications for understanding of atmospheric chemistry and air quality. Note that these modifications are simplified and should be interpreted with caution for error apportionment.

Error analysis in inverse scatterometry. I. Modeling.

PubMed

Al-Assaad, Rayan M; Byrne, Dale M

2007-02-01

Scatterometry is an optical technique that has been studied and tested in recent years in semiconductor fabrication metrology for critical dimensions. Previous work presented an iterative linearized method to retrieve surface-relief profile parameters from reflectance measurements upon diffraction. With the iterative linear solution model in this work, rigorous models are developed to represent the random and deterministic or offset errors in scatterometric measurements. The propagation of different types of error from the measurement data to the profile parameter estimates is then presented. The improvement in solution accuracies is then demonstrated with theoretical and experimental data by adjusting for the offset errors. In a companion paper (in process) an improved optimization method is presented to account for unknown offset errors in the measurements based on the offset error model.

Systematic evaluation of a time-domain Monte Carlo fitting routine to estimate the adult brain optical properties

NASA Astrophysics Data System (ADS)

Selb, Juliette; Ogden, Tyler M.; Dubb, Jay; Fang, Qianqian; Boas, David A.

2013-03-01

Time-domain near-infrared spectroscopy (TD-NIRS) offers the ability to measure the absolute baseline optical properties of a tissue. Specifically, for brain imaging, the robust assessment of cerebral blood volume and oxygenation based on measurement of cerebral hemoglobin concentrations is essential for reliable cross-sectional and longitudinal studies. In adult heads, these baseline measurements are complicated by the presence of thick extra-cerebral tissue (scalp, skull, CSF). A simple semi-infinite homogeneous model of the head has proven to have limited use because of the large errors it introduces in the recovered brain absorption. Analytical solutions for layered media have shown improved performance on Monte-Carlo simulated data and layered phantom experiments, but their validity on real adult head data has never been demonstrated. With the advance of fast Monte Carlo approaches based on GPU computation, numerical methods to solve the radiative transfer equation become viable alternatives to analytical solutions of the diffusion equation. Monte Carlo approaches provide the additional advantage to be adaptable to any geometry, in particular more realistic head models. The goals of the present study were twofold: (1) to implement a fast and flexible Monte Carlo-based fitting routine to retrieve the brain optical properties; (2) to characterize the performances of this fitting method on realistic adult head data. We generated time-resolved data at various locations over the head, and fitted them with different models of light propagation: the homogeneous analytical model, and Monte Carlo simulations for three head models: a two-layer slab, the true subject's anatomy, and that of a generic atlas head. We found that the homogeneous model introduced a median 20 to 25% error on the recovered brain absorption, with large variations over the range of true optical properties. The two-layer slab model only improved moderately the results over the homogeneous one. On the other hand, using a generic atlas head registered to the subject's head surface decreased the error by a factor of 2. When the information is available, using the true subject anatomy offers the best performance.

Phase retrieval by constrained power inflation and signum flipping

NASA Astrophysics Data System (ADS)

Laganà, A. R.; Morabito, A. F.; Isernia, T.

2016-12-01

In this paper we consider the problem of retrieving a signal from the modulus of its Fourier transform (or other suitable transformations) and some additional information, which is also known as "Phase Retrieval" problem. The problem arises in many areas of applied Sciences such as optics, electron microscopy, antennas, and crystallography. In particular, we introduce a new approach, based on power inflation and tunneling, allowing an increased robustness with respect to the possible occurrence of false solutions. Preliminary results are presented for the simple yet relevant case of one-dimensional arrays and noisy data.

Automatic Error Analysis Using Intervals

ERIC Educational Resources Information Center

Rothwell, E. J.; Cloud, M. J.

2012-01-01

A technique for automatic error analysis using interval mathematics is introduced. A comparison to standard error propagation methods shows that in cases involving complicated formulas, the interval approach gives comparable error estimates with much less effort. Several examples are considered, and numerical errors are computed using the INTLAB…

Quantifying the impact of material-model error on macroscale quantities-of-interest using multiscale a posteriori error-estimation techniques

DOE PAGES

Brown, Judith A.; Bishop, Joseph E.

2016-07-20

An a posteriori error-estimation framework is introduced to quantify and reduce modeling errors resulting from approximating complex mesoscale material behavior with a simpler macroscale model. Such errors may be prevalent when modeling welds and additively manufactured structures, where spatial variations and material textures may be present in the microstructure. We consider a case where a <100> fiber texture develops in the longitudinal scanning direction of a weld. Transversely isotropic elastic properties are obtained through homogenization of a microstructural model with this texture and are considered the reference weld properties within the error-estimation framework. Conversely, isotropic elastic properties are considered approximatemore » weld properties since they contain no representation of texture. Errors introduced by using isotropic material properties to represent a weld are assessed through a quantified error bound in the elastic regime. Lastly, an adaptive error reduction scheme is used to determine the optimal spatial variation of the isotropic weld properties to reduce the error bound.« less

Assimilation of Atmospheric InfraRed Sounder (AIRS) Profiles using WRF-Var

NASA Technical Reports Server (NTRS)

Zavodsky, Brad; Jedlovec, Gary J.; Lapenta, William

2008-01-01

The Weather Research and Forecasting (WRF) model contains a three-dimensional variational (3DVAR) assimilation system (WRF-Var), which allows a user to join data from multiple sources into one coherent analysis. WRF-Var combines observations with a background field traditionally generated using a previous model forecast through minimization of a cost function. In data sparse regions, remotely-sensed observations may be able to improve analyses and produce improved forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The combined AIRS/AMSU system provides radiance measurements used as input to a sophisticated retrieval scheme which has been shown to produce temperature profiles with an accuracy of 1 K over 1 km layers and humidity profiles with accuracy of 15% in 2 km layers in both clear and partly cloudy conditions. The retrieval algorithm also provides estimates of the accuracy of the retrieved values at each pressure level, allowing the user to select profiles based on the required error tolerances of the application. The purpose of this paper is to describe a procedure to optimally assimilate high-resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type using gen_be and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics in the WRF-Var. The AIRS thermodynamic profiles are obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators are used to select the highest quality temperature and moisture data for each profile location and pressure level. Analyses are run to produce quasi-real-time regional weather forecasts over the continental U.S. The preliminary assessment of the impact of the AIRS profiles will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes.

Retrieval of carbon dioxide vertical profiles from solar occultation observations and associated error budgets for ACE-FTS and CASS-FTS

NASA Astrophysics Data System (ADS)

Sioris, C. E.; Boone, C. D.; Nassar, R.; Sutton, K. J.; Gordon, I. E.; Walker, K. A.; Bernath, P. F.

2014-07-01

An algorithm is developed to retrieve the vertical profile of carbon dioxide in the 5 to 25 km altitude range using mid-infrared solar occultation spectra from the main instrument of the ACE (Atmospheric Chemistry Experiment) mission, namely the Fourier transform spectrometer (FTS). The main challenge is to find an atmospheric phenomenon which can be used for accurate tangent height determination in the lower atmosphere, where the tangent heights (THs) calculated from geometric and timing information are not of sufficient accuracy. Error budgets for the retrieval of CO2 from ACE-FTS and the FTS on a potential follow-on mission named CASS (Chemical and Aerosol Sounding Satellite) are calculated and contrasted. Retrieved THs have typical biases of 60 m relative to those retrieved using the ACE version 3.x software after revisiting the temperature dependence of the N2 CIA (collision-induced absorption) laboratory measurements and accounting for sulfate aerosol extinction. After correcting for the known residual high bias of ACE version 3.x THs expected from CO2 spectroscopic/isotopic inconsistencies, the remaining bias for tangent heights determined with the N2 CIA is -20 m. CO2 in the 5-13 km range in the 2009-2011 time frame is validated against aircraft measurements from CARIBIC (Civil Aircraft for the Regular Investigation of the atmosphere Based on an Instrument Container), CONTRAIL (Comprehensive Observation Network for Trace gases by Airline), and HIPPO (HIAPER Pole-to-Pole Observations), yielding typical biases of -1.7 ppm in the 5-13 km range. The standard error of these biases in this vertical range is 0.4 ppm. The multi-year ACE-FTS data set is valuable in determining the seasonal variation of the latitudinal gradient which arises from the strong seasonal cycle in the Northern Hemisphere troposphere. The annual growth of CO2 in this time frame is determined to be 2.6 ± 0.4 ppm year-1, in agreement with the currently accepted global growth rate based on ground-based measurements.

