A Bayesian Retrieval of Greenland Ice Sheet Internal Temperature from Ultra-wideband Software-defined Microwave Radiometer (UWBRAD) Measurements

NASA Astrophysics Data System (ADS)

Duan, Y.; Durand, M. T.; Jezek, K. C.; Yardim, C.; Bringer, A.; Aksoy, M.; Johnson, J. T.

2017-12-01

The ultra-wideband software-defined microwave radiometer (UWBRAD) is designed to provide ice sheet internal temperature product via measuring low frequency microwave emission. Twelve channels ranging from 0.5 to 2.0 GHz are covered by the instrument. A Greenland air-borne demonstration was demonstrated in September 2016, provided first demonstration of Ultra-wideband radiometer observations of geophysical scenes, including ice sheets. Another flight is planned for September 2017 for acquiring measurements in central ice sheet. A Bayesian framework is designed to retrieve the ice sheet internal temperature from simulated UWBRAD brightness temperature (Tb) measurements over Greenland flight path with limited prior information of the ground. A 1-D heat-flow model, the Robin Model, was used to model the ice sheet internal temperature profile with ground information. Synthetic UWBRAD Tb observations was generated via the partially coherent radiation transfer model, which utilizes the Robin model temperature profile and an exponential fit of ice density from Borehole measurement as input, and corrupted with noise. The effective surface temperature, geothermal heat flux, the variance of upper layer ice density, and the variance of fine scale density variation at deeper ice sheet were treated as unknown variables within the retrieval framework. Each parameter is defined with its possible range and set to be uniformly distributed. The Markov Chain Monte Carlo (MCMC) approach is applied to make the unknown parameters randomly walk in the parameter space. We investigate whether the variables can be improved over priors using the MCMC approach and contribute to the temperature retrieval theoretically. UWBRAD measurements near camp century from 2016 was also treated with the MCMC to examine the framework with scattering effect. The fine scale density fluctuation is an important parameter. It is the most sensitive yet highly unknown parameter in the estimation framework. Including the fine scale density fluctuation greatly improved the retrieval results. The ice sheet vertical temperature profile, especially the 10m temperature, can be well retrieved via the MCMC process. Future retrieval work will apply the Bayesian approach to UWBRAD airborne measurements.

Polarimetric SAR Interferometry based modeling for tree height and aboveground biomass retrieval in a tropical deciduous forest

NASA Astrophysics Data System (ADS)

Kumar, Shashi; Khati, Unmesh G.; Chandola, Shreya; Agrawal, Shefali; Kushwaha, Satya P. S.

2017-08-01

The regulation of the carbon cycle is a critical ecosystem service provided by forests globally. It is, therefore, necessary to have robust techniques for speedy assessment of forest biophysical parameters at the landscape level. It is arduous and time taking to monitor the status of vast forest landscapes using traditional field methods. Remote sensing and GIS techniques are efficient tools that can monitor the health of forests regularly. Biomass estimation is a key parameter in the assessment of forest health. Polarimetric SAR (PolSAR) remote sensing has already shown its potential for forest biophysical parameter retrieval. The current research work focuses on the retrieval of forest biophysical parameters of tropical deciduous forest, using fully polarimetric spaceborne C-band data with Polarimetric SAR Interferometry (PolInSAR) techniques. PolSAR based Interferometric Water Cloud Model (IWCM) has been used to estimate aboveground biomass (AGB). Input parameters to the IWCM have been extracted from the decomposition modeling of SAR data as well as PolInSAR coherence estimation. The technique of forest tree height retrieval utilized PolInSAR coherence based modeling approach. Two techniques - Coherence Amplitude Inversion (CAI) and Three Stage Inversion (TSI) - for forest height estimation are discussed, compared and validated. These techniques allow estimation of forest stand height and true ground topography. The accuracy of the forest height estimated is assessed using ground-based measurements. PolInSAR based forest height models showed enervation in the identification of forest vegetation and as a result height values were obtained in river channels and plain areas. Overestimation in forest height was also noticed at several patches of the forest. To overcome this problem, coherence and backscatter based threshold technique is introduced for forest area identification and accurate height estimation in non-forested regions. IWCM based modeling for forest AGB retrieval showed R2 value of 0.5, RMSE of 62.73 (t ha-1) and a percent accuracy of 51%. TSI based PolInSAR inversion modeling showed the most accurate result for forest height estimation. The correlation between the field measured forest height and the estimated tree height using TSI technique is 62% with an average accuracy of 91.56% and RMSE of 2.28 m. The study suggested that PolInSAR coherence based modeling approach has significant potential for retrieval of forest biophysical parameters.

Studying the Relationship between High-Latitude Geomagnetic Activity and Parameters of Interplanetary Magnetic Clouds with the Use of Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Barkhatov, N. A.; Revunov, S. E.; Vorobjev, V. G.; Yagodkina, O. I.

2018-03-01

The cause-and-effect relations of the dynamics of high-latitude geomagnetic activity (in terms of the AL index) and the type of the magnetic cloud of the solar wind are studied with the use of artificial neural networks. A recurrent neural network model has been created based on the search for the optimal physically coupled input and output parameters characterizing the action of a plasma flux belonging to a certain magnetic cloud type on the magnetosphere. It has been shown that, with IMF components as input parameters of neural networks with allowance for a 90-min prehistory, it is possible to retrieve the AL sequence with an accuracy to 80%. The successful retrieval of the AL dynamics by the used data indicates the presence of a close nonlinear connection of the AL index with cloud parameters. The created neural network models can be applied with high efficiency to retrieve the AL index, both in periods of isolated magnetospheric substorms and in periods of the interaction between the Earth's magnetosphere and magnetic clouds of different types. The developed model of AL index retrieval can be used to detect magnetic clouds.

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.

High Vertically Resolved Atmospheric and Surface/Cloud Parameters Retrieved with Infrared Atmospheric Sounding Interferometer (IASI)

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, WIlliam L.; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

2008-01-01

The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the cloud-free and/or clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals are achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals will be further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated indicating a high vertical structure of atmosphere is retrieved.

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)..

Kalman filters for assimilating near-surface observations into the Richards equation - Part 2: A dual filter approach for simultaneous retrieval of states and parameters

NASA Astrophysics Data System (ADS)

Medina, H.; Romano, N.; Chirico, G. B.

2014-07-01

This study presents a dual Kalman filter (DSUKF - dual standard-unscented Kalman filter) for retrieving states and parameters controlling the soil water dynamics in a homogeneous soil column, by assimilating near-surface state observations. The DSUKF couples a standard Kalman filter for retrieving the states of a linear solver of the Richards equation, and an unscented Kalman filter for retrieving the parameters of the soil hydraulic functions, which are defined according to the van Genuchten-Mualem closed-form model. The accuracy and the computational expense of the DSUKF are compared with those of the dual ensemble Kalman filter (DEnKF) implemented with a nonlinear solver of the Richards equation. Both the DSUKF and the DEnKF are applied with two alternative state-space formulations of the Richards equation, respectively differentiated by the type of variable employed for representing the states: either the soil water content (θ) or the soil water matric pressure head (h). The comparison analyses are conducted with reference to synthetic time series of the true states, noise corrupted observations, and synthetic time series of the meteorological forcing. The performance of the retrieval algorithms are examined accounting for the effects exerted on the output by the input parameters, the observation depth and assimilation frequency, as well as by the relationship between retrieved states and assimilated variables. The uncertainty of the states retrieved with DSUKF is considerably reduced, for any initial wrong parameterization, with similar accuracy but less computational effort than the DEnKF, when this is implemented with ensembles of 25 members. For ensemble sizes of the same order of those involved in the DSUKF, the DEnKF fails to provide reliable posterior estimates of states and parameters. The retrieval performance of the soil hydraulic parameters is strongly affected by several factors, such as the initial guess of the unknown parameters, the wet or dry range of the retrieved states, the boundary conditions, as well as the form (h-based or θ-based) of the state-space formulation. Several analyses are reported to show that the identifiability of the saturated hydraulic conductivity is hindered by the strong correlation with other parameters of the soil hydraulic functions defined according to the van Genuchten-Mualem closed-form model.

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.

Mesospheric Water Vapor Retrieved from SABER/TIMED Measurements

NASA Technical Reports Server (NTRS)

Feofilov, Arte, G.; Yankovsky, Valentine A.; Marshall, Benjamin T.; Russell, J. M., III; Pesnell, W. D.; Kutepov, Alexander A.; Goldberg, Richard A.; Gordley, Larry L.; Petelina, Svetlama; Mauilova, Rada O.;

Retrieving the optical parameters of biological tissues using diffuse reflectance spectroscopy and Fourier series expansions. I. theory and application.

PubMed

Muñoz Morales, Aarón A; Vázquez Y Montiel, Sergio

2012-10-01

The determination of optical parameters of biological tissues is essential for the application of optical techniques in the diagnosis and treatment of diseases. Diffuse Reflection Spectroscopy is a widely used technique to analyze the optical characteristics of biological tissues. In this paper we show that by using diffuse reflectance spectra and a new mathematical model we can retrieve the optical parameters by applying an adjustment of the data with nonlinear least squares. In our model we represent the spectra using a Fourier series expansion finding mathematical relations between the polynomial coefficients and the optical parameters. In this first paper we use spectra generated by the Monte Carlo Multilayered Technique to simulate the propagation of photons in turbid media. Using these spectra we determine the behavior of Fourier series coefficients when varying the optical parameters of the medium under study. With this procedure we find mathematical relations between Fourier series coefficients and optical parameters. Finally, the results show that our method can retrieve the optical parameters of biological tissues with accuracy that is adequate for medical applications.

Relative skills of soil moisture and vegetation optical depth retrievals for agricultural drought monitoring

USDA-ARS?s Scientific Manuscript database

Soil moisture condition is an important indicator for agricultural drought monitoring. Through the Land Parameter Retrieval Model (LPRM), vegetation optical depth (VOD) as well as surface soil moisture (SM) can be retrieved simultaneously from brightness temperature observations from the Advanced Mi...

Customised search and comparison of in situ, satellite and model data for ocean modellers

NASA Astrophysics Data System (ADS)

Hamre, Torill; Vines, Aleksander; Lygre, Kjetil

2014-05-01

For the ocean modelling community, the amount of available data from historical and upcoming in situ sensor networks and satellite missions, provides an rich opportunity to validate and improve their simulation models. However, the problem of making the different data interoperable and intercomparable remains, due to, among others, differences in terminology and format used by different data providers and the different granularity provided by e.g. in situ data and ocean models. The GreenSeas project (Development of global plankton data base and model system for eco-climate early warning) aims to advance the knowledge and predictive capacities of how marine ecosystems will respond to global change. In the project, one specific objective has been to improve the technology for accessing historical plankton and associated environmental data sets, along with earth observation data and simulation outputs. To this end, we have developed a web portal enabling ocean modellers to easily search for in situ or satellite data overlapping in space and time, and compare the retrieved data with their model results. The in situ data are retrieved from a geo-spatial repository containing both historical and new physical, biological and chemical parameters for the Southern Ocean, Atlantic, Nordic Seas and the Arctic. The satellite-derived quantities of similar parameters from the same areas are retrieved from another geo-spatial repository established in the project. Both repositories are accessed through standard interfaces, using the Open Geospatial Consortium (OGC) Web Map Service (WMS) and Web Feature Service (WFS), and OPeNDAP protocols, respectively. While the developed data repositories use standard terminology to describe the parameters, especially the measured in situ biological parameters are too fine grained to be immediately useful for modelling purposes. Therefore, the plankton parameters were grouped according to category, size and if available by element. This grouping was reflected in the web portal's graphical user interface, where the groups and subgroups were organized in a tree structure, enabling the modeller to quickly get an overview of available data, going into more detail (subgroups) if needed or staying at a higher level of abstraction (merging the parameters below) if this provided a better base for comparison with the model parameters. Once a suitable level of detail, as determined by the modeller, was decided, the system would retrieve available in situ parameters. The modellers could then select among the pre-defined models or upload his own model forecast file (in NetCDF/CF format), for comparison with the retrieved in situ data. The comparison can be shown in different kinds of plots (e.g. scatter plots), through simple statistical measures or near-coincident values of in situ of model points can be exported for further analysis in the modeller's own tools. During data search and presentation, the modeller can determine both query criteria and what associated metadata to include in the display and export of the retrieved data. Satellite-derived parameters can be queried and compared with model results in the same manner. With the developed prototype system, we have demonstrated that a customised tool for searching, presenting, comparing and exporting ocean data from multiple platforms (in situ, satellite, model), makes it easy to compare model results with independent observations. With further enhancement of functionality and inclusion of more data, we believe the resulting system can greatly benefit the wider community of ocean modellers looking for data and tools to validate their models.

Assimilation of concentration measurements for retrieving multiple point releases in atmosphere: A least-squares approach to inverse modelling

NASA Astrophysics Data System (ADS)

Singh, Sarvesh Kumar; Rani, Raj

2015-10-01

The study addresses the identification of multiple point sources, emitting the same tracer, from their limited set of merged concentration measurements. The identification, here, refers to the estimation of locations and strengths of a known number of simultaneous point releases. The source-receptor relationship is described in the framework of adjoint modelling by using an analytical Gaussian dispersion model. A least-squares minimization framework, free from an initialization of the release parameters (locations and strengths), is presented to estimate the release parameters. This utilizes the distributed source information observable from the given monitoring design and number of measurements. The technique leads to an exact retrieval of the true release parameters when measurements are noise free and exactly described by the dispersion model. The inversion algorithm is evaluated using the real data from multiple (two, three and four) releases conducted during Fusion Field Trials in September 2007 at Dugway Proving Ground, Utah. The release locations are retrieved, on average, within 25-45 m of the true sources with the distance from retrieved to true source ranging from 0 to 130 m. The release strengths are also estimated within a factor of three to the true release rates. The average deviations in retrieval of source locations are observed relatively large in two release trials in comparison to three and four release trials.

Waveform-based spaceborne GNSS-R wind speed observation: Demonstration and analysis using UK TechDemoSat-1 data

NASA Astrophysics Data System (ADS)

Wang, Feng; Yang, Dongkai; Zhang, Bo; Li, Weiqiang

2018-03-01

This paper explores two types of mathematical functions to fit single- and full-frequency waveform of spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R), respectively. The metrics of the waveforms, such as the noise floor, peak magnitude, mid-point position of the leading edge, leading edge slope and trailing edge slope, can be derived from the parameters of the proposed models. Because the quality of the UK TDS-1 data is not at the level required by remote sensing mission, the waveforms buried in noise or from ice/land are removed by defining peak-to-mean ratio, cosine similarity of the waveform before wind speed are retrieved. The single-parameter retrieval models are developed by comparing the peak magnitude, leading edge slope and trailing edge slope derived from the parameters of the proposed models with in situ wind speed from the ASCAT scatterometer. To improve the retrieval accuracy, three types of multi-parameter observations based on the principle component analysis (PCA), minimum variance (MV) estimator and Back Propagation (BP) network are implemented. The results indicate that compared to the best results of the single-parameter observation, the approaches based on the principle component analysis and minimum variance could not significantly improve retrieval accuracy, however, the BP networks obtain improvement with the RMSE of 2.55 m/s and 2.53 m/s for single- and full-frequency waveform, respectively.

Data Mining for Efficient and Accurate Large Scale Retrieval of Geophysical Parameters

NASA Astrophysics Data System (ADS)

Obradovic, Z.; Vucetic, S.; Peng, K.; Han, B.

2004-12-01

Our effort is devoted to developing data mining technology for improving efficiency and accuracy of the geophysical parameter retrievals by learning a mapping from observation attributes to the corresponding parameters within the framework of classification and regression. We will describe a method for efficient learning of neural network-based classification and regression models from high-volume data streams. The proposed procedure automatically learns a series of neural networks of different complexities on smaller data stream chunks and then properly combines them into an ensemble predictor through averaging. Based on the idea of progressive sampling the proposed approach starts with a very simple network trained on a very small chunk and then gradually increases the model complexity and the chunk size until the learning performance no longer improves. Our empirical study on aerosol retrievals from data obtained with the MISR instrument mounted at Terra satellite suggests that the proposed method is successful in learning complex concepts from large data streams with near-optimal computational effort. We will also report on a method that complements deterministic retrievals by constructing accurate predictive algorithms and applying them on appropriately selected subsets of observed data. The method is based on developing more accurate predictors aimed to catch global and local properties synthesized in a region. The procedure starts by learning the global properties of data sampled over the entire space, and continues by constructing specialized models on selected localized regions. The global and local models are integrated through an automated procedure that determines the optimal trade-off between the two components with the objective of minimizing the overall mean square errors over a specific region. Our experimental results on MISR data showed that the combined model can increase the retrieval accuracy significantly. The preliminary results on various large heterogeneous spatial-temporal datasets provide evidence that the benefits of the proposed methodology for efficient and accurate learning exist beyond the area of retrieval of geophysical parameters.

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).

Surface and Atmospheric Parameter Retrieval From AVIRIS Data: The Importance of Non-Linear Effects

NASA Technical Reports Server (NTRS)

Green Robert O.; Moreno, Jose F.

1996-01-01

AVIRIS data represent a new and important approach for the retrieval of atmospheric and surface parameters from optical remote sensing data. Not only as a test for future space systems, but also as an operational airborne remote sensing system, the development of algorithms to retrieve information from AVIRIS data is an important step to these new approaches and capabilities. Many things have been learned since AVIRIS became operational, and the successive technical improvements in the hardware and the more sophisticated calibration techniques employed have increased the quality of the data to the point of almost meeting optimum user requirements. However, the potential capabilities of imaging spectrometry over the standard multispectral techniques have still not been fully demonstrated. Reasons for this are the technical difficulties in handling the data, the critical aspect of calibration for advanced retrieval methods, and the lack of proper models with which to invert the measured AVIRIS radiances in all the spectral channels. To achieve the potential of imaging spectrometry, these issues must be addressed. In this paper, an algorithm to retrieve information about both atmospheric and surface parameters from AVIRIS data, by using model inversion techniques, is described. Emphasis is put on the derivation of the model itself as well as proper inversion techniques, robust to noise in the data and an inadequate ability of the model to describe natural variability in the data. The problem of non-linear effects is addressed, as it has been demonstrated to be a major source of error in the numerical values retrieved by more simple, linear-based approaches. Non-linear effects are especially critical for the retrieval of surface parameters where both scattering and absorption effects are coupled, as well as in the cases of significant multiple-scattering contributions. However, sophisticated modeling approaches can handle such non-linear effects, which are especially important over vegetated surfaces. All the data used in this study were acquired during the 1991 Multisensor Airborne Campaign (MAC-Europe), as part of the European Field Experiment on a Desertification-threatened Area (EFEDA), carried out in Spain in June-July 1991.

Retrieving relevant time-course experiments: a study on Arabidopsis microarrays.

PubMed

Şener, Duygu Dede; Oğul, Hasan

2016-06-01

Understanding time-course regulation of genes in response to a stimulus is a major concern in current systems biology. The problem is usually approached by computational methods to model the gene behaviour or its networked interactions with the others by a set of latent parameters. The model parameters can be estimated through a meta-analysis of available data obtained from other relevant experiments. The key question here is how to find the relevant experiments which are potentially useful in analysing current data. In this study, the authors address this problem in the context of time-course gene expression experiments from an information retrieval perspective. To this end, they introduce a computational framework that takes a time-course experiment as a query and reports a list of relevant experiments retrieved from a given repository. These retrieved experiments can then be used to associate the environmental factors of query experiment with the findings previously reported. The model is tested using a set of time-course Arabidopsis microarrays. The experimental results show that relevant experiments can be successfully retrieved based on content similarity.

Results and Validation of MODIS Aerosol Retrievals Over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, Lorraine; Einaudi, Franco (Technical Monitor)

2001-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

Results and Validation of MODIS Aerosol Retrievals over Land and Ocean

NASA Technical Reports Server (NTRS)

Remer, L. A.; Kaufman, Y. J.; Tanre, D.; Ichoku, C.; Chu, D. A.; Mattoo, S.; Levy, R.; Martins, J. V.; Li, R.-R.; Einaudi, Franco (Technical Monitor)

2000-01-01

The MODerate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Terra spacecraft has been retrieving aerosol parameters since late February 2000. Initial qualitative checking of the products showed very promising results including matching of land and ocean retrievals at coastlines. Using AERONET ground-based radiometers as our primary validation tool, we have established quantitative validation as well. Our results show that for most aerosol types, the MODIS products fall within the pre-launch estimated uncertainties. Surface reflectance and aerosol model assumptions appear to be sufficiently accurate for the optical thickness retrieval. Dust provides a possible exception, which may be due to non-spherical effects. Over ocean the MODIS products include information on particle size, and these parameters are also validated with AERONET retrievals.

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.

A Four–Component Model of Age–Related Memory Change

PubMed Central

Healey, M. Karl; Kahana, Michael J.

2015-01-01

We develop a novel, computationally explicit, theory of age–related memory change within the framework of the context maintenance and retrieval (CMR2) model of memory search. We introduce a set of benchmark findings from the free recall and recognition tasks that includes aspects of memory performance that show both age-related stability and decline. We test aging theories by lesioning the corresponding mechanisms in a model fit to younger adult free recall data. When effects are considered in isolation, many theories provide an adequate account, but when all effects are considered simultaneously, the existing theories fail. We develop a novel theory by fitting the full model (i.e., allowing all parameters to vary) to individual participants and comparing the distributions of parameter values for older and younger adults. This theory implicates four components: 1) the ability to sustain attention across an encoding episode, 2) the ability to retrieve contextual representations for use as retrieval cues, 3) the ability to monitor retrievals and reject intrusions, and 4) the level of noise in retrieval competitions. We extend CMR2 to simulate a recognition memory task using the same mechanisms the free recall model uses to reject intrusions. Without fitting any additional parameters, the four–component theory that accounts for age differences in free recall predicts the magnitude of age differences in recognition memory accuracy. Confirming a prediction of the model, free recall intrusion rates correlate positively with recognition false alarm rates. Thus we provide a four–component theory of a complex pattern of age differences across two key laboratory tasks. PMID:26501233

Thermodynamic and cloud parameter retrieval using infrared spectral data

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Huang, Hung-Lung A.; Li, Jun; McGill, Matthew J.; Mango, Stephen A.

2005-01-01

High-resolution infrared radiance spectra obtained from near nadir observations provide atmospheric, surface, and cloud property information. A fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The retrieval algorithm is presented along with its application to recent field experiment data from the NPOESS Airborne Sounding Testbed - Interferometer (NAST-I). The retrieval accuracy dependence on cloud properties is discussed. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with an accuracy of approximately 1.0 km. Preliminary NAST-I retrieval results from the recent Atlantic-THORPEX Regional Campaign (ATReC) are presented and compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL).

Estimation of Multiple Parameters over Vegetated Surfaces by Integrating Optical-Thermal Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Ma, H.

2016-12-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface parameters are generally parameter-specific algorithms and are based on instantaneous physical models, which result in spatial, temporal and physical inconsistencies in current global products. Besides, optical and Thermal Infrared (TIR) remote sensing observations are usually separated to use based on different models , and the Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal that mixes both reflected and emitted fluxes. In this paper, we proposed a unified algorithm for simultaneously retrieving a total of seven land surface parameters, including Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Temperature (LST), surface emissivity, downward and upward longwave radiation, by exploiting remote sensing observations from visible to TIR domain based on a common physical Radiative Transfer (RT) model and a data assimilation framework. The coupled PROSPECT-VISIR and 4SAIL RT model were used for canopy reflectance modeling. At first, LAI was estimated using a data assimilation method that combines MODIS daily reflectance observation and a phenology model. The estimated LAI values were then input into the RT model to simulate surface spectral emissivity and surface albedo. Besides, the background albedo and the transmittance of solar radiation, and the canopy albedo were also calculated to produce FAPAR. Once the spectral emissivity of seven MODIS MIR to TIR bands were retrieved, LST can be estimated from the atmospheric corrected surface radiance by exploiting an optimization method. At last, the upward longwave radiation were estimated using the retrieved LST, broadband emissivity (converted from spectral emissivity) and the downward longwave radiation (modeled by MODTRAN). These seven parameters were validated over several representative sites with different biome type, and compared with MODIS and GLASS product. Results showed that this unified inversion algorithm can retrieve temporally complete and physical consistent land surface parameters with high accuracy.

Calibration to improve forward model simulation of microwave emissivity at GPM frequencies over the U.S. Southern Great Plains

PubMed Central

Harrison, Kenneth W.; Tian, Yudong; Peters-Lidard, Christa D.; Ringerud, Sarah; Kumar, Sujay V.

2018-01-01

Better estimation of land surface microwave emissivity promises to improve over-land precipitation retrievals in the GPM era. Forward models of land microwave emissivity are available but have suffered from poor parameter specification and limited testing. Here, forward models are calibrated and the accompanying change in predictive power is evaluated. With inputs (e.g., soil moisture) from the Noah land surface model and applying MODIS LAI data, two microwave emissivity models are tested, the Community Radiative Transfer Model (CRTM) and Community Microwave Emission Model (CMEM). The calibration is conducted with the NASA Land Information System (LIS) parameter estimation subsystem using AMSR-E based emissivity retrievals for the calibration dataset. The extent of agreement between the modeled and retrieved estimates is evaluated using the AMSR-E retrievals for a separate 7-year validation period. Results indicate that calibration can significantly improve the agreement, simulating emissivity with an across-channel average root-mean-square-difference (RMSD) of about 0.013, or about 20% lower than if relying on daily estimates based on climatology. The results also indicate that calibration of the microwave emissivity model alone, as was done in prior studies, results in as much as 12% higher across-channel average RMSD, as compared to joint calibration of the land surface and microwave emissivity models. It remains as future work to assess the extent to which the improvements in emissivity estimation translate into improvements in precipitation retrieval accuracy. PMID:29795962

Cloud, Aerosol, and Volcanic Ash Retrievals Using ASTR and SLSTR with ORAC

NASA Astrophysics Data System (ADS)

McGarragh, Gregory; Poulsen, Caroline; Povey, Adam; Thomas, Gareth; Christensen, Matt; Sus, Oliver; Schlundt, Cornelia; Stapelberg, Stefan; Stengel, Martin; Grainger, Don

2015-12-01

The Optimal Retrieval of Aerosol and Cloud (ORAC) is a generalized optimal estimation system that retrieves cloud, aerosol and volcanic ash parameters using satellite imager measurements in the visible to infrared. Use of the same algorithm for different sensors and parameters leads to consistency that facilitates inter-comparison and interaction studies. ORAC currently supports ATSR, AVHRR, MODIS and SEVIRI. In this proceeding we discuss the ORAC retrieval algorithm applied to ATSR data including the retrieval methodology, the forward model, uncertainty characterization and discrimination/classification techniques. Application of ORAC to SLSTR data is discussed including the additional features that SLSTR provides relative to the ATSR heritage. The ORAC level 2 and level 3 results are discussed and an application of level 3 results to the study of cloud/aerosol interactions is presented.

Modeling the bidirectional reflectance distribution function of mixed finite plant canopies and soil

NASA Technical Reports Server (NTRS)

Schluessel, G.; Dickinson, R. E.; Privette, J. L.; Emery, W. J.; Kokaly, R.

1994-01-01

An analytical model of the bidirectional reflectance for optically semi-infinite plant canopies has been extended to describe the reflectance of finite depth canopies contributions from the underlying soil. The model depends on 10 independent parameters describing vegetation and soil optical and structural properties. The model is inverted with a nonlinear minimization routine using directional reflectance data for lawn (leaf area index (LAI) is equal to 9.9), soybeans (LAI, 2.9) and simulated reflectance data (LAI, 1.0) from a numerical bidirectional reflectance distribution function (BRDF) model (Myneni et al., 1988). While the ten-parameter model results in relatively low rms differences for the BRDF, most of the retrieved parameters exhibit poor stability. The most stable parameter was the single-scattering albedo of the vegetation. Canopy albedo could be derived with an accuracy of less than 5% relative error in the visible and less than 1% in the near-infrared. Sensitivity were performed to determine which of the 10 parameters were most important and to assess the effects of Gaussian noise on the parameter retrievals. Out of the 10 parameters, three were identified which described most of the BRDF variability. At low LAI values the most influential parameters were the single-scattering albedos (both soil and vegetation) and LAI, while at higher LAI values (greater than 2.5) these shifted to the two scattering phase function parameters for vegetation and the single-scattering albedo of the vegetation. The three-parameter model, formed by fixing the seven least significant parameters, gave higher rms values but was less sensitive to noise in the BRDF than the full ten-parameter model. A full hemispherical reflectance data set for lawn was then interpolated to yield BRDF values corresponding to advanced very high resolution radiometer (AVHRR) scan geometries collected over a period of nine days. The resulting parameters and BRDFs are similar to those for the full sampling geometry, suggesting that the limited geometry of AVHRR measurements might be used to reliably retrieve BRDF and canopy albedo with this model.

Estimating effective roughness parameters of the L-MEB model for soil moisture retrieval using passive microwave observations from SMAPVEX12

USDA-ARS?s Scientific Manuscript database

Although there have been efforts to improve existing soil moisture retrieval algorithms, the ability to estimate soil moisture from passive microwave observations is still hampered by problems in accurately modeling the observed microwave signal. This paper focuses on the estimation of effective sur...

Evaluation of the tau-omega model for passive microwave soil moisture retrieval using SMAPEx data sets

USDA-ARS?s Scientific Manuscript database

The parameters used for passive soil moisture retrieval algorithms reported in the literature encompass a wide range, leading to a large uncertainty in the applicability of those values. This paper presents an evaluation of the proposed parameterizations of the tau-omega model from 1) SMAP ATBD for ...

Snow Water Equivalent Retrieval By Markov Chain Monte Carlo Based on Memls and Hut Snow Emission Model

NASA Astrophysics Data System (ADS)

Pan, J.; Durand, M. T.; Vanderjagt, B. J.

2014-12-01

The Markov chain Monte Carlo (MCMC) method had been proved to be successful in snow water equivalent retrieval based on synthetic point-scale passive microwave brightness temperature (TB) observations. This method needs only general prior information about distribution of snow parameters, and could estimate layered snow properties, including the thickness, temperature, density and snow grain size (or exponential correlation length) of each layer. In this study, the multi-layer HUT (Helsinki University of Technology) model and the MEMLS (Microwave Emission Model of Layered Snowpacks) will be used as observation models to assimilate the observed TB into snow parameter prediction. Previous studies had shown that the multi-layer HUT model tends to underestimate TB at 37 GHz for deep snow, while the MEMLS does not show sensitivity of model bias to snow depth. Therefore, results using HUT model and MEMLS will be compared to see how the observation model will influence the retrieval of snow parameters. The radiometric measurements at 10.65, 18.7, 36.5 and 90 GHz at Sodankyla, Finland will be used as MCMC input, and the statistics of all snow property measurement will be used to calculate the prior information. 43 dry snowpits with complete measurements of all snow parameters will be used for validation. The entire dataset are from NorSREx (Nordic Snow Radar Experiment) experiments carried out by Juha Lemmetyinen, Anna Kontu and Jouni Pulliainen in FMI in 2009-2011 winters, and continued two more winters from 2011 to Spring of 2013. Besides the snow thickness and snow density that are directly related to snow water equivalent, other parameters will be compared with observations, too. For thin snow, the previous studies showed that influence of underlying soil is considerable, especially when the soil is half frozen with part of unfrozen liquid water and part of ice. Therefore, this study will also try to employ a simple frozen soil permittivity model to improve the performance of retrieval. The behavior of the Markov chain in soil parameters will be studied.

Real-time Retrieving Atmospheric Parameters from Multi-GNSS Constellations

NASA Astrophysics Data System (ADS)

Li, X.; Zus, F.; Lu, C.; Dick, G.; Ge, M.; Wickert, J.; Schuh, H.

2016-12-01

The multi-constellation GNSS (e.g. GPS, GLONASS, Galileo, and BeiDou) bring great opportunities and challenges for real-time retrieval of atmospheric parameters for supporting numerical weather prediction (NWP) nowcasting or severe weather event monitoring. In this study, the observations from different GNSS are combined together for atmospheric parameter retrieving based on the real-time precise point positioning technique. The atmospheric parameters retrieved from multi-GNSS observations, including zenith total delay (ZTD), integrated water vapor (IWV), horizontal gradient (especially high-resolution gradient estimates) and slant total delay (STD), are carefully analyzed and evaluated by using the VLBI, radiosonde, water vapor radiometer and numerical weather model to independently validate the performance of individual GNSS and also demonstrate the benefits of multi-constellation GNSS for real-time atmospheric monitoring. Numerous results show that the multi-GNSS processing can provide real-time atmospheric products with higher accuracy, stronger reliability and better distribution, which would be beneficial for atmospheric sounding systems, especially for nowcasting of extreme weather.

A retrieval algorithm of hydrometer profile for submillimeter-wave radiometer

NASA Astrophysics Data System (ADS)

Liu, Yuli; Buehler, Stefan; Liu, Heguang

2017-04-01

Vertical profiles of particle microphysics perform vital functions for the estimation of climatic feedback. This paper proposes a new algorithm to retrieve the profile of the parameters of the hydrometeor(i.e., ice, snow, rain, liquid cloud, graupel) based on passive submillimeter-wave measurements. These parameters include water content and particle size. The first part of the algorithm builds the database and retrieves the integrated quantities. Database is built up by Atmospheric Radiative Transfer Simulator(ARTS), which uses atmosphere data to simulate the corresponding brightness temperature. Neural network, trained by the precalculated database, is developed to retrieve the water path for each type of particles. The second part of the algorithm analyses the statistical relationship between water path and vertical parameters profiles. Based on the strong dependence existing between vertical layers in the profiles, Principal Component Analysis(PCA) technique is applied. The third part of the algorithm uses the forward model explicitly to retrieve the hydrometeor profiles. Cost function is calculated in each iteration, and Differential Evolution(DE) algorithm is used to adjust the parameter values during the evolutionary process. The performance of this algorithm is planning to be verified for both simulation database and measurement data, by retrieving profiles in comparison with the initial one. Results show that this algorithm has the ability to retrieve the hydrometeor profiles efficiently. The combination of ARTS and optimization algorithm can get much better results than the commonly used database approach. Meanwhile, the concept that ARTS can be used explicitly in the retrieval process shows great potential in providing solution to other retrieval problems.

Retrieving Liquid Water Path and Precipitable Water Vapor from the Atmospheric Radiation Measurement (ARM) Microwave Radiometers

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

Turner, David D.; Clough, Shepard A.; Liljegren, James C.

2007-11-01

Ground-based two-channel microwave radiometers have been used for over 15 years by the Atmospheric Radiation Measurement (ARM) program to provide observations of downwelling emitted radiance from which precipitable water vapor (PWV) and liquid water path (LWP) – twp geophysical parameters critical for many areas of atmospheric research – are retrieved. An algorithm that utilizes two advanced retrieval techniques, a computationally expensive physical-iterative approach and an efficient statistical method, has been developed to retrieve these parameters. An important component of this Microwave Retrieval (MWRRET) algorithm is the determination of small (< 1K) offsets that are subtracted from the observed brightness temperaturesmore » before the retrievals are performed. Accounting for these offsets removes systematic biases from the observations and/or the model spectroscopy necessary for the retrieval, significantly reducing the systematic biases in the retrieved LWP. The MWRRET algorithm provides significantly more accurate retrievals than the original ARM statistical retrieval which uses monthly retrieval coefficients. By combining the two retrieval methods with the application of brightness temperature offsets to reduce the spurious LWP bias in clear skies, the MWRRET algorithm provides significantly better retrievals of PWV and LWP from the ARM 2-channel microwave radiometers compared to the original ARM product.« less

Surface Roughness Retrieval By Inversion Of Hapke Model: A Multi-scale Approach

NASA Astrophysics Data System (ADS)

Labarre, S.; Ferrari, C. C.; Jacquemoud, S.

2015-12-01

Surface roughness is a key property of soils that affects the various processes involved in their evolution such as solar absorption, erosion or moisture, both on Earth and other Solar System surfaces. In the 80's, B.Hapke provided an approximate analytic solution for the bidirectional reflectance distribution function (BRDF) of a particulate medium and, later on, included the effect of surface roughness as a correction factor for the BRDF of a smooth surface. The effect of roughness on the BRDF is modeled as a shadowing function of the so-called roughness parameter, which is the mean slope angle of the facets composing the surface integrated over all scales from the sub-millimeter to the kilometer scales. Hapke model is widely used in planetary sciences to retrieve the roughness parameter from observed BRDFs. Yet the physical meaning of the retrieved roughness is not clear as the scale at which it happens is not defined. This work aims at understanding the relative impact of the roughness defined at each scale to the BRDF in order to test the ability of the singly retrieved roughness parameter at describing the ground truth. We propose to perform a wavelet analysis on meter-sized digital elevation models (DEM) generated from various volcanic and sedimentary terrains at high-mm-scale spatial resolution. It consists in splitting the DEM in several spatial frequencies and in simulating the BRDF at each scale with a ray-tracing code. Also the global BRDF is simulated so that the relative contribution of each scale can be studied. Then the Hapke model is fitted to the global BRDF to retrieve the roughness parameter. We will expose and discuss the results of this study. Figure: BRDF of a'a lava DEM simulated at varying azimut (φi) and incidence angles (i), in the principal plan. The direction of the light source is given by the colored squares. Mean slope angle of the surface is 36°.

[Simulation of vegetation indices optimizing under retrieval of vegetation biochemical parameters based on PROSPECT + SAIL model].

PubMed

Wu, Ling; Liu, Xiang-Nan; Zhou, Bo-Tian; Liu, Chuan-Hao; Li, Lu-Feng

2012-12-01

This study analyzed the sensitivities of three vegetation biochemical parameters [chlorophyll content (Cab), leaf water content (Cw), and leaf area index (LAI)] to the changes of canopy reflectance, with the effects of each parameter on the wavelength regions of canopy reflectance considered, and selected three vegetation indices as the optimization comparison targets of cost function. Then, the Cab, Cw, and LAI were estimated, based on the particle swarm optimization algorithm and PROSPECT + SAIL model. The results showed that retrieval efficiency with vegetation indices as the optimization comparison targets of cost function was better than that with all spectral reflectance. The correlation coefficients (R2) between the measured and estimated values of Cab, Cw, and LAI were 90.8%, 95.7%, and 99.7%, and the root mean square errors of Cab, Cw, and LAI were 4.73 microg x cm(-2), 0.001 g x cm(-2), and 0.08, respectively. It was suggested that to adopt vegetation indices as the optimization comparison targets of cost function could effectively improve the efficiency and precision of the retrieval of biochemical parameters based on PROSPECT + SAIL model.

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 1: A cloud ensemble/radiative parameterization for sensor response (report version)

NASA Technical Reports Server (NTRS)

Olson, William S.; Raymond, William H.

1990-01-01

The physical retrieval of geophysical parameters based upon remotely sensed data requires a sensor response model which relates the upwelling radiances that the sensor observes to the parameters to be retrieved. In the retrieval of precipitation water contents from satellite passive microwave observations, the sensor response model has two basic components. First, a description of the radiative transfer of microwaves through a precipitating atmosphere must be considered, because it is necessary to establish the physical relationship between precipitation water content and upwelling microwave brightness temperature. Also the spatial response of the satellite microwave sensor (or antenna pattern) must be included in the description of sensor response, since precipitation and the associated brightness temperature field can vary over a typical microwave sensor resolution footprint. A 'population' of convective cells, as well as stratiform clouds, are simulated using a computationally-efficient multi-cylinder cloud model. Ensembles of clouds selected at random from the population, distributed over a 25 km x 25 km model domain, serve as the basis for radiative transfer calculations of upwelling brightness temperatures at the SSM/I frequencies. Sensor spatial response is treated explicitly by convolving the upwelling brightness temperature by the domain-integrated SSM/I antenna patterns. The sensor response model is utilized in precipitation water content retrievals.