Sensitivity Analysis for Atmospheric Infrared Sounder (AIRS) CO2 Retrieval

NASA Technical Reports Server (NTRS)

Gat, Ilana

2012-01-01

The Atmospheric Infrared Sounder (AIRS) is a thermal infrared sensor able to retrieve the daily atmospheric state globally for clear as well as partially cloudy field-of-views. The AIRS spectrometer has 2378 channels sensing from 15.4 micrometers to 3.7 micrometers, of which a small subset in the 15 micrometers region has been selected, to date, for CO2 retrieval. To improve upon the current retrieval method, we extended the retrieval calculations to include a prior estimate component and developed a channel ranking system to optimize the channels and number of channels used. The channel ranking system uses a mathematical formalism to rapidly process and assess the retrieval potential of large numbers of channels. Implementing this system, we identifed a larger optimized subset of AIRS channels that can decrease retrieval errors and minimize the overall sensitivity to other iridescent contributors, such as water vapor, ozone, and atmospheric temperature. This methodology selects channels globally by accounting for the latitudinal, longitudinal, and seasonal dependencies of the subset. The new methodology increases accuracy in AIRS CO2 as well as other retrievals and enables the extension of retrieved CO2 vertical profiles to altitudes ranging from the lower troposphere to upper stratosphere. The extended retrieval method for CO2 vertical profile estimation using a maximum-likelihood estimation method. We use model data to demonstrate the beneficial impact of the extended retrieval method using the new channel ranking system on CO2 retrieval.

Comparison Spatial Pattern of Land Surface Temperature with Mono Window Algorithm and Split Window Algorithm: A Case Study in South Tangerang, Indonesia

NASA Astrophysics Data System (ADS)

Bunai, Tasya; Rokhmatuloh; Wibowo, Adi

2018-05-01

In this paper, two methods to retrieve the Land Surface Temperature (LST) from thermal infrared data supplied by band 10 and 11 of the Thermal Infrared Sensor (TIRS) onboard the Landsat 8 is compared. The first is mono window algorithm developed by Qin et al. and the second is split window algorithm by Rozenstein et al. The purpose of this study is to perform the spatial distribution of land surface temperature, as well as to determine more accurate algorithm for retrieving land surface temperature by calculated root mean square error (RMSE). Finally, we present comparison the spatial distribution of land surface temperature by both of algorithm, and more accurate algorithm is split window algorithm refers to the root mean square error (RMSE) is 7.69° C.

Content based image retrieval for matching images of improvised explosive devices in which snake initialization is viewed as an inverse problem

NASA Astrophysics Data System (ADS)

Acton, Scott T.; Gilliam, Andrew D.; Li, Bing; Rossi, Adam

2008-02-01

Improvised explosive devices (IEDs) are common and lethal instruments of terrorism, and linking a terrorist entity to a specific device remains a difficult task. In the effort to identify persons associated with a given IED, we have implemented a specialized content based image retrieval system to search and classify IED imagery. The system makes two contributions to the art. First, we introduce a shape-based matching technique exploiting shape, color, and texture (wavelet) information, based on novel vector field convolution active contours and a novel active contour initialization method which treats coarse segmentation as an inverse problem. Second, we introduce a unique graph theoretic approach to match annotated printed circuit board images for which no schematic or connectivity information is available. The shape-based image retrieval method, in conjunction with the graph theoretic tool, provides an efficacious system for matching IED images. For circuit imagery, the basic retrieval mechanism has a precision of 82.1% and the graph based method has a precision of 98.1%. As of the fall of 2007, the working system has processed over 400,000 case images.

An overview of selected information storage and retrieval issues in computerized document processing

NASA Technical Reports Server (NTRS)

Dominick, Wayne D. (Editor); Ihebuzor, Valentine U.

1984-01-01

The rapid development of computerized information storage and retrieval techniques has introduced the possibility of extending the word processing concept to document processing. A major advantage of computerized document processing is the relief of the tedious task of manual editing and composition usually encountered by traditional publishers through the immense speed and storage capacity of computers. Furthermore, computerized document processing provides an author with centralized control, the lack of which is a handicap of the traditional publishing operation. A survey of some computerized document processing techniques is presented with emphasis on related information storage and retrieval issues. String matching algorithms are considered central to document information storage and retrieval and are also discussed.

Airplane wing vibrations due to atmospheric turbulence

NASA Technical Reports Server (NTRS)

Pastel, R. L.; Caruthers, J. E.; Frost, W.

1981-01-01

The magnitude of error introduced due to wing vibration when measuring atmospheric turbulence with a wind probe mounted at the wing tip was studied. It was also determined whether accelerometers mounted on the wing tip are needed to correct this error. A spectrum analysis approach is used to determine the error. Estimates of the B-57 wing characteristics are used to simulate the airplane wing, and von Karman's cross spectrum function is used to simulate atmospheric turbulence. It was found that wing vibration introduces large error in measured spectra of turbulence in the frequency's range close to the natural frequencies of the wing.

Grazing Incidence Wavefront Sensing and Verification of X-Ray Optics Performance

NASA Technical Reports Server (NTRS)

Saha, Timo T.; Rohrbach, Scott; Zhang, William W.

2011-01-01

Evaluation of interferometrically measured mirror metrology data and characterization of a telescope wavefront can be powerful tools in understanding of image characteristics of an x-ray optical system. In the development of soft x-ray telescope for the International X-Ray Observatory (IXO), we have developed new approaches to support the telescope development process. Interferometrically measuring the optical components over all relevant spatial frequencies can be used to evaluate and predict the performance of an x-ray telescope. Typically, the mirrors are measured using a mount that minimizes the mount and gravity induced errors. In the assembly and mounting process the shape of the mirror segments can dramatically change. We have developed wavefront sensing techniques suitable for the x-ray optical components to aid us in the characterization and evaluation of these changes. Hartmann sensing of a telescope and its components is a simple method that can be used to evaluate low order mirror surface errors and alignment errors. Phase retrieval techniques can also be used to assess and estimate the low order axial errors of the primary and secondary mirror segments. In this paper we describe the mathematical foundation of our Hartmann and phase retrieval sensing techniques. We show how these techniques can be used in the evaluation and performance prediction process of x-ray telescopes.

Inference of effective river properties from remotely sensed observations of water surface

NASA Astrophysics Data System (ADS)

Garambois, Pierre-André; Monnier, Jérôme

2015-05-01

The future SWOT mission (Surface Water and Ocean Topography) will provide cartographic measurements of inland water surfaces (elevation, widths and slope) at an unprecedented spatial and temporal resolution. Given synthetic SWOT like data, forward flow models of hierarchical-complexity are revisited and few inverse formulations are derived and assessed for retrieving the river low flow bathymetry, roughness and discharge (A0, K, Q) . The concept of an effective low flow bathymetry A0 (the real one being never observed) and roughness K , hence an effective river dynamics description, is introduced. The few inverse models elaborated for inferring (A0, K, Q) are analyzed in two contexts: (1) only remotely sensed observations of the water surface (surface elevation, width and slope) are available; (2) one additional water depth measurement (or estimate) is available. The inverse models elaborated are independent of data acquisition dynamics; they are assessed on 91 synthetic test cases sampling a wide range of steady-state river flows (the Froude number varying between 0.05 and 0.5 for 1 km reaches) and in the case of a flood on the Garonne River (France) characterized by large spatio-temporal variabilities. It is demonstrated that the most complete shallow-water like model allowing to separate the roughness and bathymetry terms is the so-called low Froude model. In Case (1), the resulting RMSE on infered discharges are on the order of 15% for first guess errors larger than 50%. An important feature of the present inverse methods is the fairly good accuracy of the discharge Q obtained, while the identified roughness coefficient K includes the measurement errors and the misfit of physics between the real flow and the hypothesis on which the inverse models rely; the later neglecting the unobserved temporal variations of the flow and the inertia effects. A compensation phenomena between the indentifiedvalues of K and the unobserved bathymetry A0 is highlighted, while the present inverse models lead to an effective river dynamics model that is accurate in the range of the discharge variability observed. In Case (2), the effective bathymetry profile for 80 km of the Garonne River is retrieved with 1% relative error only. Next, accurate effective topography-friction pairs and also discharge can be inferred. Finally, defining river reaches from the observation grid tends to average the river properties in each reach, hence tends to smooth the hydraulic variability.

Retrieval dynamics in self-terminated memory search.

PubMed

Hussey, Erika K; Dougherty, Michael R; Harbison, J Isaiah; Davelaar, Eddy J

2014-02-01

Most free-recall experiments employ a paradigm in which participants are given a preset amount of time to retrieve items from a list. While much has been learned using this paradigm, it ignores an important component of many real-world retrieval tasks: the decision to terminate memory search. The present study examines the temporal characteristics underlying memory search by comparing within subjects a standard retrieval paradigm with a finite, preset amount of time (closed interval) to a design that allows participants to terminate memory search on their own (open interval). Calling on the results of several presented simulations, we anticipated that the threshold for number of retrieval failures varied as a function of the nature of the recall paradigm, such that open intervals should result in lower thresholds than closed intervals. Moreover, this effect was expected to manifest in interretrieval times (IRTs). Although retrieval-interval type did not significantly impact the number of items recalled or error rates, IRTs were sensitive to the manipulation. Specifically, the final IRTs in the closed-interval paradigm were longer than those of the open-interval paradigm. This pattern suggests that providing participants with a preset retrieval interval not only masks an important component of the retrieval process (the memory search termination decision), but also alters temporal retrieval dynamics. Task demands may compel people to strategically control aspects of their retrieval by implementing different stopping rules.

An Assessment of State-of-the-Art Mean Sea Surface and Geoid Models of the Arctic Ocean: Implications for Sea Ice Freeboard Retrieval

NASA Astrophysics Data System (ADS)

Skourup, Henriette; Farrell, Sinéad Louise; Hendricks, Stefan; Ricker, Robert; Armitage, Thomas W. K.; Ridout, Andy; Andersen, Ole Baltazar; Haas, Christian; Baker, Steven

2017-11-01

State-of-the-art Arctic Ocean mean sea surface (MSS) models and global geoid models (GGMs) are used to support sea ice freeboard estimation from satellite altimeters, as well as in oceanographic studies such as mapping sea level anomalies and mean dynamic ocean topography. However, errors in a given model in the high-frequency domain, primarily due to unresolved gravity features, can result in errors in the estimated along-track freeboard. These errors are exacerbated in areas with a sparse lead distribution in consolidated ice pack conditions. Additionally model errors can impact ocean geostrophic currents, derived from satellite altimeter data, while remaining biases in these models may impact longer-term, multisensor oceanographic time series of sea level change in the Arctic. This study focuses on an assessment of five state-of-the-art Arctic MSS models (UCL13/04 and DTU15/13/10) and a commonly used GGM (EGM2008). We describe errors due to unresolved gravity features, intersatellite biases, and remaining satellite orbit errors, and their impact on the derivation of sea ice freeboard. The latest MSS models, incorporating CryoSat-2 sea surface height measurements, show improved definition of gravity features, such as the Gakkel Ridge. The standard deviation between models ranges 0.03-0.25 m. The impact of remaining MSS/GGM errors on freeboard retrieval can reach several decimeters in parts of the Arctic. While the maximum observed freeboard difference found in the central Arctic was 0.59 m (UCL13 MSS minus EGM2008 GGM), the standard deviation in freeboard differences is 0.03-0.06 m.

Discretization vs. Rounding Error in Euler's Method

ERIC Educational Resources Information Center

Borges, Carlos F.

2011-01-01

Euler's method for solving initial value problems is an excellent vehicle for observing the relationship between discretization error and rounding error in numerical computation. Reductions in stepsize, in order to decrease discretization error, necessarily increase the number of steps and so introduce additional rounding error. The problem is…

Morpho-syntactic processing of Arabic plurals after aphasia: dissecting lexical meaning from morpho-syntax within word boundaries.

PubMed

Khwaileh, Tariq; Body, Richard; Herbert, Ruth

2015-01-01

Within the domain of inflectional morpho-syntax, differential processing of regular and irregular forms has been found in healthy speakers and in aphasia. One view assumes that irregular forms are retrieved as full entities, while regular forms are compiled on-line. An alternative view holds that a single mechanism oversees regular and irregular forms. Arabic offers an opportunity to study this phenomenon, as Arabic nouns contain a consonantal root, delivering lexical meaning, and a vocalic pattern, delivering syntactic information, such as gender and number. The aim of this study is to investigate morpho-syntactic processing of regular (sound) and irregular (broken) Arabic plurals in patients with morpho-syntactic impairment. Three participants with acquired agrammatic aphasia produced plural forms in a picture-naming task. We measured overall response accuracy, then analysed lexical errors and morpho-syntactic errors, separately. Error analysis revealed different patterns of morpho-syntactic errors depending on the type of pluralization (sound vs broken). Omissions formed the vast majority of errors in sound plurals, while substitution was the only error mechanism that occurred in broken plurals. The dissociation was statistically significant for retrieval of morpho-syntactic information (vocalic pattern) but not for lexical meaning (consonantal root), suggesting that the participants' selective impairment was an effect of the morpho-syntax of plurals. These results suggest that irregular plurals forms are stored, while regular forms are derived. The current findings support the findings from other languages and provide a new analysis technique for data from languages with non-concatenative morpho-syntax.

Evaluation of AVHRR Aerosol Properties Over Mainland China from Deepblue Algorithm

NASA Astrophysics Data System (ADS)

Xue, Y.; Che, Y.; She, L.

2017-12-01

Advanced Very High Resolution Radiometer (AVHRR) on-board NOAA series satellites is the only operational senor which keeps observing surface of the Earth and cloud over 30 years since 1979. Such long time coverage helps to expand the application of AVHRR to aerosol properties retrieval over both land and ocean successfully. Recently in 2017, the Deep Blue Project has published AVHRR `Deep Blue' dataset version 001 (V001) using `Deep Blue (DB)' algorithm(Sayer et al., 2017). This dataset includes not only aerosol properties over land but also oceanic aerosol product at three periods (NOAA-11: 1989-1990, NOAA-14: 1995-1999, NOAA-18: 2006-2011). We pay much of our attention to DB's performance over mainland China. Therefore, in the presenting paper, we focus on validating AVHRR/DB dataset over different land covers in China in 2007, 2008 and 2010. Both of data from ground-based networks from the Aerosol Robotic NETwork (AERONET) and China Aerosol Remote Sensing Network (CARSNET) are used as reference data. The collocation method is to match data at a time range of of satellite pass-by and at a spatial frame of pixels around ground-based site. Totally, data from 18 AERONET and 25 CARSNET are used as shown in figure, collocating 922 matches with AERONET and 2325 matches with CARSNET. Additionally, we introduced a corrected RMS error as main evaluation metric. As a result, AVHRR/DB underestimates AOD increasingly and more uncertainties and errors will be introduced with the growth of AOD. Otherwise, the performance of AVHRR/DB are better compared with AERONET data than with CARSNET data from RMSbc of 0.35 vs. 0.42. Their Rs (0.757 vs. 0.654) prove this characteristic too. For urban areas, the performances in Beijing are better than that in Xi'an from RMSbc, otherwise RMS in Xi'an (0.324) is lower than others' (0.346 and 0.383) mainly because of small AOD observed range and low R (0.624). For croplands, those performances are at same levels with RMSbc from 0.312 to 0.380 except Huimin with RMSbc = 0.445. For grasslands and sparsely vegetated areas, it lacks AERONET observation sites that only SACOL in central China. Obviously, the algorithm has best performance over Dunhuang site, where the RMSbc = 0.338 and highest R about 0.771. Over the rest of sites, the AVHRR/DB has serious problem in retrieving AOD, high dispersion or poor correlation.

A circular median filter approach for resolving directional ambiguities in wind fields retrieved from spaceborne scatterometer data

NASA Technical Reports Server (NTRS)

Schultz, Howard

1990-01-01

The retrieval algorithm for spaceborne scatterometry proposed by Schultz (1985) is extended. A circular median filter (CMF) method is presented, which operates on wind directions independently of wind speed, removing any implicit wind speed dependence. A cell weighting scheme is included in the algorithm, permitting greater weights to be assigned to more reliable data. The mathematical properties of the ambiguous solutions to the wind retrieval problem are reviewed. The CMF algorithm is tested on twelve simulated data sets. The effects of spatially correlated likelihood assignment errors on the performance of the CMF algorithm are examined. Also, consideration is given to a wind field smoothing technique that uses a CMF.

An evaluation of information retrieval accuracy with simulated OCR output

DOE Office of Scientific and Technical Information (OSTI.GOV)

Croft, W.B.; Harding, S.M.; Taghva, K.

Optical Character Recognition (OCR) is a critical part of many text-based applications. Although some commercial systems use the output from OCR devices to index documents without editing, there is very little quantitative data on the impact of OCR errors on the accuracy of a text retrieval system. Because of the difficulty of constructing test collections to obtain this data, we have carried out evaluation using simulated OCR output on a variety of databases. The results show that high quality OCR devices have little effect on the accuracy of retrieval, but low quality devices used with databases of short documents canmore » result in significant degradation.« less

Aeolus End-To-End Simulator and Wind Retrieval Algorithms up to Level 1B

NASA Astrophysics Data System (ADS)

Reitebuch, Oliver; Marksteiner, Uwe; Rompel, Marc; Meringer, Markus; Schmidt, Karsten; Huber, Dorit; Nikolaus, Ines; Dabas, Alain; Marshall, Jonathan; de Bruin, Frank; Kanitz, Thomas; Straume, Anne-Grete

2018-04-01

The first wind lidar in space ALADIN will be deployed on ESÁs Aeolus mission. In order to assess the performance of ALADIN and to optimize the wind retrieval and calibration algorithms an end-to-end simulator was developed. This allows realistic simulations of data downlinked by Aeolus. Together with operational processors this setup is used to assess random and systematic error sources and perform sensitivity studies about the influence of atmospheric and instrument parameters.