An advanced retrieval algorithm for greenhouse gases using polarization information measured by GOSAT TANSO-FTS SWIR I: Simulation study

NASA Astrophysics Data System (ADS)

Kikuchi, N.; Yoshida, Y.; Uchino, O.; Morino, I.; Yokota, T.

2016-11-01

We present an algorithm for retrieving column-averaged dry air mole fraction of carbon dioxide (XCO2) and methane (XCH4) from reflected spectra in the shortwave infrared (SWIR) measured by the TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation Fourier Transform Spectrometer) sensor on board the Greenhouse gases Observing SATellite (GOSAT). The algorithm uses the two linear polarizations observed by TANSO-FTS to improve corrections to the interference effects of atmospheric aerosols, which degrade the accuracy in the retrieved greenhouse gas concentrations. To account for polarization by the land surface reflection in the forward model, we introduced a bidirectional reflection matrix model that has two parameters to be retrieved simultaneously with other state parameters. The accuracy in XCO2 and XCH4 values retrieved with the algorithm was evaluated by using simulated retrievals over both land and ocean, focusing on the capability of the algorithm to correct imperfect prior knowledge of aerosols. To do this, we first generated simulated TANSO-FTS spectra using a global distribution of aerosols computed by the aerosol transport model SPRINTARS. Then the simulated spectra were submitted to the algorithms as measurements both with and without polarization information, adopting a priori profiles of aerosols that differ from the true profiles. We found that the accuracy of XCO2 and XCH4, as well as profiles of aerosols, retrieved with polarization information was considerably improved over values retrieved without polarization information, for simulated observations over land with aerosol optical thickness greater than 0.1 at 1.6 μm.

Dreaming of Atmospheres

NASA Astrophysics Data System (ADS)

Waldmann, Ingo

2016-10-01

Radiative transfer retrievals have become the standard in modelling of exoplanetary transmission and emission spectra. Analysing currently available observations of exoplanetary atmospheres often invoke large and correlated parameter spaces that can be difficult to map or constrain.To address these issues, we have developed the Tau-REx (tau-retrieval of exoplanets) retrieval and the RobERt spectral recognition algorithms. Tau-REx is a bayesian atmospheric retrieval framework using Nested Sampling and cluster computing to fully map these large correlated parameter spaces. Nonetheless, data volumes can become prohibitively large and we must often select a subset of potential molecular/atomic absorbers in an atmosphere.In the era of open-source, automated and self-sufficient retrieval algorithms, such manual input should be avoided. User dependent input could, in worst case scenarios, lead to incomplete models and biases in the retrieval. The RobERt algorithm is build to address these issues. RobERt is a deep belief neural (DBN) networks trained to accurately recognise molecular signatures for a wide range of planets, atmospheric thermal profiles and compositions. Using these deep neural networks, we work towards retrieval algorithms that themselves understand the nature of the observed spectra, are able to learn from current and past data and make sensible qualitative preselections of atmospheric opacities to be used for the quantitative stage of the retrieval process.In this talk I will discuss how neural networks and Bayesian Nested Sampling can be used to solve highly degenerate spectral retrieval problems and what 'dreaming' neural networks can tell us about atmospheric characteristics.

New model for distributed multimedia databases and its application to networking of museums

NASA Astrophysics Data System (ADS)

Kuroda, Kazuhide; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

1998-02-01

This paper proposes a new distributed multimedia data base system where the databases storing MPEG-2 videos and/or super high definition images are connected together through the B-ISDN's, and also refers to an example of the networking of museums on the basis of the proposed database system. The proposed database system introduces a new concept of the 'retrieval manager' which functions an intelligent controller so that the user can recognize a set of image databases as one logical database. A user terminal issues a request to retrieve contents to the retrieval manager which is located in the nearest place to the user terminal on the network. Then, the retrieved contents are directly sent through the B-ISDN's to the user terminal from the server which stores the designated contents. In this case, the designated logical data base dynamically generates the best combination of such a retrieving parameter as a data transfer path referring to directly or data on the basis of the environment of the system. The generated retrieving parameter is then executed to select the most suitable data transfer path on the network. Therefore, the best combination of these parameters fits to the distributed multimedia database system.

Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O2 A band observations from GOME-2A

NASA Astrophysics Data System (ADS)

Sanders, A. F. J.; de Haan, J. F.; Sneep, M.; Apituley, A.; Stammes, P.; Vieitez, M. O.; Tilstra, L. G.; Tuinder, O. N. E.; Koning, C. E.; Veefkind, J. P.

2015-06-01

An algorithm setup for the operational Aerosol Layer Height product for TROPOMI on the Sentinel-5 Precursor mission is described and discussed, applied to GOME-2A data, and evaluated with lidar measurements. The algorithm makes a spectral fit of reflectance at the O2 A band in the near-infrared and the fit window runs from 758 to 770 nm. The aerosol profile is parameterized by a scattering layer with constant aerosol volume extinction coefficient and aerosol single scattering albedo and with a fixed pressure thickness. The algorithm's target parameter is the height of this layer. In this paper, we apply the algorithm to observations from GOME-2A in a number of systematic and extensive case studies and we compare retrieved aerosol layer heights with lidar measurements. Aerosol scenes cover various aerosol types, both elevated and boundary layer aerosols, and land and sea surfaces. The aerosol optical thicknesses for these scenes are relatively moderate. Retrieval experiments with GOME-2A spectra are used to investigate various sensitivities, in which particular attention is given to the role of the surface albedo. From retrieval simulations with the single-layer model, we learn that the surface albedo should be a fit parameter when retrieving aerosol layer height from the O2 A band. Current uncertainties in surface albedo climatologies cause biases and non-convergences when the surface albedo is fixed in the retrieval. Biases disappear and convergence improves when the surface albedo is fitted, while precision of retrieved aerosol layer pressure is still largely within requirement levels. Moreover, we show that fitting the surface albedo helps to ameliorate biases in retrieved aerosol layer height when the assumed aerosol model is inaccurate. Subsequent retrievals with GOME-2A spectra confirm that convergence is better when the surface albedo is retrieved simultaneously with aerosol parameters. However, retrieved aerosol layer pressures are systematically low (i.e., layer high in the atmosphere) to the extent that retrieved values are not realistically representing actual extinction profiles anymore. When the surface albedo is fixed in retrievals with GOME-2A spectra, convergence deteriorates as expected, but retrieved aerosol layer pressures become much higher (i.e., layer lower in atmosphere). The comparison with lidar measurements indicates that retrieved aerosol layer heights are indeed representative of the underlying profile in that case. Finally, subsequent retrieval simulations with two-layer aerosol profiles show that a model error in the assumed profile (two layers in the simulation but only one in the retrieval) is partly absorbed by the surface albedo when this parameter is fitted. This is expected in view of the correlations between errors in fit parameters and the effect is relatively small for elevated layers (less than 100 hPa). In case one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large such that the retrieved height of the single layer is above the two-layer profile. Furthermore, we find that the retrieval solution, once retrieval converges, hardly depends on the starting values for the fit. Sensitivity experiments with GOME-2A spectra also show that aerosol layer height is indeed relatively robust against inaccuracies in the assumed aerosol model, even when the surface albedo is not fitted. We show spectral fit residuals, which can be used for further investigations. Fit residuals may be partly explained by spectroscopic uncertainties, which is suggested by an experiment showing the improvement of convergence when the absorption cross section is scaled in agreement with Butz et al. (2012) and Crisp et al. (2012) and a temperature offset to the a priori ECMWF temperature profile is fitted. Retrieved temperature offsets are always negative and quite large (ranging between -4 and -8 K), which is not expected if temperature offsets absorb remaining inaccuracies in meteorological data. Other sensitivity experiments investigate fitting of stray light and fluorescence emissions. We find negative radiance offsets and negative fluorescence emissions, also for non-vegetated areas, but from the results it is not clear whether fitting these parameters improves the retrieval. Based on the present results, the operational baseline for the Aerosol Layer Height product currently will not fit the surface albedo. The product will be particularly suited for elevated, optically thick aerosol layers. In addition to its scientific value in climate research, anticipated applications of the product for TROPOMI are providing aerosol height information for aviation safety and improving interpretation of the Absorbing Aerosol Index.

Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O2 A band observations from GOME-2A

NASA Astrophysics Data System (ADS)

Sanders, A. F. J.; de Haan, J. F.; Sneep, M.; Apituley, A.; Stammes, P.; Vieitez, M. O.; Tilstra, L. G.; Tuinder, O. N. E.; Koning, C. E.; Veefkind, J. P.

2015-11-01

An algorithm setup for the operational Aerosol Layer Height product for TROPOMI on the Sentinel-5 Precursor mission is described and discussed, applied to GOME-2A data, and evaluated with lidar measurements. The algorithm makes a spectral fit of reflectance at the O2 A band in the near-infrared and the fit window runs from 758 to 770 nm. The aerosol profile is parameterised by a scattering layer with constant aerosol volume extinction coefficient and aerosol single scattering albedo and with a fixed pressure thickness. The algorithm's target parameter is the height of this layer. In this paper, we apply the algorithm to observations from GOME-2A in a number of systematic and extensive case studies, and we compare retrieved aerosol layer heights with lidar measurements. Aerosol scenes cover various aerosol types, both elevated and boundary layer aerosols, and land and sea surfaces. The aerosol optical thicknesses for these scenes are relatively moderate. Retrieval experiments with GOME-2A spectra are used to investigate various sensitivities, in which particular attention is given to the role of the surface albedo. From retrieval simulations with the single-layer model, we learn that the surface albedo should be a fit parameter when retrieving aerosol layer height from the O2 A band. Current uncertainties in surface albedo climatologies cause biases and non-convergences when the surface albedo is fixed in the retrieval. Biases disappear and convergence improves when the surface albedo is fitted, while precision of retrieved aerosol layer pressure is still largely within requirement levels. Moreover, we show that fitting the surface albedo helps to ameliorate biases in retrieved aerosol layer height when the assumed aerosol model is inaccurate. Subsequent retrievals with GOME-2A spectra confirm that convergence is better when the surface albedo is retrieved simultaneously with aerosol parameters. However, retrieved aerosol layer pressures are systematically low (i.e., layer high in the atmosphere) to the extent that retrieved values no longer realistically represent actual extinction profiles. When the surface albedo is fixed in retrievals with GOME-2A spectra, convergence deteriorates as expected, but retrieved aerosol layer pressures become much higher (i.e., layer lower in atmosphere). The comparison with lidar measurements indicates that retrieved aerosol layer heights are indeed representative of the underlying profile in that case. Finally, subsequent retrieval simulations with two-layer aerosol profiles show that a model error in the assumed profile (two layers in the simulation but only one in the retrieval) is partly absorbed by the surface albedo when this parameter is fitted. This is expected in view of the correlations between errors in fit parameters and the effect is relatively small for elevated layers (less than 100 hPa). If one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large, in such a way that the retrieved height of the single layer is above the two-layer profile. Furthermore, we find that the retrieval solution, once retrieval converges, hardly depends on the starting values for the fit. Sensitivity experiments with GOME-2A spectra also show that aerosol layer height is indeed relatively robust against inaccuracies in the assumed aerosol model, even when the surface albedo is not fitted. We show spectral fit residuals, which can be used for further investigations. Fit residuals may be partly explained by spectroscopic uncertainties, which is suggested by an experiment showing the improvement of convergence when the absorption cross section is scaled in agreement with Butz et al. (2013) and Crisp et al. (2012), and a temperature offset to the a priori ECMWF temperature profile is fitted. Retrieved temperature offsets are always negative and quite large (ranging between -4 and -8 K), which is not expected if temperature offsets absorb remaining inaccuracies in meteorological data. Other sensitivity experiments investigate fitting of stray light and fluorescence emissions. We find negative radiance offsets and negative fluorescence emissions, also for non-vegetated areas, but from the results it is not clear whether fitting these parameters improves the retrieval. Based on the present results, the operational baseline for the Aerosol Layer Height product currently will not fit the surface albedo. The product will be particularly suited for elevated, optically thick aerosol layers. In addition to its scientific value in climate research, anticipated applications of the product for TROPOMI are providing aerosol height information for aviation safety and improving interpretation of the Absorbing Aerosol Index.

A Numerical Testbed for Remote Sensing of Aerosols, and its Demonstration for Evaluating Retrieval Synergy from a Geostationary Satellite Constellation of GEO-CAPE and GOES-R

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael I.

2014-01-01

We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEOCAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the synergic use of two future geostationary satellites, GOES-R (Geostationary Operational Environmental Satellite R-series) and TEMPO (Tropospheric Emissions: Monitoring of Pollution). Strong synergy between GEOS-R and TEMPO are found especially in their characterization of surface bi-directional reflectance, and thereby, can potentially improve the AOD retrieval to the accuracy required by GEO-CAPE.

Internally Consistent MODIS Estimate of Aerosol Clear-Sky Radiative Effect Over the Global Oceans

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Kaufman, Yoram J.

2004-01-01

Modern satellite remote sensing, and in particular the MODerate resolution Imaging Spectroradiometer (MODIS), offers a measurement-based pathway to estimate global aerosol radiative effects and aerosol radiative forcing. Over the Oceans, MODIS retrieves the total aerosol optical thickness, but also reports which combination of the 9 different aerosol models was used to obtain the retrieval. Each of the 9 models is characterized by a size distribution and complex refractive index, which through Mie calculations correspond to a unique set of single scattering albedo, assymetry parameter and spectral extinction for each model. The combination of these sets of optical parameters weighted by the optical thickness attributed to each model in the retrieval produces the best fit to the observed radiances at the top of the atmosphere. Thus the MODIS Ocean aerosol retrieval provides us with (1) An observed distribution of global aerosol loading, and (2) An internally-consistent, observed, distribution of aerosol optical models that when used in combination will best represent the radiances at the top of the atmosphere. We use these two observed global distributions to initialize the column climate model by Chou and Suarez to calculate the aerosol radiative effect at top of the atmosphere and the radiative efficiency of the aerosols over the global oceans. We apply the analysis to 3 years of MODIS retrievals from the Terra satellite and produce global and regional, seasonally varying, estimates of aerosol radiative effect over the clear-sky oceans.

Implementation of Cloud Retrievals for Tropospheric Emission Spectrometer (TES) Atmospheric Retrievals: Part 1. Description and Characterization of Errors on Trace Gas Retrievals

NASA Technical Reports Server (NTRS)

Kulawik, Susan S.; Worden, John; Eldering, Annmarie; Bowman, Kevin; Gunson, Michael; Osterman, Gregory B.; Zhang, Lin; Clough, Shepard A.; Shephard, Mark W.; Beer, Reinhard

2006-01-01

We develop an approach to estimate and characterize trace gas retrievals in the presence of clouds in high spectral measurements of upwelling radiance in the infrared spectral region (650-2260/cm). The radiance contribution of clouds is parameterized in terms of a set of frequency-dependent nonscattering optical depths and a cloud height. These cloud parameters are retrieved jointly with surface temperature, emissivity, atmospheric temperature, and trace gases such as ozone from spectral data. We demonstrate the application of this approach using data from the Tropospheric Emission Spectrometer (TES) and test data simulated with a scattering radiative transfer model. We show the value of this approach in that it results in accurate estimates of errors for trace gas retrievals, and the retrieved values improve over the initial guess for a wide range of cloud conditions. Comparisons are made between TES retrievals of ozone, temperature, and water to model fields from the Global Modeling and Assimilation Office (GMAO), temperature retrievals from the Atmospheric Infrared Sounder (AIRS), tropospheric ozone columns from the Goddard Earth Observing System (GEOS) GEOS-Chem, and ozone retrievals from the Total Ozone Mapping Spectrometer (TOMS). In each of these cases, this cloud retrieval approach does not introduce observable biases into TES retrievals.

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.

Assimilation of Sea Color Data Into A Three Dimensional Biogeochemical Model: Sensitivity Experiments

NASA Astrophysics Data System (ADS)

Echevin, V.; Levy, M.; Memery, L.

The assimilation of two dimensional sea color data fields into a 3 dimensional coupled dynamical-biogeochemical model is performed using a 4DVAR algorithm. The biogeochemical model includes description of nitrates, ammonium, phytoplancton, zooplancton, detritus and dissolved organic matter. A subset of the biogeochemical model poorly known parameters (for example,phytoplancton growth, mortality,grazing) are optimized by minimizing a cost function measuring misfit between the observations and the model trajectory. Twin experiments are performed with an eddy resolving model of 5 km resolution in an academic configuration. Starting from oligotrophic conditions, an initially unstable baroclinic anticyclone splits into several eddies. Strong vertical velocities advect nitrates into the euphotic zone and generate a phytoplancton bloom. Biogeochemical parameters are perturbed to generate surface pseudo-observations of chlorophyll,which are assimilated in the model in order to retrieve the correct parameter perturbations. The impact of the type of measurement (quasi-instantaneous, daily mean, weekly mean) onto the retrieved set of parameters is analysed. Impacts of additional subsurface measurements and of errors in the circulation are also presented.

Improvement and further development of SSM/I overland parameter algorithms using the WetNet workstation

NASA Technical Reports Server (NTRS)

Neale, Christopher M. U.; Mcdonnell, Jeffrey J.; Ramsey, Douglas; Hipps, Lawrence; Tarboton, David

1993-01-01

Since the launch of the DMSP Special Sensor Microwave/Imager (SSM/I), several algorithms have been developed to retrieve overland parameters. These include the present operational algorithms resulting from the Navy calibration/validation effort such as land surface type (Neale et al. 1990), land surface temperature (McFarland et al. 1990), surface moisture (McFarland and Neale, 1991) and snow parameters (McFarland and Neale, 1991). In addition, other work has been done including the classification of snow cover and precipitation using the SSM/I (Grody, 1991). Due to the empirical nature of most of the above mentioned algorithms, further research is warranted and improvements can probably be obtained through a combination of radiative transfer modelling to study the physical processes governing the microwave emissions at the SSM/I frequencies, and the incorporation of additional ground truth data and special cases into the regression data sets. We have proposed specifically to improve the retrieval of surface moisture and snow parameters using the WetNet SSM/I data sets along with ground truth information namely climatic variables from the NOAA cooperative network of weather stations as well as imagery from other satellite sensors such as the AVHRR and Thematic Mapper. In the case of surface moisture retrievals the characterization of vegetation density is of primary concern. The higher spatial resolution satellite imagery collected at concurrent periods will be used to characterize vegetation types and amounts which, along with radiative transfer modelling should lead to more physically based retrievals. Snow parameter retrieval algorithm improvement will initially concentrate on the classification of snowpacks (dry snow, wet snow, refrozen snow) and later on specific products such as snow water equivalent. Significant accomplishments in the past year are presented.

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.

Improving land surface parameter retrieval by integrating plant traits priors in the MULTIPLY data assimilation platform

NASA Astrophysics Data System (ADS)

Corbin, A. E.; Timmermans, J.; Hauser, L.; Bodegom, P. V.; Soudzilovskaia, N. A.

2017-12-01

There is a growing demand for accurate land surface parameterization from remote sensing (RS) observations. This demand has not been satisfied, because most estimation schemes apply 1) a single-sensor single-scale approach, and 2) require specific key-variables to be `guessed'. This is because of the relevant observational information required to accurately retrieve parameters of interest. Consequently, many schemes assume specific variables to be constant or not present; subsequently leading to more uncertainty. In this aspect, the MULTIscale SENTINEL land surface information retrieval Platform (MULTIPLY) was created. MULTIPLY couples a variety of RS sources with Radiative Transfer Models (RTM) over varying spectral ranges using data-assimilation to estimate geophysical parameters. In addition, MULTIPLY also uses prior information about the land surface to constrain the retrieval problem. This research aims to improve the retrieval of plant biophysical parameters through the use of priors of biophysical parameters/plant traits. Of particular interest are traits (physical, morphological or chemical trait) affecting individual performance and fitness of species. Plant traits that are able to be retrieved via RS and with RTMs include traits such as leaf-pigments, leaf water, LAI, phenols, C/N, etc. In-situ data for plant traits that are retrievable via RS techniques were collected for a meta-analysis from databases such as TRY, Ecosis, and individual collaborators. Of particular interest are the following traits: chlorophyll, carotenoids, anthocyanins, phenols, leaf water, and LAI. ANOVA statistics were generated for each traits according to species, plant functional groups (such as evergreens, grasses, etc.), and the trait itself. Afterwards, traits were also compared using covariance matrices. Using these as priors, MULTIPLY was is used to retrieve several plant traits in two validation sites in the Netherlands (Speulderbos) and in Finland (Sodankylä). Initial comparisons show significant improved results over non-a priori based retrievals.

A New Paradigm for Satellite Retrieval of Hydrologic Variables: The CDRD Methodology

NASA Astrophysics Data System (ADS)

Smith, E. A.; Mugnai, A.; Tripoli, G. J.

2009-09-01

Historically, retrieval of thermodynamically active geophysical variables in the atmosphere (e.g., temperature, moisture, precipitation) involved some time of inversion scheme - embedded within the retrieval algorithm - to transform radiometric observations (a vector) to the desired geophysical parameter(s) (either a scalar or a vector). Inversion is fundamentally a mathematical operation involving some type of integral-differential radiative transfer equation - often resisting a straightforward algebraic solution - in which the integral side of the equation (typically the right-hand side) contains the desired geophysical vector, while the left-hand side contains the radiative measurement vector often free of operators. Inversion was considered more desirable than forward modeling because the forward model solution had to be selected from a generally unmanageable set of parameter-observation relationships. However, in the classical inversion problem for retrieval of temperature using multiple radiative frequencies along the wing of an absorption band (or line) of a well-mixed radiatively active gas, in either the infrared or microwave spectrums, the inversion equation to be solved consists of a Fredholm integral equation of the 2nd kind - a specific type of transform problem in which there are an infinite number of solutions. This meant that special treatment of the transform process was required in order to obtain a single solution. Inversion had become the method of choice for retrieval in the 1950s because it appealed to the use of mathematical elegance, and because the numerical approaches used to solve the problems (typically some type of relaxation or perturbation scheme) were computationally fast in an age when computers speeds were slow. Like many solution schemes, inversion has lingered on regardless of the fact that computer speeds have increased many orders of magnitude and forward modeling itself has become far more elegant in combination with Bayesian averaging procedures given that the a priori probabilities of occurrence in the true environment of the parameter(s) in question can be approximated (or are actually known). In this presentation, the theory of the more modern retrieval approach using a combination of cloud, radiation and other specialized forward models in conjunction with Bayesian weighted averaging will be reviewed in light of a brief history of inversion. The application of the theory will be cast in the framework of what we call the Cloud-Dynamics-Radiation-Database (CDRD) methodology - which we now use for the retrieval of precipitation from spaceborne passive microwave radiometers. In a companion presentation, we will specifically describe the CDRD methodology and present results for its application within the Mediterranean basin.

Supervised machine learning for analysing spectra of exoplanetary atmospheres

NASA Astrophysics Data System (ADS)

Márquez-Neila, Pablo; Fisher, Chloe; Sznitman, Raphael; Heng, Kevin

2018-06-01

The use of machine learning is becoming ubiquitous in astronomy1-3, but remains rare in the study of the atmospheres of exoplanets. Given the spectrum of an exoplanetary atmosphere, a multi-parameter space is swept through in real time to find the best-fit model4-6. Known as atmospheric retrieval, this technique originates in the Earth and planetary sciences7. Such methods are very time-consuming, and by necessity there is a compromise between physical and chemical realism and computational feasibility. Machine learning has previously been used to determine which molecules to include in the model, but the retrieval itself was still performed using standard methods8. Here, we report an adaptation of the `random forest' method of supervised machine learning9,10, trained on a precomputed grid of atmospheric models, which retrieves full posterior distributions of the abundances of molecules and the cloud opacity. The use of a precomputed grid allows a large part of the computational burden to be shifted offline. We demonstrate our technique on a transmission spectrum of the hot gas-giant exoplanet WASP-12b using a five-parameter model (temperature, a constant cloud opacity and the volume mixing ratios or relative abundances of molecules of water, ammonia and hydrogen cyanide)11. We obtain results consistent with the standard nested-sampling retrieval method. We also estimate the sensitivity of the measured spectrum to the model parameters, and we are able to quantify the information content of the spectrum. Our method can be straightforwardly applied using more sophisticated atmospheric models to interpret an ensemble of spectra without having to retrain the random forest.

Multispectrum retrieval techniques applied to Venus deep atmosphere and surface problems

NASA Astrophysics Data System (ADS)

Kappel, David; Arnold, Gabriele; Haus, Rainer

The Visible and Infrared Thermal Imaging Spectrometer (VIRTIS) aboard ESA's Venus Express is continuously collecting nightside emission data (among others) from Venus. A radiative transfer model of Venus' atmosphere in conjunction with a suitable retrieval algorithm can be used to estimate atmospheric and surface parameters by fitting simulated spectra to the measured data. Because of the limited spectral resolution of VIRTIS-M-IR-spectra, that have been used so far, many different parameter sets can explain the same measurement equally well. As a common regulative measure, reasonable a priori knowledge of some parameters is applied to suppress solutions implausibly far from the expected range. It is beneficial to introduce a parallel coupled retrieval of several measurements. Since spa-tially and temporally contiguous measurements are not expected to originate from completely unrelated parameters, an assumed a priori correlation of the parameters during the retrieval can help to reduce arbitrary fluctuations of the solutions, to avoid subsidiary solutions, and to attenuate the interference of measurement noise by keeping the parameters close to a gen-eral trend. As an illustration, the resulting improvements for some swaths on the Northern hemisphere are presented. Some atmospheric features are still not very well constrained, for instance CO2 absorption under the extreme environmental conditions close to the surface. A broad band continuum due to far wing and collisional induced absorptions is commonly used to correct individual line absorption. Since the spectrally dependent continuum is constant for all measurements, the retrieval of parameters common to all spectra may be used to give some estimates of the continuum absorption. These estimates are necessary, for example, for the coupled parallel retrieval of a consistent local cloud modal composition, which in turn enables a refined surface emissivity retrieval. We gratefully acknowledge the support from the VIRTIS/Venus Express Team, from ASI, CNES, CNRS, and from the DFG funding the ongoing work.

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.

A self-consistency approach to improve microwave rainfall rate estimation from space

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Mack, Robert A.; Hakkarinen, Ida M.

1989-01-01

A multichannel statistical approach is used to retrieve rainfall rates from the brightness temperature T(B) observed by passive microwave radiometers flown on a high-altitude NASA aircraft. T(B) statistics are based upon data generated by a cloud radiative model. This model simulates variabilities in the underlying geophysical parameters of interest, and computes their associated T(B) in each of the available channels. By further imposing the requirement that the observed T(B) agree with the T(B) values corresponding to the retrieved parameters through the cloud radiative transfer model, the results can be made to agree quite well with coincident radar-derived rainfall rates. Some information regarding the cloud vertical structure is also obtained by such an added requirement. The applicability of this technique to satellite retrievals is also investigated. Data which might be observed by satellite-borne radiometers, including the effects of nonuniformly filled footprints, are simulated by the cloud radiative model for this purpose.

[Retrieval of the Optical Thickness and Cloud Top Height of Cirrus Clouds Based on AIRS IR High Spectral Resolution Data].

PubMed

Cao, Ya-nan; Wei, He-li; Dai, Cong-ming; Zhang, Xue-hai

2015-05-01

A study was carried out to retrieve optical thickness and cloud top height of cirrus clouds from the Atmospheric Infrared Sounder (AIRS) high spectral resolution data in 1070~1135 cm-1 IR band using a Combined Atmospheric Radiative Transfer model (CART) by brightness temperature difference between model simulation and AIRS observation. The research is based on AIRS LIB high spectral infrared observation data combined with Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product data. Brightness temperature spectra based, on the retrieved cirrus optical thickness and cloud top height were simulated and compared with brightness temperature spectra of AIRS observation in the 650~1150 cm-1 band. The cirrus optical thickness and cloud top height retrieved were compared with brightness temperature of AIRS for channel 760 (900.56 cm-1, 11. 1 µm) and cirrus reflectance of MODIS cloud product. And cloud top height retrieved was compared with cloud top height from MODIS. Results show that the brightness temperature spectra simulated were basically consistent with AIRS observation under the condition of retrieval in the 650~1150 cm-1 band. It means that CART can be used to simulate AIRS brightness temperature spectra. The retrieved cirrus parameters are consistent with brightness temperature of AIRS for channel 11. 1 µm with low brightness temperature corresponding to large cirrus optical thickness and high cloud top height. And the retrieved cirrus parameters are consistent with cirrus reflectance of MODIS cloud product with high cirrus reflectance corresponding to large cirrus optical thickness and high cloud top height. Correlation coefficient of brightness temperature between retrieved cloud top height and MODIS cloud top height was relatively high. They are mostly located in the range of 8. 5~11.5 km, and their probability distribution trend is approximately identical. CART model is feasible to retrieve cirrus properties, and the retrieval is reliable.

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

NASA Technical Reports Server (NTRS)

Koshak, William; Krider, E. Philip; Murray, Natalie; Boccippio, Dennis

2007-01-01

A "dimensional reduction" (DR) method is introduced for analyzing lightning field changes whereby the number of unknowns in a discrete two-charge model is reduced from the standard eight to just four. The four unknowns are found by performing a numerical minimization of a chi-squared goodness-of-fit function. At each step of the minimization, an Overdetermined Fixed Matrix (OFM) method is used to immediately retrieve the best "residual source". In this way, all 8 parameters are found, yet a numerical search of only 4 parameters is required. The inversion method is applied to the understanding of lightning charge retrievals. The accuracy of the DR method has been assessed by comparing retrievals with data provided by the Lightning Detection And Ranging (LDAR) instrument. Because lightning effectively deposits charge within thundercloud charge centers and because LDAR traces the geometrical development of the lightning channel with high precision, the LDAR data provides an ideal constraint for finding the best model charge solutions. In particular, LDAR data can be used to help determine both the horizontal and vertical positions of the model charges, thereby eliminating dipole ambiguities. The results of the LDAR-constrained charge retrieval method have been compared to the locations of optical pulses/flash locations detected by the Lightning Imaging Sensor (LIS).

Synergistic estimation of surface parameters from jointly using optical and microwave observations in EOLDAS

NASA Astrophysics Data System (ADS)

Timmermans, Joris; Gomez-Dans, Jose; Lewis, Philip; Loew, Alexander; Schlenz, Florian

2017-04-01

The large amount of remote sensing data nowadays available provides a huge potential for monitoring crop development, drought conditions and water efficiency. This potential however not been realized yet because algorithms for land surface parameter retrieval mostly use data from only a single sensor. Consequently products that combine different low-level observations from different sensors are hard to find. The lack of synergistic retrieval is caused because it is easier to focus on single sensor types/footprints and temporal observation times, than to find a way to compensate for differences. Different sensor types (microwave/optical) require different radiative transfer (RT) models and also require consistency between the models to have any impact on the retrieval of soil moisture by a microwave instrument. Varying spatial footprints require first proper collocation of the data before one can scale between different resolutions. Considering these problems, merging optical and microwave observations have not been performed yet. The goal of this research was to investigate the potential of integrating optical and microwave RT models within the Earth Observation Land Data Assimilation System (EOLDAS) synergistically to derive biophysical parameters. This system uses a Bayesian data assimilation approach together with observation operators such as the PROSAIL model to estimate land surface parameters. For the purpose of enabling the system to integrate passive microwave radiation (from an ELBARRA II passive microwave radiometer), the Community Microwave Emission Model (CMEM) RT-model, was integrated within the EOLDAS system. In order to quantify the potential, a variety of land surface parameters was chosen to be retrieved from the system, in particular variables that a) impact only optical RT (such as leaf water content and leaf dry matter), b) only impact the microwave RT (such as soil moisture and soil temperature), and c) Leaf Area Index (LAI) that impacts both optical and microwave RT. The results show a high potential when both optical and microwave are used independently. Using only RapidEye only with SAIL RT model, LAI was estimated with R=0.68 with p=0.09, although estimating leaf water content and dry matter showed lower correlations |R|<0.4. The results for retrieving soil temperature and leaf area index retrievals using only (passive microwave) Elbarra-II observations were good with respectively R=[0.85, 0.79], P=[0.0, 0.0], when focusing on dry-spells (of at least 9 days) only the results respectively [R=0.73, and P=0.0], and R=0.89 and R=0.77 for respectively the trend and anomalies. Synergistically using optical and microwave shows also a good potential. This scenario shows that absolute errors improved (with RMSE=1.22 and S=0.89), but with degrading correlations (R=0.59 and P=0.04); the sparse optical observations only improved part of the temporal domain. However in general the synergistic retrieval showed good potential; microwave data provides better information concerning the overall trend of the retrieved LAI due to the regular acquisitions, while optical data provides better information concerning the absolute values of the LAI.

A Ground Flash Fraction Retrieval Algorithm for GLM

NASA Technical Reports Server (NTRS)

Koshak, William J.

2010-01-01

A Bayesian inversion method is introduced for retrieving the fraction of ground flashes in a set of N lightning observed by a satellite lightning imager (such as the Geostationary Lightning Mapper, GLM). An exponential model is applied as a physically reasonable constraint to describe the measured lightning optical parameter distributions. Population statistics (i.e., the mean and variance) are invoked to add additional constraints to the retrieval process. The Maximum A Posteriori (MAP) solution is employed. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The approach is feasible for N greater than 2000, and retrieval errors decrease as N is increased.

Quantitative estimation of the fluorescent parameters for crop leaves with the Bayesian inversion

USDA-ARS?s Scientific Manuscript database

In this study, the fluorescent parameters of crop leaves were retrieved from the leaf hyperspectral measurements by inverting the FluorMODleaf model, which is a leaf-level fluorescence model that is based on the widely used and validated PROSPECT (leaf optical properties) model and can simulate the ...

Exploiting Surface Albedos Products to Bridge the Gap Between Remote Sensing Information and Climate Models

NASA Astrophysics Data System (ADS)

Pinty, Bernard; Andredakis, Ioannis; Clerici, Marco; Kaminski, Thomas; Taberner, Malcolm; Stephen, Plummer

2011-01-01

We present results from the application of an inversion method conducted using MODIS derived broadband visible and near-infrared surface albedo products. This contribution is an extension of earlier efforts to optimally retrieve land surface fluxes and associated two- stream model parameters based on the Joint Research Centre Two-stream Inversion Package (JRC-TIP). The discussion focuses on products (based on the mean and one-sigma values of the Probability Distribution Functions (PDFs)) obtained during the summer and winter and highlight specific issues related to snowy conditions. This paper discusses the retrieved model parameters including the effective Leaf Area Index (LAI), the background brightness and the scattering efficiency of the vegetation elements. The spatial and seasonal changes exhibited by these parameters agree with common knowledge and underscore the richness of the high quality surface albedo data sets. At the same time, the opportunity to generate global maps of new products, such as the background albedo, underscores the advantages of using state of the art algorithmic approaches capable of fully exploiting accurate satellite remote sensing datasets. The detailed analyses of the retrieval uncertainties highlight the central role and contribution of the LAI, the main process parameter to interpret radiation transfer observations over vegetated surfaces. The posterior covariance matrix of the uncertainties is further exploited to quantify the knowledge gain from the ingestion of MODIS surface albedo products. The estimation of the radiation fluxes that are absorbed, transmitted and scattered by the vegetation layer and its background is achieved on the basis of the retrieved PDFs of the model parameters. The propagation of uncertainties from the observations to the model parameters is achieved via the Hessian of the cost function and yields a covariance matrix of posterior parameter uncertainties. This matrix is propagated to the radiation fluxes via the model’s Jacobian matrix of first derivatives. A definite asset of the JRC-TIP lies in its capability to control and ultimately relax a number of assumptions that are often implicit in traditional approaches. These features greatly help understand the discrepancies between the different data sets of land surface properties and fluxes that are currently available. Through a series of selected examples, the inverse procedure implemented in the JRC-TIP is shown to be robust, reliable and compliant with large scale processing requirements. Furthermore, this package ensures the physical consistency between the set of observations, the two-stream model parameters and radiation fluxes. It also documents the retrieval of associated uncertainties. The knowledge gained from the availability of remote sensing surface albedo products can be expressed in quantitative terms using a simple metric. This metric helps identify the geographical locations and periods of the year where the remote sensing products fail in reducing the uncertainty on the process model parameters as can be specified from current knowledge.

Expected Improvements in the Quantitative Remote Sensing of Optically Complex Waters with the Use of an Optically Fast Hyperspectral Spectrometer—A Modeling Study

PubMed Central

Moses, Wesley J.; Bowles, Jeffrey H.; Corson, Michael R.

2015-01-01

Using simulated data, we investigated the effect of noise in a spaceborne hyperspectral sensor on the accuracy of the atmospheric correction of at-sensor radiances and the consequent uncertainties in retrieved water quality parameters. Specifically, we investigated the improvement expected as the F-number of the sensor is changed from 3.5, which is the smallest among existing operational spaceborne hyperspectral sensors, to 1.0, which is foreseeable in the near future. With the change in F-number, the uncertainties in the atmospherically corrected reflectance decreased by more than 90% across the visible-near-infrared spectrum, the number of pixels with negative reflectance (caused by over-correction) decreased to almost one-third, and the uncertainties in the retrieved water quality parameters decreased by more than 50% and up to 92%. The analysis was based on the sensor model of the Hyperspectral Imager for the Coastal Ocean (HICO) but using a 30-m spatial resolution instead of HICO’s 96 m. Atmospheric correction was performed using Tafkaa. Water quality parameters were retrieved using a numerical method and a semi-analytical algorithm. The results emphasize the effect of sensor noise on water quality parameter retrieval and the need for sensors with high Signal-to-Noise Ratio for quantitative remote sensing of optically complex waters. PMID:25781507

In-flight calibration/validation of the ENVISAT/MWR

NASA Astrophysics Data System (ADS)

Tran, N.; Obligis, E.; Eymard, L.

2003-04-01

Retrieval algorithms for wet tropospheric correction, integrated vapor and liquid water contents, atmospheric attenuations of backscattering coefficients in Ku and S band, have been developed using a database of geophysical parameters from global analyses from a meteorological model and corresponding simulated brightness temperatures and backscattering cross-sections by a radiative transfer model. Meteorological data correspond to 12 hours predictions from the European Center for Medium range Weather Forecasts (ECMWF) model. Relationships between satellite measurements and geophysical parameters are determined using a statistical method. The quality of the retrieval algorithms depends therefore on the representativity of the database, the accuracy of the radiative transfer model used for the simulations and finally on the quality of the inversion model. The database has been built using the latest version of the ECMWF forecast model, which has been operationally run since November 2000. The 60 levels in the model allow a complete description of the troposphere/stratosphere profiles and the horizontal resolution is now half of a degree. The radiative transfer model is the emissivity model developed at the Université Catholique de Louvain [Lemaire, 1998], coupled to an atmospheric model [Liebe et al, 1993] for gaseous absorption. For the inversion, we have replaced the classical log-linear regression with a neural networks inversion. For Envisat, the backscattering coefficient in Ku band is used in the different algorithms to take into account the surface roughness as it is done with the 18 GHz channel for the TOPEX algorithms or an additional term in wind speed for ERS2 algorithms. The in-flight calibration/validation of the Envisat radiometer has been performed with the tuning of 3 internal parameters (the transmission coefficient of the reflector, the sky horn feed transmission coefficient and the main antenna transmission coefficient). First an adjustment of the ERS2 brightness temperatures to the simulations for the 2000/2001 version of the ECMWF model has been applied. Then, Envisat brightness temperatures have been calibrated on these adjusted ERS2 values. The advantages of this calibration approach are that : i) such a method provides the relative discrepancy with respect to the simulation chain. The results, obtained simultaneously for several radiometers (we repeat the same analyze with TOPEX and JASON radiometers), can be used to detect significant calibration problems, more than 2 3 K). ii) the retrieval algorithms have been developed using the same meteorological model (2000/2001 version of the ECMWF model), and the same radiative transfer model than the calibration process, insuring the consistency between calibration and retrieval processing. Retrieval parameters are then optimized. iii) the calibration of the Envisat brightness temperatures over the 2000/2001 version of the ECMWF model, as well as the recommendation to use the same model as a reference to correct ERS2 brightness temperatures, allow the use of the same retrieval algorithms for the two missions, providing the continuity between the two. iv) by comparison with other calibration methods (such as systematic calibration of an instrument or products by using respectively the ones from previous mission), this method is more satisfactory since improvements in terms of technology, modelisation, retrieval processing are taken into account. For the validation of the brightness temperatures, we use either a direct comparison with measurements provided by other instruments in similar channel, or the monitoring over stable areas (coldest ocean points, stable continental areas). The validation of the wet tropospheric correction can be also provided by comparison with other radiometer products, but the only real validation rely on the comparison between in-situ measurements (performed by radiosonding) and retrieved products in coincidence.