Temperature profile retrievals with extended Kalman-Bucy filters

NASA Technical Reports Server (NTRS)

Ledsham, W. H.; Staelin, D. H.

1979-01-01

The Extended Kalman-Bucy Filter is a powerful technique for estimating non-stationary random parameters in situations where the received signal is a noisy non-linear function of those parameters. A practical causal filter for retrieving atmospheric temperature profiles from radiances observed at a single scan angle by the Scanning Microwave Spectrometer (SCAMS) carried on the Nimbus 6 satellite typically shows approximately a 10-30% reduction in rms error about the mean at almost all levels below 70 mb when compared with a regression inversion.

Translation position determination in ptychographic coherent diffraction imaging.

PubMed

Zhang, Fucai; Peterson, Isaac; Vila-Comamala, Joan; Diaz, Ana; Berenguer, Felisa; Bean, Richard; Chen, Bo; Menzel, Andreas; Robinson, Ian K; Rodenburg, John M

2013-06-03

Accurate knowledge of translation positions is essential in ptychography to achieve a good image quality and the diffraction limited resolution. We propose a method to retrieve and correct position errors during the image reconstruction iterations. Sub-pixel position accuracy after refinement is shown to be achievable within several tens of iterations. Simulation and experimental results for both optical and X-ray wavelengths are given. The method improves both the quality of the retrieved object image and relaxes the position accuracy requirement while acquiring the diffraction patterns.

Comparison of Gaussian and non-Gaussian Atmospheric Profile Retrievals from Satellite Microwave Data

NASA Astrophysics Data System (ADS)

Kliewer, A.; Forsythe, J. M.; Fletcher, S. J.; Jones, A. S.

2017-12-01

The Cooperative Institute for Research in the Atmosphere at Colorado State University has recently developed two different versions of a mixed-distribution (lognormal combined with a Gaussian) based microwave temperature and mixing ratio retrieval system as well as the original Gaussian-based approach. These retrieval systems are based upon 1DVAR theory but have been adapted to use different descriptive statistics of the lognormal distribution to minimize the background errors. The input radiance data is from the AMSU-A and MHS instruments on the NOAA series of spacecraft. To help illustrate how the three retrievals are affected by the change in the distribution we are in the process of creating a new website to show the output from the different retrievals. Here we present initial results from different dynamical situations to show how the tool could be used by forecasters as well as for educators. However, as the new retrieved values are from a non-Gaussian based 1DVAR then they will display non-Gaussian behaviors that need to pass a quality control measure that is consistent with this distribution, and these new measures are presented here along with initial results for checking the retrievals.

Ground-based FTIR retrievals of SF6 on Reunion Island

NASA Astrophysics Data System (ADS)

Zhou, Minqiang; Langerock, Bavo; Vigouroux, Corinne; Wang, Pucai; Hermans, Christian; Stiller, Gabriele; Walker, Kaley A.; Dutton, Geoff; Mahieu, Emmanuel; De Mazière, Martine

2018-02-01

SF6 total columns were successfully retrieved from FTIR (Fourier transform infrared) measurements (Saint Denis and Maïdo) on Reunion Island (21° S, 55° E) between 2004 and 2016 using the SFIT4 algorithm: the retrieval strategy and the error budget were presented. The FTIR SF6 retrieval has independent information in only one individual layer, covering the whole of the troposphere and the lower stratosphere. The trend in SF6 was analysed based on the FTIR-retrieved dry-air column-averaged mole fractions (XSF6) on Reunion Island, the in situ measurements at America Samoa (SMO) and the collocated satellite measurements (Michelson Interferometer for Passive Atmospheric Sounding, MIPAS, and Atmospheric Chemistry Experiment Fourier Transform Spectrometer, ACE-FTS) in the southern tropics. The SF6 annual growth rate from FTIR retrievals is 0.265 ± 0.013 pptv year-1 for 2004-2016, which is slightly weaker than that from the SMO in situ measurements (0.285 ± 0.002 pptv year-1) for the same time period. The SF6 trend in the troposphere from MIPAS and ACE-FTS observations is also close to the ones from the FTIR retrievals and the SMO in situ measurements.

Unconditioned- and Conditioned- Stimuli Induce Differential Memory Reconsolidation and β-AR-Dependent CREB Activation

PubMed Central

Huang, Bing; Zhu, Huiwen; Zhou, Yiming; Liu, Xing; Ma, Lan

2017-01-01

Consolidated long-term fear memories become labile and reconsolidated upon retrieval by the presentation of conditioned stimulus (CS) or unconditioned stimulus (US). Whether CS-retrieval or US-retrieval will trigger different memory reconsolidation processes is unknown. In this study, we introduced a sequential fear conditioning paradigm in which footshock (FS) was paired with two distinct sounds (CS-A and CS-B). The treatment with propranolol, a β-adrenergic receptor (β-AR) antagonist, after US (FS)-retrieval impaired freezing behavior evoked by either CS-A or CS-B. Betaxolol, a selective β1-AR antagonist, showed similar effects. However, propranolol treatment after retrieval by one CS (e.g., CS-A) only inhibited freezing behavior evoked by the same CS (i.e., CS-A), not the other CS (CS-B). These data suggest that β-AR is critically involved in reconsolidation of fear memory triggered by US- and CS-retrieval, whereas β-AR blockade after US-retrieval disrupts more CS-US associations than CS-retrieval does. Furthermore, significant CREB activation in almost the whole amygdala and hippocampus was observed after US-retrieval, but CS-retrieval only stimulated CREB activation in the lateral amygdala and the CA3 of hippocampus. In addition, propranolol treatment suppressed memory retrieval-induced CREB activation. These data indicate that US-retrieval activates more memory traces than CS-retrieval does, leading to memory reconsolidation of more CS-US associations. PMID:28848401

Stratospheric N2O5, CH4, and N2O profiles from IR solar occultation spectra

NASA Technical Reports Server (NTRS)

Camy-Peyret, C.; Flaud, J.-M.; Perrin, A.; Rinsland, C. P.; Goldman, A.; Murcray, F. J.

1993-01-01

Stratospheric volume mixing ratio profiles of N2O5, CH4, and N2O have been retrieved from a set of 0.052/cm resolution (FWHM) solar occultation spectra recorded at sunrise during a balloon flight from Aire sur l'Adour, France (44 N latitude) on 12 October 1990. The N2O5 results have been derived from measurements of the integrated absorption by the 1246/cm band. Assuming a total intensity of 4.32 x 10 exp -17 cm/molecule/sq cm independent of temperature, the retrieved N2O5 volume mixing ratios in ppbv, interpolated to 2 km height spacings, are 1.64 +/- 0.49 at 37.5 km, 1.92 +/- 0.56 at 35.5 km, 2.06 +/- 0.47 at 33.5 km, 1.95 +/- 0.42 at 31.5 km, 1.60 +/- 0.33 at 29.5 km, 1.26 +/- 0.28 at 27.5 km, and 0.85 +/- 0.20 at 25.5 km. Error bars indicate the estimated 1-sigma uncertainty including the error in the total band intensity. The retrieved profiles are compared with previous measurements and photochemical model results.

Recounting a Common Experience: On the Effectiveness of Instructing Eyewitness Pairs

PubMed Central

Vredeveldt, Annelies; van Koppen, Peter J.

2018-01-01

Pairs of eyewitnesses with a content-focused interaction style remember significantly more about witnessed incidents. We examined whether content-focused retrieval strategies can be taught. Seventy-five pairs of witnesses were interviewed thrice about an event. The first and third interview were conducted individually for all witnesses. The second interview was individual, collaborative without instruction, or collaborative with instruction. Pairs in the latter condition were instructed to actively listen to and elaborate upon each other's contributions. The strategy instruction had no effect on retrieval strategies used, nor on the amount or accuracy of reported information. However, pairs who spontaneously adopted a content-focused interaction style during the collaborative interview remembered significantly more. Thus, our findings show that effective retrieval strategies cannot be taught, at least not with the current instructions. During the second interview, we observed collaborative inhibition and error pruning. When considering the total amount of information reported across the first two interviews, however, collaboration had no inhibitory effect on correct recall, yet the error pruning benefits remained. These findings suggest that investigative interviewers should interview witnesses separately first, and then interview pairs of witnesses collaboratively. PMID:29593599

Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

NASA Astrophysics Data System (ADS)

Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

2017-01-01

Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

Particle size distribution of river-suspended sediments determined by in situ measured remote-sensing reflectance.