Considering Combined or Separated Roughness and Vegetation Effects in Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Parrens, Marie; Wigernon, Jean-Pierre; Richaume, Philippe; Al Bitar, Ahmad; Mialon, Arnaud; Fernandez-Moran, Roberto; Al-Yarri, Amen; O'Neill, Peggy; Kerr, Yann

2016-01-01

For more than six years, the Soil Moisture and Ocean Salinity (SMOS) mission has provided multi angular and full-polarization brightness temperature (TB) measurements at L-band. Geophysical products such as soil moisture (SM) and vegetation optical depth at nadir (tau(sub nad)) are retrieved by an operational algorithm using TB observations at different angles of incidence and polarizations. However, the quality of the retrievals depends on several surface effects, such as vegetation, soil roughness and texture, etc. In the microwave forward emission model used in the retrievals (L-band Microwave Emission Model, L-MEB),soil roughness is modeled with a semi-empirical equation using four main parameters (Q(sub r), H(sub r), N(sub rp), with p = H or V polarizations). At present, these parameters are calibrated with data provided by airborne studies and in situ measurements made at a local scale that is not necessarily representative of the large SMOS footprints (43 km on average) at global scale. In this study, we evaluate the impact of the calibrated values of N(sub rp) and H(sub r) on the SM and tau(sub nad) retrievals based on SMOS TB measurements (SMOS Level 3 product) over the Soil Climate Analysis Network (SCAN) network located in North America over five years (2011-2015). In this study, Qr was set equal to zero and we assumed that N(sub rH)= N(sub rV). The retrievals were performed by varying N(sub rp) from -1 to 2 by steps of 1 and H(sub r) from 0 to 0.6 by steps of 0.1. At satellite scale, the results show that combining vegetation and roughness effects in a single parameter provides the best results in terms of soil moisture retrievals, as evaluated against the in situ SM data. Even though our retrieval approach was very simplified, as we did not account for pixel heterogeneity, the accuracy we obtained in the SM retrievals was almost systematically better than those of the Level 3 product. Improved results were also obtained in terms of optical depth retrievals. These new results may have key consequences in terms of calibration of roughness effects within the algorithms of the SMOS (ESA) and the SMAP (NASA) space missions.

Physical retrieval of precipitation water contents from Special Sensor Microwave/Imager (SSM/I) data. Part 2: Retrieval method and applications (report version)

NASA Technical Reports Server (NTRS)

Olson, William S.

1990-01-01

A physical retrieval method for estimating precipitating water distributions and other geophysical parameters based upon measurements from the DMSP-F8 SSM/I is developed. Three unique features of the retrieval method are (1) sensor antenna patterns are explicitly included to accommodate varying channel resolution; (2) precipitation-brightness temperature relationships are quantified using the cloud ensemble/radiative parameterization; and (3) spatial constraints are imposed for certain background parameters, such as humidity, which vary more slowly in the horizontal than the cloud and precipitation water contents. The general framework of the method will facilitate the incorporation of measurements from the SSMJT, SSM/T-2 and geostationary infrared measurements, as well as information from conventional sources (e.g., radiosondes) or numerical forecast model fields.

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.

SMOS first results over land

NASA Astrophysics Data System (ADS)

Kerr, Yann; Waldteufel, Philippe; Cabot, François; Richaume, Philippe; Jacquette, Elsa; Bitar, Ahmad Al; Mamhoodi, Ali; Delwart, Steven; Wigneron, Jean-Pierre

2010-05-01

The Soil Moisture and Ocean Salinity (SMOS) mission is ESA's (European Space Agency ) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint programme between ESA CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-band 2D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere and hence the instrument probes the Earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. In order to prepare the data use and dissemination, the ground segment will produce level 1 and 2 data. Level 1 consists mainly of angular brightness temperatures while level 2 consists of geophysical products. In this context, a group of institutes prepared the soil moisture and ocean salinity Algorithm Theoretical Basis documents (ATBD) to be used to produce the operational algorithm. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. This is achieved by finding the best suited set of the parameters which drive the direct TB model, e.g. soil moisture (SM) and vegetation characteristics. Despite the simplicity of this principle, the main reason for the complexity of the algorithm is that SMOS "pixels" can correspond to rather large, inhomogeneous surface areas whose contribution to the radiometric signal is difficult to model. Moreover, the exact description of pixels, given by a weighting function which expresses the directional pattern of the SMOS interferometric radiometer, depends on the incidence angle. The goal is to retrieve soil moisture over fairly large and thus inhomogeneous areas. The retrieval is carried out at nodes of a fixed Earth surface grid. To achieve this purpose, after checking input data quality and ingesting auxiliary data, the retrieval process per se can be initiated. This cannot be done blindly as the direct model will be dependent upon surface characteristics. It is thus necessary to first assess what is the dominant land use of a node. For this, an average weighing function (MEAN_WEF) which takes into account the "antenna"pattern is run over the high resolution land use map to assess the dominant cover type. This is used to drive the decision tree which, step by step, selects the type of model to be used as per surface conditions. All this being said and done the retrieval procedure starts if all the conditions are satisfied, ideally to retrieve 3 parameters over the dominant class (the so-called rich retrieval). If the algorithm does not converge satisfactorily, a new trial is made with less floating parameters ("poorer retrieval") until either results are satisfactory or the algorithm is considered to fail. The retrieval algorithm also delivers whenever possible a dielectric constant parameter (using the-so called cardioid approach). Finally, once the retrieval converged, it is possible to compute the brightness temperature at a given fixed angle (42.5°) using the selected forward models applied to the set of parameters obtained at the end of the retrieval process. So the output product of the level 2 soil moisture algorithm should be node position, soil moisture, dielectric constants, computed brightness temperature at 42.5°, flags and quality indices. During the presentation we will describe in more details the algorithm and accompanying work in particular decision tree principle and characteristics, the auxiliary data used and the special and "exotic"cases. We will also be more explicit on the algorithm validation and verification through the data collected during the commissioning phase. The main hurdle being working in spite of spurious signals (RFI) on some areas of the globe.

The effect of row structure on soil moisture retrieval accuracy from passive microwave data.

PubMed

Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding

2014-01-01

Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

Global Scale Simultaneous Retrieval of Smoothened Vegetation Optical Depth and Surface Roughness Parameter using AMSR-E X-band Observations

NASA Astrophysics Data System (ADS)

Lanka, Karthikeyan; Pan, Ming; Konings, Alexandra; Piles, María; D, Nagesh Kumar; Wood, Eric

2017-04-01

Traditionally, passive microwave retrieval algorithms such as Land Parameter Retrieval Model (LPRM) estimate simultaneously soil moisture and Vegetation Optical Depth (VOD) using brightness temperature (Tb) data. The algorithm requires a surface roughness parameter which - despite implications - is generally assumed to be constant at global scale. Due to inherent noise in the satellite data and retrieval algorithm, the VOD retrievals are usually observed to be highly fluctuating at daily scale which may not occur in reality. Such noisy VOD retrievals along with spatially invariable roughness parameter may affect the quality of soil moisture retrievals. The current work aims to smoothen the VOD retrievals (with an assumption that VOD remains constant over a period of time) and simultaneously generate, for the first time, global surface roughness map using multiple descending X-band Tb observations of AMSR-E. The methodology utilizes Tb values under a moving-time-window-setup to estimate concurrently the soil moisture of each day and a constant VOD in the window. Prior to this step, surface roughness parameter is estimated using the complete time series of Tb record. Upon carrying out the necessary sensitivity analysis, the smoothened VOD along with soil moisture retrievals is generated for the 10-year duration of AMSR-E (2002-2011) with a 7-day moving window using the LPRM framework. The spatial patterns of resulted global VOD maps are in coherence with vegetation biomass and climate conditions. The VOD results also exhibit a smoothening effect in terms of lower values of standard deviation. This is also evident from time series comparison of VOD and LPRM VOD retrievals without optimization over moving windows at several grid locations across the globe. The global surface roughness map also exhibited spatial patterns that are strongly influenced by topography and land use conditions. Some of the noticeable features include high roughness over mountainous regions and heavily vegetated tropical rainforests, low roughness in desert areas and moderate roughness value over higher latitudes. The new datasets of VOD and surface roughness can help improving the quality of soil moisture retrievals. Also, the methodology proposed is generic by nature and can be implemented over currently operating AMSR2, SMOS, and SMAP soil moisture missions.

Integrated optimization of location assignment and sequencing in multi-shuttle automated storage and retrieval systems under modified 2n-command cycle pattern

NASA Astrophysics Data System (ADS)

Yang, Peng; Peng, Yongfei; Ye, Bin; Miao, Lixin

2017-09-01

This article explores the integrated optimization problem of location assignment and sequencing in multi-shuttle automated storage/retrieval systems under the modified 2n-command cycle pattern. The decision of storage and retrieval (S/R) location assignment and S/R request sequencing are jointly considered. An integer quadratic programming model is formulated to describe this integrated optimization problem. The optimal travel cycles for multi-shuttle S/R machines can be obtained to process S/R requests in the storage and retrieval request order lists by solving the model. The small-sized instances are optimally solved using CPLEX. For large-sized problems, two tabu search algorithms are proposed, in which the first come, first served and nearest neighbour are used to generate initial solutions. Various numerical experiments are conducted to examine the heuristics' performance and the sensitivity of algorithm parameters. Furthermore, the experimental results are analysed from the viewpoint of practical application, and a parameter list for applying the proposed heuristics is recommended under different real-life scenarios.

Retrieval of river discharge solely from satellite imagery and at-many-stations hydraulic geometry: Sensitivity to river form and optimization parameters

NASA Astrophysics Data System (ADS)

Gleason, Colin J.; Smith, Laurence C.; Lee, Jinny

2014-12-01

Knowledge of river discharge is critically important for water resource management, climate modeling, and improved understanding of the global water cycle, yet discharge is poorly known in much of the world. Remote sensing holds promise to mitigate this gap, yet current approaches for quantitative retrievals of river discharge require in situ calibration or a priori knowledge of river hydraulics, limiting their utility in unmonitored regions. Recently, Gleason and Smith (2014) demonstrated discharge retrievals within 20-30% of in situ observations solely from Landsat TM satellite images through discovery of a river-specific geomorphic scaling phenomenon termed at-many-stations hydraulic geometry (AMHG). This paper advances the AMHG discharge retrieval approach via additional parameter optimizations and validation on 34 gauged rivers spanning a diverse range of geomorphic and climatic settings. Sensitivity experiments reveal that discharge retrieval accuracy varies with river morphology, reach averaging procedure, and optimization parameters. Quality of remotely sensed river flow widths is also important. Recommended best practices include a proposed global parameter set for use when a priori information is unavailable. Using this global parameterization, AMHG discharge retrievals are successful for most investigated river morphologies (median RRMSE 33% of in situ gauge observations), except braided rivers (median RRMSE 74%), rivers having low at-a-station hydraulic geometry b exponents (reach-averaged b < 0.1, median RRMSE 86%), and arid rivers having extreme discharge variability (median RRMSE > 1000%). Excluding such environments, 26-41% RRMSE agreement between AMHG discharge retrievals and in situ gauge observations suggests AMHG can meaningfully address global discharge knowledge gaps solely from repeat satellite imagery.

Simultaneous inversion of multiple land surface parameters from MODIS optical-thermal observations

NASA Astrophysics Data System (ADS)

Ma, Han; Liang, Shunlin; Xiao, Zhiqiang; Shi, Hanyu

2017-06-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface variables usually focus on individual parameters separately even from the same satellite observations, resulting in inconsistent products. Moreover, no efforts have been made to generate global products from integrated observations from the optical to Thermal InfraRed (TIR) spectrum. Particularly, Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal, which contains both reflected and emitted radiation. In this paper, we propose a unified algorithm for simultaneously retrieving six land surface parameters - Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Emissivity (LSE), Land Surface Temperature (LST), and Upwelling Longwave radiation (LWUP) by exploiting MODIS visible-to-TIR observations. We incorporate a unified physical radiative transfer model into a data assimilation framework. The MODIS visible-to-TIR time series datasets include the daily surface reflectance product and MIR-to-TIR surface radiance, which are atmospherically corrected from the MODIS data using the Moderate Resolution Transmittance program (MODTRAN, ver. 5.0). LAI was first estimated using a data assimilation method that combines MODIS daily reflectance data and a LAI phenology model, and then the LAI was input to the unified radiative transfer model to simulate spectral surface reflectance and surface emissivity for calculating surface broadband albedo and emissivity, and FAPAR. LST was estimated from the MIR-TIR surface radiance data and the simulated emissivity, using an iterative optimization procedure. Lastly, LWUP was estimated using the LST and surface emissivity. The retrieved six parameters were extensively validated across six representative sites with different biome types, and compared with MODIS, GLASS, and GlobAlbedo land surface products. The results demonstrate that the unified inversion algorithm can retrieve temporally complete and physically consistent land surface parameters, and provides more accurate estimates of surface albedo, LST, and LWUP than existing products, with R2 values of 0.93 and 0.62, RMSE of 0.029 and 0.037, and BIAS values of 0.016 and 0.012 for the retrieved and MODIS albedo products, respectively, compared with field albedo measurements; R2 values of 0.95 and 0.93, RMSE of 2.7 and 4.2 K, and BIAS values of -0.6 and -2.7 K for the retrieved and MODIS LST products, respectively, compared with field LST measurements; and R2 values of 0.93 and 0.94, RMSE of 18.2 and 22.8 W/m2, and BIAS values of -2.7 and -14.6 W/m2 for the retrieved and MODIS LWUP products, respectively, compared with field LWUP measurements.

Effective material parameter retrieval of anisotropic elastic metamaterials with inherent nonlocality

NASA Astrophysics Data System (ADS)

Lee, Hyung Jin; Lee, Heung Son; Ma, Pyung Sik; Kim, Yoon Young

2016-09-01

In this paper, the scattering (S-) parameter retrieval method is presented specifically for anisotropic elastic metamaterials; so far, no retrieval has been accomplished when elastic metamaterials exhibit fully anisotropic behavior. Complex constitutive property and intrinsic scattering behavior of elastic metamaterials make their characterization far more complicated than that for acoustic and electromagnetic metamaterials. In particular, elastic metamaterials generally exhibit anisotropic scattering behavior due to higher scattering modes associated with shear deformation. They also exhibit nonlocal responses to some degrees, which originate from strong multiple scattering interactions even in the long wavelength limit. Accordingly, the conventional S-parameter retrieval methods cannot be directly used for elastic metamaterials, because they determine only the diagonal components in effective tensor property. Also, the conventional methods simply use the analytic inversion formulae for the material characterization so that inherent nonlocality cannot be taken into account. To establish a retrieval method applicable to anisotropic elastic metamaterials, we propose an alternative S-parameter method to deal with full anisotropy of elastic metamaterials. To retrieve the whole effective anisotropic parameter, we utilize not only normal but also oblique wave incidences. For the retrieval, we first retrieve the ratio of the effective stiffness tensor to effective density and then determine the effective density. The proposed retrieval method is validated by characterizing the effective material parameters of various types of non-resonant anisotropic metamaterials. It is found that the whole effective parameters are retrieved consistently regardless of used retrieval conditions in spite of inherent nonlocality.

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.

Retrieval of Venus' cloud parameters from VIRTIS nightside spectra in the latitude band 25°-55°N

NASA Astrophysics Data System (ADS)

Magurno, Davide; Maestri, Tiziano; Grassi, Davide; Piccioni, Giuseppe; Sindoni, Giuseppe

2017-09-01

Two years of data from the M-channel of the Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS), on board the European Space Agency mission Venus Express operating around the planet Venus, are analysed. Nocturnal data from a nadir viewpoint in the latitude band 25°N-55°N are selected for their configuration advantages and maximisation of the scene homogeneity. A reference model, and radiance spectrum, is defined based on average accepted values of the Venus main atmospheric and cloud parameters found in the literature. Extensive radiative transfer simulations are performed to provide a synthetic database of more than 10 000 VIRTIS radiances representing the natural variability of the system parameters (atmospheric temperature profile, cloud H2Osbnd H2SO4 solution concentration and vertical distribution, particle size distribution density and modal radius). A simulated-observed fitting algorithm of spectral radiances in window channels, based on a weighting procedure accounting for the latitudinal observed radiance variations, is used to derive the best atmosphere-cloud configuration for each observation. Results show that the reference Venus model does not adequately reproduce the observed VIRTIS spectra. In particular, the model accounting for a constant sulphuric acid concentration along the vertical extent of the clouds is never selected as a best fit. The 75%/96% and 84%/96% concentrations (the first values refer to the upper cloud layers and the second values to the lower ones) are the most commonly retrieved models representing more than 85% of the retrieved cases for any latitudinal band considered. It is shown that the assumption of stratified concentration of aqueous sulphuric acid allows to adequately fit the observed radiance, in particular the peak at 1.74 μm and around 4 μm. The analysis of the results concerning the microphysics suggests larger radii for the upper cloud layers in conjunction with a large reduction of their number density with respect to the reference standard. Considerable variation of the particle concentration in the Venus' atmosphere is retrieved for altitudes between 60 and 70 km. The retrieved models also suggest that lower cloud layers have smaller particle radii and larger number density than expected from the reference model. Latitudinal variations of microphysical and chemical parameters are also analysed.

CLAES Product Improvement by use of GSFC Data Assimilation System

NASA Technical Reports Server (NTRS)

Kumer, J. B.; Douglass, Anne (Technical Monitor)

2001-01-01

Recent development in chemistry transport models (CTM) and in data assimilation systems (DAS) indicate impressive predictive capability for the movement of airparcels and the chemistry that goes on within these. This project was aimed at exploring the use of this capability to achieve improved retrieval of geophysical parameters from remote sensing data. The specific goal was to improve retrieval of the CLAES CH4 data obtained during the active north high latitude dynamics event of 18 to 25 February 1992. The model capabilities would be used: (1) rather than climatology to improve on the first guess and the a-priori fields, and (2) to provide horizontal gradients to include in the retrieval forward model. The retrieval would be implemented with the first forward DAS prediction. The results would feed back to the DAS and a second DAS prediction for first guess, a-priori and gradients would feed to the retrieval. The process would repeat to convergence and then proceed to the next day.

Retrieval of cloud cover parameters from multispectral satellite images

NASA Technical Reports Server (NTRS)

Arking, A.; Childs, J. D.

1985-01-01

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

Current Sounding Capability From Satellite Meteorological Observation With Ultraspectral Infrared Instruments

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.

2008-01-01

Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. The intent of the measurement of tropospheric thermodynamic state and trace abundances is the initialization of climate models and the monitoring of air quality. The NPOESS Airborne Sounder Testbed-Interferometer (NAST-I), designed to support the development of future satellite temperature and moisture sounders, aboard high altitude aircraft has been collecting data throughout many field campaigns. An advanced retrieval algorithm developed with NAST-I is now applied to satellite data collected with the Atmospheric InfraRed Sounder (AIRS) on the Aqua satellite launched on 4 May 2002 and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite launched on October 19, 2006. These instruments possess an ultra-spectral resolution, for example, both IASI and NAST-I have 0.25 cm-1 and a spectral coverage from 645 to 2760 cm-1. The retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error less than 1 km). Retrievals of atmospheric soundings, surface properties, and cloud microphysical properties with the AIRS and IASI observations are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed? Interferometer (NAST I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the AIRS and IASI are investigated. These advanced satellite ultraspectral infrared instruments are now playing an important role in satellite meteorological observation for numerical weather prediction.

The design of optimum remote-sensing instruments

NASA Technical Reports Server (NTRS)

Peckham, G. E.; Flower, D. A.

1983-01-01

Remote-sensing instruments allow values for certain properties of a target to be retrieved from measurements of radiation emitted, reflected or transmitted by the target. The retrieval accuracy is affected by random variations in the many target properties which affect the measurements. A method is described, by which statistical properties of the target and theoretical models of its electromagnetic behavior can be used to choose values for the instrument parameters which maximize the retrieval accuracy. The technique is applicable to a wide range of remote-sensing instruments.

HELIOS-R: An Ultrafast, Open-Source Retrieval Code For Exoplanetary Atmosphere Characterization

NASA Astrophysics Data System (ADS)

LAVIE, Baptiste

2015-12-01

Atmospheric retrieval is a growing, new approach in the theory of exoplanet atmosphere characterization. Unlike self-consistent modeling it allows us to fully explore the parameter space, as well as the degeneracies between the parameters using a Bayesian framework. We present HELIOS-R, a very fast retrieving code written in Python and optimized for GPU computation. Once it is ready, HELIOS-R will be the first open-source atmospheric retrieval code accessible to the exoplanet community. As the new generation of direct imaging instruments (SPHERE, GPI) have started to gather data, the first version of HELIOS-R focuses on emission spectra. We use a 1D two-stream forward model for computing fluxes and couple it to an analytical temperature-pressure profile that is constructed to be in radiative equilibrium. We use our ultra-fast opacity calculator HELIOS-K (also open-source) to compute the opacities of CO2, H2O, CO and CH4 from the HITEMP database. We test both opacity sampling (which is typically used by other workers) and the method of k-distributions. Using this setup, we compute a grid of synthetic spectra and temperature-pressure profiles, which is then explored using a nested sampling algorithm. By focusing on model selection (Occam’s razor) through the explicit computation of the Bayesian evidence, nested sampling allows us to deal with current sparse data as well as upcoming high-resolution observations. Once the best model is selected, HELIOS-R provides posterior distributions of the parameters. As a test for our code we studied HR8799 system and compared our results with the previous analysis of Lee, Heng & Irwin (2013), which used the proprietary NEMESIS retrieval code. HELIOS-R and HELIOS-K are part of the set of open-source community codes we named the Exoclimes Simulation Platform (www.exoclime.org).

Spaceborne SAR Data for Aboveground-Biomass Retrieval of Indian Tropical Forests

NASA Astrophysics Data System (ADS)

Khati, U.; Singh, G.; Musthafa, M.

2017-12-01

Forests are important and indispensable part of the terrestrial ecosystems, and have a direct impact on the global carbon cycle. Forest biophysical parameters such as forest stand height and forest above-ground biomass (AGB) are forest health indicators. Measuring the forest biomass using traditional ground survey techniques are man-power consuming and have very low spatial coverage. Satellite based remote sensing techniques provide synoptic view of the earth with continuous measurements over large, inaccessible forest regions. Satellite Synthetic Aperture Radar (SAR) data has been shown to be sensitive to these forest bio-physical parameters and have been extensively utilized over boreal and tropical forests. However, there are limited studies over Indian tropical forests due to lack of auxiliary airborne data and difficulties in manual in situ data collection. In this research work we utilize spaceborne data from TerraSAR-X/TanDEM-X and ALOS-2/PALSAR-2 and implement both Polarimetric SAR and PolInSAR techniques for retrieval of AGB of a managed tropical forest in India. The TerraSAR-X/TanDEM-X provide a single-baseline PolInSAR data robust to temporal decorrelation. This would be used to accurately estimate the forest stand height. The retrieved height would be an input parameter for modelling AGB using the L-band ALOS-2/PALSAR-2 data. The IWCM model is extensively utilized to estimate AGB from SAR observations. In this research we utilize the six component scattering power decomposition (6SD) parameters and modify the IWCM based technique for a better retrieval of forest AGB. PolInSAR data shows a high estimation accuracy with r2 of 0.8 and a RMSE of 2 m. With this accurate height provided as input to the modified model along with 6SD parameters shows promising results. The results are validated with extensive field based measurements, and are further analysed in detail.

Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels.

PubMed

Yu, Chao; Di Girolamo, Larry; Chen, Liangfu; Zhang, Xueying; Liu, Yang

2015-01-01

The spatial and temporal characteristics of fine particulate matter (PM2.5, particulate matter <2.5 μm in aerodynamic diameter) are increasingly being studied from satellite aerosol remote sensing data. However, cloud cover severely limits the coverage of satellite-driven PM2.5 models, and little research has been conducted on the association between cloud properties and PM2.5 levels. In this study, we analyzed the relationships between ground PM2.5 concentrations and two satellite-retrieved cloud parameters using data from the Southeastern Aerosol Research and Characterization (SEARCH) Network during 2000-2010. We found that both satellite-retrieved cloud fraction (CF) and cloud optical thickness (COT) are negatively associated with PM2.5 levels. PM2.5 speciation and meteorological analysis suggested that the main reason for these negative relationships might be the decreased secondary particle generation. Stratified analyses by season, land use type, and site location showed that seasonal impacts on this relationship are significant. These associations do not vary substantially between urban and rural sites or inland and coastal sites. The statistically significant negative associations of PM2.5 mass concentrations with CF and COT suggest that satellite-retrieved cloud parameters have the potential to serve as predictors to fill the data gap left by satellite aerosol optical depth in satellite-driven PM2.5 models.

Forecast model applications of retrieved three dimensional liquid water fields

NASA Technical Reports Server (NTRS)

Raymond, William H.; Olson, William S.

1990-01-01

Forecasts are made for tropical storm Emily using heating rates derived from the SSM/I physical retrievals described in chapters 2 and 3. Average values of the latent heating rates from the convective and stratiform cloud simulations, used in the physical retrieval, are obtained for individual 1.1 km thick vertical layers. Then, the layer-mean latent heating rates are regressed against the slant path-integrated liquid and ice precipitation water contents to determine the best fit two parameter regression coefficients for each layer. The regression formulae and retrieved precipitation water contents are utilized to infer the vertical distribution of heating rates for forecast model applications. In the forecast model, diabatic temperature contributions are calculated and used in a diabatic initialization, or in a diabatic initialization combined with a diabatic forcing procedure. Our forecasts show that the time needed to spin-up precipitation processes in tropical storm Emily is greatly accelerated through the application of the data.

Retrieval of ammonia abundances and cloud opacities on Jupiter from Voyager IRIS spectra

NASA Technical Reports Server (NTRS)

Conrath, B. J.; Gierasch, P. J.

1986-01-01

Gaseous ammonia abundances and cloud opacities are retrieved from Voyager IRIS 5- and 45-micron data on the basis of a simplified atmospheric model and a two-stream radiative transfer approximation, assuming a single cloud layer with 680-mbar base pressure and 0.14 gas scale height. Brightness temperature measurements obtained as a function of emission angle from selected planetary locations are used to verify the model and constrain a number of its parameters.

On the Response of the Special Sensor Microwave/Imager to the Marine Environment: Implications for Atmospheric Parameter Retrievals. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Petty, Grant W.

1990-01-01

A reasonably rigorous basis for understanding and extracting the physical information content of Special Sensor Microwave/Imager (SSM/I) satellite images of the marine environment is provided. To this end, a comprehensive algebraic parameterization is developed for the response of the SSM/I to a set of nine atmospheric and ocean surface parameters. The brightness temperature model includes a closed-form approximation to microwave radiative transfer in a non-scattering atmosphere and fitted models for surface emission and scattering based on geometric optics calculations for the roughened sea surface. The combined model is empirically tuned using suitable sets of SSM/I data and coincident surface observations. The brightness temperature model is then used to examine the sensitivity of the SSM/I to realistic variations in the scene being observed and to evaluate the theoretical maximum precision of global SSM/I retrievals of integrated water vapor, integrated cloud liquid water, and surface wind speed. A general minimum-variance method for optimally retrieving geophysical parameters from multichannel brightness temperature measurements is outlined, and several global statistical constraints of the type required by this method are computed. Finally, a unified set of efficient statistical and semi-physical algorithms is presented for obtaining fields of surface wind speed, integrated water vapor, cloud liquid water, and precipitation from SSM/I brightness temperature data. Features include: a semi-physical method for retrieving integrated cloud liquid water at 15 km resolution and with rms errors as small as approximately 0.02 kg/sq m; a 3-channel statistical algorithm for integrated water vapor which was constructed so as to have improved linear response to water vapor and reduced sensitivity to precipitation; and two complementary indices of precipitation activity (based on 37 GHz attenuation and 85 GHz scattering, respectively), each of which are relatively insensitive to variations in other environmental parameters.

Status on Iterative Transform Phase Retrieval Applied to the GBT Data

NASA Technical Reports Server (NTRS)

Dean, Bruce; Aronstein, David; Smith, Scott; Shiri, Ron; Hollis, Jan M.; Lyons, Richard; Prestage, Richard; Hunter, Todd; Ghigo, Frank; Nikolic, Bojan

2007-01-01

This slide presentation reviews the use of iterative transform phase retrieval in the analysis of the Green Bank Radio Telescope (GBT) Data. It reviews the NASA projects that have used phase retrieval, and the testbed for the algorithm to be used for the James Webb Space Telescope. It shows the comparison of phase retrieval with an interferometer, and reviews the two approaches used for phase retrieval, iterative transform (ITA) or parametric (non-linear least squares model fitting). The concept of ITA Phase Retrieval is reviewed, and the application to Radio Antennas is reviewed. The presentation also examines the National Radio Astronomy Observatory (NRAO) data from the GBT, and the Fourier model that NRAO uses to analyze the data. The challenge for ITA phase retrieval is reviewed, and the coherent approximation for incoherent data is shown. The validity of the approximation is good for a large tilt. There is a review of the proof of concept of the Phase Review simulation using the input wavefront, and the initial sampling parameters estimate from the focused GBT data.

Retrieval of Optical Parameters From Seawifs Observations Over The Pomme Area (north-est Atlantic): Biogeochemical Applications

NASA Astrophysics Data System (ADS)

Loisel, H.; Nicolas, J.-M.; Merien, D.; Claustre, H.; Sciandra, A.; Becu, G.; Deschamps, P.-Y.

Since the success of the first ocean color instrument, the Coastal Zone Color Sen- sor (CZCS), the interpretation of ocean color in terms of phytoplankton pigment (the chlorophyll, Chl) is now well recognized. The chlorophyll data, as detected from space, are now currently used to constraint oceanic biological models. New gener- ation of biological models now integrate explicitly 2 or more species of plankton, as well as dissolved organic and particulate matter, DOC and POC, respectively. The as- sessment of such information from the Sea-viewing Wide Field-of-view Sensor and inverse modeling will be discussed. In the frame of the POMME (Programme Océan Multidisciplinaire Méso-Echelle) project we will present the seasonal variability of the absorption, a, the backscattering, bb, and the scattering, b, coefficients as retrieved from SeaWiFS observations over the POMME area. These optical parameters will be compared with in situ measurements made during winter, spring and summer 2001, and biological information derived from these optical properties retrieved at different wavelengths will be presented.

[Modeling continuous scaling of NDVI based on fractal theory].

PubMed

Luan, Hai-Jun; Tian, Qing-Jiu; Yu, Tao; Hu, Xin-Li; Huang, Yan; Du, Ling-Tong; Zhao, Li-Min; Wei, Xi; Han, Jie; Zhang, Zhou-Wei; Li, Shao-Peng

2013-07-01

Scale effect was one of the very important scientific problems of remote sensing. The scale effect of quantitative remote sensing can be used to study retrievals' relationship between different-resolution images, and its research became an effective way to confront the challenges, such as validation of quantitative remote sensing products et al. Traditional up-scaling methods cannot describe scale changing features of retrievals on entire series of scales; meanwhile, they are faced with serious parameters correction issues because of imaging parameters' variation of different sensors, such as geometrical correction, spectral correction, etc. Utilizing single sensor image, fractal methodology was utilized to solve these problems. Taking NDVI (computed by land surface radiance) as example and based on Enhanced Thematic Mapper Plus (ETM+) image, a scheme was proposed to model continuous scaling of retrievals. Then the experimental results indicated that: (a) For NDVI, scale effect existed, and it could be described by fractal model of continuous scaling; (2) The fractal method was suitable for validation of NDVI. All of these proved that fractal was an effective methodology of studying scaling of quantitative remote sensing.

Retrieving Temperature Anomaly in the Global Subsurface and Deeper Ocean From Satellite Observations

NASA Astrophysics Data System (ADS)

Su, Hua; Li, Wene; Yan, Xiao-Hai

2018-01-01

Retrieving the subsurface and deeper ocean (SDO) dynamic parameters from satellite observations is crucial for effectively understanding ocean interior anomalies and dynamic processes, but it is challenging to accurately estimate the subsurface thermal structure over the global scale from sea surface parameters. This study proposes a new approach based on Random Forest (RF) machine learning to retrieve subsurface temperature anomaly (STA) in the global ocean from multisource satellite observations including sea surface height anomaly (SSHA), sea surface temperature anomaly (SSTA), sea surface salinity anomaly (SSSA), and sea surface wind anomaly (SSWA) via in situ Argo data for RF training and testing. RF machine-learning approach can accurately retrieve the STA in the global ocean from satellite observations of sea surface parameters (SSHA, SSTA, SSSA, SSWA). The Argo STA data were used to validate the accuracy and reliability of the results from the RF model. The results indicated that SSHA, SSTA, SSSA, and SSWA together are useful parameters for detecting SDO thermal information and obtaining accurate STA estimations. The proposed method also outperformed support vector regression (SVR) in global STA estimation. It will be a useful technique for studying SDO thermal variability and its role in global climate system from global-scale satellite observations.

Using the ARTMO toolbox for automated retrieval of biophysical parameters through radiative transfer model inversion: Optimizing LUT-based inversion

NASA Astrophysics Data System (ADS)

Verrelst, J.; Rivera, J. P.; Leonenko, G.; Alonso, L.; Moreno, J.

2012-04-01

Radiative transfer (RT) modeling plays a key role for earth observation (EO) because it is needed to design EO instruments and to develop and test inversion algorithms. The inversion of a RT model is considered as a successful approach for the retrieval of biophysical parameters because of being physically-based and generally applicable. However, to the broader community this approach is considered as laborious because of its many processing steps and expert knowledge is required to realize precise model parameterization. We have recently developed a radiative transfer toolbox ARTMO (Automated Radiative Transfer Models Operator) with the purpose of providing in a graphical user interface (GUI) essential models and tools required for terrestrial EO applications such as model inversion. In short, the toolbox allows the user: i) to choose between various plant leaf and canopy RT models (e.g. models from the PROSPECT and SAIL family, FLIGHT), ii) to choose between spectral band settings of various air- and space-borne sensors or defining own sensor settings, iii) to simulate a massive amount of spectra based on a look up table (LUT) approach and storing it in a relational database, iv) to plot spectra of multiple models and compare them with measured spectra, and finally, v) to run model inversion against optical imagery given several cost options and accuracy estimates. In this work ARTMO was used to tackle some well-known problems related to model inversion. According to Hadamard conditions, mathematical models of physical phenomena are mathematically invertible if the solution of the inverse problem to be solved exists, is unique and depends continuously on data. This assumption is not always met because of the large number of unknowns and different strategies have been proposed to overcome this problem. Several of these strategies have been implemented in ARTMO and were here analyzed to optimize the inversion performance. Data came from the SPARC-2003 dataset, which was acquired on the agricultural test site Barrax, Spain. LUTs were created using the 4SAIL and FLIGHT models and were inverted against CHRIS data in order to retrieve maps of chlorophyll content (chl) and leaf area index (LAI). The following inversion steps have been optimized: 1. Cost function. The performances of about 50 different cost functions (i.e. minimum distance functions) were compared. Remarkably, in none of the studied cases the widely used root mean square error (RMSE) led to most accurate results. Depending on the retrieved parameter, more successful functions were: 'Sharma and Mittal', 'Shannońs entropy', 'Hellinger distance', 'Pearsońs chi-square'. 2. Gaussian noise. Earth observation data typically encompass a certain degree of noise due to errors related to radiometric and geometric processing. In all cases, adding 5% Gaussian noise to the simulated spectra led to more accurate retrievals as compared to without noise. 3. Average of multiple best solutions. Because multiple parameter combinations may lead to the same spectra, a way to overcome this problem is not searching for the top best match but for a percentage of best matches. Optimized retrievals were encountered when including an average of 7% (Chl) to 10% (LAI) top best matches. 4. Integration of estimates. The option is provided to integrate estimates of biochemical contents at the canopy level (e.g., total chlorophyll: Chl × LAI, or water: Cw × LAI), which can lead to increased robustness and accuracy. 5. Class-based inversion. This option is probably ARTMÓs most powerful feature as it allows model parameterization depending on the imagés land cover classes (e.g. different soil or vegetation types). Class-based inversion can lead to considerably improved accuracies compared to one generic class. Results suggest that 4SAIL and FLIGHT performed alike for Chl but not for LAI. While both models rely on the leaf model PROSPECT for Chl retrieval, their different nature (e.g. numerical vs. ray tracing) may cause that retrieval of structural parameters such as LAI differ. Finally, it should be noted that the whole analysis can be intuitively performed by the toolbox. ARTMO is freely available to the EO community for further development. Expressions of interest are welcome and should be directed to the corresponding author.

Retrieve sea surface salinity using principal component regression model based on SMOS satellite data

NASA Astrophysics Data System (ADS)

Zhao, Hong; Li, Changjun; Li, Hongping; Lv, Kebo; Zhao, Qinghui

2016-06-01

The sea surface salinity (SSS) is a key parameter in monitoring ocean states. Observing SSS can promote the understanding of global water cycle. This paper provides a new approach for retrieving sea surface salinity from Soil Moisture and Ocean Salinity (SMOS) satellite data. Based on the principal component regression (PCR) model, SSS can also be retrieved from the brightness temperature data of SMOS L2 measurements and Auxiliary data. 26 pair matchup data is used in model validation for the South China Sea (in the area of 4°-25°N, 105°-125°E). The RMSE value of PCR model retrieved SSS reaches 0.37 psu (practical salinity units) and the RMSE of SMOS SSS1 is 1.65 psu when compared with in-situ SSS. The corresponding Argo daily salinity data during April to June 2013 is also used in our validation with RMSE value 0.46 psu compared to 1.82 psu for daily averaged SMOS L2 products. This indicates that the PCR model is valid and may provide us with a good approach for retrieving SSS from SMOS satellite data.

Physically-Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Mango, Stephen A.; Huang, Hung-Lung

2007-01-01

A physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). NPOESS Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the Atlantic-THORPEX Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and the Hyperspectral Environmental Suite (HES). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on Polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project and the following NPOESS series of satellites.

Constraining the Structure of Hot Jupiter Atmospheres Using a Hybrid Version of the NEMESIS Retrieval Algorithm

NASA Astrophysics Data System (ADS)

Badhan, Mahmuda A.; Mandell, Avi M.; Hesman, Brigette; Nixon, Conor; Deming, Drake; Irwin, Patrick; Barstow, Joanna; Garland, Ryan

2015-11-01

Understanding the formation environments and evolution scenarios of planets in nearby planetary systems requires robust measures for constraining their atmospheric physical properties. Here we have utilized a combination of two different parameter retrieval approaches, Optimal Estimation and Markov Chain Monte Carlo, as part of the well-validated NEMESIS atmospheric retrieval code, to infer a range of temperature profiles and molecular abundances of H2O, CO2, CH4 and CO from available dayside thermal emission observations of several hot-Jupiter candidates. In order to keep the number of parameters low and henceforth retrieve more plausible profile shapes, we have used a parametrized form of the temperature profile based upon an analytic radiative equilibrium derivation in Guillot et al. 2010 (Line et al. 2012, 2014). We show retrieval results on published spectroscopic and photometric data from both the Hubble Space Telescope and Spitzer missions, and compare them with simulations from the upcoming JWST mission. In addition, since NEMESIS utilizes correlated distribution of absorption coefficients (k-distribution) amongst atmospheric layers to compute these models, updates to spectroscopic databases can impact retrievals quite significantly for such high-temperature atmospheres. As high-temperature line databases are continually being improved, we also compare retrievals between old and newer databases.

Measurement of the Temperature Dependence of Line Mixing and Pressure Broadening Parameters between 296 and 90 K in the v3 band of 12CH4 and their Influence on Atmospheric Methane Retrievals

NASA Technical Reports Server (NTRS)

Mondelain, Didier; Payan, Sebastien; Deng, Wenping; Camy-Peyret, Claude; Hurtmans, Daniel; Mantz, Arlan W.

2007-01-01

We measured the temperature dependence of the nitrogen broadening, narrowing and line-mixing coefficients of four lines of the P9 manifold in the v3 band of 12CH4 for atmospheric purposes. The data were collected using our tunable diode laser (TDL) spectrometer with active wavenumber control coupled to a newly developed cold Herriott cell with a path length of 5.37 m and a temperature uniformity of better than 0.01 K along the cell. We recorded and analyzed spectra recorded at sample temperature between 90 K and room temperature. We have investigate the influence of our new results in the inversion model used to retrieve methane profiles from atmospheric spectra; our new results make it possible to retrieve significantly more precise methane profiles. The atmospheric spectra we utilized were obtained by several of us with a balloon-born Fourier Transform infrared experiment in a limb configuration. Differences up to 7% on the retrieved volume mixing ratio were found compared to an inversion model using only HITRAN04 spectroscopic parameters.

Information content of thermal infrared a microwave bands for simultaneous retrieval of cirrus ice water path and particle effective diameter

NASA Astrophysics Data System (ADS)

Bell, A.; Tang, G.; Yang, P.; Wu, D.

2017-12-01

Due to their high spatial and temporal coverage, cirrus clouds have a profound role in regulating the Earth's energy budget. Variability of their radiative, geometric, and microphysical properties can pose significant uncertainties in global climate model simulations if not adequately constrained. Thus, the development of retrieval methodologies able to accurately retrieve ice cloud properties and present associated uncertainties is essential. The effectiveness of cirrus cloud retrievals relies on accurate a priori understanding of ice radiative properties, as well as the current state of the atmosphere. Current studies have implemented information content theory analyses prior to retrievals to quantify the amount of information that should be expected on parameters to be retrieved, as well as the relative contribution of information provided by certain measurement channels. Through this analysis, retrieval algorithms can be designed in a way to maximize the information in measurements, and therefore ensure enough information is present to retrieve ice cloud properties. In this study, we present such an information content analysis to quantify the amount of information to be expected in retrievals of cirrus ice water path and particle effective diameter using sub-millimeter and thermal infrared radiometry. Preliminary results show these bands to be sensitive to changes in ice water path and effective diameter, and thus lend confidence their ability to simultaneously retrieve these parameters. Further quantification of sensitivity and the information provided from these bands can then be used to design and optimal retrieval scheme. While this information content analysis is employed on a theoretical retrieval combining simulated radiance measurements, the methodology could in general be applicable to any instrument or retrieval approach.

A Physical Model to Estimate Snowfall over Land using AMSU-B Observations

NASA Technical Reports Server (NTRS)

Kim, Min-Jeong; Weinman, J. A.; Olson, W. S.; Chang, D.-E.; Skofronick-Jackson, G.; Wang, J. R.

2008-01-01

In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3 +/- 1 GHz, 183.3 +/- 3 GHz, and 183.3 +/- 7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York. In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes. Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies. Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about +/- 5 K at all five frequencies. Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z(sub e) and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z(sub e)-R relationships fall in the range of previously established Z(sub e)-R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures.

Photopolarimetric Retrievals of Snow Properties

NASA Technical Reports Server (NTRS)

Ottaviani, M.; van Diedenhoven, B.; Cairns, B.

2015-01-01

Polarimetric observations of snow surfaces, obtained in the 410-2264 nm range with the Research Scanning Polarimeter onboard the NASA ER-2 high-altitude aircraft, are analyzed and presented. These novel measurements are of interest to the remote sensing community because the overwhelming brightness of snow plagues aerosol and cloud retrievals based on airborne and spaceborne total reflection measurements. The spectral signatures of the polarized reflectance of snow are therefore worthwhile investigating in order to provide guidance for the adaptation of algorithms currently employed for the retrieval of aerosol properties over soil and vegetated surfaces. At the same time, the increased information content of polarimetric measurements allows for a meaningful characterization of the snow medium. In our case, the grains are modeled as hexagonal prisms of variable aspect ratios and microscale roughness, yielding retrievals of the grains' scattering asymmetry parameter, shape and size. The results agree with our previous findings based on a more limited data set, with the majority of retrievals leading to moderately rough crystals of extreme aspect ratios, for each scene corresponding to a single value of the asymmetry parameter.

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.

Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

NASA Astrophysics Data System (ADS)

Moradizadeh, Mina; Saradjian, Mohammad R.

2018-03-01

Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

Impact of line parameter database, continuum absorption, full grind configuration, and L1B update on GOSAT TIR methane retrieval

NASA Astrophysics Data System (ADS)

Yamada, A.; Saitoh, N.; Nonogaki, R.; Imasu, R.; Shiomi, K.; Kuze, A.

2016-12-01

The thermal infrared (TIR) band of Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) onboard Greenhouse Gases Observing Satellite (GOSAT) observes CH4 profile at wavenumber range from 1210 cm-1 to 1360 cm-1 including CH4 ν4 band. The current retrieval algorithm (V1.0) uses LBLRTM V12.1 with AER V3.1 line database to calculate optical depth. LBLRTM V12.1 include MT_CKD 2.5.2 model to calculate continuum absorption. The continuum absorption has large uncertainty, especially temperature dependent coefficient, between BPS model and MT_CKD model in the wavenumber region of 1210-1250 cm-1(Paynter and Ramaswamy, 2014). The purpose of this study is to assess the impact on CH4 retrieval from the line parameter databases and the uncertainty of continuum absorption. We used AER v1.0 database, HITRAN2004 database, HITRAN2008 database, AER V3.2 database, and HITRAN2012 database (Rothman et al. 2005, 2009, and 2013. Clough et al., 2005). AER V1.0 database is based on HITRAN2000. The CH4 line parameters of AER V3.1 and V3.2 databases are developed from HITRAN2008 including updates until May 2009 with line mixing parameters. We compared the retrieved CH4 with the HIPPO CH4 observation (Wofsy et al., 2012). The difference of AER V3.2 was the smallest and 24.1 ± 45.9 ppbv. The differences of AER V1.0, HITRAN2004, HITRAN2008, and HITRAN2012 were 35.6 ± 46.5 ppbv, 37.6 ± 46.3 ppbv, 32.1 ± 46.1 ppbv, and 35.2 ± 46.0 ppbv, respectively. Compare AER V3.2 case to HITRAN2008 case, the line coupling effect reduced difference by 8.0 ppbv. Median values of Residual difference from HITRAN2008 to AER V1.0, HITRAN2004, AER V3.2, and HITRAN2012 were 0.6 K, 0.1 K, -0.08 K, and 0.08 K, respectively, while median values of transmittance difference were less than 0.0003 and transmittance differences have small wavenumber dependence. We also discuss the retrieval error from the uncertainty of the continuum absorption, the test of full grid configuration for retrieval, and the retrieval results using GOSAT TIR L1B V203203, which are sample products to evaluate the next level 1B algorithm.

Investigation of Atmospheric Effects on Retrieval of Sun-Induced Fluorescence Using Hyperspectral Imagery.

PubMed

Ni, Zhuoya; Liu, Zhigang; Li, Zhao-Liang; Nerry, Françoise; Huo, Hongyuan; Sun, Rui; Yang, Peiqi; Zhang, Weiwei

2016-04-06

Significant research progress has recently been made in estimating fluorescence in the oxygen absorption bands, however, quantitative retrieval of fluorescence data is still affected by factors such as atmospheric effects. In this paper, top-of-atmosphere (TOA) radiance is generated by the MODTRAN 4 and SCOPE models. Based on simulated data, sensitivity analysis is conducted to assess the sensitivities of four indicators-depth_absorption_band, depth_nofs-depth_withfs, radiance and Fs/radiance-to atmospheric parameters (sun zenith angle (SZA), sensor height, elevation, visibility (VIS) and water content) in the oxygen absorption bands. The results indicate that the SZA and sensor height are the most sensitive parameters and that variations in these two parameters result in large variations calculated as the variation value/the base value in the oxygen absorption depth in the O₂-A and O₂-B bands (111.4% and 77.1% in the O₂-A band; and 27.5% and 32.6% in the O₂-B band, respectively). A comparison of fluorescence retrieval using three methods (Damm method, Braun method and DOAS) and SCOPE Fs indicates that the Damm method yields good results and that atmospheric correction can improve the accuracy of fluorescence retrieval. Damm method is the improved 3FLD method but considering atmospheric effects. Finally, hyperspectral airborne images combined with other parameters (SZA, VIS and water content) are exploited to estimate fluorescence using the Damm method and 3FLD method. The retrieval fluorescence is compared with the field measured fluorescence, yielding good results (R² = 0.91 for Damm vs. SCOPE SIF; R² = 0.65 for 3FLD vs. SCOPE SIF). Five types of vegetation, including ailanthus, elm, mountain peach, willow and Chinese ash, exhibit consistent associations between the retrieved fluorescence and field measured fluorescence.

Investigation of Atmospheric Effects on Retrieval of Sun-Induced Fluorescence Using Hyperspectral Imagery

PubMed Central

Ni, Zhuoya; Liu, Zhigang; Li, Zhao-Liang; Nerry, Françoise; Huo, Hongyuan; Sun, Rui; Yang, Peiqi; Zhang, Weiwei

2016-01-01

Significant research progress has recently been made in estimating fluorescence in the oxygen absorption bands, however, quantitative retrieval of fluorescence data is still affected by factors such as atmospheric effects. In this paper, top-of-atmosphere (TOA) radiance is generated by the MODTRAN 4 and SCOPE models. Based on simulated data, sensitivity analysis is conducted to assess the sensitivities of four indicators—depth_absorption_band, depth_nofs-depth_withfs, radiance and Fs/radiance—to atmospheric parameters (sun zenith angle (SZA), sensor height, elevation, visibility (VIS) and water content) in the oxygen absorption bands. The results indicate that the SZA and sensor height are the most sensitive parameters and that variations in these two parameters result in large variations calculated as the variation value/the base value in the oxygen absorption depth in the O2-A and O2-B bands (111.4% and 77.1% in the O2-A band; and 27.5% and 32.6% in the O2-B band, respectively). A comparison of fluorescence retrieval using three methods (Damm method, Braun method and DOAS) and SCOPE Fs indicates that the Damm method yields good results and that atmospheric correction can improve the accuracy of fluorescence retrieval. Damm method is the improved 3FLD method but considering atmospheric effects. Finally, hyperspectral airborne images combined with other parameters (SZA, VIS and water content) are exploited to estimate fluorescence using the Damm method and 3FLD method. The retrieval fluorescence is compared with the field measured fluorescence, yielding good results (R2 = 0.91 for Damm vs. SCOPE SIF; R2 = 0.65 for 3FLD vs. SCOPE SIF). Five types of vegetation, including ailanthus, elm, mountain peach, willow and Chinese ash, exhibit consistent associations between the retrieved fluorescence and field measured fluorescence. PMID:27058542

Realistic uncertainties on Hapke model parameters from photometric measurement

NASA Astrophysics Data System (ADS)

Schmidt, Frédéric; Fernando, Jennifer

2015-11-01

The single particle phase function describes the manner in which an average element of a granular material diffuses the light in the angular space usually with two parameters: the asymmetry parameter b describing the width of the scattering lobe and the backscattering fraction c describing the main direction of the scattering lobe. Hapke proposed a convenient and widely used analytical model to describe the spectro-photometry of granular materials. Using a compilation of the published data, Hapke (Hapke, B. [2012]. Icarus 221, 1079-1083) recently studied the relationship of b and c for natural examples and proposed the hockey stick relation (excluding b > 0.5 and c > 0.5). For the moment, there is no theoretical explanation for this relationship. One goal of this article is to study a possible bias due to the retrieval method. We expand here an innovative Bayesian inversion method in order to study into detail the uncertainties of retrieved parameters. On Emission Phase Function (EPF) data, we demonstrate that the uncertainties of the retrieved parameters follow the same hockey stick relation, suggesting that this relation is due to the fact that b and c are coupled parameters in the Hapke model instead of a natural phenomena. Nevertheless, the data used in the Hapke (Hapke, B. [2012]. Icarus 221, 1079-1083) compilation generally are full Bidirectional Reflectance Diffusion Function (BRDF) that are shown not to be subject to this artifact. Moreover, the Bayesian method is a good tool to test if the sampling geometry is sufficient to constrain the parameters (single scattering albedo, surface roughness, b, c , opposition effect). We performed sensitivity tests by mimicking various surface scattering properties and various single image-like/disk resolved image, EPF-like and BRDF-like geometric sampling conditions. The second goal of this article is to estimate the favorable geometric conditions for an accurate estimation of photometric parameters in order to provide new constraints for future observation campaigns and instrumentations.

Synergistically combining Optical and Thermal radiative transfer modelswithin the EO-LDAS data assimilation framework to estimate land surfaceand component temperatures from MODIS and Sentinel-3

NASA Astrophysics Data System (ADS)

Timmermans, J.; Gomez-Dans, J. L.; Verhoef, W.; Tol, C. V. D.; Lewis, P.

2017-12-01

Evapotranspiration (ET) cannot be directly measured from space. Instead it relies on modelling approaches that use several land surface parameters (LSP), LAI and LST, in conjunction with meteorological parameters. Such a modelling approach presents two caveats: the validity of the model, and the consistency between the different input parameters. Often this second step is not considered, ignoring that without good inputs no decent output can provided. When LSP- dynamics contradict each other, the output of the model cannot be representative of reality. At present however, the LSPs used in large scale ET estimations originate from different single-sensor retrieval-approaches and even from different satellite sensors. In response, the Earth Observation Land Data Assimilation System (EOLDAS) was developed. EOLDAS uses a multi-sensor approach to couple different satellite observations/types to radiative transfer models (RTM), consistently. It is therefore capable of synergistically estimating a variety of LSPs. Considering that ET is most sensitive to the temperatures of the land surface (components), the goal of this research is to expand EOLDAS to the thermal domain. This research not only focuses on estimating LST, but also on retrieving (soil/vegetation, Sunlit/shaded) component temperatures, to facilitate dual/quad-source ET models. To achieve this, The Soil Canopy Observations of Photosynthesis and Energy (SCOPE) model was integrated into EOLDAS. SCOPE couples key-parameters to key-processes, such as photosynthesis, ET and optical/thermal RT. In this research SCOPE was also coupled to MODTRAN RTM, in order to estimate BOA component temperatures directly from TOA observations. This paper presents the main modelling steps of integrating these complex models into an operational platform. In addition it highlights the actual retrieval using different satellite observations, such as MODIS and Sentinel-3, and meteorological variables from the ERA-Interim.

Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre

2017-01-01

The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.

[Model and analysis of spectropolarimetric BRDF of painted target based on GA-LM method].

PubMed

Chen, Chao; Zhao, Yong-Qiang; Luo, Li; Pan, Quan; Cheng, Yong-Mei; Wang, Kai

2010-03-01

Models based on microfacet were used to describe spectropolarimetric BRDF (short for bidirectional reflectance distribution function) with experimental data. And the spectropolarimetric BRDF values of targets were measured with the comparison to the standard whiteboard, which was considered as Lambert and had a uniform reflectance rate up to 98% at arbitrary angle of view. And then the relationships between measured spectropolarimetric BRDF values and the angles of view, as well as wavelengths which were in a range of 400-720 nm were analyzed in details. The initial value needed to be input to the LM optimization method was difficult to get and greatly impacted the results. Therefore, optimization approach which combines genetic algorithm and Levenberg-Marquardt (LM) was utilized aiming to retrieve parameters of nonlinear models, and the initial values were obtained using GA approach. Simulated experiments were used to test the efficiency of the adopted optimization method. And the simulated experiment ensures the optimization method to have a good performance and be able to retrieve the parameters of nonlinear model efficiently. The correctness of the models was validated by real outdoor sampled data. The parameters of DoP model retrieved are the refraction index of measured targets. The refraction index of the same color painted target but with different materials was also obtained. Conclusion has been drawn that the refraction index from these two targets are very near and this slight difference could be understood by the difference in the conditions of paint targets' surface, not the material of the targets.

Optical property retrievals of subvisual cirrus clouds from OSIRIS limb-scatter measurements

NASA Astrophysics Data System (ADS)

Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

2012-08-01

We present a technique for retrieving the optical properties of subvisual cirrus clouds detected by OSIRIS, a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Optical properties from an in-situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is demonstrated that the retrieved extinction profile models accurately the measured in-cloud radiances from OSIRIS. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

Modeling challenges and approaches in simulating the Jovian synchrotron radiation belts from an in-situ perspective

NASA Astrophysics Data System (ADS)

Adumitroaie, V.; Oyafuso, F. A.; Levin, S.; Gulkis, S.; Janssen, M. A.; Santos-Costa, D.; Bolton, S. J.

2017-12-01

In order to obtain credible atmospheric composition retrieval values from Jupiter's observed radiative signature via Juno's MWR instrument, it is necessary to separate as robustly as possible the contributions from three emission sources: CMB, planet and synchrotron radiation belts. The numerical separation requires a refinement, based on the in-situ data, of a higher fidelity model for the synchrotron emission, namely the multi-parameter, multi-zonal model of Levin at al. (2001). This model employs an empirical electron energy distribution, which prior to the Juno mission, has been adjusted exclusively from VLA observations. At minimum 8 sets of perijove observations (i.e. by PJ9) have to be delivered to an inverse model for retrieval of the electron distribution parameters with the goal of matching the synchrotron emission observed along MWR's lines of sight. The challenges and approaches taken to perform this task are discussed here. The model will be continuously improved with the availability of additional information, both from the MWR and magnetometer instruments.

Smsynth: AN Imagery Synthesis System for Soil Moisture Retrieval

NASA Astrophysics Data System (ADS)

Cao, Y.; Xu, L.; Peng, J.

2018-04-01

Soil moisture (SM) is a important variable in various research areas, such as weather and climate forecasting, agriculture, drought and flood monitoring and prediction, and human health. An ongoing challenge in estimating SM via synthetic aperture radar (SAR) is the development of the retrieval SM methods, especially the empirical models needs as training samples a lot of measurements of SM and soil roughness parameters which are very difficult to acquire. As such, it is difficult to develop empirical models using realistic SAR imagery and it is necessary to develop methods to synthesis SAR imagery. To tackle this issue, a SAR imagery synthesis system based on the SM named SMSynth is presented, which can simulate radar signals that are realistic as far as possible to the real SAR imagery. In SMSynth, SAR backscatter coefficients for each soil type are simulated via the Oh model under the Bayesian framework, where the spatial correlation is modeled by the Markov random field (MRF) model. The backscattering coefficients simulated based on the designed soil parameters and sensor parameters are added into the Bayesian framework through the data likelihood where the soil parameters and sensor parameters are set as realistic as possible to the circumstances on the ground and in the validity range of the Oh model. In this way, a complete and coherent Bayesian probabilistic framework is established. Experimental results show that SMSynth is capable of generating realistic SAR images that suit the needs of a large amount of training samples of empirical models.

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.

Retrieval of Snow Properties for Ku- and Ka-band Dual-Frequency Radar

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert; Tokay, Ali; Bliven, Larry F.

2016-01-01

The focus of this study is on the estimation of snow microphysical properties and the associated bulk parameters such as snow water content and water equivalent snowfall rate for Ku- and Ka-band dual-frequency radar. This is done by exploring a suitable scattering model and the proper particle size distribution (PSD) assumption that accurately represent, in the electromagnetic domain, the micro/macro-physical properties of snow. The scattering databases computed from simulated aggregates for small-to-moderate particle sizes are combined with a simple scattering model for large particle sizes to characterize snow scattering properties over the full range of particle sizes. With use of the single-scattering results, the snow retrieval lookup tables can be formed in a way that directly links the Ku- and Ka-band radar reflectivities to snow water content and equivalent snowfall rate without use of the derived PSD parameters. A sensitivity study of the retrieval results to the PSD and scattering models is performed to better understand the dual-wavelength retrieval uncertainties. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, self-consistency tests are conducted using measurements of the snow PSD and fall velocity acquired from the Snow Video Imager Particle Image Probe (SVIPIP) duringthe winter of 2014 at the NASA Wallops Flight Facility site in Wallops Island, Virginia.

Retrieval of Snow Properties for Ku- and Ka-Band Dual-Frequency Radar

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert; Tokay, Ali; Bliven, Larry F.

2016-01-01

The focus of this study is on the estimation of snow microphysical properties and the associated bulk parameters such as snow water content and water equivalent snowfall rate for Ku- and Ka-band dual-frequency radar. This is done by exploring a suitable scattering model and the proper particle size distribution (PSD) assumption that accurately represent, in the electromagnetic domain, the micro-macrophysical properties of snow. The scattering databases computed from simulated aggregates for small-to-moderate particle sizes are combined with a simple scattering model for large particle sizes to characterize snow-scattering properties over the full range of particle sizes. With use of the single-scattering results, the snow retrieval lookup tables can be formed in a way that directly links the Ku- and Ka-band radar reflectivities to snow water content and equivalent snowfall rate without use of the derived PSD parameters. A sensitivity study of the retrieval results to the PSD and scattering models is performed to better understand the dual-wavelength retrieval uncertainties. To aid in the development of the Ku- and Ka-band dual-wavelength radar technique and to further evaluate its performance, self-consistency tests are conducted using measurements of the snow PSD and fall velocity acquired from the Snow Video Imager Particle Image Probe (SVIPIP) during the winter of 2014 at the NASA Wallops Flight Facility site in Wallops Island, Virginia.

Atmospherical simulations of the OMEGA/MEX observations

NASA Astrophysics Data System (ADS)

Melchiorri, R.; Drossart, P.; Combes, M.; Encrenaz, T.; Fouchet, T.; Forget, F.; Bibring, J. P.; Ignatiev, N.; Moroz, V.; OMEGA Team

The modelization of the atmospheric contribution in the martian spectrum is an important step for the OMEGA data analysis.A full line by line radiative transfer calculation is made for the gas absorption; the dust opacity component, in a first approximation, is calculated as an optically thin additive component.Due to the large number of parameters needed in the calculations, the building of a huge data base to be interpolated is not envisageable, for each observed OMEGA spectrum with calculation for all the involved parameters (atmospheric pressure, water abundance, CO abundance, dust opacity and geometric angles of observation). The simulation of the observations allows us to fix all the orbital parameters and leave the unknown parameters as the only variables.Starting from the predictions of the current meteorological models of Mars we build a smaller data base corresponding on each observation. We present here a first order simulation, which consists in retrieving atmospheric contribution from the solar reflected component as a multiplicative (for gas absorption) and an additive component (for suspended dust contribution); although a fully consistent approach will require to include surface and atmosphere contributions together in synthetic calculations, this approach is sufficient for retrieving mineralogic information cleaned from atmospheric absorption at first order.First comparison to OMEGA spectra will be presented, with first order retrieval of CO2 pressure, CO and H2O abundance, and dust opacity.

DEVELOPING ATMOSPHERIC RETRIEVAL METHODS FOR DIRECT IMAGING SPECTROSCOPY OF GAS GIANTS IN REFLECTED LIGHT. I. METHANE ABUNDANCES AND BASIC CLOUD PROPERTIES

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

Lupu, Roxana E.; Marley, Mark S.; Zahnle, Kevin

Upcoming space-based coronagraphic instruments in the next decade will perform reflected light spectroscopy and photometry of cool directly imaged extrasolar giant planets. We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs a geometric albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler ( emcee ) and a multimodal nested sampling algorithm ( MultiNest ) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model andmore » highlights possible discrepancies in the likelihood maps. As a proof of concept, our current atmospheric model contains one or two cloud layers, methane as a major absorber, and a H{sub 2}–He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise ratio in the presence of spectral noise correlations. After internal validation, the method is applied to realistic spectra of Jupiter, Saturn, and HD 99492c, a model observing target. We find that the presence or absence of clouds and methane can be determined with high confidence, while parameter uncertainties are model dependent and correlated. Such general methods will also be applicable to the interpretation of direct imaging spectra of cloudy terrestrial planets.« less

EM Bias-Correction for Ice Thickness and Surface Roughness Retrievals over Rough Deformed Sea Ice

NASA Astrophysics Data System (ADS)

Li, L.; Gaiser, P. W.; Allard, R.; Posey, P. G.; Hebert, D. A.; Richter-Menge, J.; Polashenski, C. M.

2016-12-01

The very rough ridge sea ice accounts for significant percentage of total ice areas and even larger percentage of total volume. The commonly used Radar altimeter surface detection techniques are empirical in nature and work well only over level/smooth sea ice. Rough sea ice surfaces can modify the return waveforms, resulting in significant Electromagnetic (EM) bias in the estimated surface elevations, and thus large errors in the ice thickness retrievals. To understand and quantify such sea ice surface roughness effects, a combined EM rough surface and volume scattering model was developed to simulate radar returns from the rough sea ice `layer cake' structure. A waveform matching technique was also developed to fit observed waveforms to a physically-based waveform model and subsequently correct the roughness induced EM bias in the estimated freeboard. This new EM Bias Corrected (EMBC) algorithm was able to better retrieve surface elevations and estimate the surface roughness parameter simultaneously. In situ data from multi-instrument airborne and ground campaigns were used to validate the ice thickness and surface roughness retrievals. For the surface roughness retrievals, we applied this EMBC algorithm to co-incident LiDAR/Radar measurements collected during a Cryosat-2 under-flight by the NASA IceBridge missions. Results show that not only does the waveform model fit very well to the measured radar waveform, but also the roughness parameters derived independently from the LiDAR and radar data agree very well for both level and deformed sea ice. For sea ice thickness retrievals, validation based on in-situ data from the coordinated CRREL/NRL field campaign demonstrates that the physically-based EMBC algorithm performs fundamentally better than the empirical algorithm over very rough deformed sea ice, suggesting that sea ice surface roughness effects can be modeled and corrected based solely on the radar return waveforms.

Four-Dimensional Data Assimilation Using the Adjoint Method

NASA Astrophysics Data System (ADS)

Bao, Jian-Wen

The calculus of variations is used to confirm that variational four-dimensional data assimilation (FDDA) using the adjoint method can be implemented when the numerical model equations have a finite number of first-order discontinuous points. These points represent the on/off switches associated with physical processes, for which the Jacobian matrix of the model equation does not exist. Numerical evidence suggests that, in some situations when the adjoint method is used for FDDA, the temperature field retrieved using horizontal wind data is numerically not unique. A physical interpretation of this type of non-uniqueness of the retrieval is proposed in terms of energetics. The adjoint equations of a numerical model can also be used for model-parameter estimation. A general computational procedure is developed to determine the size and distribution of any internal model parameter. The procedure is then applied to a one-dimensional shallow -fluid model in the context of analysis-nudging FDDA: the weighting coefficients used by the Newtonian nudging technique are determined. The sensitivity of these nudging coefficients to the optimal objectives and constraints is investigated. Experiments of FDDA using the adjoint method are conducted using the dry version of the hydrostatic Penn State/NCAR mesoscale model (MM4) and its adjoint. The minimization procedure converges and the initialization experiment is successful. Temperature-retrieval experiments involving an assimilation of the horizontal wind are also carried out using the adjoint of MM4.

Modelling of the L-band brightness temperatures measured with ELBARA III radiometer on Bubnow wetland

NASA Astrophysics Data System (ADS)

Gluba, Lukasz; Sagan, Joanna; Lukowski, Mateusz; Szlazak, Radoslaw; Usowicz, Boguslaw

2017-04-01

Microwave radiometry has become the main tool for investigating soil moisture (SM) with remote sensing methods. ESA - SMOS (Soil Moisture and Ocean Salinity) satellite operating at L-band provides global distribution of soil moisture. An integral part of SMOS mission are calibration and validation activities involving measurements with ELBARA III which is an L-band microwave passive radiometer. It is done in order to improve soil moisture retrievals - make them more time-effective and accurate. The instrument is located at Bubnow test-site, on the border of cultivated field, fallow, meadow and natural wetland being a part of Polesie National Park (Poland). We obtain both temporal and spatial dependences of brightness temperatures for varied types of land covers with the ELBARA III directed at different azimuths. Soil moisture is retrieved from brightness temperature using L-band Microwave Emission of the Biosphere (L-MEB) model, the same as currently used radiative transfer model for SMOS. Parametrization of L-MEB, as well as input values are still under debate. We discuss the results of SM retrievals basing on data obtained during first year of the radiometer's operation. We analyze temporal dependences of retrieved SM for one-parameter (SM), two-parameter (SM, τ - optical depth) and three-parameter (SM, τ, Hr - roughness parameter) retrievals, as well as spatial dependences for specific dates. Special case of Simplified Roughness Parametrization, combining the roughness parameter and optical depth, is considered. L-MEB processing is supported by the continuous measurements of soil moisture and temperature obtained from nearby agrometeorological station, as well as studies on the soil granulometric composition of the Bubnow test-site area. Furthermore, for better estimation of optical depth, the satellite-derived Normalized Difference Vegetation Index (NDVI) was employed, supported by measured in situ vegetation parameters (such as Leaf Area Index and Vegetation Water Content) obtained during the field campaigns. The values of NDVI around ELBARA III radiometer are provided by Sentinel-2 satellite with approximately 10 m spatial resolution and average 10 days of time interval within studied period of time. The work was partially funded under two ESA projects: 1) "ELBARA_PD (Penetration Depth)" No. 4000107897/13/NL/KML, funded by the Government of Poland through an ESA-PECS contract (Plan for European Cooperating States). 2) "Technical Support for the fabrication and deployment of the radiometer ELBARA-III in Bubnow, Poland" No. 4000113360/15/NL/FF/gp.

Estimation of surface soil moisture and roughness from multi-angular ASAR imagery in the Watershed Allied Telemetry Experimental Research (WATER)

NASA Astrophysics Data System (ADS)

Wang, S. G.; Li, X.; Han, X. J.; Jin, R.

2011-05-01

Radar remote sensing has demonstrated its applicability to the retrieval of basin-scale soil moisture. The mechanism of radar backscattering from soils is complicated and strongly influenced by surface roughness. Additionally, retrieval of soil moisture using AIEM (advanced integrated equation model)-like models is a classic example of underdetermined problem due to a lack of credible known soil roughness distributions at a regional scale. Characterization of this roughness is therefore crucial for an accurate derivation of soil moisture based on backscattering models. This study aims to simultaneously obtain surface roughness parameters (standard deviation of surface height σ and correlation length cl) along with soil moisture from multi-angular ASAR images by using a two-step retrieval scheme based on the AIEM. The method firstly used a semi-empirical relationship that relates the roughness slope, Zs (Zs = σ2/cl) and the difference in backscattering coefficient (Δσ) from two ASAR images acquired with different incidence angles. Meanwhile, by using an experimental statistical relationship between σ and cl, both these parameters can be estimated. Then, the deduced roughness parameters were used for the retrieval of soil moisture in association with the AIEM. An evaluation of the proposed method was performed in an experimental area in the middle stream of the Heihe River Basin, where the Watershed Allied Telemetry Experimental Research (WATER) was taken place. It is demonstrated that the proposed method is feasible to achieve reliable estimation of soil water content. The key challenge is the presence of vegetation cover, which significantly impacts the estimates of surface roughness and soil moisture.

Multispectral information for gas and aerosol retrieval from TANSO-FTS instrument

NASA Astrophysics Data System (ADS)

Herbin, H.; Labonnote, L. C.; Dubuisson, P.

2012-11-01

The Greenhouse gases Observing SATellite (GOSAT) mission and in particular TANSO-FTS instrument has the advantage to measure simultaneously the same field of view in different spectral ranges with a high spectral resolution. These features are promising to improve, not only, gaseous retrieval in clear sky or scattering atmosphere, but also to retrieve aerosol parameters. Therefore, this paper is dedicated to an Information Content (IC) analysis of potential synergy between thermal infrared, shortwave infrared and visible, in order to obtain a more accurate retrieval of gas and aerosol. The latter is based on Shannon theory and used a sophisticated radiative transfer algorithm developed at "Laboratoire d'Optique Atmosphérique", dealing with multiple scattering. This forward model can be relied to an optimal estimation method, which allows simultaneously retrieving gases profiles and aerosol granulometry and concentration. The analysis of the information provided by the spectral synergy is based on climatology of dust, volcanic ash and biomass burning aerosols. This work was conducted in order to develop a powerful tool that allows retrieving simultaneously not only the gas concentrations but also the aerosol characteristics by selecting the so called "best channels", i.e. the channels that bring most of the information concerning gas and aerosol. The methodology developed in this paper could also be used to define the specifications of future high spectral resolution mission to reach a given accuracy on retrieved parameters.

New Non-LTE Model of OH and CO2 Emission in the Mesosphere-Lower Thermosphere and its Application to Retrieving Nighttime Parameters

NASA Astrophysics Data System (ADS)

Panka, Peter A.

The hydroxyl, OH, and carbon dioxide, CO2, molecules and oxygen atoms, O(3P), are important parameters that characterize the chemistry, energetics, and dynamics of the nighttime mesosphere and lower thermosphere (MLT) region. Hence, there is much interest in obtaining high quality observations of these parameters in order to study the short-term variability as well as the long-term trends in characteristics of the MLT region. The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on board the Thermosphere, Ionosphere, Mesosphere, Energetics, and Dynamics (TIMED) satellite has been taking global, simultaneous measurements of limb infrared radiance in 10 spectral channels, including the OH 2.0 and 1.6-micron and CO2 4.3-micron emissions channels, continuously since late January 2002. These measurements can be interpreted using sophisticated non-Local Thermodynamic Equilibrium (non-LTE) models of OH and CO2 infrared emissions which can then be applied to obtain densities of these parameters (2.0 and 1.6-micron channel for O(3P)/OH and 4.3-micron channel for CO2). The latest non-LTE models of these molecules, however, do not fully represent all the dominant energy transfer mechanisms which influence their vibrational level distributions and infrared emissions. In particular, non-LTE models of CO2 4.3-micron emissions currently under-predict SABER measurements by up to 80%, and its application for the retrieval of CO2 will result in unrealistic densities. Additionally, current O(3P) retrievals from SABER OH emissions have been reported to be at least 30% higher compared to studies using other instruments. Methods to obtain OH total densities from SABER measurements have yet to be developed. Recent studies, however, have discovered a new energy transfer mechanism which influences both OH and CO2 infrared emissions, OH(v) → O(1D) → N2( v) → CO2(v3). This study focuses on the impact of this new mechanism on OH and CO2 infrared emissions as well as model applications for the retrieval of nighttime O( 3P), OH, and CO2 densities. We first study in detail the impact of the new mechanism on OH( v) vibrational level populations and emissions. We compared our calculations with the SABER/TIMED OH 1.6 and 2.0-micron limb radiances of the MLT and with ground and space observations of OH(v) densities in the nighttime mesosphere. We find that the new mechanism produces OH(v) density distributions which are in good agreement with both SABER limb OH emission observations and ground and space measurements. We then couple our OH non-LTE model with CO2 to study the impact of the new mechanism on CO2(v3) vibrational level populations and emissions. We compare our calculations with the SABER/TIMED 4.3-micron CO2 limb radiances and find that the new mechanism provides a strong enhancement of the 4.3-micron CO2 emissions, agreeing to within a 10-30% range. Further, a two-channel retrieval algorithm is developed to self-consistently invert the SABER measured radiances in the OH 2.0 and 1.6-micron channel to obtain vertical profiles of OH and O(3P) Volume Mixing Ratio (VMR). Studies of the inversion algorithm made with synthetic radiances indicate that a stable solution of the inverse problem can be obtained that is nearly independent of the starting conditions. The results presented from the two-channel algorithm to the SABER v2.0 data include comparisons of retrieved O(3P) with current SABER O(3P), in addition to O(3P) retrievals measured by the SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument, as well as those calculated by the WACCM (Whole Atmosphere Community Climate Model) model for four different days. The O( 3P) density retrieved between 90-95 km are, on average, lower than current SABER O(3P) by 10-50%. OH retrievals are performed over the same days and are compared with OH WACCM calculations as well as other studies. Finally, a similar self-consistent algorithm used for the retrieval of daytime CO2 densities is adopted for nighttime. The situation, however, is more complex for nighttime CO2, where lack of solar irradiation excitation greatly reduce 4.3-micron emission sensitivity to CO 2 density and, therefore, produces unrealistic retrievals. Alternative retrieval methods will be required to overcome these obstacles. For daytime, retrieval of temperature and CO2 are performed simultaneously due to strong coupling between these two parameters. Consideration of this effect will be crucial to obtain accurate nighttime CO2 densities.

AIRS Retrieval Validation During the EAQUATE

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L.; Cuomo, Vincenzo; Taylor, Jonathan P.; Barnet, Christopher D.; DiGirolamo, Paolo; Pappalardo, Gelsomina; Larar, Allen M.; Liu, Xu; Newman, Stuart M.

2006-01-01

Atmospheric and surface thermodynamic parameters retrieved with advanced hyperspectral remote sensors of Earth observing satellites are critical for weather prediction and scientific research. The retrieval algorithms and retrieved parameters from satellite sounders must be validated to demonstrate the capability and accuracy of both observation and data processing systems. The European AQUA Thermodynamic Experiment (EAQUATE) was conducted mainly for validation of the Atmospheric InfraRed Sounder (AIRS) on the AQUA satellite, but also for assessment of validation systems of both ground-based and aircraft-based instruments which will be used for other satellite systems such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) from the NPOESS Preparatory Project and the following NPOESS series of satellites. Detailed inter-comparisons were conducted and presented using different retrieval methodologies: measurements from airborne ultraspectral Fourier transform spectrometers, aircraft in-situ instruments, dedicated dropsondes and radiosondes, and ground based Raman Lidar, as well as from the European Center for Medium range Weather Forecasting (ECMWF) modeled thermal structures. The results of this study not only illustrate the quality of the measurements and retrieval products but also demonstrate the capability of these validation systems which are put in place to validate current and future hyperspectral sounding instruments and their scientific products.

Retrieval of seasonal dynamics of forest understory reflectance from semiarid to boreal forests using MODIS BRDF data

NASA Astrophysics Data System (ADS)

Pisek, Jan; Chen, Jing M.; Kobayashi, Hideki; Rautiainen, Miina; Schaepman, Michael E.; Karnieli, Arnon; Sprinstin, Michael; Ryu, Youngryel; Nikopensius, Maris; Raabe, Kairi

2016-03-01

Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. In this communication, we retrieved seasonal courses of understory normalized difference vegetation index (NDVI) from multiangular Moderate Resolution Imaging Spectroradiometer bidirectional reflectance distribution function (MODIS BRDF)/albedo data. We compared satellite-based seasonal courses of understory NDVI to understory NDVI values measured in different types of forests distributed along a wide latitudinal gradient (65.12°N-31.35°N). Our results indicated that the retrieval method performs well particularly over open forests of different types. We also demonstrated the limitations of the method for closed canopies, where the understory signal retrieval is much attenuated.

Developing Atmospheric Retrieval Methods for Direct Imaging Spectroscopy of Gas Giants in Reflected Light I: Methane Abundances and Basic Cloud Properties

NASA Technical Reports Server (NTRS)

Lupu, R. E.; Marley, M. S.; Lewis, N.; Line, M.; Traub, W.; Zahnle, K.