PubMed

Zhang, Yuanzhi; Huang, Zhaojun; Chen, Chuqun; He, Yijun; Jiang, Tingchen

2015-07-10

Suspended sediments in water bodies are classified into organic and inorganic matter and have been investigated by remote-sensing technology for years. Focusing on inorganic matter, however, detailed information such as the grain size of this matter has not been provided yet. In this study, we present a new solution for estimating inorganic suspended sediments' size distribution in highly complex Case 2 waters by using a simple spectrometer sensor rather than a backscattering sensor. An experiment was carried out in the Pearl River Estuary (PRE) in the dry season to collect the remote-sensing reflectance (R_rs) and particle size distribution (PSD) of inorganic suspended sediments. Based on Mie theory, PSDs in the PRE waters were retrieved by R_rs, colored dissolved organic matter, and phytoplankton. The retrieved median diameters in 12 stations show good agreement with those of laboratory analysis at root mean square error of 2.604 μm (27.63%), bias of 1.924 μm (20.42%), and mean absolute error of 2.298 μm (24.37%). The retrieved PSDs and previous PSDs were compared, and the features of PSDs in the PRE waters were concluded.

Optimized retrievals of precipitable water from the VAS 'split window'

NASA Technical Reports Server (NTRS)

Chesters, Dennis; Robinson, Wayne D.; Uccellini, Louis W.

1987-01-01

Precipitable water fields have been retrieved from the VISSR Atmospheric Sounder (VAS) using a radiation transfer model for the differential water vapor absorption between the 11- and 12-micron 'split window' channels. Previous moisture retrievals using only the split window channels provided very good space-time continuity but poor absolute accuracy. This note describes how retrieval errors can be significantly reduced from plus or minus 0.9 to plus or minus 0.6 gm/sq cm by empirically optimizing the effective air temperature and absorption coefficients used in the two-channel model. The differential absorption between the VAS 11- and 12-micron channels, empirically estimated from 135 colocated VAS-RAOB observations, is found to be approximately 50 percent smaller than the theoretical estimates. Similar discrepancies have been noted previously between theoretical and empirical absorption coefficients applied to the retrieval of sea surface temperatures using radiances observed by VAS and polar-orbiting satellites. These discrepancies indicate that radiation transfer models for the 11-micron window appear to be less accurate than the satellite observations.

Vertical profiles of the 3-D wind velocity retrieved from multiple wind lidars performing triple range-height-indicator scans

DOE PAGES

Debnath, Mithu; Iungo, G. Valerio; Ashton, Ryan; ...

2017-02-06

Vertical profiles of 3-D wind velocity are retrieved from triple range-height-indicator (RHI) scans performed with multiple simultaneous scanning Doppler wind lidars. This test is part of the eXperimental Planetary boundary layer Instrumentation Assessment (XPIA) campaign carried out at the Boulder Atmospheric Observatory. The three wind velocity components are retrieved and then compared with the data acquired through various profiling wind lidars and high-frequency wind data obtained from sonic anemometers installed on a 300 m meteorological tower. The results show that the magnitude of the horizontal wind velocity and the wind direction obtained from the triple RHI scans are generally retrieved withmore » good accuracy. Furthermore, poor accuracy is obtained for the evaluation of the vertical velocity, which is mainly due to its typically smaller magnitude and to the error propagation connected with the data retrieval procedure and accuracy in the experimental setup.« less

Application of stochastic particle swarm optimization algorithm to determine the graded refractive index distribution in participating media

NASA Astrophysics Data System (ADS)

Wei, Lin-Yang; Qi, Hong; Ren, Ya-Tao; Ruan, Li-Ming

2016-11-01

Inverse estimation of the refractive index distribution in one-dimensional participating media with graded refractive index (GRI) is investigated. The forward radiative transfer problem is solved by the Chebyshev collocation spectral method. The stochastic particle swarm optimization (SPSO) algorithm is employed to retrieve three kinds of GRI distribution, i.e. the linear, sinusoidal and quadratic GRI distribution. The retrieval accuracy of GRI distribution with different wall emissivity, optical thickness, absorption coefficients and scattering coefficients are discussed thoroughly. To improve the retrieval accuracy of quadratic GRI distribution, a double-layer model is proposed to supply more measurement information. The influence of measurement errors upon the precision of estimated results is also investigated. Considering the GRI distribution is unknown beforehand in practice, a quadratic function is employed to retrieve the linear GRI by SPSO algorithm. All the results show that the SPSO algorithm is applicable to retrieve different GRI distributions in participating media accurately even with noisy data.

Trade-off studies of a hyperspectral infrared sounder on a geostationary satellite.

PubMed

Wang, Fang; Li, Jun; Schmit, Timothy J; Ackerman, Steven A

2007-01-10

Trade-off studies on spectral coverage, signal-to-noise ratio (SNR), and spectral resolution for a hyperspectral infrared (IR) sounder on a geostationary satellite are summarized. The data density method is applied for the vertical resolution analysis, and the rms error between true and retrieved profiles is used to represent the retrieval accuracy. The effects of spectral coverage, SNR, and spectral resolution on vertical resolution and retrieval accuracy are investigated. The advantages of IR and microwave sounder synergy are also demonstrated. When focusing on instrument performance and data processing, the results from this study show that the preferred spectral coverage combines long-wave infrared (LWIR) with the shorter middle-wave IR (SMidW). Using the appropriate spectral coverage, a hyperspectral IR sounder with appropriate SNR can achieve the required science performance (1 km vertical resolution, 1 K temperature, and 10% relative humidity retrieval accuracy). The synergy of microwave and IR sounders can improve the vertical resolution and retrieval accuracy compared to either instrument alone.

Information operator approach applied to the retrieval of vertical distributions of atmospheric constituents from ground-based FTIR measurements

NASA Astrophysics Data System (ADS)

Senten, Cindy; de Mazière, Martine; Vanhaelewyn, Gauthier; Vigouroux, Corinne; Delmas, Robert

2010-05-01

The retrieval of information about the vertical distribution of an atmospheric absorber from high spectral resolution ground-based Fourier Transform infrared (FTIR) solar absorption spectra is an important issue in remote sensing. A frequently used technique at present is the optimal estimation method. This work introduces the application of an alternative method, namely the information operator approach (Doicu et al., 2007; Hoogen et al., 1999), for extracting the available information from such FTIR measurements. This approach has been implemented within the well-known retrieval code SFIT2, by adapting the optimal estimation method such as to take into account only the significant contributions to the solution. In particular, we demonstrate the feasibility of the method when applied to ground-based FTIR spectra taken at the southern (sub)tropical site Ile de La Réunion (21° S, 55° E) in 2007. A thorough comparison has been made between the retrieval results obtained with the original optimal estimation method and the ones obtained with the information operator approach, regarding profile and column stability, information content and corresponding full error budget evaluation. This has been done for the target species ozone (O3), methane (CH4), nitrous oxide (N2O), and carbon monoxide (CO). It is shown that the information operator approach performs well and is capable of achieving the same accuracy as optimal estimation, with a gain of stability and with the additional advantage of being less sensitive to the choice of a priori information as well as to the actual signal-to-noise ratio. Keywords: ground-based FTIR, solar absorption spectra, greenhouse gases, information operator approach References Doicu, A., Hilgers, S., von Bargen, A., Rozanov, A., Eichmann, K.-U., von Savigny, C., and Burrows, J.P.: Information operator approach and iterative regularization methods for atmospheric remote sensing, J. Quant. Spectrosc. Radiat. Transfer, 103, 340-350, 2007. Hoogen, R., Rozanov, V.V., and Burrows, J.P.: Ozone profiles from GOME satellite data: description and first validation, J. Geophys. Res., 104(D7), 8263-8280, 1999.

Information Management For Tactical Reconnaissance

NASA Astrophysics Data System (ADS)

White, James P.