2016-01-01

Reflected light spectroscopy and photometry of cool, directly imaged extrasolar giant planets are expected to be performed in the next decade by space-based telescopes equipped with optical wavelength coronagraphs and integral field spectrographs, such as the Wide-Field Infrared Survey Telescope (WFIRST). We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs an albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler (emcee) and a multimodal nested sampling algorithm (MultiNest) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model, and highlights possible discrepancies in the likelihood maps. Here we apply this methodology to simulated spectra of cool giant planets. As a proof-of-concept, our current atmospheric model contains 1 or 2 cloud layers, methane as a major absorber, and a H2-He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise, in the presence of spectral noise correlations. After internal validation, the method is applied to realistic reflected-light spectra of Jupiter, Saturn, and HD 99492 c, a likely observing target. We find that the presence or absence of clouds and methane can be determined with high accuracy, while parameters uncertainties are model-dependent.

Cloud and Thermodynamic Parameters Retrieved from Satellite Ultraspectral Infrared Measurements

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L.; Larar, Allen M.; Liu, Xu; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

2008-01-01

Atmospheric-thermodynamic parameters and surface properties are basic meteorological parameters for weather forecasting. A physical geophysical parameter retrieval scheme dealing with cloudy and cloud-free radiance observed with satellite ultraspectral infrared sounders has been developed and applied to the Infrared Atmospheric Sounding Interferometer (IASI) and the Atmospheric InfraRed Sounder (AIRS). The retrieved parameters presented herein are from radiance data gathered during the Joint Airborne IASI Validation Experiment (JAIVEx). JAIVEx provided intensive aircraft observations obtained from airborne Fourier Transform Spectrometer (FTS) systems, in-situ measurements, and dedicated dropsonde and radiosonde measurements for the validation of the IASI products. Here, IASI atmospheric profile retrievals are compared with those obtained from dedicated dropsondes, radiosondes, and the airborne FTS system. The IASI examples presented here demonstrate the ability to retrieve fine-scale horizontal features with high vertical resolution from satellite ultraspectral sounder radiance spectra.

Impact of line parameter database and continuum absorption on GOSAT TIR methane retrieval

NASA Astrophysics Data System (ADS)

Yamada, A.; Saitoh, N.; Nonogaki, R.; Imasu, R.; Shiomi, K.; Kuze, A.

2017-12-01

The current methane retrieval algorithm (V1) at wavenumber range from 1210 cm-1 to 1360 cm-1 including CH4 ν 4 band from the thermal infrared (TIR) band of Thermal and Near-infrared Sensor for Carbon Observation Fourier Transform Spectrometer (TANSO-FTS) onboard Greenhouse Gases Observing Satellite (GOSAT) uses LBLRTM V12.1 with AER V3.1 line database and MT CKD 2.5.2 continuum absorption model to calculate optical depth. Since line parameter databases have been updated and the continuum absorption may have large uncertainty, the purpose of this study is to assess the impact on {CH}4 retrieval from the choice of line parameter databases and the uncertainty of continuum absorption. We retrieved {CH}4 profiles with replacement of line parameter database from AER V3.1 to AER v1.0, HITRAN 2004, HITRAN 2008, AER V3.2, or HITRAN 2012 (Rothman et al. 2005, 2009, and 2013. Clough et al., 2005), we assumed 10% larger continuum absorption coefficients and 50% larger temperature dependent coefficient of continuum absorption based on the report by Paynter and Ramaswamy (2014). We compared the retrieved CH4 with the HIPPO CH4 observation (Wofsy et al., 2012). The difference from HIPPO observation of AER V3.2 was the smallest and 24.1 ± 45.9 ppbv. The differences of AER V1.0, HITRAN 2004, HITRAN 2008, and HITRAN 2012 were 35.6 ± 46.5 ppbv, 37.6 ± 46.3 ppbv, 32.1 ± 46.1 ppbv, and 35.2 ± 46.0 ppbv, respectively. Maximum {CH}4 retrieval differences were -0.4 ppbv at the layer of 314 hPa when we used 10% larger absorption coefficients of {H}2O foreign continuum. Comparing AER V3.2 case to HITRAN 2008 case, the line coupling effect reduced difference by 8.0 ppbv. Line coupling effects were important for GOSAT TIR {CH}4 retrieval. Effects from the uncertainty of continuum absorption were negligible small for GOSAT TIR CH4 retrieval.

Wave optics-based LEO-LEO radio occultation retrieval

NASA Astrophysics Data System (ADS)

Benzon, Hans-Henrik; Høeg, Per

2016-06-01

This paper describes the theory for performing retrieval of radio occultations that use probing frequencies in the XK and KM band. Normally, radio occultations use frequencies in the L band, and GPS satellites are used as the transmitting source, and the occultation signals are received by a GPS receiver on board a Low Earth Orbit (LEO) satellite. The technique is based on the Doppler shift imposed, by the atmosphere, on the signal emitted from the GPS satellite. Two LEO satellites are assumed in the occultations discussed in this paper, and the retrieval is also dependent on the decrease in the signal amplitude caused by atmospheric absorption. The radio wave transmitter is placed on one of these satellites, while the receiver is placed on the other LEO satellite. One of the drawbacks of normal GPS-based radio occultations is that external information is needed to calculate some of the atmospheric products such as the correct water vapor content in the atmosphere. These limitations can be overcome when a proper selected range of high-frequency waves are used to probe the atmosphere. Probing frequencies close to the absorption line of water vapor have been included, thus allowing the retrieval of the water vapor content. Selecting the correct probing frequencies would make it possible to retrieve other information such as the content of ozone. The retrieval is performed through a number of processing steps which are based on the Full Spectrum Inversion (FSI) technique. The retrieval chain is therefore a wave optics-based retrieval chain, and it is therefore possible to process measurements that include multipath. In this paper simulated LEO to LEO radio occultations based on five different frequencies are used. The five frequencies are placed in the XK or KM frequency band. This new wave optics-based retrieval chain is used on a number of examples, and the retrieved atmospheric parameters are compared to the parameters from a global European Centre for Medium-Range Weather Forecasts analysis model. This model is used in a forward propagator that simulates the electromagnetic field amplitudes and phases at the receiver on board the LEO satellite. LEO-LEO cross-link radio occultations using high frequencies are a relatively new technique, and the possibilities and advantages of the technique still need to be investigated. The retrieval of this type of radio occultations is considerably more complicated than standard GPS to LEO radio occultations, because the attenuation of the probing radio waves is used in the retrieval and the atmospheric parameters are found using a least squares solver. The best algorithms and the number of probing frequencies that is economically viable must also be determined. This paper intends to answer some of these questions using end-to-end simulations.

A Grobner Basis Solution for Lightning Ground Flash Fraction Retrieval

NASA Technical Reports Server (NTRS)

Solakiewicz, Richard; Attele, Rohan; Koshak, William

2011-01-01

A Bayesian inversion method was previously introduced for retrieving the fraction of ground flashes in a set of flashes observed from a (low earth orbiting or geostationary) satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters, a scalar function was minimized by a numerical method. In order to improve this optimization, we introduce a Grobner basis solution to obtain analytic representations of the model parameters that serve as a refined initialization scheme to the numerical optimization. Using the Grobner basis, we show that there are exactly 2 solutions involving the first 3 moments of the (exponentially distributed) data. When the mean of the ground flash optical characteristic (e.g., such as the Maximum Group Area, MGA) is larger than that for cloud flashes, then a unique solution can be obtained.

Simultaneous retrieval of water vapour, temperature and cirrus clouds properties from measurements of far infrared spectral radiance over the Antarctic Plateau

NASA Astrophysics Data System (ADS)

Di Natale, Gianluca; Palchetti, Luca; Bianchini, Giovanni; Del Guasta, Massimo

2017-03-01

The possibility separating the contributions of the atmospheric state and ice clouds by using spectral infrared measurements is a fundamental step to quantifying the cloud effect in climate models. A simultaneous retrieval of cloud and atmospheric parameters from infrared wideband spectra will allow the disentanglement of the spectral interference between these variables. In this paper, we describe the development of a code for the simultaneous retrieval of atmospheric state and ice cloud parameters, and its application to the analysis of the spectral measurements acquired by the Radiation Explorer in the Far Infrared - Prototype for Applications and Development (REFIR-PAD) spectroradiometer, which has been in operation at Concordia Station on the Antarctic Plateau since 2012. The code performs the retrieval with a computational time that is comparable with the instrument acquisition time. Water vapour and temperature profiles and the cloud optical and microphysical properties, such as the generalised effective diameter and the ice water path, are retrieved by exploiting the 230-980 cm-1 spectral band. To simulate atmospheric radiative transfer, the Line-By-Line Radiative Transfer Model (LBLRTM) has been integrated with a specifically developed subroutine based on the δ-Eddington two-stream approximation, whereas the single-scattering properties of cirrus clouds have been derived from a database for hexagonal column habits. In order to detect ice clouds, a backscattering and depolarisation lidar, co-located with REFIR-PAD has been used, allowing us to infer the position and the cloud thickness to be used in the retrieval. A climatology of the vertical profiles of water vapour and temperature has been performed by using the daily radiosounding available at the station at 12:00 UTC. The climatology has been used to build an a priori profile correlation to constrain the fitting procedure. An optimal estimation method with the Levenberg-Marquardt approach has been used to perform the retrieval. In most cases, the retrieved humidity and temperature profiles show a good agreement with the radiosoundings, demonstrating that the simultaneous retrieval of the atmospheric state is not biased by the presence of cirrus clouds. Finally, the retrieved cloud parameters allow us to study the relationships between cloud temperature and optical depth and between effective particle diameter and ice water content. These relationships are similar to the statistical correlations measured on the Antarctic coast at Dumont d'Urville and in the Arctic region.

Soil moisture retrieval by active/passive microwave remote sensing data

NASA Astrophysics Data System (ADS)

Wu, Shengli; Yang, Lijuan

2012-09-01

This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship between Qpparameter and root mean square slope. So here, root mean square slope is a parameter that both models shared. Because of its big influence to backscattering and emissivity, we need to throw it out during the process of the combination of GO model and Qp model. The result we obtain from the combined model is the Fresnel reflection coefficient in the normal direction gama(0). It has a good relationship with the soil dielectric constant. In Dobson Model, there is a detailed description about Fresnel reflection coefficient and soil moisture. With the help of Dobson model and gama(0) that we have obtained, we can get the soil moisture that we want. The backscattering coefficient and emissivity data used in combined model is from TRMM/PR, TMI; with this data, we can obtain gama(0); further, we get the soil moisture by the relationship of the two parameters-- gama(0) and soil moisture. To validate the accuracy of the retrieval soil moisture, there is an experiment conducted in Tibet. The soil moisture data which is used to validate the retrieval algorithm is from GAME-Tibet IOP98 Soil Moisture and Temperature Measuring System (SMTMS). There are 9 observing sites in SMTMS to validate soil moisture. Meanwhile, we use the SMTMS soil moisture data obtained by Time Domain Reflectometer (TDR) to do the validation. And the result shows the comparison of retrieval and measured results is very good. Through the analysis, we can see that the retrieval and measured results in D66 is nearly close; and in MS3608, the measured result is a little higher than retrieval result; in MS3637, the retrieval result is a little higher than measured result. According to the analysis of the simulation results, we found that this combined active and passive approach to retrieve the soil moisture improves the retrieval accuracy.

[Mapping environmental vulnerability from ETM + data in the Yellow River Mouth Area].

PubMed

Wang, Rui-Yan; Yu, Zhen-Wen; Xia, Yan-Ling; Wang, Xiang-Feng; Zhao, Geng-Xing; Jiang, Shu-Qian

2013-10-01

The environmental vulnerability retrieval is important to support continuing data. The spatial distribution of regional environmental vulnerability was got through remote sensing retrieval. In view of soil and vegetation, the environmental vulnerability evaluation index system was built, and the environmental vulnerability of sampling points was calculated by the AHP-fuzzy method, then the correlation between the sampling points environmental vulnerability and ETM + spectral reflectance ratio including some kinds of conversion data was analyzed to determine the sensitive spectral parameters. Based on that, models of correlation analysis, traditional regression, BP neural network and support vector regression were taken to explain the quantitative relationship between the spectral reflectance and the environmental vulnerability. With this model, the environmental vulnerability distribution was retrieved in the Yellow River Mouth Area. The results showed that the correlation between the environmental vulnerability and the spring NDVI, the September NDVI and the spring brightness was better than others, so they were selected as the sensitive spectral parameters. The model precision result showed that in addition to the support vector model, the other model reached the significant level. While all the multi-variable regression was better than all one-variable regression, and the model accuracy of BP neural network was the best. This study will serve as a reliable theoretical reference for the large spatial scale environmental vulnerability estimation based on remote sensing data.

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.

Predicting inferior vena cava (IVC) filter retrievability using positional parameters: A comparative study of various filter types.

PubMed

Gotra, A; Doucet, C; Delli Fraine, P; Bessissow, A; Dey, C; Gallix, B; Boucher, L-M; Valenti, D

2018-05-14

To compare changes in inferior vena cava (IVC) filter positional parameters from insertion to removal and examine how they affect retrievability amongst various filter types. A total of 447 patients (260 men, 187 women) with a mean age of 55 years (range: 13-91 years) who underwent IVC filter retrieval between 2007-2014 were retrospectively included. Post-insertion and pre-retrieval angiographic studies were assessed for filter tilt, migration, strut wall penetration and retrieval outcomes. ANCOVA and multiple logistic regression models were used to analyze factors affecting retrieval success. Pairwise comparisons between filter types were performed. Of 488 IVC filter retrieval attempts, 94.1% were ultimately successful. The ALN filter had the highest mean absolute value of tilt (5.6 degrees), the Optease filter demonstrated the largest mean migration (-8.0mm) and the Bard G2 filter showed highest mean penetration (5.2mm). Dwell time of 0-90 days (OR, 11.1; P=0.01) or 90-180 days (OR, 2.6; P=0.02), net tilt of 10-15 degrees (OR 8.9; P=0.05), caudal migration of -10 to 0mm (OR, 3.46; P=0.03) and penetration less than 3mm (OR, 2.6; P=0.01) were positive predictors of successful retrievability. Higher odds of successful retrieval were obtained for the Bard G2X, Bard G2 and Cook Celect when compared to the ALN and Cordis Optease filters. Shorter dwell time, lower mean tilt, caudal migration and less caval wall penetration are positive predictors of successful IVC filter retrieval. Copyright © 2018 Société française de radiologie. Published by Elsevier Masson SAS. All rights reserved.

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.

Large memory capacity in chaotic artificial neural networks: a view of the anti-integrable limit.

PubMed

Lin, Wei; Chen, Guanrong

2009-08-01

In the literature, it was reported that the chaotic artificial neural network model with sinusoidal activation functions possesses a large memory capacity as well as a remarkable ability of retrieving the stored patterns, better than the conventional chaotic model with only monotonic activation functions such as sigmoidal functions. This paper, from the viewpoint of the anti-integrable limit, elucidates the mechanism inducing the superiority of the model with periodic activation functions that includes sinusoidal functions. Particularly, by virtue of the anti-integrable limit technique, this paper shows that any finite-dimensional neural network model with periodic activation functions and properly selected parameters has much more abundant chaotic dynamics that truly determine the model's memory capacity and pattern-retrieval ability. To some extent, this paper mathematically and numerically demonstrates that an appropriate choice of the activation functions and control scheme can lead to a large memory capacity and better pattern-retrieval ability of the artificial neural network models.

Temperature Crosstalk Sensitivity of the Kummerow Rainfall Algorithm

NASA Technical Reports Server (NTRS)

Spencer, Roy W.; Petrenko, Boris

1999-01-01

Even though the signal source for passive microwave retrievals is thermal emission, retrievals of non-temperature geophysical parameters typically do not explicitly take into account the effects of temperature change on the retrievals. For global change research, changes in geophysical parameters (e.g. water vapor, rainfall, etc.) are referenced to the accompanying changes in temperature. If the retrieval of a certain parameter has a cross-talk response from temperature change alone, the retrievals might not be very useful for climate research. We investigated the sensitivity of the Kummerow rainfall retrieval algorithm to changes in air temperature. It was found that there was little net change in total rainfall with air temperature change. However, there were non-negligible changes within individual rain rate categories.

Outcome of the third cloud retrieval evaluation workshop

NASA Astrophysics Data System (ADS)

Roebeling, Rob; Baum, Bryan; Bennartz, Ralf; Hamann, Ulrich; Heidinger, Andy; Thoss, Anke; Walther, Andi

2013-05-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and interannual variations are needed to improve understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role for such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics must be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), held from 15-18 Nov. 2011 in Madison, Wisconsin, USA, is to enhance knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimizing these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods used to prepare daily and monthly cloud parameter climatologies. An important workshop component is discussion on results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on reasons for observed differences. More in depth discussions were held on retrieval principles and validation, and utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement, cloud physical properties, and cloud climatologies. We present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize actions defined to tailor CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention is given to increase the traceability and uniformity of different longterm and homogeneous records of cloud parameters.

Retrieval of effective cloud field parameters from radiometric data

NASA Astrophysics Data System (ADS)

Paulescu, Marius; Badescu, Viorel; Brabec, Marek

2017-06-01

Clouds play a key role in establishing the Earth's climate. Real cloud fields are very different and very complex in both morphological and microphysical senses. Consequently, the numerical description of the cloud field is a critical task for accurate climate modeling. This study explores the feasibility of retrieving the effective cloud field parameters (namely the cloud aspect ratio and cloud factor) from systematic radiometric measurements at high frequency (measurement is taken every 15 s). Two different procedures are proposed, evaluated, and discussed with respect to both physical and numerical restrictions. None of the procedures is classified as best; therefore, the specific advantages and weaknesses are discussed. It is shown that the relationship between the cloud shade and point cloudiness computed using the estimated cloud field parameters recovers the typical relationship derived from measurements.

The review of dynamic monitoring technology for crop growth

NASA Astrophysics Data System (ADS)

Zhang, Hong-wei; Chen, Huai-liang; Zou, Chun-hui; Yu, Wei-dong

2010-10-01

In this paper, crop growth monitoring methods are described elaborately. The crop growth models, Netherlands-Wageningen model system, the United States-GOSSYM model and CERES models, Australia APSIM model and CCSODS model system in China, are introduced here more focus on the theories of mechanism, applications, etc. The methods and application of remote sensing monitoring methods, which based on leaf area index (LAI) and biomass were proposed by different scholars at home and abroad, are highly stressed in the paper. The monitoring methods of remote sensing coupling with crop growth models are talked out at large, including the method of "forced law" which using remote sensing retrieval state parameters as the crop growth model parameters input, and then to enhance the dynamic simulation accuracy of crop growth model and the method of "assimilation of Law" which by reducing the gap difference between the value of remote sensing retrieval and the simulated values of crop growth model and thus to estimate the initial value or parameter values to increasing the simulation accuracy. At last, the developing trend of monitoring methods are proposed based on the advantages and shortcomings in previous studies, it is assured that the combination of remote sensing with moderate resolution data of FY-3A, MODIS, etc., crop growth model, "3S" system and observation in situ are the main methods in refinement of dynamic monitoring and quantitative assessment techniques for crop growth in future.

Numerical determination of visible/NIR optical constants from laboratory spectra of HED meteorites

NASA Astrophysics Data System (ADS)

Davalos, Jorge A. G.; Carvano, Jorge Márcio; Blanco, Julio

2017-03-01

Radiative transfer models in particulate media (Hapke, 1981, 1993, 2012b; Shkuratov et al., 1999) are the most versatile tool that can be used to retrieve both composition and surface physical properties from observation of asteroids and other atmosphereless bodies of the Solar System. One caveat is that these methods require as input a sufficiently comprehensive set of optical constants of suitable template materials. These optical constants are the real and imaginary parts of the refractive indexes of the material as function of wavelength, and have to be derived from laboratory measurements of samples of minerals and meteorites. Optical constants can be calculated from a variety of types of measurements, and each has its problems and limitations. In particular, a problem with the determination of optical constants from measurement of reflectance is that the measurements need to be themselves interpreted using radiative transfer models. This is an issue because the number of parameters used in the most accurate versions of the radiative transfer models is large, and for most of the samples many of these parameters were not measured independently. As a result, attempts in the literature to retrieve optical constants from reflectance measurements tend to assume values for the unknown parameters, which can lead to uncertainties in the retrieved optical constants that can be difficult to quantify. In this work we propose a numerical method that allows the simultaneous inversion of the optical constant and the model parameters. This model is then applied to a set of reflectance spectra of 5 HED meteorites from the RELAB database that were measured with the same setup for samples with several particle size intervals. Our results indicate that our method is able to retrieve optical constants which are able to reproduce the measured reflectance of the samples over a large range (25-500 μm) of particle diameters. It is also found that the solutions obtained in this way are non-unique, in the sense that many combination of the model parameters can yield different sets of optical constants that fit equally well the reflectance spectra. Thus, in the absence of the independent determination of at least some of the model parameter the method is unable to decide which solution correspond to the physical optical constants of the materials. Even so, the dispersion of the model parameters (in particular effective particle diameter and porosity) for acceptable solutions (defined as the ones that reproduce the measured reflectance spectra at all size range with residues smaller than 10%) is within a radius of around 30% of the value of the best fit solution for each parameter. Given the ability of the optical constants derived with this method to reproduce the sample spectra over a large range of particle sizes, they can be used without other restriction to assess if a given meteorite assemblage is contributing to the observed spectra of asteroids. However, quantitative informations that can also be derived using these optical constants, like particle sizes, porosity and volumetric fractions of each end-member in a mixture should be regarded only as rough estimates.

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.

Observing the ExoEarth: Simulating the Retrieval of Exoplanet Parameters Using DSCOVR

NASA Astrophysics Data System (ADS)

Kane, S.; Cowan, N. B.; Domagal-Goldman, S. D.; Herman, J. R.; Robinson, T.; Stine, A.

2017-12-01

The field of exoplanets has rapidly expanded from detection to include exoplanet characterization. This has been enabled by developments such as the detection of terrestrial-sized planets and the use of transit spectroscopy to study exoplanet atmospheres. Studies of rocky planets are leading towards the direct imaging of exoplanets and the development of techniques to extract their intrinsic properties. The importance of properties such as rotation, albedo, and obliquity are significant since they inform planet formation theories and are key input parameters for Global Circulation Models used to determine surface conditions, including habitability. Thus, a complete characterization of exoplanets for understanding habitable climates requires the ability to measure these key planetary parameters. The retrieval of planetary rotation rates, albedos, and obliquities from highly undersampled imaging data can be honed using satellites designed to study the Earth's atmosphere. In this talk I will describe how the Deep Space Climate Observatory (DSCOVR) provides a unique opportunity to test such retrieval methods using data for the sunlit hemisphere of the Earth. Our methods use the high-resolution DSCOVR-EPIC images to simulate the Earth as an exoplanet, by deconvolving the images to match a variety of expected exoplanet mission requirements, and by comparing EPIC data with the cavity radiometer data from DSCOVR-NISTAR that views the Earth as a single pixel. Through this methodology, we are creating a grid of retrieval states as a function of image resolution, observing cadence, passband, etc. Our modeling of the DSCOVR data will provide an effective baseline from which to develop tools that can be applied to a variety of exoplanet imaging data.

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

NASA Technical Reports Server (NTRS)

Molnar, Gyula; Susskind, Joel

2008-01-01

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

A joint method to retrieve directional ocean wave spectra from SAR and wave spectrometer data

NASA Astrophysics Data System (ADS)

Ren, Lin; Yang, Jingsong; Zheng, Gang; Wang, Juan

2016-07-01

This paper proposes a joint method to simultaneously retrieve wave spectra at different scales from spaceborne Synthetic Aperture Radar (SAR) and wave spectrometer data. The method combines the output from the two different sensors to overcome retrieval limitations that occur in some sea states. The wave spectrometer sensitivity coefficient is estimated using an effective significant wave height (SWH), which is an average of SAR-derived and wave spectrometer-derived SWH. This averaging extends the area of the sea surface sampled by the nadir beam of the wave spectrometer to improve the accuracy of the estimated sensitivity coefficient in inhomogeneous sea states. Wave spectra are then retrieved from SAR data using wave spectrometer-derived spectra as first guess spectra to complement the short waves lost in SAR data retrieval. In addition, the problem of 180° ambiguity in retrieved spectra is overcome using SAR imaginary cross spectra. Simulated data were used to validate the joint method. The simulations demonstrated that retrieved wave parameters, including SWH, peak wave length (PWL), and peak wave direction (PWD), agree well with reference parameters. Collocated data from ENVISAT advanced SAR (ASAR), the airborne wave spectrometer STORM, the PHAROS buoy, and the European Centre for Medium-Range Weather Forecasting (ECMWF) were then used to verify the proposed method. Wave parameters retrieved from STORM and two ASAR images were compared to buoy and ECMWF wave data. Most of the retrieved parameters were comparable to reference parameters. The results of this study show that the proposed joint retrieval method could be a valuable complement to traditional methods used to retrieve directional ocean wave spectra, particularly in inhomogeneous sea states.

Retrieval of Aerosol Microphysical Properties Based on the Optimal Estimation Method: Information Content Analysis for Satellite Polarimetric Remote Sensing Measurements

NASA Astrophysics Data System (ADS)

Hou, W. Z.; Li, Z. Q.; Zheng, F. X.; Qie, L. L.

2018-04-01

This paper evaluates the information content for the retrieval of key aerosol microphysical and surface properties for multispectral single-viewing satellite polarimetric measurements cantered at 410, 443, 555, 670, 865, 1610 and 2250 nm over bright land. To conduct the information content analysis, the synthetic data are simulated by the Unified Linearized Vector Radiative Transfer Model (UNLVTM) with the intensity and polarization together over bare soil surface for various scenarios. Following the optimal estimation theory, a principal component analysis method is employed to reconstruct the multispectral surface reflectance from 410 nm to 2250 nm, and then integrated with a linear one-parametric BPDF model to represent the contribution of polarized surface reflectance, thus further to decouple the surface-atmosphere contribution from the TOA measurements. Focusing on two different aerosol models with the aerosol optical depth equal to 0.8 at 550 nm, the total DFS and DFS component of each retrieval aerosol and surface parameter are analysed. The DFS results show that the key aerosol microphysical properties, such as the fine- and coarse-mode columnar volume concentration, the effective radius and the real part of complex refractive index at 550 nm, could be well retrieved with the surface parameters simultaneously over bare soil surface type. The findings of this study can provide the guidance to the inversion algorithm development over bright surface land by taking full use of the single-viewing satellite polarimetric measurements.

Estimation of surface soil moisture and roughness from multi-angular ASAR imagery in the Watershed Allied Telemetry Experimental Research (WATER)

NASA Astrophysics Data System (ADS)

Wang, S. G.; Li, X.; Han, X. J.; Jin, R.

2010-06-01

Radar remote sensing has demonstrated its applicability to the retrieval of basin-scale soil moisture. The mechanism of radar backscattering from soils is complicated and strongly influenced by surface roughness. Furthermore, retrieval of soil moisture using AIEM-like models is a classic example of the underdetermined problem due to a lack of credible known soil roughness distributions at a regional scale. Characterization of this roughness is therefore crucial for an accurate derivation of soil moisture based on backscattering models. This study aims to directly obtain surface roughness information along with soil moisture from multi-angular ASAR images. The method first used a semi-empirical relationship that connects the roughness slope (Zs) and the difference in backscattering coefficient (Δσ) from ASAR data in different incidence angles, in combination with an optimal calibration form consisting of two roughness parameters (the standard deviation of surface height and the correlation length), to estimate the roughness parameters. The deduced surface roughness was then used in the AIEM model for the retrieval of soil moisture. An evaluation of the proposed method was performed in a grassland site in the middle stream of the Heihe River Basin, where the Watershed Allied Telemetry Experimental Research (WATER) was taken place. It has demonstrated that the method is feasible to achieve reliable estimation of soil water content. The key challenge to surface soil moisture retrieval is the presence of vegetation cover, which significantly impacts the estimates of surface roughness and soil moisture.

PubMed Interact: an Interactive Search Application for MEDLINE/PubMed

PubMed Central

Muin, Michael; Fontelo, Paul; Ackerman, Michael

2006-01-01

Online search and retrieval systems are important resources for medical literature research. Progressive Web 2.0 technologies provide opportunities to improve search strategies and user experience. Using PHP, Document Object Model (DOM) manipulation and Asynchronous JavaScript and XML (Ajax), PubMed Interact allows greater functionality so users can refine search parameters with ease and interact with the search results to retrieve and display relevant information and related articles. PMID:17238658

Unlearning of Mixed States in the Hopfield Model —Extensive Loading Case—

NASA Astrophysics Data System (ADS)

Hayashi, Kao; Hashimoto, Chinami; Kimoto, Tomoyuki; Uezu, Tatsuya

2018-05-01

We study the unlearning of mixed states in the Hopfield model for the extensive loading case. Firstly, we focus on case I, where several embedded patterns are correlated with each other, whereas the rest are uncorrelated. Secondly, we study case II, where patterns are divided into clusters in such a way that patterns in any cluster are correlated but those in two different clusters are not correlated. By using the replica method, we derive the saddle point equations for order parameters under the ansatz of replica symmetry. The same equations are also derived by self-consistent signal-to-noise analysis in case I. In both cases I and II, we find that when the correlation between patterns is large, the network loses its ability to retrieve the embedded patterns and, depending on the parameters, a confused memory, which is a mixed state and/or spin glass state, emerges. By unlearning the mixed state, the network acquires the ability to retrieve the embedded patterns again in some parameter regions. We find that to delete the mixed state and to retrieve the embedded patterns, the coefficient of unlearning should be chosen appropriately. We perform Markov chain Monte Carlo simulations and find that the simulation and theoretical results agree reasonably well, except for the spin glass solution in a parameter region due to the replica symmetry breaking. Furthermore, we find that the existence of many correlated clusters reduces the stabilities of both embedded patterns and mixed states.

Neural-Network Approach to Hyperspectral Data Analysis for Volcanic Ash Clouds Monitoring

NASA Astrophysics Data System (ADS)

Piscini, Alessandro; Ventress, Lucy; Carboni, Elisa; Grainger, Roy Gordon; Del Frate, Fabio

2015-11-01

In this study three artificial neural networks (ANN) were implemented in order to emulate a retrieval model and to estimate the ash Aerosol optical Depth (AOD), particle effective radius (reff) and cloud height from volcanic eruption using hyperspectral remotely sensed data. ANNs were trained using a selection of Infrared Atmospheric Sounding Interferometer (IASI) channels in Thermal Infrared (TIR) as inputs, and the corresponding ash parameters retrieved obtained using the Oxford retrievals as target outputs. The retrieval is demonstrated for the eruption of the Eyjafjallajo ̈kull volcano (Iceland) occurred in 2010. The results of validation provided root mean square error (RMSE) values between neural network outputs and targets lower than standard deviation (STD) of corresponding target outputs, therefore demonstrating the feasibility to estimate volcanic ash parameters using an ANN approach, and its importance in near real time monitoring activities, owing to its fast application. A high accuracy has been achieved for reff and cloud height estimation, while a decreasing in accuracy was obtained when applying the NN approach for AOD estimation, in particular for those values not well characterized during NN training phase.

On the remote sensing of cloud properties from satellite infrared sounder data

NASA Technical Reports Server (NTRS)

Yeh, H. Y. M.

1984-01-01

A method for remote sensing of cloud parameters by using infrared sounder data has been developed on the basis of the parameterized infrared transfer equation applicable to cloudy atmospheres. The method is utilized for the retrieval of the cloud height, amount, and emissivity in 11 micro m region. Numerical analyses and retrieval experiments have been carried out by utilizing the synthetic sounder data for the theoretical study. The sensitivity of the numerical procedures to the measurement and instrument errors are also examined. The retrieved results are physically discussed and numerically compared with the model atmospheres. Comparisons reveal that the recovered cloud parameters agree reasonably well with the pre-assumed values. However, for cases when relatively thin clouds and/or small cloud fractional cover within a field of view are present, the recovered cloud parameters show considerable fluctuations. Experiments on the proposed algorithm are carried out utilizing High Resolution Infrared Sounder (HIRS/2) data of NOAA 6 and TIROS-N. Results of experiments show reasonably good comparisons with the surface reports and GOES satellite images.

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

NASA Technical Reports Server (NTRS)

Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

2007-01-01

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for constraining the use of the passive retrieval data in models and for improving the accuracy of the retrievals.

VIRTIS on Venus Express: retrieval of real surface emissivity on global scales

NASA Astrophysics Data System (ADS)

Arnold, Gabriele E.; Kappel, David; Haus, Rainer; Telléz Pedroza, Laura; Piccioni, Giuseppe; Drossart, Pierre

2015-09-01

The extraction of surface emissivity data provides the data base for surface composition analyses and enables to evaluate Venus' geology. The Visible and InfraRed Thermal Imaging Spectrometer (VIRTIS) aboard ESA's Venus Express mission measured, inter alia, the nightside thermal emission of Venus in the near infrared atmospheric windows between 1.0 and 1.2 μm. These data can be used to determine information about surface properties on global scales. This requires a sophisticated approach to understand and consider the effects and interferences of different atmospheric and surface parameters influencing the retrieved values. In the present work, results of a new technique for retrieval of the 1.0 - 1.2 μm - surface emissivity are summarized. It includes a Multi-Window Retrieval Technique, a Multi-Spectrum Retrieval technique (MSR), and a detailed reliability analysis. The MWT bases on a detailed radiative transfer model making simultaneous use of information from different atmospheric windows of an individual spectrum. MSR regularizes the retrieval by incorporating available a priori mean values, standard deviations as well as spatial-temporal correlations of parameters to be retrieved. The capability of this method is shown for a selected surface target area. Implications for geologic investigations are discussed. Based on these results, the work draws conclusions for future Venus surface composition analyses on global scales using spectral remote sensing techniques. In that context, requirements for observational scenarios and instrumental performances are investigated, and recommendations are derived to optimize spectral measurements for Venus' surface studies.

Evolutionary Computing Methods for Spectral Retrieval

NASA Technical Reports Server (NTRS)

Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna

2009-01-01

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

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.

Uniform Atmospheric Retrievals of Ultracool Late-T and Early-Y dwarfs

NASA Astrophysics Data System (ADS)

Garland, Ryan; Irwin, Patrick

2017-10-01

A significant number of ultracool (<600K) extrasolar objects have been discovered in the past decade thanks to wide-field surveys such as WISE. These objects present a perfect testbed for examining the evolution of atmospheric structure as we transition from typically hot extrasolar temperatures to the temperatures found within our Solar System.By examining these types of objects with a uniform retrieval method, we hope to elucidate any trends and (dis)similarities found in atmospheric parameters, such as chemical abundances, temperature-pressure profile, and cloud structure, for a sample of 7 ultracool brown dwarfs as we transition from hotter (~700K) to colder objects (~450K).We perform atmospheric retrievals on two late-T and five early-Y dwarfs. We use the NEMESIS atmospheric retrieval code coupled to a Nested Sampling algorithm, along with a standard uniform model for all of our retrievals. The uniform model assumes the atmosphere is described by a gray radiative-convective temperature profile, (optionally) a gray cloud, and a number of relevant gases. We first verify our methods by comparing it to a benchmark retrieval for Gliese 570D, which is found to be consistent. Furthermore, we present the retrieved gaseous composition, temperature structure, spectroscopic mass and radius, cloud structure and the trends associated with decreasing temperature found in this small sample of objects.

Retrieval of BRDF/Albedo by the Angular and Spectral Kernel Driven Model with Global Soil and Leaf Optical Database

NASA Astrophysics Data System (ADS)

Zhang, Y.; Wen, J.; Xiao, Q.; You, D.

2016-12-01

Operational algorithms for land surface BRDF/Albedo products are mainly developed from kernel-driven model, combining atmospherically corrected, multidate, multiband surface reflectance to extract BRDF parameters. The Angular and Spectral Kernel Driven model (ASK model), which incorporates the component spectra as a priori knowledge, provides a potential way to make full use of the multi-sensor data with multispectral information and accumulated observations. However, the ASK model is still not feasible for global BRDF/Albedo inversions due to the lack of sufficient field measurements of component spectra at the large scale. This research outlines a parameterization scheme on the component spectra for global scale BRDF/Albedo inversions in the frame of ASK. The parameter γ(λ) can be derived from the ratio of the leaf reflectance and soil reflectance, supported by globally distributed soil spectral library, ANGERS and LOPEX leaf optical properties database. To consider the intrinsic variability in both the land cover and spectral dimension, the mean and standard deviation of γ(λ) for 28 soil units and 4 leaf types in seven MODIS bands were calculated, with a world soil map used for global BRDF/Albedo products retrieval. Compared to the retrievals from BRF datasets simulated by the PROSAIL model, ASK model shows an acceptable accuracy on the parameterization strategy, with the RMSE 0.007 higher at most than inversion by true component spectra. The results indicate that the classification on ratio contributed to capture the spectral characteristics in BBRDF/Albedo retrieval, whereas the ratio range should be controlled within 8% in each band. Ground-based measurements in Heihe river basin were used to validate the accuracy of the improved ASK model, and the generated broadband albedo products shows good agreement with in situ data, which suggests that the improvement of the component spectra on the ASK model has potential for global scale BRDF/Albedo inversions.

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.

The Invigoration of Deep Convective Clouds Over the Atlantic: Aerosol Effect, Meteorology or Retrieval Artifact?

NASA Technical Reports Server (NTRS)

Koren, Ilan; Feingold, Graham; Remer, Lorraine A.

2010-01-01

Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case that the aerosol does play a role in invigorating convective clouds.

Two-dimensional radiative transfer for the retrieval of limb emission measurements in the martian atmosphere

NASA Astrophysics Data System (ADS)

Kleinböhl, Armin; Friedson, A. James; Schofield, John T.

2017-01-01

The remote sounding of infrared emission from planetary atmospheres using limb-viewing geometry is a powerful technique for deriving vertical profiles of structure and composition on a global scale. Compared with nadir viewing, limb geometry provides enhanced vertical resolution and greater sensitivity to atmospheric constituents. However, standard limb profile retrieval techniques assume spherical symmetry and are vulnerable to biases produced by horizontal gradients in atmospheric parameters. We present a scheme for the correction of horizontal gradients in profile retrievals from limb observations of the martian atmosphere. It characterizes horizontal gradients in temperature, pressure, and aerosol extinction along the line-of-sight of a limb view through neighboring measurements, and represents these gradients by means of two-dimensional radiative transfer in the forward model of the retrieval. The scheme is applied to limb emission measurements from the Mars Climate Sounder instrument on Mars Reconnaissance Orbiter. Retrieval simulations using data from numerical models indicate that biases of up to 10 K in the winter polar region, obtained with standard retrievals using spherical symmetry, are reduced to about 2 K in most locations by the retrieval with two-dimensional radiative transfer. Retrievals from Mars atmospheric measurements suggest that the two-dimensional radiative transfer greatly reduces biases in temperature and aerosol opacity caused by observational geometry, predominantly in the polar winter regions.

Derivation of global vegetation biophysical parameters from EUMETSAT Polar System

NASA Astrophysics Data System (ADS)

García-Haro, Francisco Javier; Campos-Taberner, Manuel; Muñoz-Marí, Jordi; Laparra, Valero; Camacho, Fernando; Sánchez-Zapero, Jorge; Camps-Valls, Gustau

2018-05-01

This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological-Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key parameters for a wide range of land-biosphere applications. The algorithm is based on a hybrid approach that blends the generalization capabilities offered by physical radiative transfer models with the accuracy and computational efficiency of machine learning methods. One major feature is the implementation of multi-output retrieval methods able to jointly and more consistently estimate all the biophysical parameters at the same time. We propose a multi-output Gaussian process regression (GPRmulti), which outperforms other considered methods over PROSAIL (coupling of PROSPECT and SAIL (Scattering by Arbitrary Inclined Leaves) radiative transfer models) EPS simulations. The global EPS products include uncertainty estimates taking into account the uncertainty captured by the retrieval method and input errors propagation. A sensitivity analysis is performed to assess several sources of uncertainties in retrievals and maximize the positive impact of modeling the noise in training simulations. The paper discusses initial validation studies and provides details about the characteristics and overall quality of the products, which can be of interest to assist the successful use of the data by a broad user's community. The consistent generation and distribution of the EPS vegetation products will constitute a valuable tool for monitoring of earth surface dynamic processes.

Effective Tree Scattering at L-Band

NASA Technical Reports Server (NTRS)

Kurum, Mehmet; ONeill, Peggy E.; Lang, Roger H.; Joseph, Alicia T.; Cosh, Michael H.; Jackson, Thomas J.

2011-01-01

For routine microwave Soil Moisture (SM) retrieval through vegetation, the tau-omega [1] model [zero-order Radiative Transfer (RT) solution] is attractive due to its simplicity and eases of inversion and implementation. It is the model used in baseline retrieval algorithms for several planned microwave space missions, such as ESA's Soil Moisture Ocean Salinity (SMOS) mission (launched November 2009) and NASA's Soil Moisture Active Passive (SMAP) mission (to be launched 2014/2015) [2 and 3]. These approaches are adapted for vegetated landscapes with effective vegetation parameters tau and omega by fitting experimental data or simulation outputs of a multiple scattering model [4-7]. The model has been validated over grasslands, agricultural crops, and generally light to moderate vegetation. As the density of vegetation increases, sensitivity to the underlying SM begins to degrade significantly and errors in the retrieved SM increase accordingly. The zero-order model also loses its validity when dense vegetation (i.e. forest, mature corn, etc.) includes scatterers, such as branches and trunks (or stalks in the case of corn), which are large with respect to the wavelength. The tau-omega model (when applied over moderately to densely vegetated landscapes) will need modification (in terms of form or effective parameterization) to enable accurate characterization of vegetation parameters with respect to specific tree types, anisotropic canopy structure, presence of leaves and/or understory. More scattering terms (at least up to first-order at L-band) should be included in the RT solutions for forest canopies [8]. Although not really suitable to forests, a zero-order tau-omega model might be applied to such vegetation canopies with large scatterers, but that equivalent or effective parameters would have to be used [4]. This requires that the effective values (vegetation opacity and single scattering albedo) need to be evaluated (compared) with theoretical definitions of these parameters. In a recent study [9], effective vegetation opacity of coniferous trees was compared with two independent estimates of the same parameter. First, a zero-order RT model was fitted to multiangular microwave emissivity data in a least-square sense to provide effective vegetation optical depth as done in spaceborne retrieval algorithms. Second, a ratio between radar backscatter measurements with a corner reflector under trees and in an open area was calculated to obtain measured tree propagation characteristics. Finally, the theoretical propagation constant was determined by forward scattering theorem using detailed measurements of size/angle distributions and dielectric constants of the tree constituents (trunk, branches, and needles). Results indicated that the effective attenuation values are smaller than but of similar magnitude to both the theoretical and measured values. This study will complement the previous work [9] and will focus on characterization of effective scattering albedo by assuming that effective vegetation opacity is same as theoretical opacity. The resultant effective albedo will not be the albedo of single forest canopy element anymore, but it becomes a global parameter, which depends on all the processes taking place within the canopy including multiple scattering as described.

Advantages of measuring the Q Stokes parameter in addition to the total radiance I in the detection of absorbing aerosols

NASA Astrophysics Data System (ADS)

Stamnes, Snorre; Fan, Yongzhen; Chen, Nan; Li, Wei; Tanikawa, Tomonori; Lin, Zhenyi; Liu, Xu; Burton, Sharon; Omar, Ali; Stamnes, Jakob J.; Cairns, Brian; Stamnes, Knut

2018-05-01

A simple but novel study was conducted to investigate whether an imager-type spectroradiometer instrument like MODIS, currently flying on board the Aqua and Terra satellites, or MERIS, which flew on board Envisat, could detect absorbing aerosols if they could measure the Q Stokes parameter in addition to the total radiance I, that is if they could also measure the linear polarization of the light. Accurate radiative transfer calculations were used to train a fast neural network forward model, which together with a simple statistical optimal estimation scheme was used to retrieve three aerosol parameters: aerosol optical depth at 869 nm, optical depth fraction of fine mode (absorbing) aerosols at 869 nm, and aerosol vertical location. The aerosols were assumed to be bimodal, each with a lognormal size distribution, located either between 0 and 2 km or between 2 and 4 km in the Earth's atmosphere. From simulated data with 3% random Gaussian measurement noise added for each Stokes parameter, it was found that by itself the total radiance I at the nine MODIS VIS channels was generally insufficient to accurately retrieve all three aerosol parameters (˜ 15% to 37% successful), but that together with the Q Stokes component it was possible to retrieve values of aerosol optical depth at 869 nm to ± 0.03, single-scattering albedo at 869 nm to ± 0.04, and vertical location in ˜ 65% of the cases. This proof-of-concept retrieval algorithm uses neural networks to overcome the computational burdens of using vector radiative transfer to accurately simulate top-of-atmosphere (TOA) total and polarized radiances, enabling optimal estimation techniques to exploit information from multiple channels. Therefore such an algorithm could, in concept, be readily implemented for operational retrieval of aerosol and ocean products from moderate or hyperspectral spectroradiometers.

A Well-Calibrated Ocean Algorithm for Special Sensor Microwave/Imager

NASA Technical Reports Server (NTRS)

Wentz, Frank J.

1997-01-01

I describe an algorithm for retrieving geophysical parameters over the ocean from special sensor microwave/imager (SSM/I) observations. This algorithm is based on a model for the brightness temperature T(sub B) of the ocean and intervening atmosphere. The retrieved parameters are the near-surface wind speed W, the columnar water vapor V, the columnar cloud liquid water L, and the line-of-sight wind W(sub LS). I restrict my analysis to ocean scenes free of rain, and when the algorithm detects rain, the retrievals are discarded. The model and algorithm are precisely calibrated using a very large in situ database containing 37,650 SSM/I overpasses of buoys and 35,108 overpasses of radiosonde sites. A detailed error analysis indicates that the T(sub B) model rms accuracy is between 0.5 and 1 K and that the rms retrieval accuracies for wind, vapor, and cloud are 0.9 m/s, 1.2 mm, and 0.025 mm, respectively. The error in specifying the cloud temperature will introduce an additional 10% error in the cloud water retrieval. The spatial resolution for these accuracies is 50 km. The systematic errors in the retrievals are smaller than the rms errors, being about 0.3 m/s, 0.6 mm, and 0.005 mm for W, V, and L, respectively. The one exception is the systematic error in wind speed of -1.0 m/s that occurs for observations within +/-20 deg of upwind. The inclusion of the line-of-sight wind W(sub LS) in the retrieval significantly reduces the error in wind speed due to wind direction variations. The wind error for upwind observations is reduced from -3.0 to -1.0 m/s. Finally, I find a small signal in the 19-GHz, horizontal polarization (h(sub pol) T(sub B) residual DeltaT(sub BH) that is related to the effective air pressure of the water vapor profile. This information may be of some use in specifying the vertical distribution of water vapor.

A Consistent Treatment of Microwave Emissivity and Radar Backscatter for Retrieval of Precipitation over Water Surfaces

NASA Technical Reports Server (NTRS)

Munchak, S. Joseph; Meneghini, Robert; Grecu, Mircea; Olson, William S.

2016-01-01

The Global Precipitation Measurement satellite's Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) are designed to provide the most accurate instantaneous precipitation estimates currently available from space. The GPM Combined Algorithm (CORRA) plays a key role in this process by retrieving precipitation profiles that are consistent with GMI and DPR measurements; therefore, it is desirable that the forward models in CORRA use the same geophysical input parameters. This study explores the feasibility of using internally consistent emissivity and surface backscatter cross-sectional (sigma(sub 0)) models for water surfaces in CORRA. An empirical model for DPR Ku and Ka sigma(sub 0) as a function of 10m wind speed and incidence angle is derived from GMI-only wind retrievals under clear-sky conditions. This allows for the sigma(sub 0) measurements, which are also influenced by path-integrated attenuation (PIA) from precipitation, to be used as input to CORRA and for wind speed to be retrieved as output. Comparisons to buoy data give a wind rmse of 3.7 m/s for Ku+GMI and 3.2 m/s for Ku+Ka+GMI retrievals under precipitation (compared to 1.3 m/s for clear-sky GMI-only), and there is a reduction in bias from GANAL background data (-10%) to the Ku+GMI (-3%) and Ku+Ka+GMI (-5%) retrievals. Ku+GMI retrievals of precipitation increase slightly in light (less than 1 mm/h) and decrease in moderate to heavy precipitation (greater than 1 mm/h). The Ku+Ka+GMI retrievals, being additionally constrained by the Ka reflectivity, increase only slightly in moderate and heavy precipitation at low wind speeds (less than 5 m/s) relative to retrievals using the surface reference estimate of PIA as input.

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.

Simultaneous Retrieval of Aerosol Optical Depth and Surface Reflectance over Land within Short Temporal Interval Using MSG Data

NASA Astrophysics Data System (ADS)

Li, C.; Xue, Y.; Li, Y. J.; Yang, L. K.; Hou, T. T.

2012-04-01

Aerosols cause a major uncertainty in the research of climatology and global change, whereas satellite aerosol remote sensing over land still remains a big challenge. Due to their short time repeat cycle, geostationary satellites are capable of monitoring the temporal features of aerosols, while its limited number of visible bands is an obstacle. On the other hand, a main uncertainty in aerosol retrieval is the difficulty to separate the relatively weaker contribution of the atmosphere to the signal received by the satellite from the contribution of the Earth's surface. In this paper, an analytical retrieval strategy is presented to solve the both problems above. For the lack of surface reflectance, we use the Ross-Li BRDF (Bidirectional Reflectance Distribution Function) model and assume that the surface reflective property changes mainly due to the change of illumination geometry in a short time interval while the kernals of Ross-Li model remain the same. For the limited visible band, we take advantage of the Aerosol Optical Depth (AOD) consistence within short distances, thus to reduce the number of unknown parameters. A parameterization of the atmospheric radiative transfer model is used which is proved to be proper to retrieve aerosol and surface parameters by sensitivity analysis. Taking the three kernels of kernel-driven BRDF model and AOD as unknown parameters and based on prior knowledge of aerosol types, a series of nonlinear equations can be established then. Both AOD and surface reflectance can be obtained by using a numerical method to solve these equations. By applying this method, called LABITS-MSG (Land Aerosol and Bidirectional reflectance Inversion by Time Series technique for MSG), to data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) observations on board Meteosat Second Generation (MSG), we obtain regional maps of AOD and surface reflectance in July 11, 2010 within a temporal interval of as short as 1 hour, and a spatial resolution of 10 km. Preliminary validation results by comparing our retrieved AOD with Aerosol Robotic Network (AERONET) data show that the correlation coefficient R is about 0.81, the root-mean-square error (RMSE) is less than 0.1, and the uncertainty is found to be Δτ = ± 0.05 ± 0.20τ. Time serial comparison of MSG and AERONET AODs on Granada site also shows a good fitting. To conclude, this algorithm shows its potential to retrieve real-time AODs over land from geostationary satellites.

Potential of Higher Moments of the Radar Doppler Spectrum for Studying Ice Clouds

NASA Astrophysics Data System (ADS)

Loehnert, U.; Maahn, M.

2015-12-01

More observations of ice clouds are required to fill gaps in understanding of microphysical properties and processes. However, in situ observations by aircraft are costly and cannot provide long term observations which are required for a deeper understanding of the processes. Ground based remote sensing observations have the potential to fill this gap, but their observations do not contain sufficient information to unambiguously constrain ice cloud properties which leads to high uncertainties. For vertically pointing cloud radars, usually only reflectivity and mean Doppler velocity are used for retrievals; some studies proposed also the use of Doppler spectrum width.In this study, it is investigated whether additional information can be obtained by exploiting also higher moments of the Doppler spectrum such as skewness and kurtosis together with the slope of the Doppler peak. For this, observations of pure ice clouds from the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in Alaska 2008 are analyzed. Using the ISDAC data set, an Optimal Estimation based retrieval is set up based on synthetic and real radar observations. The passive and active microwave radiative transfer model (PAMTRA) is used as a forward model together with the Self-Similar Rayleigh-Gans approximation for estimation of the scattering properties. The state vector of the retrieval consists of the parameters required to simulate the radar Doppler spectrum and describes particle mass, cross section area, particle size distribution, and kinematic conditions such as turbulence and vertical air motion. Using the retrieval, the information content (degrees of freedom for signal) is quantified that higher moments and slopes can contribute to an ice cloud retrieval. The impact of multiple frequencies, radar sensitivity and radar calibration is studied. For example, it is found that a single-frequency measurement using all moments and slopes contains already more information content than a dual-frequency measurement using only reflectivity and mean Doppler velocity. Eventually, the errors and uncertainties of the retrieved ice cloud parameters are investigated for the various retrieval configurations.

Potential of Higher Moments of the Radar Doppler Spectrum for Studying Ice Clouds

NASA Astrophysics Data System (ADS)

Lunt, M. F.; Rigby, M. L.; Ganesan, A.; Manning, A.; O'Doherty, S.; Prinn, R. G.; Saito, T.; Harth, C. M.; Muhle, J.; Weiss, R. F.; Salameh, P.; Arnold, T.; Yokouchi, Y.; Krummel, P. B.; Steele, P.; Fraser, P. J.; Li, S.; Park, S.; Kim, J.; Reimann, S.; Vollmer, M. K.; Lunder, C. R.; Hermansen, O.; Schmidbauer, N.; Young, D.; Simmonds, P. G.

2014-12-01

More observations of ice clouds are required to fill gaps in understanding of microphysical properties and processes. However, in situ observations by aircraft are costly and cannot provide long term observations which are required for a deeper understanding of the processes. Ground based remote sensing observations have the potential to fill this gap, but their observations do not contain sufficient information to unambiguously constrain ice cloud properties which leads to high uncertainties. For vertically pointing cloud radars, usually only reflectivity and mean Doppler velocity are used for retrievals; some studies proposed also the use of Doppler spectrum width.In this study, it is investigated whether additional information can be obtained by exploiting also higher moments of the Doppler spectrum such as skewness and kurtosis together with the slope of the Doppler peak. For this, observations of pure ice clouds from the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in Alaska 2008 are analyzed. Using the ISDAC data set, an Optimal Estimation based retrieval is set up based on synthetic and real radar observations. The passive and active microwave radiative transfer model (PAMTRA) is used as a forward model together with the Self-Similar Rayleigh-Gans approximation for estimation of the scattering properties. The state vector of the retrieval consists of the parameters required to simulate the radar Doppler spectrum and describes particle mass, cross section area, particle size distribution, and kinematic conditions such as turbulence and vertical air motion. Using the retrieval, the information content (degrees of freedom for signal) is quantified that higher moments and slopes can contribute to an ice cloud retrieval. The impact of multiple frequencies, radar sensitivity and radar calibration is studied. For example, it is found that a single-frequency measurement using all moments and slopes contains already more information content than a dual-frequency measurement using only reflectivity and mean Doppler velocity. Eventually, the errors and uncertainties of the retrieved ice cloud parameters are investigated for the various retrieval configurations.

Quantifying the Uncertainties and Multi-parameter Trade-offs in Joint Inversion of Receiver Functions and Surface Wave Velocity and Ellipticity

NASA Astrophysics Data System (ADS)

Gao, C.; Lekic, V.

2016-12-01

When constraining the structure of the Earth's continental lithosphere, multiple seismic observables are often combined due to their complementary sensitivities.The transdimensional Bayesian (TB) approach in seismic inversion allows model parameter uncertainties and trade-offs to be quantified with few assumptions. TB sampling yields an adaptive parameterization that enables simultaneous inversion for different model parameters (Vp, Vs, density, radial anisotropy), without the need for strong prior information or regularization. We use a reversible jump Markov chain Monte Carlo (rjMcMC) algorithm to incorporate different seismic observables - surface wave dispersion (SWD), Rayleigh wave ellipticity (ZH ratio), and receiver functions - into the inversion for the profiles of shear velocity (Vs), compressional velocity (Vp), density (ρ), and radial anisotropy (ξ) beneath a seismic station. By analyzing all three data types individually and together, we show that TB sampling can eliminate the need for a fixed parameterization based on prior information, and reduce trade-offs in model estimates. We then explore the effect of different types of misfit functions for receiver function inversion, which is a highly non-unique problem. We compare the synthetic inversion results using the L2 norm, cross-correlation type and integral type misfit function by their convergence rates and retrieved seismic structures. In inversions in which only one type of model parameter (Vs for the case of SWD) is inverted, assumed scaling relationships are often applied to account for sensitivity to other model parameters (e.g. Vp, ρ, ξ). Here we show that under a TB framework, we can eliminate scaling assumptions, while simultaneously constraining multiple model parameters to varying degrees. Furthermore, we compare the performance of TB inversion when different types of model parameters either share the same or use independent parameterizations. We show that different parameterizations can lead to differences in retrieved model parameters, consistent with limited data constraints. We then quantitatively examine the model parameter trade-offs and find that trade-offs between Vp and radial anisotropy might limit our ability to constrain shallow-layer radial anisotropy using current seismic observables.

Chlorophyll content retrieval from hyperspectral remote sensing imagery.

PubMed

Yang, Xiguang; Yu, Ying; Fan, Wenyi

2015-07-01

Chlorophyll content is the essential parameter in the photosynthetic process determining leaf spectral variation in visible bands. Therefore, the accurate estimation of the forest canopy chlorophyll content is a significant foundation in assessing forest growth and stress affected by diseases. Hyperspectral remote sensing with high spatial resolution can be used for estimating chlorophyll content. In this study, the chlorophyll content was retrieved step by step using Hyperion imagery. Firstly, the spectral curve of the leaf was analyzed, 25 spectral characteristic parameters were identified through the correlation coefficient matrix, and a leaf chlorophyll content inversion model was established using a stepwise regression method. Secondly, the pixel reflectance was converted into leaf reflectance by a geometrical-optical model (4-scale). The three most important parameters of reflectance conversion, including the multiple scattering factor (M 0 ), and the probability of viewing the sunlit tree crown (P T ) and the background (P G ), were estimated by leaf area index (LAI), respectively. The results indicated that M 0 , P T , and P G could be described as a logarithmic function of LAI, with all R (2) values above 0.9. Finally, leaf chlorophyll content was retrieved with RMSE = 7.3574 μg/cm(2), and canopy chlorophyll content per unit ground surface area was estimated based on leaf chlorophyll content and LAI. Chlorophyll content mapping can be useful for the assessment of forest growth stage and diseases.

Modeling and Simulation of a Tethered Harpoon for Comet Sampling

NASA Technical Reports Server (NTRS)

Quadrelli, Marco B.

2014-01-01

This paper describes the development of a dynamic model and simulation results of a tethered harpoon for comet sampling. This model and simulation was done in order to carry out an initial sensitivity analysis for key design parameters of the tethered system. The harpoon would contain a canister which would collect a sample of soil from a cometary surface. Both a spring ejected canister and a tethered canister are considered. To arrive in close proximity of the spacecraft at the end of its trajectory so it could be captured, the free-flying canister would need to be ejected at the right time and with the proper impulse, while the tethered canister must be recovered by properly retrieving the tether at a rate that would avoid an excessive amplitude of oscillatory behavior during the retrieval. The paper describes the model of the tether dynamics and harpoon penetration physics. The simulations indicate that, without the tether, the canister would still reach the spacecraft for collection, that the tether retrieval of the canister would be achievable with reasonable fuel consumption, and that the canister amplitude upon retrieval would be insensitive to variations in vertical velocity dispersion.

A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm

NASA Astrophysics Data System (ADS)

Fernandez-Moran, R.; Wigneron, J.-P.; De Lannoy, G.; Lopez-Baeza, E.; Parrens, M.; Mialon, A.; Mahmoodi, A.; Al-Yaari, A.; Bircher, S.; Al Bitar, A.; Richaume, P.; Kerr, Y.

2017-10-01

This study focuses on the calibration of the effective vegetation scattering albedo (ω) and surface soil roughness parameters (HR, and NRp, p = H,V) in the Soil Moisture (SM) retrieval from L-band passive microwave observations using the L-band Microwave Emission of the Biosphere (L-MEB) model. In the current Soil Moisture and Ocean Salinity (SMOS) Level 2 (L2), v620, and Level 3 (L3), v300, SM retrieval algorithms, low vegetated areas are parameterized by ω = 0 and HR = 0.1, whereas values of ω = 0.06 - 0.08 and HR = 0.3 are used for forests. Several parameterizations of the vegetation and soil roughness parameters (ω, HR and NRp, p = H,V) were tested in this study, treating SMOS SM retrievals as homogeneous over each pixel instead of retrieving SM over a representative fraction of the pixel, as implemented in the operational SMOS L2 and L3 algorithms. Globally-constant values of ω = 0.10, HR = 0.4 and NRp = -1 (p = H,V) were found to yield SM retrievals that compared best with in situ SM data measured at many sites worldwide from the International Soil Moisture Network (ISMN). The calibration was repeated for collections of in situ sites classified in different land cover categories based on the International Geosphere-Biosphere Programme (IGBP) scheme. Depending on the IGBP land cover class, values of ω and HR varied, respectively, in the range 0.08-0.12 and 0.1-0.5. A validation exercise based on in situ measurements confirmed that using either a global or an IGBP-based calibration, there was an improvement in the accuracy of the SM retrievals compared to the SMOS L3 SM product considering all statistical metrics (R = 0.61, bias = -0.019 m3 m-3, ubRMSE = 0.062 m3 m-3 for the IGBP-based calibration; against R = 0.54, bias = -0.034 m3 m-3 and ubRMSE = 0.070 m3 m-3 for the SMOS L3 SM product). This result is a key step in the calibration of the roughness and vegetation parameters in the operational SMOS retrieval algorithm. The approach presented here is the core of a new forthcoming SMOS optimized SM product.

Kalman filters for assimilating near-surface observations in the Richards equation - Part 2: A dual filter approach for simultaneous retrieval of states and parameters

NASA Astrophysics Data System (ADS)

Medina, H.; Romano, N.; Chirico, G. B.

2012-12-01

We present a dual Kalman Filter (KF) approach for retrieving states and parameters controlling soil water dynamics in a homogenous soil column by using near-surface state observations. The dual Kalman filter couples a standard KF algorithm for retrieving the states and an unscented KF algorithm for retrieving the parameters. We examine the performance of the dual Kalman Filter applied to two alternative state-space formulations of the Richards equation, respectively differentiated by the type of variable employed for representing the states: either the soil water content (θ) or the soil matric pressure head (h). We use a synthetic time-series series of true states and noise corrupted observations and a synthetic time-series of meteorological forcing. The performance analyses account for the effect of the input parameters, the observation depth and the assimilation frequency as well as the relationship between the retrieved states and the assimilated variables. We show that the identifiability of the parameters is strongly conditioned by several factors, such as the initial guess of the unknown parameters, the wet or dry range of the retrieved states, the boundary conditions, as well as the form (h-based or θ-based) of the state-space formulation. State identifiability is instead efficient even with a relatively coarse time-resolution of the assimilated observation. The accuracy of the retrieved states exhibits limited sensitivity to the observation depth and the assimilation frequency.

Retrieving transient conformational molecular structure information from inner-shell photoionization of laser-aligned molecules

PubMed Central

Wang, Xu; Le, Anh-Thu; Yu, Chao; Lucchese, R. R.; Lin, C. D.

2016-01-01

We discuss a scheme to retrieve transient conformational molecular structure information using photoelectron angular distributions (PADs) that have averaged over partial alignments of isolated molecules. The photoelectron is pulled out from a localized inner-shell molecular orbital by an X-ray photon. We show that a transient change in the atomic positions from their equilibrium will lead to a sensitive change in the alignment-averaged PADs, which can be measured and used to retrieve the former. Exploiting the experimental convenience of changing the photon polarization direction, we show that it is advantageous to use PADs obtained from multiple photon polarization directions. A simple single-scattering model is proposed and benchmarked to describe the photoionization process and to do the retrieval using a multiple-parameter fitting method. PMID:27025410

Retrieving transient conformational molecular structure information from inner-shell photoionization of laser-aligned molecules

NASA Astrophysics Data System (ADS)

Wang, Xu; Le, Anh-Thu; Yu, Chao; Lucchese, R. R.; Lin, C. D.

2016-03-01

We discuss a scheme to retrieve transient conformational molecular structure information using photoelectron angular distributions (PADs) that have averaged over partial alignments of isolated molecules. The photoelectron is pulled out from a localized inner-shell molecular orbital by an X-ray photon. We show that a transient change in the atomic positions from their equilibrium will lead to a sensitive change in the alignment-averaged PADs, which can be measured and used to retrieve the former. Exploiting the experimental convenience of changing the photon polarization direction, we show that it is advantageous to use PADs obtained from multiple photon polarization directions. A simple single-scattering model is proposed and benchmarked to describe the photoionization process and to do the retrieval using a multiple-parameter fitting method.

Evaluation Of The MODIS-VIIRS Land Surface Reflectance Fundamental Climate Data Record.

NASA Astrophysics Data System (ADS)

Roger, J. C.; Vermote, E.; Skakun, S.; Murphy, E.; Holben, B. N.; Justice, C. O.

2016-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and has been recognized as a key parameter in the understanding of the land-surface-climate processes. Here, we present the validation of the Land surface reflectance used for MODIS and VIIRS data. This methodology uses the 6SV Code and data from the AERONET network. The first part was to define a protocol to use the AERONET data. To correctly take into account the aerosol model, we used the aerosol microphysical properties provided by the AERONET network including size-distribution (%Cf, %Cc, rf, rc, σr, σc), complex refractive indices and sphericity. Over the 670 available AERONET sites, we selected 230 sites with sufficient data. To be useful for validation, the aerosol model should be readily available anytime, which is rarely the case. We then used regressions for each microphysical parameter using the aerosol optical thickness at 440nm and the Angström coefficient as parameters. Comparisons with the AERONET dataset give good APU (Accuracy-Precision-Uncertainties) for each parameter. The second part of the study relies on the theoretical land surface retrieval. We generated TOA synthetic data using aerosol models from AERONET and determined APU on the surface reflectance retrieval while applying the MODIS and VIRRS Atmospheric correction software. Over 250 AERONET sites, the global uncertainties are for MODIS band 1 (red) is always lower than 0.0015 (when surface reflectance is > 0.04). This very good result shows the validity of our reference. Then, we used this reference for validating the MODIS and VIIRS surface reflectance products. The overall accuracy clearly reaches specifications. Finally, we will present an error budget of the surface reflectance retrieval. Indeed, to better understand how to improve the methodology, we defined an exhaustive error budget. We included all inputs i.e. sensor, calibration, aerosol properties, atmospheric conditions… This latter work provides a lot of information, such as the aerosol optical thickness obviously drives the uncertainties of the retrieval, the absorption and the volume concentration of the fine aerosol mode have an important impact as well…

Retrieval of biophysical parameters with AVIRIS and ISM: The Landes Forest, south west France

NASA Technical Reports Server (NTRS)

Zagolski, F.; Gastellu-Etchegorry, J. P.; Mougin, E.; Giordano, G.; Marty, G.; Letoan, T.; Beaudoin, A.

1992-01-01

The first steps of an experiment for investigating the capability of airborne spectrometer data for retrieval of biophysical parameters of vegetation, especially water conditions are presented. Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and ISM data were acquired in the frame of the 1991 NASA/JPL and CNES campaigns on the Landes, South west France, a large and flat forest area with mainly maritime pines. In-situ measurements were completed at that time; i.e. reflectance spectra, atmospheric profiles, sampling for further laboratory analyses of elements concentrations (lignin, water, cellulose, nitrogen,...). All information was integrated in an already existing data base (age, LAI, DBH, understory cover,...). A methodology was designed for (1) obtaining geometrically and atmospherically corrected reflectance data, (2) registering all available information, and (3) analyzing these multi-source informations. Our objective is to conduct comparative studies with simulation reflectance models, and to improve these models, especially in the MIR.

Forward and inverse models of electromagnetic scattering from layered media with rough interfaces

NASA Astrophysics Data System (ADS)

Tabatabaeenejad, Seyed Alireza

This work addresses the problem of electromagnetic scattering from layered dielectric structures with rough boundaries and the associated inverse problem of retrieving the subsurface parameters of the structure using the scattered field. To this end, a forward scattering model based on the Small Perturbation Method (SPM) is developed to calculate the first-order spectral-domain bistatic scattering coefficients of a two-layer rough surface structure. SPM requires the boundaries to be slightly rough compared to the wavelength, but to understand the range of applicability of this method in scattering from two-layer rough surfaces, its region of validity is investigated by comparing its output with that of a first principle solver that does not impose roughness restrictions. The Method of Moments (MoM) is used for this purpose. Finally, for retrieval of the model parameters of the layered structure using scattered field, an inversion scheme based on the Simulated Annealing method is investigated and a strategy is proposed to address convergence to local minimum.

Aerosol particle size distribution in the stratosphere retrieved from SCIAMACHY limb measurements

NASA Astrophysics Data System (ADS)

Malinina, Elizaveta; Rozanov, Alexei; Rozanov, Vladimir; Liebing, Patricia; Bovensmann, Heinrich; Burrows, John P.

2018-04-01

The Goddard Snow Radiance Assimilation Project: An Integrated Snow Radiance and Snow Physics Modeling Framework for Snow/cold Land Surface Modeling

NASA Technical Reports Server (NTRS)

Kim, E.; Tedesco, M.; Reichle, R.; Choudhury, B.; Peters-Lidard C.; Foster, J.; Hall, D.; Riggs, G.

2006-01-01

Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.

Retrieval of subvisual cirrus cloud optical thickness from limb-scatter measurements

NASA Astrophysics Data System (ADS)

Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

2013-01-01

We present a technique for estimating the optical thickness of subvisual cirrus clouds detected by OSIRIS (Optical Spectrograph and Infrared Imaging System), a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Cross-sections and phase functions from an in situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is shown that the retrieved extinction profile, for an assumed effective cloud particle size, models well the measured in-cloud radiances from OSIRIS. The greatest sensitivity of the retrieved optical thickness is to the effective cloud particle size. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

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.

[The progress in retrieving land surface temperature based on thermal infrared and microwave remote sensing technologies].

PubMed

Zhang, Jia-Hua; Li, Xin; Yao, Feng-Mei; Li, Xian-Hua

2009-08-01

Land surface temperature (LST) is an important parameter in the study on the exchange of substance and energy between land surface and air for the land surface physics process at regional and global scales. Many applications of satellites remotely sensed data must provide exact and quantificational LST, such as drought, high temperature, forest fire, earthquake, hydrology and the vegetation monitor, and the models of global circulation and regional climate also need LST as input parameter. Therefore, the retrieval of LST using remote sensing technology becomes one of the key tasks in quantificational remote sensing study. Normally, in the spectrum bands, the thermal infrared (TIR, 3-15 microm) and microwave bands (1 mm-1 m) are important for retrieval of the LST. In the present paper, firstly, several methods for estimating the LST on the basis of thermal infrared (TIR) remote sensing were synthetically reviewed, i. e., the LST measured with an ground-base infrared thermometer, the LST retrieval from mono-window algorithm (MWA), single-channel algorithm (SCA), split-window techniques (SWT) and multi-channels algorithm(MCA), single-channel & multi-angle algorithm and multi-channels algorithm & multi-angle algorithm, and retrieval method of land surface component temperature using thermal infrared remotely sensed satellite observation. Secondly, the study status of land surface emissivity (epsilon) was presented. Thirdly, in order to retrieve LST for all weather conditions, microwave remotely sensed data, instead of thermal infrared data, have been developed recently, and the LST retrieval method from passive microwave remotely sensed data was also introduced. Finally, the main merits and shortcomings of different kinds of LST retrieval methods were discussed, respectively.

Soil Moisture Estimate Under Forest Using a Semi-Empirical Model at P-Band

NASA Technical Reports Server (NTRS)

Truong-Loi, My-Linh; Saatchi, Sassan; Jaruwatanadilok, Sermsak

2013-01-01

Here we present the result of a semi-empirical inversion model for soil moisture retrieval using the three backscattering coefficients: sigma(sub HH), sigma(sub VV) and sigma(sub HV). In this paper we focus on the soil moisture estimate and use the biomass as an ancillary parameter estimated automatically from the algorithm and used as a validation parameter, We will first remind the model analytical formulation. Then we will sow some results obtained with real SAR data and compare them to ground estimates.

Towards soil property retrieval from space: Proof of concept using in situ observations

NASA Astrophysics Data System (ADS)

Bandara, Ranmalee; Walker, Jeffrey P.; Rüdiger, Christoph

2014-05-01

Soil moisture is a key variable that controls the exchange of water and energy fluxes between the land surface and the atmosphere. However, the temporal evolution of soil moisture is neither easy to measure nor monitor at large scales because of its high spatial variability. This is mainly a result of the local variation in soil properties and vegetation cover. Thus, land surface models are normally used to predict the evolution of soil moisture and yet, despite their importance, these models are based on low-resolution soil property information or typical values. Therefore, the availability of more accurate and detailed soil parameter data than are currently available is vital, if regional or global soil moisture predictions are to be made with the accuracy required for environmental applications. The proposed solution is to estimate the soil hydraulic properties via model calibration to remotely sensed soil moisture observation, with in situ observations used as a proxy in this proof of concept study. Consequently, the feasibility is assessed, and the level of accuracy that can be expected determined, for soil hydraulic property estimation of duplex soil profiles in a semi-arid environment using near-surface soil moisture observations under naturally occurring conditions. The retrieved soil hydraulic parameters were then assessed by their reliability to predict the root zone soil moisture using the Joint UK Land Environment Simulator model. When using parameters that were retrieved using soil moisture observations, the root zone soil moisture was predicted to within an accuracy of 0.04 m3/m3, which is an improvement of ∼0.025 m3/m3 on predictions that used published values or pedo-transfer functions.

Outcome of the Third Cloud Retrieval Evaluation Workshop

NASA Astrophysics Data System (ADS)

Roebeling, R.; Baum, B.; Bennartz, R.; Hamann, U.; Heidinger, A.; Thoss, A.; Walther, A.

2012-04-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and inter-annual variations are needed to improve the understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics need to be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), which was held from 15-18 November 2011 in Madison, Wisconsin, USA, is to enhance our knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimising these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods that are used to prepare daily and monthly cloud parameter climatologies. An important component of the workshop is the discussion on the results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we will summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on the reasons for the observed differences. More in depth discussions were held on retrieval principles and validation, and the utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement; cloud physical properties, and cloud climatologies. We will present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize the actions defined to tailor the CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention will be given to increase the traceability and uniformity of different long-term and homogeneous records of cloud parameters.

GPS PPP-derived precipitable water vapor retrieval based on Tm/Ps from multiple sources of meteorological data sets in China

NASA Astrophysics Data System (ADS)

Zhang, Hongxing; Yuan, Yunbin; Li, Wei; Ou, Jikun; Li, Ying; Zhang, Baocheng

2017-04-01

Weighted mean temperature (Tm) and pressure (Ps) are two parameters of great relevance to precipitable water vapor (PWV) retrieval from global positioning system (GPS) data. However, information about the Tm and Ps cannot be available for those GPS stations that are not colocated with meteorological sensors. To investigate the optimal GPS-PWV retrieval method for China, two enhanced Tm models, GM-Tm (temperature dependent) and GH-Tm (temperature independent), are developed. Additionally, the potentials of the Ps data from the two reanalysis data sets, the National Centers for Environmental Prediction (NCEP)-Department of Energy (DOE) Reanalysis II (NCEP II) and ERA-Interim, and from the empirical model GPT2w for GPS-PWV retrieval are investigated over China. To evaluate the performances of multisources Tm and Ps data for GPS-PWV retrieval, GPS data (2011-2013) collected from 22 stations of the Crustal Movement Observation Network of China (CMONOC) were processed by using the precise point positioning (PPP) technique, estimating the zenith tropospheric delay (ZTD) so as to be subsequently converted to GPS-PWV. The retrieved GPS-PWVs are compared with their counterparts derived from NCEP II and radiosonde data over China. The results show that (1) the GM-Tm model consistently shows the highest accuracy (with root mean square error of 2.3 K), and the GH-Tm model should be selected when temperature observations are not available, and that (2) the performances of Ps from NCEP II and ERA-Interim differ marginally for GPS-PWV retrieval, and significant seasonal variations are found in the agreement between the GPS-PWVs and the PWVs derived from NCEP II and radiosonde data over China.

A neural network to retrieve the mesoscale instantaneous latent heat flux over oceans from SSM/I observations

NASA Technical Reports Server (NTRS)

Bourras, D.; Eymard, L.; Liu, W. T.

2000-01-01

The turbulent latent and sensible heat fluxes are necessary to study heat budget of the upper ocean or initialize ocean general circulation models. In order to retrieve the latent heat flux from satellite observations authors mostly use a bulk approximation of the flux whose parameters are derived from different instrument. In this paper, an approach based on artificial neural networks is proposed and compared to the bulk method on a global data set and 3 local data sets.

Unveiling hidden properties of young star clusters: differential reddening, star-formation spread, and binary fraction

NASA Astrophysics Data System (ADS)

Bonatto, C.; Lima, E. F.; Bica, E.

2012-04-01

Context. Usually, important parameters of young, low-mass star clusters are very difficult to obtain by means of photometry, especially when differential reddening and/or binaries occur in large amounts. Aims: We present a semi-analytical approach (ASAmin) that, when applied to the Hess diagram of a young star cluster, is able to retrieve the values of mass, age, star-formation spread, distance modulus, foreground and differential reddening, and binary fraction. Methods: The global optimisation method known as adaptive simulated annealing (ASA) is used to minimise the residuals between the observed and simulated Hess diagrams of a star cluster. The simulations are realistic and take the most relevant parameters of young clusters into account. Important features of the simulations are a normal (Gaussian) differential reddening distribution, a time-decreasing star-formation rate, the unresolved binaries, and the smearing effect produced by photometric uncertainties on Hess diagrams. Free parameters are cluster mass, age, distance modulus, star-formation spread, foreground and differential reddening, and binary fraction. Results: Tests with model clusters built with parameters spanning a broad range of values show that ASAmin retrieves the input values with a high precision for cluster mass, distance modulus, and foreground reddening, but they are somewhat lower for the remaining parameters. Given the statistical nature of the simulations, several runs should be performed to obtain significant convergence patterns. Specifically, we find that the retrieved (absolute minimum) parameters converge to mean values with a low dispersion as the Hess residuals decrease. When applied to actual young clusters, the retrieved parameters follow convergence patterns similar to the models. We show how the stochasticity associated with the early phases may affect the results, especially in low-mass clusters. This effect can be minimised by averaging out several twin clusters in the simulated Hess diagrams. Conclusions: Even for low-mass star clusters, ASAmin is sensitive to the values of cluster mass, age, distance modulus, star-formation spread, foreground and differential reddening, and to a lesser degree, binary fraction. Compared with simpler approaches, including binaries, a decaying star-formation rate, and a normally distributed differential reddening appears to yield more constrained parameters, especially the mass, age, and distance from the Sun. A robust determination of cluster parameters may have a positive impact on many fields. For instance, age, mass, and binary fraction are important for establishing the dynamical state of a cluster or for deriving a more precise star-formation rate in the Galaxy.

Multi-sensor Cloud Retrieval Simulator and Remote Sensing from Model Parameters . Pt. 1; Synthetic Sensor Radiance Formulation; [Synthetic Sensor Radiance Formulation

NASA Technical Reports Server (NTRS)

Wind, G.; DaSilva, A. M.; Norris, P. M.; Platnick, S.