1984-12-01

The expected battlefield tactics of the 1980's and 1990's will be fluid and dynamic. If tactical reconnaissance is to meet this challenge, it must explore all ways of accelerating the flow of information through the reconnaissance cycle, from the moment a tasking request is received to the time the mission results are delivered to the requestor. In addition to near real-time dissemination of reconnaissance information, the mission planning phase needs to be more responsive to the rapidly changing battlefield scenario. By introducing Artificial Intelligence (AI) via an expert system to the mission planning phase, repetitive and computational tasks can be more readily performed by the ground-based mission planning system, thereby permitting the aircrew to devote more of their time to target study. Transporting the flight plan, plus other mission data, to the aircraft is simple with the Fairchild Data Transfer Equipment (DTE). Aircrews are relieved of the tedious, error-prone, and time-consuming task of manually keying-in avionics initialization data. Post-flight retrieval of mission data via the DTE will permit follow-on aircrews, just starting their mission planning phase, to capitalize on current threat data collected by the returning aircrew. Maintenance data retrieved from the recently flown mission will speed-up the aircraft turn-around by providing near-real time fault detection/isolation. As future avionics systems demand more information, a need for a computer-controlled, smart data base or expert system on-board the aircraft will emerge.

Satellite-based estimation of cloud-base updrafts for convective clouds and stratocumulus

NASA Astrophysics Data System (ADS)

Zheng, Y.; Rosenfeld, D.; Li, Z.

2017-12-01

Updraft speeds of thermals have always been notoriously difficult to measure, despite significant roles they play in transporting pollutants and in cloud formation and precipitation. To our knowledge, no attempt to date has been made to estimate updraft speed from satellite information. In this study, we introduce three methods of retrieving updraft speeds at cloud base () for convective clouds and marine stratocumulus with VIIRS onboard Suomi-NPP satellite. The first method uses ground-air temperature difference to characterize the surface sensible heat flux, which is found to be correlated with updraft speeds measured by the Doppler lidar over the Southern Great Plains (SGP). Based on the relationship, we use the satellite-retrieved surface skin temperature and reanalysis surface air temperature to estimate the updrafts. The second method is based on a good linear correlation between cloud base height and updrafts, which was found over the SGP, the central Amazon, and on board a ship sailing between Honolulu and Los Angeles. We found a universal relationship for both land and ocean. The third method is for marine stratocumulus. A statistically significant relationship between Wb and cloud-top radiative cooling rate (CTRC) is found from measurements over northeastern Pacific and Atlantic. Based on this relation, satellite- and reanalysis-derived CTRC is utilized to infer the Wb of stratocumulus clouds. Evaluations against ground-based Doppler lidar measurements show estimation errors of 24%, 21% and 22% for the three methods, respectively.

Role of Forcing Uncertainty and Background Model Error Characterization in Snow Data Assimilation

NASA Technical Reports Server (NTRS)

Kumar, Sujay V.; Dong, Jiarul; Peters-Lidard, Christa D.; Mocko, David; Gomez, Breogan

2017-01-01

Accurate specification of the model error covariances in data assimilation systems is a challenging issue. Ensemble land data assimilation methods rely on stochastic perturbations of input forcing and model prognostic fields for developing representations of input model error covariances. This article examines the limitations of using a single forcing dataset for specifying forcing uncertainty inputs for assimilating snow depth retrievals. Using an idealized data assimilation experiment, the article demonstrates that the use of hybrid forcing input strategies (either through the use of an ensemble of forcing products or through the added use of the forcing climatology) provide a better characterization of the background model error, which leads to improved data assimilation results, especially during the snow accumulation and melt-time periods. The use of hybrid forcing ensembles is then employed for assimilating snow depth retrievals from the AMSR2 (Advanced Microwave Scanning Radiometer 2) instrument over two domains in the continental USA with different snow evolution characteristics. Over a region near the Great Lakes, where the snow evolution tends to be ephemeral, the use of hybrid forcing ensembles provides significant improvements relative to the use of a single forcing dataset. Over the Colorado headwaters characterized by large snow accumulation, the impact of using the forcing ensemble is less prominent and is largely limited to the snow transition time periods. The results of the article demonstrate that improving the background model error through the use of a forcing ensemble enables the assimilation system to better incorporate the observational information.

Reach distance but not judgment error is associated with falls in older people.

PubMed

Butler, Annie A; Lord, Stephen R; Fitzpatrick, Richard C

2011-08-01

Reaching is a vital action requiring precise motor coordination and attempting to reach for objects that are too far away can destabilize balance and result in falls and injury. This could be particularly important for many elderly people with age-related loss of sensorimotor function and a reduced ability to recover balance. Here, we investigate the interaction between reaching ability, errors in judging reach, and the incidence of falling (retrospectively and prospectively) in a large cohort of older people. Participants (n = 415, 70-90 years) had to estimate the furthest distance they could reach to retrieve a broomstick hanging in front of them. In an iterative dialog with the experimenter, the stick was moved until it was at the furthest distance they estimated to be reached successfully. At this point, participants were asked to attempt to retrieve the stick. Actual maximal reach was then measured. The difference between attempted reach and actual maximal reach provided a measure of judgment error. One-year retrospective fall rates were obtained at initial assessment and prospective falls were monitored by monthly calendar. Participants with poor maximal reach attempted shorter reaches than those who had good reaching ability. Those with the best reaching ability most accurately judged their maximal reach, whereas poor performers were dichotomous and either underestimated or overestimated their reach with few judging exactly. Fall rates were significantly associated with reach distance but not with reach judgment error. Maximal reach but not error in perceived reach is associated with falls in older people.

Is ozone model bias driven by errors in cloud predictions? A quantitative assessment using satellite cloud retrievals in WRF-Chem

NASA Astrophysics Data System (ADS)

Ryu, Y. H.; Hodzic, A.; Barré, J.; Descombes, G.; Minnis, P.

2017-12-01

Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much of the bias in O3 predictions is caused by inaccurate cloud predictions. This study quantifies the errors in surface O3 predictions associated with clouds in summertime over CONUS using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Cloud fields used for photochemistry are corrected based on satellite cloud retrievals in sensitivity simulations. It is found that the WRF-Chem model is able to detect about 60% of clouds in the right locations and generally underpredicts cloud optical depths. The errors in hourly O3 due to the errors in cloud predictions can be up to 60 ppb. On average in summertime over CONUS, the errors in 8-h average O3 of 1-6 ppb are found to be attributable to those in cloud predictions under cloudy sky conditions. The contribution of changes in photolysis rates due to clouds is found to be larger ( 80 % on average) than that of light-dependent BVOC emissions. The effects of cloud corrections on O­3 are about 2 times larger in VOC-limited than NOx-limited regimes, suggesting that the benefits of accurate cloud predictions would be greater in VOC-limited than NOx-limited regimes.

MERIS albedo climatology and its effect on the FRESCO+ O2 A-band cloud retrieval from SCIAMACHY data

NASA Astrophysics Data System (ADS)

Popp, Christoph; Wang, Ping; Brunner, Dominik; Stammes, Piet; Zhou, Yipin

2010-05-01

Accurate cloud information is an important prerequisite for the retrieval of atmospheric trace gases from spaceborne UV/VIS sensors. Errors in the estimated cloud fraction and cloud height (pressure) result in an erroneous air mass factor and thus can lead to inaccuracies in the vertical column densities of the retrieved trace gas. In ESA's TEMIS (Tropospheric Emission Monitoring Internet Service) project, the FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A-band) cloud retrieval is applied to, amongst others, SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY) data to determine these quantities. Effective cloud fraction and pressure are inverted by (i) radiative transfer simulations of top-of-atmosphere reflectance based on O2 absorption, single Rayleigh scattering, surface and cloud albedo in three spectral windows covering the O2 A-band and (ii) a subsequent fitting of the simulated to the measured spectrum. However, FRESCO+ relies on a relatively coarse resolution surface albedo climatology (1° x 1°) compiled from GOME (Global Ozone Monitoring Experiment) measurements in the 1990's which introduces several artifacts, e.g. an overestimation of cloud fraction at coastlines or over some mountainous regions. Therefore, we test the substitution of the GOME climatology with a new land surface albedo climatology compiled for every month from MEdium Resolution Imaging Spectrometer (MERIS) Albedomap data (0.05° x 0.05°) covering the period January 2003 to October 2006. The MERIS channels at 754nm and 775nm are located spectrally close to the corresponding GOME channels (758nm and 772nm) on both sides of the O2 A-band. Further, the increased spatial resolution of the MERIS product allows to better account for SCIAMACHY's pixel size of approximately 30x60km. The aim of this study is to describe and assess (i) the compilation and quality of the MERIS climatology (ii) the differences to the GOME climatology, and (iii) possible enhancements of the SCIAMACHY cloud retrieval after integrating the MERIS climatology into FRESCO+. First results indicate that in areas where FRESCO+ is overestimating cloud fraction using the GOME climatology, MERIS generally reveals higher albedo values which in turn will lead to lower cloud fractions, e.g. at coastlines, some arid or mountainous areas. The differences between the two data sets are also higher in winter than in summer. It can therefore be expected that the new data base with increased spatial resolution improves SCIAMACHY cloud retrieval with FRESCO+. The most limiting factors for the compilation of the MERIS climatology can be assigned to inappropriate snow cover masking and occasionally unfavorable illumination conditions in high northern latitudes during winter.