2013-01-01

In this paper we describe a general procedure for calculating synthetic sensor radiances from variable output from a global atmospheric forecast model. In order to take proper account of the discrepancies between model resolution and sensor footprint, the algorithm takes explicit account of the model subgrid variability, in particular its description of the probability density function of total water (vapor and cloud condensate.) The simulated sensor radiances are then substituted into an operational remote sensing algorithm processing chain to produce a variety of remote sensing products that would normally be produced from actual sensor output. This output can then be used for a wide variety of purposes such as model parameter verification, remote sensing algorithm validation, testing of new retrieval methods and future sensor studies.We show a specific implementation using the GEOS-5 model, the MODIS instrument and the MODIS Adaptive Processing System (MODAPS) Data Collection 5.1 operational remote sensing cloud algorithm processing chain (including the cloud mask, cloud top properties and cloud optical and microphysical properties products). We focus on clouds because they are very important to model development and improvement.

The Parallel Episodic Processing (PEP) model 2.0: A single computational model of stimulus-response binding, contingency learning, power curves, and mixing costs.

PubMed

Schmidt, James R; De Houwer, Jan; Rothermund, Klaus

2016-12-01

The current paper presents an extension of the Parallel Episodic Processing model. The model is developed for simulating behaviour in performance (i.e., speeded response time) tasks and learns to anticipate both how and when to respond based on retrieval of memories of previous trials. With one fixed parameter set, the model is shown to successfully simulate a wide range of different findings. These include: practice curves in the Stroop paradigm, contingency learning effects, learning acquisition curves, stimulus-response binding effects, mixing costs, and various findings from the attentional control domain. The results demonstrate several important points. First, the same retrieval mechanism parsimoniously explains stimulus-response binding, contingency learning, and practice effects. Second, as performance improves with practice, any effects will shrink with it. Third, a model of simple learning processes is sufficient to explain phenomena that are typically (but perhaps incorrectly) interpreted in terms of higher-order control processes. More generally, we argue that computational models with a fixed parameter set and wider breadth should be preferred over those that are restricted to a narrow set of phenomena. Copyright © 2016 Elsevier Inc. All rights reserved.

Uniform Atmospheric Retrievals of Ultracool Late-T and Early-Y dwarfs

NASA Astrophysics Data System (ADS)

Garland, Ryan; Irwin, Patrick

2018-01-01

A significant number of ultracool (<600K) extrasolar objects have been unearthed in the past decade thanks to wide-field surveys such as WISE. These objects present a perfect testbed for examining the evolution of atmospheric structure as we transition from typically hot extrasolar temperatures to the temperatures found within our Solar System.By examining these types of objects with a uniform retrieval method, we hope to elucidate any trends and (dis)similarities found in atmospheric parameters, such as chemical abundances, temperature-pressure profile, and cloud structure, for a sample of 7 ultracool brown dwarfs as we transition from hotter (~700K) to colder objects (~450K).We perform atmospheric retrievals on two late-T and five early-Y dwarfs. We use the NEMESIS atmospheric retrieval code coupled to a Nested Sampling algorithm, along with a standard uniform model for all of our retrievals. The uniform model assumes the atmosphere is described by a gray radiative-convective temperature profile, (optionally) a self-consistent Mie scattering cloud, and a number of relevant gases. We first verify our methods by comparing it to a benchmark retrieval for Gliese 570D, which is found to be consistent. Furthermore, we present the retrieved gaseous composition, temperature structure, spectroscopic mass and radius, cloud structure and the trends associated with decreasing temperature found in this small sample of objects.

A statistical retrieval of cloud parameters for the millimeter wave Ice Cloud Imager on board MetOp-SG

NASA Astrophysics Data System (ADS)

Prigent, Catherine; Wang, Die; Aires, Filipe; Jimenez, Carlos

2017-04-01

The meteorological observations from satellites in the microwave domain are currently limited to below 190 GHz. However, the next generation of European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation-EPS-SG will carry an instrument, the Ice Cloud Imager (ICI), with frequencies up to 664 GHz, to improve the characterization of the cloud frozen phase. In this paper, a statistical retrieval of cloud parameters for ICI is developed, trained on a synthetic database derived from the coupling of a mesoscale cloud model and radiative transfer calculations. The hydrometeor profiles simulated with the Weather Research and Forecasting model (WRF) for twelve diverse European mid-latitude situations are used to simulate the brightness temperatures with the Atmospheric Radiative Transfer Simulator (ARTS) to prepare the retrieval database. The WRF+ARTS simulations have been compared to the Special Sensor Microwave Imager/Sounder (SSMIS) observations up to 190 GHz: this successful evaluation gives us confidence in the simulations at the ICI channels from 183 to 664 GHz. Statistical analyses have been performed on this simulated retrieval database, showing that it is not only physically realistic but also statistically satisfactory for retrieval purposes. A first Neural Network (NN) classifier is used to detect the cloud presence. A second NN is developed to retrieve the liquid and ice integrated cloud quantities over sea and land separately. The detection and retrieval of the hydrometeor quantities (i.e., ice, snow, graupel, rain, and liquid cloud) are performed with ICI-only, and with ICI combined with observations from the MicroWave Imager (MWI, with frequencies from 19 to 190 GHz, also on board MetOp-SG). The ICI channels have been optimized for the detection and quantification of the cloud frozen phases: adding the MWI channels improves the performance of the vertically integrated hydrometeor contents, especially for the cloud liquid phases. The relative error for the retrieved integrated frozen water content (FWP, i.e., ice+snow+graupel) is below 40% for 0.1kg/m2 < FWP < 0.5kg/m2 and below 20% for FWP > 0.5 kg/m2.

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).

[Atmospheric correction of HJ-1 CCD data for water imagery based on dark object model].

PubMed

Zhou, Li-Guo; Ma, Wei-Chun; Gu, Wan-Hua; Huai, Hong-Yan

2011-08-01

The CCD multi-band data of HJ-1A has great potential in inland water quality monitoring, but the precision of atmospheric correction is a premise and necessary procedure for its application. In this paper, a method based on dark pixel for water-leaving radiance retrieving is proposed. Beside the Rayleigh scattering, the aerosol scattering is important to atmospheric correction, the water quality of inland lakes always are case II water and the value of water leaving radiance is not zero. So the synchronous MODIS shortwave infrared data was used to obtain the aerosol parameters, and in virtue of the characteristic that aerosol scattering is relative stabilized in 560 nm, the water-leaving radiance for each visible and near infrared band were retrieved and normalized, accordingly the remotely sensed reflectance of water was computed. The results show that the atmospheric correction method based on the imagery itself is more effective for the retrieval of water parameters for HJ-1A CCD data.

Random forest regression modelling for forest aboveground biomass estimation using RISAT-1 PolSAR and terrestrial LiDAR data

NASA Astrophysics Data System (ADS)

Mangla, Rohit; Kumar, Shashi; Nandy, Subrata

2016-05-01

SAR and LiDAR remote sensing have already shown the potential of active sensors for forest parameter retrieval. SAR sensor in its fully polarimetric mode has an advantage to retrieve scattering property of different component of forest structure and LiDAR has the capability to measure structural information with very high accuracy. This study was focused on retrieval of forest aboveground biomass (AGB) using Terrestrial Laser Scanner (TLS) based point clouds and scattering property of forest vegetation obtained from decomposition modelling of RISAT-1 fully polarimetric SAR data. TLS data was acquired for 14 plots of Timli forest range, Uttarakhand, India. The forest area is dominated by Sal trees and random sampling with plot size of 0.1 ha (31.62m*31.62m) was adopted for TLS and field data collection. RISAT-1 data was processed to retrieve SAR data based variables and TLS point clouds based 3D imaging was done to retrieve LiDAR based variables. Surface scattering, double-bounce scattering, volume scattering, helix and wire scattering were the SAR based variables retrieved from polarimetric decomposition. Tree heights and stem diameters were used as LiDAR based variables retrieved from single tree vertical height and least square circle fit methods respectively. All the variables obtained for forest plots were used as an input in a machine learning based Random Forest Regression Model, which was developed in this study for forest AGB estimation. Modelled output for forest AGB showed reliable accuracy (RMSE = 27.68 t/ha) and a good coefficient of determination (0.63) was obtained through the linear regression between modelled AGB and field-estimated AGB. The sensitivity analysis showed that the model was more sensitive for the major contributed variables (stem diameter and volume scattering) and these variables were measured from two different remote sensing techniques. This study strongly recommends the integration of SAR and LiDAR data for forest AGB estimation.

Rough case-based reasoning system for continues casting

NASA Astrophysics Data System (ADS)

Su, Wenbin; Lei, Zhufeng

2018-04-01

The continuous casting occupies a pivotal position in the iron and steel industry. The rough set theory and the CBR (case based reasoning, CBR) were combined in the research and implementation for the quality assurance of continuous casting billet to improve the efficiency and accuracy in determining the processing parameters. According to the continuous casting case, the object-oriented method was applied to express the continuous casting cases. The weights of the attributes were calculated by the algorithm which was based on the rough set theory and the retrieval mechanism for the continuous casting cases was designed. Some cases were adopted to test the retrieval mechanism, by analyzing the results, the law of the influence of the retrieval attributes on determining the processing parameters was revealed. A comprehensive evaluation model was established by using the attribute recognition theory. According to the features of the defects, different methods were adopted to describe the quality condition of the continuous casting billet. By using the system, the knowledge was not only inherited but also applied to adjust the processing parameters through the case based reasoning method as to assure the quality of the continuous casting and improve the intelligent level of the continuous casting.

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)

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

NASA Technical Reports Server (NTRS)

Grecu, Mircea; Anagnostou, Emmanouil N.; Olson, William S.; Starr, David OC. (Technical Monitor)

2002-01-01

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated using both simulated and airborne data. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) satellite multi-frequency active and passive observations. These observations are characterized by various spatial and sampling resolutions. This makes the retrieval problem mathematically more difficult and ill-determined because the quality of information decreases with decreasing resolution. A model that, given reflectivity profiles and a small set of parameters (including the cloud water content, the intercept drop size distribution, and a variable describing the frozen hydrometeor properties), simulates high-resolution brightness temperatures is used. The high-resolution simulated brightness temperatures are convolved at the real sensor resolution. An optimal estimation procedure is used to minimize the differences between simulated and observed brightness temperatures. The retrieval technique is investigated using cloud model synthetic and airborne data from the Fourth Convection And Moisture Experiment. Simulated high-resolution brightness temperatures and reflectivities and airborne observation strong are convolved at the resolution of the TRMM instruments and retrievals are performed and analyzed relative to the reference data used in observations synthesis. An illustration of the possible use of the technique in satellite rainfall estimation is presented through an application to TRMM data. The study suggests improvements in combined active and passive retrievals even when the instruments resolutions are significantly different. Future work needs to better quantify the retrievals performance, especially in connection with satellite applications, and the uncertainty of the models used in retrieval.

Sea ice - atmosphere interaction: Application of multispectral satellite data in polar surface energy flux estimates

NASA Technical Reports Server (NTRS)

Steffen, Konrad; Schweiger, A.; Maslanik, J.; Key, J.; Haefliger, M.; Weaver, R.

1991-01-01

In the past six months, work has continued on energy flux sensitivity studies, ice surface temperature retrievals, corrections to Advanced Very High Resolution Radiometer (AVHRR) thermal infrared data, modelling of cloud fraction retrievals, and radiation climatologies. We tentatively conclude that the SSM/I may not provide accurate enough estimates of ice concentration and type to improve our shorter term energy flux estimates. SSM/I derived parameters may still be applicable in longer term climatological flux characterizations. We hold promise for a system coupling observation to a ice deformation model. Such a model may provide information on ice distribution which can be used in energy flux calculations. Considerable variation was found in modelled energy flux estimates when bulk transfer coefficients are modulated by lead fetch. It is still unclear what the optimum formulation is and this will be the subject of further work. Data sets for ice surface temperature retrievals were assembled and preliminary data analysis was started. Finally, construction of a conceptual framework for further modelling of the Arctic radiation flux climatology was started.

Water sprays in space retrieval operations. [for disabled spacecraft detumbling and despinning

NASA Technical Reports Server (NTRS)

Freesland, D. C.

1978-01-01

The water spray technique (WST) for nullifying the angular momentum of a disabled spacecraft is examined. Such a despinning operation is necessary before a disabled spacecraft can be retrieved by the Space Shuttle. The WST involving the use of liquid sprays appears to be less complex and costly than other techniques proposed to despin a disabled vehicle. A series of experiments have been conducted to determine physical properties of water sprays exhausting into a vacuum. A computer model is built which together with the experimental results yields satellite despin performance parameters. The selection and retrieval of an actual disabled spacecraft is considered to demonstrate an application of the WST.

Combination of image descriptors for the exploration of cultural photographic collections

NASA Astrophysics Data System (ADS)

Bhowmik, Neelanjan; Gouet-Brunet, Valérie; Bloch, Gabriel; Besson, Sylvain

2017-01-01

The rapid growth of image digitization and collections in recent years makes it challenging and burdensome to organize, categorize, and retrieve similar images from voluminous collections. Content-based image retrieval (CBIR) is immensely convenient in this context. A considerable number of local feature detectors and descriptors are present in the literature of CBIR. We propose a model to anticipate the best feature combinations for image retrieval-related applications. Several spatial complementarity criteria of local feature detectors are analyzed and then engaged in a regression framework to find the optimal combination of detectors for a given dataset and are better adapted for each given image; the proposed model is also useful to optimally fix some other parameters, such as the k in k-nearest neighbor retrieval. Three public datasets of various contents and sizes are employed to evaluate the proposal, which is legitimized by improving the quality of retrieval notably facing classical approaches. Finally, the proposed image search engine is applied to the cultural photographic collections of a French museum, where it demonstrates its added value for the exploration and promotion of these contents at different levels from their archiving up to their exhibition in or ex situ.

Radiative Transfer Model for Operational Retrieval of Cloud Parameters from DSCOVR-EPIC Measurements

NASA Astrophysics Data System (ADS)

Yang, Y.; Molina Garcia, V.; Doicu, A.; Loyola, D. G.

2016-12-01

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) measures the radiance in the backscattering region. To make sure that all details in the backward glory are covered, a large number of streams is required by a standard radiative transfer model based on the discrete ordinates method. Even the use of the delta-M scaling and the TMS correction do not substantially reduce the number of streams. The aim of this work is to analyze the capability of a fast radiative transfer model to retrieve operationally cloud parameters from EPIC measurements. The radiative transfer model combines the discrete ordinates method with matrix exponential for the computation of radiances and the matrix operator method for the calculation of the reflection and transmission matrices. Standard acceleration techniques as, for instance, the use of the normalized right and left eigenvectors, telescoping technique, Pade approximation and successive-order-of-scattering approximation are implemented. In addition, the model may compute the reflection matrix of the cloud by means of the asymptotic theory, and may use the equivalent Lambertian cloud model. The various approximations are analyzed from the point of view of efficiency and accuracy.

Retrieving transient conformational molecular structure information from inner-shell photoionization of laser-aligned molecules

DOE PAGES

Wang, Xu; Le, Anh -Thu; Yu, Chao; ...

2016-03-30

We discuss a scheme to retrieve transient conformational molecular structure information using photoelectron angular distributions (PADs) that have averaged over partial alignments of isolated molecules. The photoelectron is pulled out from a localized inner-shell molecular orbital by an X-ray photon. We show that a transient change in the atomic positions from their equilibrium will lead to a sensitive change in the alignment-averaged PADs, which can be measured and used to retrieve the former. Exploiting the experimental convenience of changing the photon polarization direction, we show that it is advantageous to use PADs obtained from multiple photon polarization directions. Lastly, amore » simple single-scattering model is proposed and benchmarked to describe the photoionization process and to do the retrieval using a multiple-parameter fitting method.« less

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.

Using the Opposition Effect in Remotely Sensed Data to Assist in the Retrieval of Bulk Density

NASA Astrophysics Data System (ADS)

Ambeau, Brittany L.

Bulk density is an important geophysical property that impacts the mobility of military vehicles and personnel. Accurate retrieval of bulk density from remotely sensed data is, therefore, needed to estimate the mobility on "off-road" terrain. For a particulate surface, the functional form of the opposition effect can provide valuable information about composition and structure. In this research, we examine the relationship between bulk density and angular width of the opposition effect for a controlled set of laboratory experiments. Given a sample with a known bulk density, we collect reflectance measurements on a spherical grid for various illumination and view geometries -- increasing the amount of reflectance measurements collected at small phase angles near the opposition direction. Bulk densities are varied using a custom-made pluviation device, samples are measured using the Goniometer of the Rochester Institute of Technology-Two (GRIT-T), and observations are fit to the Hapke model using a grid-search method. The method that is selected allows for the direct estimation of five parameters: the single-scattering albedo, the amplitude of the opposition effect, the angular width of the opposition effect, and the two parameters that describe the single-particle phase function. As a test of the Hapke model, the retrieved bulk densities are compared to the known bulk densities. Results show that with an increase in the availability of multi-angular reflectance measurements, the prospects for retrieving the spatial distribution of bulk density from satellite and airborne sensors are imminent.

Concept-oriented indexing of video databases: toward semantic sensitive retrieval and browsing.

PubMed

Fan, Jianping; Luo, Hangzai; Elmagarmid, Ahmed K

2004-07-01

Digital video now plays an important role in medical education, health care, telemedicine and other medical applications. Several content-based video retrieval (CBVR) systems have been proposed in the past, but they still suffer from the following challenging problems: semantic gap, semantic video concept modeling, semantic video classification, and concept-oriented video database indexing and access. In this paper, we propose a novel framework to make some advances toward the final goal to solve these problems. Specifically, the framework includes: 1) a semantic-sensitive video content representation framework by using principal video shots to enhance the quality of features; 2) semantic video concept interpretation by using flexible mixture model to bridge the semantic gap; 3) a novel semantic video-classifier training framework by integrating feature selection, parameter estimation, and model selection seamlessly in a single algorithm; and 4) a concept-oriented video database organization technique through a certain domain-dependent concept hierarchy to enable semantic-sensitive video retrieval and browsing.

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.

1D-VAR Retrieval Using Superchannels

NASA Technical Reports Server (NTRS)

Liu, Xu; Zhou, Daniel; Larar, Allen; Smith, William L.; Schluessel, Peter; Mango, Stephen; SaintGermain, Karen

2008-01-01

Since modern ultra-spectral remote sensors have thousands of channels, it is difficult to include all of them in a 1D-var retrieval system. We will describe a physical inversion algorithm, which includes all available channels for the atmospheric temperature, moisture, cloud, and surface parameter retrievals. Both the forward model and the inversion algorithm compress the channel radiances into super channels. These super channels are obtained by projecting the radiance spectra onto a set of pre-calculated eigenvectors. The forward model provides both super channel properties and jacobian in EOF space directly. For ultra-spectral sensors such as Infrared Atmospheric Sounding Interferometer (IASI) and the NPOESS Airborne Sounder Testbed Interferometer (NAST), a compression ratio of more than 80 can be achieved, leading to a significant reduction in computations involved in an inversion process. Results will be shown applying the algorithm to real IASI and NAST data.

Laser pulse bidirectional reflectance from CALIPSO mission

NASA Astrophysics Data System (ADS)

Lu, Xiaomei; Hu, Yongxiang; Yang, Yuekui; Vaughan, Mark; Liu, Zhaoyan; Rodier, Sharon; Hunt, William; Powell, Kathy; Lucker, Patricia; Trepte, Charles

2018-06-01

This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. To better analyze the surface returns, the CALIOP receiver impulse response and the downlinked samples' distribution at 30 m vertical resolution are discussed. The saturated laser pulse magnitudes from snow and ice surfaces are recovered based on information extracted from the tail end of the surface signal. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud-covered regions and MODIS BRDF-albedo model parameters. In addition to the surface bidirectional reflectance, the column top-of-atmosphere bidirectional reflectances are calculated from the CALIOP lidar background data and compared with the bidirectional reflectances derived from WFC radiance measurements. The retrieved CALIOP surface bidirectional reflectance and column top-of-atmosphere bidirectional reflectance results provide unique information to complement existing MODIS standard data products and are expected to have valuable applications for modelers.

Sonora: A New Generation Model Atmosphere Grid for Brown Dwarfs and Young Extrasolar Giant Planets

NASA Astrophysics Data System (ADS)

Marley, Mark S.; Saumon, Didier; Fortney, Jonathan J.; Morley, Caroline; Lupu, Roxana E.; Freedman, Richard; Visscher, Channon

2017-06-01

Brown dwarf and giant planet atmospheric structure and composition has been studied both by forward models and, increasingly so, by retrieval methods. While indisputably informative, retrieval methods are of greatest value when judged in the context of grid model predictions. Meanwhile retrieval models can test the assumptions inherent in the forward modeling procedure.In order to provide a new, systematic survey of brown dwarf atmospheric structure, emergent spectra, and evolution, we have constructed a new grid of brown dwarf model atmospheres. We ultimately aim for our grid to span substantial ranges of atmospheric metallilcity, C/O ratios, cloud properties, atmospheric mixing, and other parameters. Spectra predicted by our modeling grid can be compared to both observations and retrieval results to aid in the interpretation and planning of future telescopic observations.We thus present Sonora, a new generation of substellar atmosphere models, appropriate for application to studies of L, T, and Y-type brown dwarfs and young extrasolar giant planets. The models describe the expected temperature-pressure profile and emergent spectra of an atmosphere in radiative-convective equilibrium for ranges of effective temperatures and gravities encompassing 200 ≤ Teff ≤ 2400 K and 2.5 ≤ log g ≤ 5.5. In our poster we briefly describe our modeling methodology, enumerate various updates since our group's previous models, and present our initial tranche of models for cloudless, solar metallicity, and solar carbon-to-oxygen ratio, chemical equilibrium atmospheres. These models will be available online and will be updated as opacities and cloud modeling methods continue to improve.

Assessment of MODIS BRDF/Albedo Model Parameters (MCD43A1 Collection 6) for directional reflectance retrieval

NASA Astrophysics Data System (ADS)

Che, X.; Feng, M.; Sexton, J. O.; Channan, S.; Yang, Y.; Song, J.

2017-12-01

Reflection of solar radiation from Earth's surface is the basis for retrieving many higher-level terrestrial attributes such as vegetation indices and albedo. However, reflectance varies with the illumination and viewing geometry of observation (Bi-directional Reflectance Distribution Function (BRDF)) even with constant surface properties, and correcting for these artifacts increases precision of comparisons of images and time series acquired from satellites with different illumination and observation geometries. The operational MODIS processing inverts MODIS BRDF/Albedo Model Parameters (MCD43A1) to retrieve directional reflectance at any solar and view angles, and recently the MCD43A1 (Collection 6) was updated and distributed. We quantified the ability of MCD43A1 Collection 6 for retrieving directional reflectance compared to Collection 5 and tested whether changes in the land surface change over a 16-day composite period affect time series of directional reflectance. Correcting the Terra MODIS daily Surface Reflectance (MOD09GA) to the illumination and view geometries of coincidental Aqua MODIS daily Surface Reflectance (MYD09GA), MCD43A4 Collection 6 and Landsat-5 TM imagery show that the BRDF-corrected results using MCD43A1 Collection 6 hold a higher consistency with higher R2 (0.63 0.955), the slopes close to unity (0.718 0.955) and the lower RMSD (0.422 3.142) and MAE (0.282 1.735) reduced by about 10% than Collection 5. A simple parameter calibration to evaluate the variability of the roughness (R) and the volumetric (V) BRDF parameters for MCD43A1 Collection 6 shows that the assumption of stable land surface characteristic over 16-days composite period, used for BRDF parameters inversion, is plausible in spite of small improvement of directional reflectance and BRDF parameters time series. The larger fluctuations for the MCD43A1 Collection 6 do not have a discernable impact on the reflectance time series. All of these results shows that MCD43A1 Collection 6 product with daily temporal resolution is a valuable product representing the anisotropy of surface features, and reasonably more accurate for directional reflectance derivation at any solar and view geometries than Collection 5, which holds a great potential for many Earth's science research.

Adjoint-Based Climate Model Tuning: Application to the Planet Simulator

NASA Astrophysics Data System (ADS)

Lyu, Guokun; Köhl, Armin; Matei, Ion; Stammer, Detlef

2018-01-01

The adjoint method is used to calibrate the medium complexity climate model "Planet Simulator" through parameter estimation. Identical twin experiments demonstrate that this method can retrieve default values of the control parameters when using a long assimilation window of the order of 2 months. Chaos synchronization through nudging, required to overcome limits in the temporal assimilation window in the adjoint method, is employed successfully to reach this assimilation window length. When assimilating ERA-Interim reanalysis data, the observations of air temperature and the radiative fluxes are the most important data for adjusting the control parameters. The global mean net longwave fluxes at the surface and at the top of the atmosphere are significantly improved by tuning two model parameters controlling the absorption of clouds and water vapor. The global mean net shortwave radiation at the surface is improved by optimizing three model parameters controlling cloud optical properties. The optimized parameters improve the free model (without nudging terms) simulation in a way similar to that in the assimilation experiments. Results suggest a promising way for tuning uncertain parameters in nonlinear coupled climate models.

Sources of interference in item and associative recognition memory.

PubMed

Osth, Adam F; Dennis, Simon

2015-04-01

A powerful theoretical framework for exploring recognition memory is the global matching framework, in which a cue's memory strength reflects the similarity of the retrieval cues being matched against the contents of memory simultaneously. Contributions at retrieval can be categorized as matches and mismatches to the item and context cues, including the self match (match on item and context), item noise (match on context, mismatch on item), context noise (match on item, mismatch on context), and background noise (mismatch on item and context). We present a model that directly parameterizes the matches and mismatches to the item and context cues, which enables estimation of the magnitude of each interference contribution (item noise, context noise, and background noise). The model was fit within a hierarchical Bayesian framework to 10 recognition memory datasets that use manipulations of strength, list length, list strength, word frequency, study-test delay, and stimulus class in item and associative recognition. Estimates of the model parameters revealed at most a small contribution of item noise that varies by stimulus class, with virtually no item noise for single words and scenes. Despite the unpopularity of background noise in recognition memory models, background noise estimates dominated at retrieval across nearly all stimulus classes with the exception of high frequency words, which exhibited equivalent levels of context noise and background noise. These parameter estimates suggest that the majority of interference in recognition memory stems from experiences acquired before the learning episode. (c) 2015 APA, all rights reserved).

A technique for routinely updating the ITU-R database using radio occultation electron density profiles

NASA Astrophysics Data System (ADS)

Brunini, Claudio; Azpilicueta, Francisco; Nava, Bruno

2013-09-01

Well credited and widely used ionospheric models, such as the International Reference Ionosphere or NeQuick, describe the variation of the electron density with height by means of a piecewise profile tied to the F2-peak parameters: the electron density,, and the height, . Accurate values of these parameters are crucial for retrieving reliable electron density estimations from those models. When direct measurements of these parameters are not available, the models compute the parameters using the so-called ITU-R database, which was established in the early 1960s. This paper presents a technique aimed at routinely updating the ITU-R database using radio occultation electron density profiles derived from GPS measurements gathered from low Earth orbit satellites. Before being used, these radio occultation profiles are validated by fitting to them an electron density model. A re-weighted Least Squares algorithm is used for down-weighting unreliable measurements (occasionally, entire profiles) and to retrieve and values—together with their error estimates—from the profiles. These values are used to monthly update the database, which consists of two sets of ITU-R-like coefficients that could easily be implemented in the IRI or NeQuick models. The technique was tested with radio occultation electron density profiles that are delivered to the community by the COSMIC/FORMOSAT-3 mission team. Tests were performed for solstices and equinoxes seasons in high and low-solar activity conditions. The global mean error of the resulting maps—estimated by the Least Squares technique—is between and elec/m for the F2-peak electron density (which is equivalent to 7 % of the value of the estimated parameter) and from 2.0 to 5.6 km for the height (2 %).

Optimizing available water capacity using microwave satellite data for improving irrigation management

NASA Astrophysics Data System (ADS)

Gupta, Manika; Bolten, John; Lakshmi, Venkat

2015-04-01

This work addresses the improvement of available water capacity by developing a technique for estimating soil hydraulic parameters through the utilization of satellite-retrieved near surface soil moisture. The prototype involves the usage of Monte Carlo analysis to assimilate historical remote sensing soil moisture data available from the Advanced Microwave Scanning Radiometer (AMSR-E) within the hydrological model. The main hypothesis used in this study is that near-surface soil moisture data contain useful information that can describe the effective hydrological conditions of the basin such that when appropriately In the method followed in this study the hydraulic parameters are derived directly from information on the soil moisture state at the AMSR-E footprint scale and the available water capacity is derived for the root zone by coupling of AMSR-E soil moisture with the physically-based hydrological model. The available capacity water, which refers to difference between the field capacity and wilting point of the soil and represent the soil moisture content at 0.33 bar and 15 bar respectively is estimated from the soil hydraulic parameters using the van Genuchten equation. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on Soil Survey Geographic (SSURGO) database within the particular AMSR-E footprint. Using the Monte Carlo simulation, the ranges are narrowed in the region where simulation shows a good match between predicted and near-surface soil moisture from AMSR-E. In this study, the uncertainties in accurately determining the parameters of the nonlinear soil water retention function for large-scale hydrological modeling is the focus of the development of the Bayesian framework. Thus, the model forecasting has been combined with the observational information to optimize the model state and the soil hydraulic parameters simultaneously. The optimization process is divided into two steps during one time interval: the state variable is optimized through the state filter and the optimal parameter values are then transferred for retrieving soil moisture. However, soil moisture from sensors such as AMSR-E can only be retrieved for the top few centimeters of soil. So, for the present study, a homogeneous soil system has been considered. By assimilating this information into the model, the accuracy of model structure in relating surface moisture dynamics to deeper soil profiles can be ascertained. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments alongwith the available water capacity, the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the soil moisture simulations. The optimized parameters as compared to the pedo-transfer based parameters were found to reduce the RMSE from 0.14 to 0.04 and 0.15 to 0.07 in surface layer and root zone respectively.

Ozone profiles retrieval from SCIAMACHY Chappuis-Wulf limb scattered spectra using MART

NASA Astrophysics Data System (ADS)

Wang, ZiJun; Chen, ShengBo; Jin, LiHua; Yang, ChunYan

2011-02-01

The Scanning Imaging Absorption spectroMeter for Atmospheric ChartographY (SCIAMACHY) instrument, launched on the Envisat satellite in March 2002, measures the earthshine radiance, simultaneously from the ultraviolet (UV) to the near infrared (NIR), in the three viewing geometries: nadir, limb, and occultation. These measurements are used to retrieve both the total amount and vertical profiles of a large number of atmospheric constituents. In this paper, stratospheric ozone profiles between 15 and 40 km altitude are retrieved on 3 km grids from SCIAMACHY limb scattered radiance in the Chappuis-Wulf band. The study employs a new multiplicative algebraic reconstruction technique (MART) coupled with the radiative transfer model SCIATRAN. This technique is outstanding in that more than one measurement vector element can be used to retrieve the ozone density at any altitude. Furthermore, it is straightforward to understand, easy to implement and likely to produce stable results. Radiance normalization and wavelength pairing is applied to radiance as an intermediate step, using the wavelengths 525 nm, 600 nm and 675 nm. The sensitivity of ozone retrieval by this method to tangent altitude pointing, surface albedo, aerosol and cloud parameters is studied, and the results show that the retrieval impact due to tangent altitude pointing bias is the biggest up to 75% with 1 km shift, and the impact of albedo is limited within 5%. The effect of boundary visibility and cloud parameters can be ignored since their impact is too small. The effectiveness of the retrieval is demonstrated using a set of coincident SCIAMACHY products at Hefei that shows a mean bias of less than 12% between 15 and 40 km, and with a better accuracy of 5% from 16 to 36 km.

Potential of the Sentinel-2 Red Edge Spectral Bands for Estimation of Eco-Physiological Plant Parameters

NASA Astrophysics Data System (ADS)

Malenovsky, Zbynek; Homolova, Lucie; Janoutova, Ruzena; Landier, Lucas; Gastellu-Etchegorry, Jean-Philippe; Berthelot, Beatrice; Huck, Alexis

2016-08-01

In this study we investigated importance of the space- borne instrument Sentinel-2 red edge spectral bands and reconstructed red edge position (REP) for retrieval of the three eco-physiological plant parameters, leaf and canopy chlorophyll content and leaf area index (LAI), in case of maize agricultural fields and beech and spruce forest stands. Sentinel-2 spectral bands and REP of the investigated vegetation canopies were simulated in the Discrete Anisotropic Radiative Transfer (DART) model. Their potential for estimation of the plant parameters was assessed through training support vector regressions (SVR) and examining their P-vector matrices indicating significance of each input. The trained SVR were then applied on Sentinel-2 simulated images and the acquired estimates were cross-compared with results from high spatial resolution airborne retrievals. Results showed that contribution of REP was significant for canopy chlorophyll content, but less significant for leaf chlorophyll content and insignificant for leaf area index estimations. However, the red edge spectral bands contributed strongly to the retrievals of all parameters, especially canopy and leaf chlorophyll content. Application of SVR on Sentinel-2 simulated images demonstrated, in general, an overestimation of leaf chlorophyll content and an underestimation of LAI when compared to the reciprocal airborne estimates. In the follow-up investigation, we will apply the trained SVR algorithms on real Sentinel-2 multispectral images acquired during vegetation seasons 2015 and 2016.

Sequential associative memory with nonuniformity of the layer sizes.

PubMed

Teramae, Jun-Nosuke; Fukai, Tomoki

2007-01-01

Sequence retrieval has a fundamental importance in information processing by the brain, and has extensively been studied in neural network models. Most of the previous sequential associative memory embedded sequences of memory patterns have nearly equal sizes. It was recently shown that local cortical networks display many diverse yet repeatable precise temporal sequences of neuronal activities, termed "neuronal avalanches." Interestingly, these avalanches displayed size and lifetime distributions that obey power laws. Inspired by these experimental findings, here we consider an associative memory model of binary neurons that stores sequences of memory patterns with highly variable sizes. Our analysis includes the case where the statistics of these size variations obey the above-mentioned power laws. We study the retrieval dynamics of such memory systems by analytically deriving the equations that govern the time evolution of macroscopic order parameters. We calculate the critical sequence length beyond which the network cannot retrieve memory sequences correctly. As an application of the analysis, we show how the present variability in sequential memory patterns degrades the power-law lifetime distribution of retrieved neural activities.

Retrievals with the Infrared Atmospheric Sounding Interferometer

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, William L.; Taylor, Jonathan P.; Schlussel, Peter; Strow, L. Larrabee; Calbet, Xavier; Mango, Stephen A.

2007-01-01

The Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite was launched on October 19, 2006. The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations during the JAIVEx are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated.

Error in Radar-Derived Soil Moisture due to Roughness Parameterization: An Analysis Based on Synthetical Surface Profiles

PubMed Central

Lievens, Hans; Vernieuwe, Hilde; Álvarez-Mozos, Jesús; De Baets, Bernard; Verhoest, Niko E.C.

2009-01-01

In the past decades, many studies on soil moisture retrieval from SAR demonstrated a poor correlation between the top layer soil moisture content and observed backscatter coefficients, which mainly has been attributed to difficulties involved in the parameterization of surface roughness. The present paper describes a theoretical study, performed on synthetical surface profiles, which investigates how errors on roughness parameters are introduced by standard measurement techniques, and how they will propagate through the commonly used Integral Equation Model (IEM) into a corresponding soil moisture retrieval error for some of the currently most used SAR configurations. Key aspects influencing the error on the roughness parameterization and consequently on soil moisture retrieval are: the length of the surface profile, the number of profile measurements, the horizontal and vertical accuracy of profile measurements and the removal of trends along profiles. Moreover, it is found that soil moisture retrieval with C-band configuration generally is less sensitive to inaccuracies in roughness parameterization than retrieval with L-band configuration. PMID:22399956

Assessing the impact of different satellite retrieval methods on forecast available potential energy

NASA Technical Reports Server (NTRS)

Whittaker, Linda M.; Horn, Lyle H.

1990-01-01

The effects of the inclusion of satellite temperature retrieval data, and of different satellite retrieval methods, on forecasts made with the NASA Goddard Laboratory for Atmospheres (GLA) fourth-order model were investigated using, as the parameter, the available potential energy (APE) in its isentropic form. Calculation of the APE were used to study the differences in the forecast sets both globally and in the Northern Hemisphere during 72-h forecast period. The analysis data sets used for the forecasts included one containing the NESDIS TIROS-N retrievals, the GLA retrievals using the physical inversion method, and a third, which did not contain satellite data, used as a control; two data sets, with and without satellite data, were used for verification. For all three data sets, the Northern Hemisphere values for the total APE showed an increase throughout the forecast period, mostly due to an increase in the zonal component, in contrast to the verification sets, which showed a steady level of total APE.

The auto-tuned land data assimilation system (ATLAS)

USDA-ARS?s Scientific Manuscript database

Land data assimilation systems are tasked with the merging remotely-sensed soil moisture retrievals with information derived from a soil water balance model driven (principally) by observed rainfall. The performance of such systems is frequently degraded by the imprecise specification of parameters ...

Case studies of aerosol and ocean color retrieval using a Markov chain radiative transfer model and AirMSPI measurements

NASA Astrophysics Data System (ADS)

Xu, F.; Diner, D. J.; Seidel, F. C.; Dubovik, O.; Zhai, P.

2014-12-01

A vector Markov chain radiative transfer method was developed for forward modeling of radiance and polarization fields in a coupled atmosphere-ocean system. The method was benchmarked against an independent Successive Orders of Scattering code and linearized through the use of Jacobians. Incorporated with the multi-patch optimization algorithm and look-up-table method, simultaneous aerosol and ocean color retrievals were performed using imagery acquired by the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) when it was operated in step-and-stare mode with 9 viewing angles ranging between ±67°. Data from channels near 355, 380, 445, 470*, 555, 660*, and 865* nm were used in the retrievals, where the asterisk denotes the polarimetric bands. Retrievals were run for AirMSPI overflights over Southern California and Monterey Bay, CA. For the relatively high aerosol optical depth (AOD) case (~0.28 at 550 nm), the retrieved aerosol concentration, size distribution, water-leaving radiance, and chlorophyll concentration were compared to those reported by the USC SeaPRISM AERONET-OC site off the coast of Southern California on 6 February 2013. For the relatively low AOD case (~0.08 at 550 nm), the retrieved aerosol concentration and size distribution were compared to those reported by the Monterey Bay AERONET site on 28 April 2014. Further, we evaluate the benefits of multi-angle and polarimetric observations by performing the retrievals using (a) all view angles and channels; (b) all view angles but radiances only (no polarization); (c) the nadir view angle only with both radiance and polarization; and (d) the nadir view angle without polarization. Optimized retrievals using different initial guesses were performed to provide a measure of retrieval uncertainty. Removal of multi-angular or polarimetric information resulted in increases in both parameter uncertainty and systematic bias. Potential accuracy improvements afforded by applying constraints on the surface and aerosol parametric models will also be discussed.

Validation of AIRS/AMSU Cloud Retrievals Using MODIS Cloud Analyses

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel

2005-01-01

The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.

Retrieving cloud, dust and ozone abundances in the Martian atmosphere using SPICAM/UV nadir spectra

NASA Astrophysics Data System (ADS)

Willame, Y.; Vandaele, A. C.; Depiesse, C.; Lefèvre, F.; Letocart, V.; Gillotay, D.; Montmessin, F.