Phase noise optimization in temporal phase-shifting digital holography with partial coherence light sources and its application in quantitative cell imaging.

PubMed

Remmersmann, Christian; Stürwald, Stephan; Kemper, Björn; Langehanenberg, Patrik; von Bally, Gert

2009-03-10

In temporal phase-shifting-based digital holographic microscopy, high-resolution phase contrast imaging requires optimized conditions for hologram recording and phase retrieval. To optimize the phase resolution, for the example of a variable three-step algorithm, a theoretical analysis on statistical errors, digitalization errors, uncorrelated errors, and errors due to a misaligned temporal phase shift is carried out. In a second step the theoretically predicted results are compared to the measured phase noise obtained from comparative experimental investigations with several coherent and partially coherent light sources. Finally, the applicability for noise reduction is demonstrated by quantitative phase contrast imaging of pancreas tumor cells.

Improvement of Aerosol Optical Depth Retrieval from MODIS Spectral Reflectance over the Global Ocean Using New Aerosol Models Archived from AERONET Inversion Data and Tri-axial Ellipsoidal Dust Database

NASA Technical Reports Server (NTRS)

Lee, J.; Kim, J.; Yang, P.; Hsu, N. C.

2012-01-01

New over-ocean aerosol models are developed by integrating the inversion data from the Aerosol Robotic Network (AERONET) sun/sky radiometers with a database for the optical properties of tri-axial ellipsoid particles. The new aerosol models allow more accurate retrieval of aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS) in the case of high AOD (AOD greater than 0.3). The aerosol models are categorized by using the fine-mode fraction (FMF) at 550 nm and the singlescattering albedo (SSA) at 440 nm from the AERONET inversion data to include a variety of aerosol types found around the globe. For each aerosol model, the changes in the aerosol optical properties (AOPs) as functions of AOD are considered to better represent aerosol characteristics. Comparisons of AODs between AERONET and MODIS for the period from 2003 to 2010 show that the use of the new aerosol models enhances the AOD accuracy with a Pearson coefficient of 0.93 and a regression slope of 0.99 compared to 0.92 and 0.85 calculated using the MODIS Collection 5 data. Moreover, the percentage of data within an expected error of +/-(0.03 + 0.05xAOD) is increased from 62 percent to 64 percent for overall data and from 39 percent to 51 percent for AOD greater than 0.3. Errors in the retrieved AOD are further characterized with respect to the Angstrom exponent (AE), scattering angle, SSA, and air mass factor (AMF). Due to more realistic AOPs assumptions, the new algorithm generally reduces systematic errors in the retrieved AODs compared with the current operational algorithm. In particular, the underestimation of fine-dominated AOD and the scattering angle dependence of dust-dominated AOD are significantly mitigated as results of the new algorithm's improved treatment of aerosol size distribution and dust particle nonsphericity.

Retrieval of Aerosol Optical Properties from Ground-Based Remote Sensing Measurements: Aerosol Asymmetry Factor and Single Scattering Albedo

NASA Astrophysics Data System (ADS)

Qie, L.; Li, Z.; Li, L.; Li, K.; Li, D.; Xu, H.

2018-04-01

The Devaux-Vermeulen-Li method (DVL method) is a simple approach to retrieve aerosol optical parameters from the Sun-sky radiance measurements. This study inherited the previous works of retrieving aerosol single scattering albedo (SSA) and scattering phase function, the DVL method was modified to derive aerosol asymmetric factor (g). To assess the algorithm performance at various atmospheric aerosol conditions, retrievals from AERONET observations were implemented, and the results are compared with AERONET official products. The comparison shows that both the DVL SSA and g were well correlated with those of AERONET. The RMSD and the absolute value of MBD deviations between the SSAs are 0.025 and 0.015 respectively, well below the AERONET declared SSA uncertainty of 0.03 for all wavelengths. For asymmetry factor g, the RMSD deviations are smaller than 0.02 and the absolute values of MBDs smaller than 0.01 at 675, 870 and 1020 nm bands. Then, considering several factors probably affecting retrieval quality (i.e. the aerosol optical depth (AOD), the solar zenith angle, and the sky residual error, sphericity proportion and Ångström exponent), the deviations for SSA and g of these two algorithms were calculated at varying value intervals. Both the SSA and g deviations were found decrease with the AOD and the solar zenith angle, and increase with sky residual error. However, the deviations do not show clear sensitivity to the sphericity proportion and Ångström exponent. This indicated that the DVL algorithm is available for both large, non-spherical particles and spherical particles. The DVL results are suitable for the evaluation of aerosol direct radiative effects of different aerosol types.

Smoke over haze: Comparative analysis of satellite, surface radiometer, and airborne in situ measurements of aerosol optical properties and radiative forcing over the eastern United States

NASA Astrophysics Data System (ADS)

Vant-Hull, Brian; Li, Zhanqing; Taubman, Brett F.; Levy, Robert; Marufu, Lackson; Chang, Fu-Lung; Doddridge, Bruce G.; Dickerson, Russell R.

2005-05-01

In July 2002 Canadian forest fires produced a major smoke episode that blanketed the east coast of the United States. Properties of the smoke aerosol were measured in situ from aircraft, complementing operational Aerosol Robotic Network (AERONET), and Moderate Resolution Imaging Spectroradiometer (MODIS) remotely sensed aerosol retrievals. This study compares single scattering albedo and phase function derived from the in situ measurements and AERONET retrievals in order to evaluate their consistency for application to satellite retrievals of optical depth and radiative forcing. These optical properties were combined with MODIS reflectance observations to calculate optical depth. The use of AERONET optical properties yielded optical depths 2-16% lower than those directly measured by AERONET. The use of in situ-derived optical properties resulted in optical depths 22-43% higher than AERONET measurements. These higher optical depths are attributed primarily to the higher absorption measured in situ, which is roughly twice that retrieved by AERONET. The resulting satellite retrieved optical depths were in turn used to calculate integrated radiative forcing at both the surface and top of atmosphere. Comparisons to surface (Surface Radiation Budget Network (SURFRAD) and ISIS) and to satellite (Clouds and Earth Radiant Energy System CERES) broadband radiometer measurements demonstrate that the use of optical properties derived from the aircraft measurements provided a better broadband forcing estimate (21% error) than those derived from AERONET (33% error). Thus AERONET-derived optical properties produced better fits to optical depth measurements, while in situ properties resulted in better fits to forcing measurements. These apparent inconsistencies underline the significant challenges facing the aerosol community in achieving column closure between narrow and broadband measurements and calculations.

Ozone column density determination from direct irradiance measurements in the ultraviolet performed by a four-channel precision filter radiometer.

PubMed

Ingold, T; Mätzler, C; Wehrli, C; Heimo, A; Kämpfer, N; Philipona, R

2001-04-20

Ultraviolet light was measured at four channels (305, 311, 318, and 332 nm) with a precision filter radiometer (UV-PFR) at Arosa, Switzerland (46.78 degrees , 9.68 degrees , 1850 m above sea level), within the instrument trial phase of a cooperative venture of the Swiss Meteorological Institute (MeteoSwiss) and the Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center. We retrieved ozone-column density data from these direct relative irradiance measurements by adapting the Dobson standard method for all possible single-difference wavelength pairs and one double-difference pair (305/311 and 305/318) under conditions of cloud-free sky and of thin clouds (cloud optical depth <2.5 at 500 nm). All UV-PFR retrievals exhibited excellent agreement with those of collocated Dobson and Brewer spectrophotometers for data obtained during two months in 1999. Combining the results of the error analysis and the findings of the validation, we propose to retrieve ozone-column density by using the 305/311 single difference pair and the double-difference pair. Furthermore, combining both retrievals by building the ratio of ozone-column density yields information that is relevant to data quality control. Estimates of the 305/311 pair agree with measurements by the Dobson and Brewer instruments within 1% for both the mean and the standard deviation of the differences. For the double pair these values are in a range up to 1.6%. However, this pair is less sensitive to model errors. The retrieval performance is also consistent with satellite-based data from the Earth Probe Total Ozone Mapping Spectrometer (EP-TOMS) and the Global Ozone Monitoring Experiment instrument (GOME).

Ozone Column Density Determination From Direct Irradiance Measurements in the Ultraviolet Performed by a Four-Channel Precision Filter Radiometer

NASA Astrophysics Data System (ADS)

Ingold, Thomas; Mätzler, Christian; Wehrli, Christoph; Heimo, Alain; Kämpfer, Niklaus; Philipona, Rolf

2001-04-01

Ultraviolet light was measured at four channels (305, 311, 318, and 332 nm) with a precision filter radiometer (UV-PFR) at Arosa, Switzerland (46.78 , 9.68 , 1850 m above sea level), within the instrument trial phase of a cooperative venture of the Swiss Meteorological Institute (MeteoSwiss) and the Physikalisch-Meteorologisches Observatorium Davos /World Radiation Center. We retrieved ozone-column density data from these direct relative irradiance measurements by adapting the Dobson standard method for all possible single-difference wavelength pairs and one double-difference pair (305 /311 and 305 /318) under conditions of cloud-free sky and of thin clouds (cloud optical depth <2.5 at 500 nm). All UV-PFR retrievals exhibited excellent agreement with those of collocated Dobson and Brewer spectrophotometers for data obtained during two months in 1999. Combining the results of the error analysis and the findings of the validation, we propose to retrieve ozone-column density by using the 305 /311 single difference pair and the double-difference pair. Furthermore, combining both retrievals by building the ratio of ozone-column density yields information that is relevant to data quality control. Estimates of the 305 /311 pair agree with measurements by the Dobson and Brewer instruments within 1% for both the mean and the standard deviation of the differences. For the double pair these values are in a range up to 1.6%. However, this pair is less sensitive to model errors. The retrieval performance is also consistent with satellite-based data from the Earth Probe Total Ozone Mapping Spectrometer (EP-TOMS) and the Global Ozone Monitoring Experiment instrument (GOME).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, R; Jee, K; Sharp, G

Purpose: Proton radiography, which images the patients with the same type of particles that they are to be treated with, is a promising approach for image guidance and range uncertainties reduction. This study aimed to realize quality proton radiography by measuring dose rate functions (DRF) in time domain using a single flat panel and retrieve water equivalent path length (WEPL) from them. Methods: An amorphous silicon flat panel (PaxScan™ 4030CB, Varian Medical Systems, Inc., Palo Alto, CA) was placed behind phantoms to measure DRFs from a proton beam modulated by the modulator wheel. To retrieve WEPL and RSP, calibration modelsmore » based on the intensity of DRFs only, root mean square (RMS) of DRFs only and the intensity weighted RMS were tested. The quality of obtained WEPL images (in terms of spatial resolution and level of details) and the accuracy of WEPL were compared. Results: RSPs for most of the Gammex phantom inserts were retrieved within ± 1% errors by calibration models based on the RMS and intensity weighted RMS. The mean percentage error for all inserts was reduced from 1.08% to 0.75% by matching intensity in the calibration model. In specific cases such as the insert with a titanium rod, the calibration model based on RMS only fails while the that based on intensity weighted RMS is still valid. The quality of retrieved WEPL images were significantly improved for calibration models including intensity matching. Conclusion: For the first time, a flat panel, which is readily available in the beamline for image guidance, was tested to acquire quality proton radiography with WEPL accurately retrieved from it. This technique is promising to be applied for image-guided proton therapy as well as patient specific RSP determination to reduce uncertainties of beam ranges.« less

Accuracy of Geophysical Parameters Derived from AIRS/AMSU as a Function of Fractional Cloud Cover

NASA Technical Reports Server (NTRS)

Susskind, Joel; Barnet, Chris; Blaisdell, John; Iredell, Lena; Keita, Fricky; Kouvaris, Lou; Molnar, Gyula; Chahine, Moustafa

2006-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and layer precipitable water with an rms error of 20 percent, in cases with up to 80 percent effective cloud cover. The basic theory used to analyze Atmospheric InfraRed Sounder/Advanced Microwave Sounding Unit/Humidity Sounder Brazil (AIRS/AMSU/HSB) data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small and the RMS accuracy of lower tropospheric temperature retrieved with 80 percent cloud cover is about 0.5 K poorer than for clear cases. HSB failed in February 2003, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC (Distributed Active Archive Center) in April 2003 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm.

Retrieval per se is not sufficient to trigger reconsolidation of human fear memory.

PubMed

Sevenster, Dieuwke; Beckers, Tom; Kindt, Merel

2012-03-01

Ample evidence suggests that consolidated memories, upon their retrieval, enter a labile state, in which they might be susceptible to change. It has been proposed that memory labilization allows for the integration of relevant information in the established memory trace (memory updating). Memory labilization and reconsolidation do not necessarily occur when a memory is being reactivated, but only when there is something to be learned during memory retrieval (prediction error). Thus, updating of a fear memory trace should not occur under retrieval conditions in which the outcome is fully predictable (no prediction error). Here, we addressed this issue, using a human differential fear conditioning procedure, by eliminating the very possibility of reinforcement of the reminder cue. A previously established fear memory (picture-shock pairings) was reactivated with shock-electrodes attached (Propranolol group, n=18) or unattached (Propranolol No-Shock Expectation group, n=19). We additionally tested a placebo-control group with the shock-electrodes attached (Placebo group, n=18). Reconsolidation was not triggered when nothing could be learned during the reminder trial, as noradrenergic blockade did not affect expression of the fear memory 24h later in the Propranolol No-Shock Expectation group. Only when the outcome of the retrieval cue was not fully predictable, propranolol, contrary to placebo, reduced the startle fear response and prevented the return of fear (reinstatement) the following day. In line with previous studies, skin conductance response and shock expectancies were not affected by propranolol. Remarkably, a double dissociation emerged between the emotional (startle response) and more cognitive expression (expectancies, SCR) of the fear memory. Our findings have important implications for reconsolidation blockade as treatment strategy for emotional disorders. First, fear reducing procedures that target the emotional component of fear memory do not necessarily affect the cognitive component and vice versa. Second, mere retrieval of the fear memory is not sufficient to induce its labilization and reconsolidation. Copyright © 2012 Elsevier Inc. All rights reserved.

Retrieval Failure Contributes to Gist-Based False Recognition

PubMed Central

Guerin, Scott A.; Robbins, Clifford A.; Gilmore, Adrian W.; Schacter, Daniel L.

2011-01-01

People often falsely recognize items that are similar to previously encountered items. This robust memory error is referred to as gist-based false recognition. A widely held view is that this error occurs because the details fade rapidly from our memory. Contrary to this view, an initial experiment revealed that, following the same encoding conditions that produce high rates of gist-based false recognition, participants overwhelmingly chose the correct target rather than its related foil when given the option to do so. A second experiment showed that this result is due to increased access to stored details provided by reinstatement of the originally encoded photograph, rather than to increased attention to the details. Collectively, these results suggest that details needed for accurate recognition are, to a large extent, still stored in memory and that a critical factor determining whether false recognition will occur is whether these details can be accessed during retrieval. PMID:22125357

Validating precision estimates in horizontal wind measurements from a Doppler lidar

DOE PAGES

Newsom, Rob K.; Brewer, W. Alan; Wilczak, James M.; ...

2017-03-30

Results from a recent field campaign are used to assess the accuracy of wind speed and direction precision estimates produced by a Doppler lidar wind retrieval algorithm. The algorithm, which is based on the traditional velocity-azimuth-display (VAD) technique, estimates the wind speed and direction measurement precision using standard error propagation techniques, assuming the input data (i.e., radial velocities) to be contaminated by random, zero-mean, errors. For this study, the lidar was configured to execute an 8-beam plan-position-indicator (PPI) scan once every 12 min during the 6-week deployment period. Several wind retrieval trials were conducted using different schemes for estimating themore » precision in the radial velocity measurements. Here, the resulting wind speed and direction precision estimates were compared to differences in wind speed and direction between the VAD algorithm and sonic anemometer measurements taken on a nearby 300 m tower.« less

Temperature-Dependence of Air-Broadened Line Widths and Shifts in the nu3 Band of Ozone

NASA Technical Reports Server (NTRS)

Smith, Mary A. H.; Rinsland, Curtis P.; Devi, V. Malathy; Benner, D. Chris; Cox, A. M.

2006-01-01

The 9.6-micron bands of O3 are used by many remote-sensing experiments for retrievals of terrestrial atmospheric ozone concentration profiles. Line parameter errors can contribute significantly to the total errors in these retrievals, particularly for nadir-viewing. The McMath-Pierce Fourier transform spectrometer at the National Solar Observatory on Kitt Peak was used to record numerous high-resolution infrared absorption spectra of O3 broadened by various gases at temperatures between 160 and 300 K. Over 30 spectra were analyzed simultaneously using a multispectrum nonlinear least squares fitting technique to determine Lorentz air-broadening and pressure-induced shift coefficients along with their temperature dependences for selected transitions in the 3 fundamental band of (16)O3. We compare the present results with other measurements reported in the literature and with the ozone parameters on the 2000 and 2004 editions of the HITRAN database.