2017-08-01

We present the retrieval algorithm developed to analyse nadir spectra from SPICAM/UV aboard Mars-Express. The purpose is to retrieve simultaneously several parameters of the Martian atmosphere and surface: the dust optical depth, the ozone total column, the cloud opacity and the surface albedo. The retrieval code couples the use of an existing complete radiative transfer code, an inversion method and a cloud detection algorithm. We describe the working principle of our algorithm and the parametrisation used to model the required absorption, scattering and reflection processes of the solar UV radiation that occur in the Martian atmosphere and at its surface. The retrieval method has been applied on 4 Martian years of SPICAM/UV data to obtain climatologies of the different quantities under investigation. An overview of the climatology is given for each species showing their seasonal and spatial distributions. The results show a good qualitative agreement with previous observations. Quantitative comparisons of the retrieved dust optical depths indicate generally larger values than previous studies. Possible shortcomings in the dust modelling (altitude profile) have been identified and may be part of the reason for this difference. The ozone results are found to be influenced by the presence of clouds. Preliminary quantitative comparisons show that our retrieved ozone columns are consistent with other results when no ice clouds are present, and are larger for the cases with clouds at high latitude. Sensitivity tests have also been performed showing that the use of other a priori assumptions such as the altitude distribution or some scattering properties can have an important impact on the retrieval.

Ice particle mass-dimensional parameter retrieval and uncertainty analysis using an Optimal Estimation framework applied to in situ data

NASA Astrophysics Data System (ADS)

Xu, Zhuocan; Mace, Jay; Avalone, Linnea; Wang, Zhien

2015-04-01

The extreme variability of ice particle habits in precipitating clouds affects our understanding of these cloud systems in every aspect (i.e. radiation transfer, dynamics, precipitation rate, etc) and largely contributes to the uncertainties in the model representation of related processes. Ice particle mass-dimensional power law relationships, M=a*(D ^ b), are commonly assumed in models and retrieval algorithms, while very little knowledge exists regarding the uncertainties of these M-D parameters in real-world situations. In this study, we apply Optimal Estimation (OE) methodology to infer ice particle mass-dimensional relationship from ice particle size distributions and bulk water contents independently measured on board the University of Wyoming King Air during the Colorado Airborne Multi-Phase Cloud Study (CAMPS). We also utilize W-band radar reflectivity obtained on the same platform (King Air) offering a further constraint to this ill-posed problem (Heymsfield et al. 2010). In addition to the values of retrieved M-D parameters, the associated uncertainties are conveniently acquired in the OE framework, within the limitations of assumed Gaussian statistics. We find, given the constraints provided by the bulk water measurement and in situ radar reflectivity, that the relative uncertainty of mass-dimensional power law prefactor (a) is approximately 80% and the relative uncertainty of exponent (b) is 10-15%. With this level of uncertainty, the forward model uncertainty in radar reflectivity would be on the order of 4 dB or a factor of approximately 2.5 in ice water content. The implications of this finding are that inferences of bulk water from either remote or in situ measurements of particle spectra cannot be more certain than this when the mass-dimensional relationships are not known a priori which is almost never the case.

Estimation of Melt Pond Fractions on First Year Sea Ice Using Compact Polarization SAR

NASA Astrophysics Data System (ADS)

Li, Haiyan; Perrie, William; Li, Qun; Hou, Yijun

2017-10-01

Melt ponds are a common feature on Arctic sea ice. They are linked to the sea ice surface albedo and transmittance of energy to the ocean from the atmosphere and thus constitute an important process to parameterize in Arctic climate models and simulations. This paper presents a first attempt to retrieve the melt pond fraction from hybrid-polarized compact polarization (CP) SAR imagery, which has wider swath and shorter revisit time than the quad-polarization systems, e.g., from RADARSAT-2 (RS-2). The co-polarization (co-pol) ratio has been verified to provide estimates of melt pond fractions. However, it is a challenge to link CP parameters and the co-pol ratio. The theoretical possibility is presented, for making this linkage with the CP parameter C22/C11 (the ratio between the elements of the coherence matrix of CP SAR) for melt pond detection and monitoring with the tilted-Bragg scattering model for the ocean surface. The empirical transformed formulation, denoted as the "compact polarization and quad-pol" ("CPQP") model, is proposed, based on 2062 RS-2 quad-pol SAR images, collocated with in situ measurements. We compared the retrieved melt pond fraction with CP parameters simulated from quad-pol SAR data with results retrieved from the co-pol ratio from quad-pol SAR observations acquired during the Arctic-Ice (Arctic-Ice Covered Ecosystem in a Rapidly Changing Environment) field project. The results are shown to be comparable for observed melt pond measurements in spatial and temporal distributions. Thus, the utility of CP mode SAR for melt pond fraction estimation on first year level ice is presented.

Retrieval of cloud microphysical parameters from INSAT-3D: a feasibility study using radiative transfer simulations

NASA Astrophysics Data System (ADS)

Jinya, John; Bipasha, Paul S.

2016-05-01

Clouds strongly modulate the Earths energy balance and its atmosphere through their interaction with the solar and terrestrial radiation. They interact with radiation in various ways like scattering, emission and absorption. By observing these changes in radiation at different wavelength, cloud properties can be estimated. Cloud properties are of utmost importance in studying different weather and climate phenomena. At present, no satellite provides cloud microphysical parameters over the Indian region with high temporal resolution. INSAT-3D imager observations in 6 spectral channels from geostationary platform offer opportunity to study continuous cloud properties over Indian region. Visible (0.65 μm) and shortwave-infrared (1.67 μm) channel radiances can be used to retrieve cloud microphysical parameters such as cloud optical thickness (COT) and cloud effective radius (CER). In this paper, we have carried out a feasibility study with the objective of cloud microphysics retrieval. For this, an inter-comparison of 15 globally available radiative transfer models (RTM) were carried out with the aim of generating a Look-up- Table (LUT). SBDART model was chosen for the simulations. The sensitivity of each spectral channel to different cloud properties was investigated. The inputs to the RT model were configured over our study region (50°S - 50°N and 20°E - 130°E) and a large number of simulations were carried out using random input vectors to generate the LUT. The determination of cloud optical thickness and cloud effective radius from spectral reflectance measurements constitutes the inverse problem and is typically solved by comparing the measured reflectances with entries in LUT and searching for the combination of COT and CER that gives the best fit. The products are available on the website www.mosdac.gov.in

Optimization and Simulation of SLM Process for High Density H13 Tool Steel Parts

NASA Astrophysics Data System (ADS)

Laakso, Petri; Riipinen, Tuomas; Laukkanen, Anssi; Andersson, Tom; Jokinen, Antero; Revuelta, Alejandro; Ruusuvuori, Kimmo

This paper demonstrates the successful printing and optimization of processing parameters of high-strength H13 tool steel by Selective Laser Melting (SLM). D-Optimal Design of Experiments (DOE) approach is used for parameter optimization of laser power, scanning speed and hatch width. With 50 test samples (1×1×1cm) we establish parameter windows for these three parameters in relation to part density. The calculated numerical model is found to be in good agreement with the density data obtained from the samples using image analysis. A thermomechanical finite element simulation model is constructed of the SLM process and validated by comparing the calculated densities retrieved from the model with the experimentally determined densities. With the simulation tool one can explore the effect of different parameters on density before making any printed samples. Establishing a parameter window provides the user with freedom for parameter selection such as choosing parameters that result in fastest print speed.

Crop effect to soil moisture retrieval at different microwave frequencies

NASA Astrophysics Data System (ADS)

Zhang, Zhongjun; Luan, Jinzhe

2006-12-01

In soil moisture retrieval by microwave remote sensing technology, vegetation effect is important, due to its emission upward as well as masking the soil surface contribution. Because of good penetration characteristics through crop at low frequencies, L-band is often used, where crop is treated as a uniform layer, and 0 th-order Brightness Temperature model is used. Higher frequencies upper than L-band, the frequencies both on NASA AQUA AMSR-E and FY-3 to be launched next year in CHINA, may be more informative in SM retrieval. The multiple-scattering effects inside crop and that between crop layer and soil surface will be increasing when frequencies go higher from L-band. In this paper, a Matrix-Doubling model that account for multiple-scattering based on ray tracing technique is used to simulate the microwave emission of vegetated-surface at C- and X-band. The orientation and size of crop element such as leaves and cylinders are accounted for in crop layer, and AIEM is used for calculation of ground surface scattering. Simulation results from this model for corn and SGP99 experiment data are in good agreement. Since complicated theoretical model as used in this paper involves too many parameters, to make SM retrieval more directly, corresponding terms from the developed model are matched with 0 th-order,so as to derive effective single scattering albedo and vegetation opacity at C- and X-band.

Water Planetary and Cometary Atmospheres: H2O/HDO Transmittance and Fluorescence Models

NASA Technical Reports Server (NTRS)

Villanueva, G. L.; Mumma, M. J.; Bonev, B. P.; Novak, R. E.; Barber, R. J.; DiSanti, M. A.

2012-01-01

We developed a modern methodology to retrieve water (H2O) and deuterated water (HDO) in planetary and cometary atmospheres, and constructed an accurate spectral database that combines theoretical and empirical results. Based on a greatly expanded set of spectroscopic parameters, we built a full non-resonance cascade fluorescence model and computed fluorescence efficiencies for H2O (500 million lines) and HDO (700 million lines). The new line list was also integrated into an advanced terrestrial radiative transfer code (LBLRTM) and adapted to the CO2 rich atmosphere of Mars, for which we adopted the complex Robert-Bonamy formalism for line shapes. We then retrieved water and D/H in the atmospheres of Mars, comet C/2007 WI, and Earth by applying the new formalism to spectra obtained with the high-resolution spectrograph NIRSPEC/Keck II atop Mauna Kea (Hawaii). The new model accurately describes the complex morphology of the water bands and greatly increases the accuracy of the retrieved abundances (and the D/H ratio in water) with respect to previously available models. The new model provides improved agreement of predicted and measured intensities for many H2O lines already identified in comets, and it identifies several unassigned cometary emission lines as new emission lines of H2O. The improved spectral accuracy permits retrieval of more accurate rotational temperatures and production rates for cometary water.

Simulation of the GEM detector for BM@N experiment

NASA Astrophysics Data System (ADS)

Baranov, Dmitriy; Rogachevsky, Oleg

2017-03-01

The Gas Electron Multiplier (GEM) detector is one of the basic parts of the BM@N experiment included in the NICA project. The simulation model that takes into account features of signal generation process in an ionization GEM chamber is presented in this article. Proper parameters for the simulation were extracted from data retrieved with the help of Garfield++ (a toolkit for the detailed simulation of particle detectors). Due to this, we are able to generate clusters in layers of the micro-strip readout that correspond to clusters retrieved from a real physics experiment.

The application of time series models to cloud field morphology analysis

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

NASA Technical Reports Server (NTRS)

Xu, Xiaoguang; Wang, Jun; Zeng, Jing; Spurr, Robert; Liu, Xiong; Dubovik, Oleg; Li, Li; Li, Zhengqiang; Mishchenko, Michael I.; Siniuk, Aliaksandr;

Autocollimation system for measuring angular deformations with reflector designed by quaternionic method

NASA Astrophysics Data System (ADS)

Hoang, Phong V.; Konyakhin, Igor A.

2017-06-01

Autocollimators are widely used for angular measurements in instrument-making and the manufacture of elements of optical systems (wedges, prisms, plane-parallel plates) to check their shape parameters (rectilinearity, parallelism and planarity) and retrieve their optical parameters (curvature radii, measure and test their flange focusing). Autocollimator efficiency is due to the high sensitivity of the autocollimation method to minor rotations of the reflecting control element or the controlled surface itself. We consider using quaternions to optimize reflector parameters during autocollimation measurements as compared to the matrix technique. Mathematical model studies have demonstrated that the orthogonal positioning of the two basic unchanged directions of the tetrahedral reflector of the autocollimator is optimal by the criterion of reducing measurement errors where the axis of actual rotation is in a bisecting position towards them. Computer results are presented of running quaternion models that yielded conditions for diminishing measurement errors provided apriori information is available on the position of rotation axis. A practical technique is considered for synthesizing the parameters of the tetrahedral reflector that employs the newly-retrieved relationships. Following the relationships found between the angles of the tetrahedral reflector and the angles of the parameters of its initial orientation, an applied technique was developed to synthesize the control element for autocollimation measurements in case apriori information is available on the axis of actual rotation during monitoring measurements of shaft or pipeline deformation.

Reliable retrieval of atmospheric and aquatic parameters in coastal and inland environments from polar-orbiting and geostationary platforms: challenges and opportunities

NASA Astrophysics Data System (ADS)

Stamnes, Knut; Li, Wei; Lin, Zhenyi; Fan, Yongzhen; Chen, Nan; Gatebe, Charles; Ahn, Jae-Hyun; Kim, Wonkook; Stamnes, Jakob J.

2017-04-01

Simultaneous retrieval of aerosol and surface properties by means of inverse techniques based on a coupled atmosphere-surface radiative transfer model, neural networks, and optimal estimation can yield considerable improvements in retrieval accuracy in complex aquatic environments compared with traditional methods. Remote sensing of such environments represent specific challenges due (i) the complexity of the atmosphere and water inherent optical properties, (ii) unique bidirectional dependencies of the water-leaving radiance, and (iii) the desire to do retrievals for large solar zenith and viewing angles. We will discuss (a) how challenges related to atmospheric gaseous absorption, absorbing aerosols, and turbid waters can be addressed by using a coupled atmosphere-surface radiative transfer (forward) model in the retrieval process, (b) how the need to correct for bidirectional effects can be accommodated in a systematic and reliable manner, (c) how polarization information can be utilized, (d) how the curvature of the atmosphere can be taken into account, and (e) how neural networks and optimal estimation can be used to obtain fast yet accurate retrievals. Special emphasis will be placed on how information from existing and future sensors deployed on polar-orbiting and geostationary platforms can be obtained in a reliable and accurate manner. The need to provide uncertainty assessments and error budgets will also be discussed.

Probing flexible thermoplastic thin films on a substrate using ultrasonic waves to retrieve mechanical moduli and density: Inverse problem

NASA Astrophysics Data System (ADS)

Lazri, H.; Ogam, E.; Amar, B.; Fellah, Z. E. A.; Sayoud, N.; Boumaiza, Y.

2018-05-01

Flexible, supple thermoplastic thin films (PVB and PET) placed on elastic substrates were probed using ultrasonic waves to identify their mechanical moduli and density. The composite medium immersed in a fluid host medium (water) was excited using a 50 Mhz transducer operating at normal incidence in reflection mode. Elastic wave propagation data from the stratified medium was captured in the host medium as scattered field. These data were used along with theoretical fluid-solid interaction forward models for stratified-media developed using elasticity theory, to solve an inverse problem for the recovery of the model parameters of the thin films. Two configurations were modeled, one considering the substrate as a semi-infinite elastic medium and the second the substrate having a finite thickness and flanked by a semi-infinite host medium. Transverse slip for the sliding interface between the films and substrate was chosen. This was found to agree with the experiments whereby the thin films were just placed on the substrate without bonding. The inverse problems for the recovery of the mechanical parameters were successful in retrieving the thin films’ parameters under the slip boundary condition. The possible improvements to the new method for the characterization of thin films are discussed.

Studies in remotely sensed geophysical parameter retrieval and analysis

NASA Technical Reports Server (NTRS)

Perkey, Donald J.

1993-01-01

This report describes Universities Space Research Association (USRA) activities in support of the Geophysical Parameter Retrieval and Analysis studies. Specifically it addresses personnel assigned to the effort, travel, consultant participants, technical progress, and contract spending.

Hyperspectral water quality retrieval model: taking Malaysia inshore sea area as an example

NASA Astrophysics Data System (ADS)

Cui, Tingwei; Zhang, Jie; Ma, Yi; Li, Jing; Lim, Boonleong; Roslinah, Samad

2007-11-01

Remote sensing technique provides the possibility of rapid and synchronous monitoring in a large area of the water quality, which is an important element for the aquatic ecosystem quality assessment of islands and coastal zones, especially for the nearshore and tourism sea area. Tioman Island of Malaysia is regarded as one of ten of the best islands in the world and attracts tourists from all over the world for its clear sea, beautiful seashore and charming scenery. In this paper, on the basis of in situ dataset in the study area, distribution discipline of water quality parameters is analyzed to find that phytoplankton pigment, rather than suspended sediment is the main water quality parameter in the study area; seawater there is clean but not very oligotrophic; seawater spectra contains distinct features. Then water quality hyperspectral retrieval models are developed based on in situ data to calculate the chlorophyll a concentration ([chl-a]), transparency (SD) with satisfactory performance. It's suggested that model precision should be validated further using more in-situ data.

Surface Emissivity Effects on Thermodynamic Retrieval of IR Spectral Radiance

NASA Technical Reports Server (NTRS)

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

2006-01-01

The surface emissivity effect on the thermodynamic parameters (e.g., the surface skin temperature, atmospheric temperature, and moisture) retrieved from satellite infrared (IR) spectral radiance is studied. Simulation analysis demonstrates that surface emissivity plays an important role in retrieval of surface skin temperature and terrestrial boundary layer (TBL) moisture. NAST-I ultraspectral data collected during the CLAMS field campaign are used to retrieve thermodynamic properties of the atmosphere and surface. The retrievals are then validated by coincident in-situ measurements, such as sea surface temperature, radiosonde temperature and moisture profiles. Retrieved surface emissivity is also validated by that computed from the observed radiance and calculated emissions based on the retrievals of surface temperature and atmospheric profiles. In addition, retrieved surface skin temperature and emissivity are validated together by radiance comparison between the observation and retrieval-based calculation in the window region where atmospheric contribution is minimized. Both simulation and validation results have lead to the conclusion that variable surface emissivity in the inversion process is needed to obtain accurate retrievals from satellite IR spectral radiance measurements. Retrieval examples are presented to reveal that surface emissivity plays a significant role in retrieving accurate surface skin temperature and TBL thermodynamic parameters.

The effect of episodic retrieval on inhibition in task switching.

PubMed

Grange, James A; Kowalczyk, Agnieszka W; O'Loughlin, Rory

2017-08-01

Inhibition in task switching is inferred from n-2 repetition costs: the observation that ABA task switching sequences are responded to slower than CBA sequences. This is thought to reflect the persisting inhibition of Task A, which slows reactivation attempts. Mayr (2002) reported an experiment testing a critical noninhibitory account of this effect, namely episodic retrieval: If the trial parameters for Task A match across an ABA sequence, responses should be facilitated because of priming from episodic retrieval; a cost would occur if trial parameters mismatch. In a rule-switching paradigm, Mayr reported no significant difference in n-2 repetition cost when the trial parameters repeated or switched across an ABA sequence, in clear contrast to the episodic retrieval account. What remains unclear is whether successful episodic retrieval modulates the n-2 repetition cost. Across 3 experiments-including a close replication of Mayr-we find clear evidence of reduced n-2 task repetition costs when episodic retrieval is controlled. We find that the effect of episodic retrieval on the n-2 task repetition cost is increased when the cue-task relationship is made more abstract, suggesting the effect is because of interference in establishing the relevant attentional set. We also demonstrate that the episodic retrieval effect is not influenced by retrieval of low-level, perceptual, elements. Together, the data suggest the n-2 task repetition cost-typically attributable to an inhibitory mechanism-also reflects episodic retrieval effects. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Linearized radiative transfer models for retrieval of cloud parameters from EPIC/DSCOVR measurements

NASA Astrophysics Data System (ADS)

Molina García, Víctor; Sasi, Sruthy; Efremenko, Dmitry S.; Doicu, Adrian; Loyola, Diego

2018-07-01

In this paper, we describe several linearized radiative transfer models which can be used for the retrieval of cloud parameters from EPIC (Earth Polychromatic Imaging Camera) measurements. The approaches under examination are (1) the linearized forward approach, represented in this paper by the linearized discrete ordinate and matrix operator methods with matrix exponential, and (2) the forward-adjoint approach based on the discrete ordinate method with matrix exponential. To enhance the performance of the radiative transfer computations, the correlated k-distribution method and the Principal Component Analysis (PCA) technique are used. We provide a compact description of the proposed methods, as well as a numerical analysis of their accuracy and efficiency when simulating EPIC measurements in the oxygen A-band channel at 764 nm. We found that the computation time of the forward-adjoint approach using the correlated k-distribution method in conjunction with PCA is approximately 13 s for simultaneously computing the derivatives with respect to cloud optical thickness and cloud top height.

Dense image matching of terrestrial imagery for deriving high-resolution topographic properties of vegetation locations in alpine terrain

NASA Astrophysics Data System (ADS)

Niederheiser, R.; Rutzinger, M.; Bremer, M.; Wichmann, V.

2018-04-01

The investigation of changes in spatial patterns of vegetation and identification of potential micro-refugia requires detailed topographic and terrain information. However, mapping alpine topography at very detailed scales is challenging due to limited accessibility of sites. Close-range sensing by photogrammetric dense matching approaches based on terrestrial images captured with hand-held cameras offers a light-weight and low-cost solution to retrieve high-resolution measurements even in steep terrain and at locations, which are difficult to access. We propose a novel approach for rapid capturing of terrestrial images and a highly automated processing chain for retrieving detailed dense point clouds for topographic modelling. For this study, we modelled 249 plot locations. For the analysis of vegetation distribution and location properties, topographic parameters, such as slope, aspect, and potential solar irradiation were derived by applying a multi-scale approach utilizing voxel grids and spherical neighbourhoods. The result is a micro-topography archive of 249 alpine locations that includes topographic parameters at multiple scales ready for biogeomorphological analysis. Compared with regional elevation models at larger scales and traditional 2D gridding approaches to create elevation models, we employ analyses in a fully 3D environment that yield much more detailed insights into interrelations between topographic parameters, such as potential solar irradiation, surface area, aspect and roughness.

The optical depth sensor (ODS) for column dust opacity measurements and cloud detection on martian atmosphere

NASA Astrophysics Data System (ADS)

Toledo, D.; Rannou, P.; Pommereau, J.-P.; Foujols, T.

2016-08-01

A lightweight and sophisticated optical depth sensor (ODS) able to measure alternatively scattered flux at zenith and the sum of the direct flux and the scattered flux in blue and red has been developed to work in martian environment. The principal goals of ODS are to perform measurements of the daily mean dust opacity and to retrieve the altitude and optical depth of high altitude clouds at twilight, crucial parameters in the understanding of martian meteorology. The retrieval procedure of dust opacity is based on the use of radiative transfer simulations reproducing observed changes in the solar flux during the day as a function of 4 free parameters: dust opacity in blue and red, and effective radius and effective width of dust size distribution. The detection of clouds is undertaken by looking at the time variation of the color index (CI), defined as the ratio between red and blue ODS channels, at twilight. The retrieval of altitude and optical depth of clouds is carried out using a radiative transfer model in spherical geometry to simulate the CI time variation at twilight. Here the different retrieval procedures to analyze ODS signals, as well as the results obtained in different sensitivity analysis are presented and discussed.

Retrieval of land parameters by multi-sensor information using the Earth Observation Land Data Assimilation System

NASA Astrophysics Data System (ADS)

Chernetskiy, Maxim; Gobron, Nadine; Gomez-Dans, Jose; Disney, Mathias

2016-07-01

Upcoming satellite constellations will substantially increase the amount of Earth Observation (EO) data, and presents us with the challenge of consistently using all these available information to infer the state of the land surface, parameterised through Essential Climate Variables (ECVs). A promising approach to this problem is the use of physically based models that describe the processes that generate the images, using e.g. radiative transfer (RT) theory. However, these models need to be inverted to infer the land surface parameters from the observations, and there is often not enough information in the EO data to satisfactorily achieve this. Data assimilation (DA) approaches supplement the EO data with prior information in the form of models or prior parameter distributions, and have the potential for solving the inversion problem. These methods however are computationally expensive. In this study, we show the use of fast surrogate models of the RT codes (emulators) based on Gaussian Processes (Gomez-Dans et al, 2016) embedded with the Earth Observation Land Data Assimilation System (EO-LDAS) framework (Lewis et al 2012) in order to estimate the surface of the land surface from a heterogeneous set of optical observations. The study uses time series of moderate spatial resolution observations from MODIS (250 m), MERIS (300 m) and MISR (275 m) over one site to infer the temporal evolution of a number of land surface parameters (and associated uncertainties) related to vegetation: leaf area index (LAI), leaf chlorophyll content, etc. These parameter estimates are then used as input to an RT model (semidiscrete or PROSAIL, for example) to calculate fluxes such as broad band albedo or fAPAR. The study demonstrates that blending different sensors in a consistent way using physical models results in a rich and coherent set of land surface parameters retrieved, with quantified uncertainties. The use of RT models also allows for the consistent prediction of fluxes, with a simple mechanism for propagating the uncertainty in the land surface parameters to the flux estimates.

Modeling regional cropland GPP by empirically incorporating sun-induced chlorophyll fluorescence into a coupled photosynthesis-fluorescence model

NASA Astrophysics Data System (ADS)

Zhang, Y.; Guanter, L.; Van der Tol, C.; Joiner, J.; Berry, J. A.

2015-12-01

Global sun-induced chlorophyll fluorescence (SIF) retrievals are currently available from several satellites. SIF is intrinsically linked to photosynthesis, so the new data sets allow to link remotely-sensed vegetation parameters and the actual photosynthetic activity of plants. In this study, we used space measurements of SIF together with the Soil-Canopy Observation of Photosynthesis and Energy (SCOPE) balance model in order to simulate regional photosynthetic uptake of croplands in the US corn belt. SCOPE couples fluorescence and photosynthesis at leaf and canopy levels. To do this, we first retrieved a key parameter of photosynthesis model, the maximum rate of carboxylation (Vcmax), from field measurements of CO2 and water flux during 2007-2012 at some crop eddy covariance flux sites in the Midwestern US. Then we empirically calibrated Vcmax with apparent fluorescence yield which is SIF divided by PAR. SIF retrievals are from the European GOME-2 instrument onboard the MetOp-A platform. The resulting apparent fluorescence yield shows a stronger relationship with Vcmax during the growing season than widely-used vegetation index, EVI and NDVI. New seasonal and regional Vcmax maps were derived based on the calibration model for the cropland of the corn belt. The uncertainties of Vcmax were also estimated through Gaussian error propagation. With the newly derived Vcmax maps, we modeled regional cropland GPP during the growing season for the Midwestern USA, with meteorological data from MERRA reanalysis data and LAI from MODIS product (MCD15A2). The results show the improvement in the seasonal and spatial patterns of cropland productivity in comparisons with both flux tower and agricultural inventory data.

An Information-theoretic Approach to Optimize JWST Observations and Retrievals of Transiting Exoplanet Atmospheres

NASA Astrophysics Data System (ADS)

Howe, Alex R.; Burrows, Adam; Deming, Drake

2017-01-01

We provide an example of an analysis to explore the optimization of observations of transiting hot Jupiters with the James Webb Space Telescope (JWST) to characterize their atmospheres based on a simple three-parameter forward model. We construct expansive forward model sets for 11 hot Jupiters, 10 of which are relatively well characterized, exploring a range of parameters such as equilibrium temperature and metallicity, as well as considering host stars over a wide range in brightness. We compute posterior distributions of our model parameters for each planet with all of the available JWST spectroscopic modes and several programs of combined observations and compute their effectiveness using the metric of estimated mutual information per degree of freedom. From these simulations, clear trends emerge that provide guidelines for designing a JWST observing program. We demonstrate that these guidelines apply over a wide range of planet parameters and target brightnesses for our simple forward model.

Sonora: A New Generation Model Atmosphere Grid for Brown Dwarfs and Young Extrasolar Giant Planets

NASA Technical Reports Server (NTRS)

Marley, Mark S.; Saumon, Didier; Fortney, Jonathan J.; Morley, Caroline; Lupu, Roxana Elena; Freedman, Richard; Visscher, Channon

2017-01-01

Brown dwarf and giant planet atmospheric structure and composition has been studied both by forward models and, increasingly so, by retrieval methods. While indisputably informative, retrieval methods are of greatest value when judged in the context of grid model predictions. Meanwhile retrieval models can test the assumptions inherent in the forward modeling procedure. In order to provide a new, systematic survey of brown dwarf atmospheric structure, emergent spectra, and evolution, we have constructed a new grid of brown dwarf model atmospheres. We ultimately aim for our grid to span substantial ranges of atmospheric metallilcity, C/O ratios, cloud properties, atmospheric mixing, and other parameters. Spectra predicted by our modeling grid can be compared to both observations and retrieval results to aid in the interpretation and planning of future telescopic observations. We thus present Sonora, a new generation of substellar atmosphere models, appropriate for application to studies of L, T, and Y-type brown dwarfs and young extrasolar giant planets. The models describe the expected temperature-pressure profile and emergent spectra of an atmosphere in radiative-convective equilibrium for ranges of effective temperatures and gravities encompassing 200 less than or equal to T(sub eff) less than or equal to 2400 K and 2.5 less than or equal to log g less than or equal to 5.5. In our poster we briefly describe our modeling methodology, enumerate various updates since our group's previous models, and present our initial tranche of models for cloudless, solar metallicity, and solar carbon-to-oxygen ratio, chemical equilibrium atmospheres. These models will be available online and will be updated as opacities and cloud modeling methods continue to improve.

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.

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.

A linear method for the retrieval of sun-induced chlorophyll fluorescence from GOME-2 and SCIAMACHY data

NASA Astrophysics Data System (ADS)

Köhler, P.; Guanter, L.; Joiner, J.

2014-12-01

Global retrievals of near-infrared sun-induced chlorophyll fluorescence (SIF) have been achieved in the last years by means of a number of space-borne atmospheric spectrometers. Here, we present a new retrieval method for medium spectral resolution instruments such as the Global Ozone Monitoring Experiment (GOME-2) and the SCanning Imaging Absorption SpectroMeter for Atmospheric ChartographY (SCIAMACHY). Building upon the previous work by Joiner et al. (2013), our approach solves existing issues in the retrieval such as the non-linearity of the forward model and the arbitrary selection of the number of free parameters. In particular, we use a backward elimination algorithm to optimize the number of coefficients to fit, which reduces also the retrieval noise and selects the number of state vector elements automatically. A sensitivity analysis with simulated spectra has been utilized to evaluate the performance of our retrieval approach. The method has also been applied to estimate SIF from real spectra from GOME-2 and for the first time, from SCIAMACHY. We find a good correspondence of the absolute SIF values and the spatial patterns from the two sensors, which suggests the robustness of the proposed retrieval method. In addition, we examine uncertainties and use our GOME-2 retrievals to show empirically the low sensitivity of the SIF retrieval to cloud contamination.

Extraction of Profile Information from Cloud Contaminated Radiances. Appendixes 2

NASA Technical Reports Server (NTRS)

Smith, W. L.; Zhou, D. K.; Huang, H.-L.; Li, Jun; Liu, X.; Larar, A. M.

2003-01-01

Clouds act to reduce the signal level and may produce noise dependence on the complexity of the cloud properties and the manner in which they are treated in the profile retrieval process. There are essentially three ways to extract profile information from cloud contaminated radiances: (1) cloud-clearing using spatially adjacent cloud contaminated radiance measurements, (2) retrieval based upon the assumption of opaque cloud conditions, and (3) retrieval or radiance assimilation using a physically correct cloud radiative transfer model which accounts for the absorption and scattering of the radiance observed. Cloud clearing extracts the radiance arising from the clear air portion of partly clouded fields of view permitting soundings to the surface or the assimilation of radiances as in the clear field of view case. However, the accuracy of the clear air radiance signal depends upon the cloud height and optical property uniformity across the two fields of view used in the cloud clearing process. The assumption of opaque clouds within the field of view permits relatively accurate profiles to be retrieved down to near cloud top levels, the accuracy near the cloud top level being dependent upon the actual microphysical properties of the cloud. The use of a physically correct cloud radiative transfer model enables accurate retrievals down to cloud top levels and below semi-transparent cloud layers (e.g., cirrus). It should also be possible to assimilate cloudy radiances directly into the model given a physically correct cloud radiative transfer model using geometric and microphysical cloud parameters retrieved from the radiance spectra as initial cloud variables in the radiance assimilation process. This presentation reviews the above three ways to extract profile information from cloud contaminated radiances. NPOESS Airborne Sounder Testbed-Interferometer radiance spectra and Aqua satellite AIRS radiance spectra are used to illustrate how cloudy radiances can be used in the profile retrieval process.

Parameterization of L-, C- and X-band Radiometer-based Soil Moisture Retrieval Algorithm Using In-situ Validation Sites

NASA Astrophysics Data System (ADS)

Gao, Y.; Colliander, A.; Burgin, M. S.; Walker, J. P.; Chae, C. S.; Dinnat, E.; Cosh, M. H.; Caldwell, T. G.

2017-12-01

Passive microwave remote sensing has become an important technique for global soil moisture estimation over the past three decades. A number of missions carrying sensors at different frequencies that are capable for soil moisture retrieval have been launched. Among them, there are Japan Aerospace Exploration Agency's (JAXA's) Advanced Microwave Scanning Radiometer-EOS (AMSR-E) launched in May 2002 on the National Aeronautics and Space Administration (NASA) Aqua satellite (ceased operation in October 2011), European Space Agency's (ESA's) Soil Moisture and Ocean Salinity (SMOS) mission launched in November 2009, JAXA's Advanced Microwave Scanning Radiometer 2 (AMSR2) onboard the GCOM-W satellite launched in May 2012, and NASA's Soil Moisture Active Passive (SMAP) mission launched in January 2015. Therefore, there is an opportunity to develop a consistent inter-calibrated long-term soil moisture data record based on the availability of these four missions. This study focuses on the parametrization of the tau-omega model at L-, C- and X-band using the brightness temperature (TB) observations from the four missions and the in-situ soil moisture and soil temperature data from core validation sites across various landcover types. The same ancillary data sets as the SMAP baseline algorithm are applied for retrieval at different frequencies. Preliminary comparison of SMAP and AMSR2 TB observations against forward-simulated TB at the Yanco site in Australia showed a generally good agreement with each other and higher correlation for the vertical polarization (R=0.96 for L-band and 0.93 for C- and X-band). Simultaneous calibrations of the vegetation parameter b and roughness parameter h at both horizontal and vertical polarizations are also performed. Finally, a set of model parameters for successfully retrieving soil moisture at different validation sites at L-, C- and X-band respectively are presented. The research described in this paper is supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with NASA. Copyright 2017. All rights reserved.

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

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.

Forest Canopy Cover and Height from MISR in Topographically Complex Southwestern US Landscape Assessed with High Quality Reference Data

NASA Technical Reports Server (NTRS)

Chopping, Mark; North, Malcolm; Chen, Jiquan; Schaaf, Crystal B.; Blair, J. Bryan; Martonchik, John V.; Bull, Michael A.

2012-01-01

This study addresses the retrieval of spatially contiguous canopy cover and height estimates in southwestern USforests via inversion of a geometric-optical (GO) model against surface bidirectional reflectance factor (BRF) estimates from the Multi-angle Imaging SpectroRadiometer (MISR). Model inversion can provide such maps if good estimates of the background bidirectional reflectance distribution function (BRDF) are available. The study area is in the Sierra National Forest in the Sierra Nevada of California. Tree number density, mean crown radius, and fractional cover reference estimates were obtained via analysis of QuickBird 0.6 m spatial resolution panchromatic imagery usingthe CANopy Analysis with Panchromatic Imagery (CANAPI) algorithm, while RH50, RH75 and RH100 (50, 75, and 100 energy return) height data were obtained from the NASA Laser Vegetation Imaging Sensor (LVIS), a full waveform light detection and ranging (lidar) instrument. These canopy parameters were used to drive a modified version of the simple GO model (SGM), accurately reproducing patterns ofMISR 672 nm band surface reflectance (mean RMSE 0.011, mean R2 0.82, N 1048). Cover and height maps were obtained through model inversion against MISR 672 nm reflectance estimates on a 250 m grid.The free parameters were tree number density and mean crown radius. RMSE values with respect to reference data for the cover and height retrievals were 0.05 and 6.65 m, respectively, with of 0.54 and 0.49. MISR can thus provide maps of forest cover and height in areas of topographic variation although refinements are required to improve retrieval precision.

Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

NASA Technical Reports Server (NTRS)

Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian

2011-01-01

Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

Vegetation Monitoring with Gaussian Processes and Latent Force Models

NASA Astrophysics Data System (ADS)

Camps-Valls, Gustau; Svendsen, Daniel; Martino, Luca; Campos, Manuel; Luengo, David

2017-04-01

Monitoring vegetation by biophysical parameter retrieval from Earth observation data is a challenging problem, where machine learning is currently a key player. Neural networks, kernel methods, and Gaussian Process (GP) regression have excelled in parameter retrieval tasks at both local and global scales. GP regression is based on solid Bayesian statistics, yield efficient and accurate parameter estimates, and provides interesting advantages over competing machine learning approaches such as confidence intervals. However, GP models are hampered by lack of interpretability, that prevented the widespread adoption by a larger community. In this presentation we will summarize some of our latest developments to address this issue. We will review the main characteristics of GPs and their advantages in vegetation monitoring standard applications. Then, three advanced GP models will be introduced. First, we will derive sensitivity maps for the GP predictive function that allows us to obtain feature ranking from the model and to assess the influence of examples in the solution. Second, we will introduce a Joint GP (JGP) model that combines in situ measurements and simulated radiative transfer data in a single GP model. The JGP regression provides more sensible confidence intervals for the predictions, respects the physics of the underlying processes, and allows for transferability across time and space. Finally, a latent force model (LFM) for GP modeling that encodes ordinary differential equations to blend data-driven modeling and physical models of the system is presented. The LFM performs multi-output regression, adapts to the signal characteristics, is able to cope with missing data in the time series, and provides explicit latent functions that allow system analysis and evaluation. Empirical evidence of the performance of these models will be presented through illustrative examples.

Structure function monitor

DOEpatents

McGraw, John T [Placitas, NM; Zimmer, Peter C [Albuquerque, NM; Ackermann, Mark R [Albuquerque, NM

2012-01-24

Methods and apparatus for a structure function monitor provide for generation of parameters characterizing a refractive medium. In an embodiment, a structure function monitor acquires images of a pupil plane and an image plane and, from these images, retrieves the phase over an aperture, unwraps the retrieved phase, and analyzes the unwrapped retrieved phase. In an embodiment, analysis yields atmospheric parameters measured at spatial scales from zero to the diameter of a telescope used to collect light from a source.

Characterizing Woody Vegetation Spectral and Structural Parameters with a 3-D Scene Model

NASA Astrophysics Data System (ADS)

Qin, W.; Yang, L.

2004-05-01

Quantification of structural and biophysical parameters of woody vegetation is of great significance in understanding vegetation condition, dynamics and functionality. Such information over a landscape scale is crucial for global and regional land cover characterization, global carbon-cycle research, forest resource inventories, and fire fuel estimation. While great efforts and progress have been made in mapping general land cover types over large area, at present, the ability to quantify regional woody vegetation structural and biophysical parameters is limited. One approach to address this research issue is through an integration of physically based 3-D scene model with multiangle and multispectral remote sensing data and in-situ measurements. The first step of this work is to model woody vegetation structure and its radiation regime using a physically based 3-D scene model and field data, before a robust operational algorithm can be developed for retrieval of important woody vegetation structural/biophysical parameters. In this study, we use an advanced 3-D scene model recently developed by Qin and Gerstl (2000), based on L-systems and radiosity theories. This 3-D scene model has been successfully applied to semi-arid shrubland to study structure and radiation regime at a regional scale. We apply this 3-D scene model to a more complicated and heterogeneous forest environment dominated by deciduous and coniferous trees. The data used in this study are from a field campaign conducted by NASA in a portion of the Superior National Forest (SNF) near Ely, Minnesota during the summers of 1983 and 1984, and supplement data collected during our revisit to the same area of SNF in summer of 2003. The model is first validated with reflectance measurements at different scales (ground observations, helicopter, aircraft, and satellite). Then its ability to characterize the structural and spectral parameters of the forest scene is evaluated. Based on the results from this study and the current multi-spectral and multi-angular satellite data (MODIS, MISR), a robust retrieval system to estimate woody vegetation structural/biophysical parameters is proposed.

Development of a modified two-scale electromagnetic model simulating both active and passive microwave measurements: Comparison to data remotely sensed over the ocean

NASA Astrophysics Data System (ADS)

Boukabara, S. A.; Eymard, L.; Guillou, C.; Lemaire, D.; Sobieski, P.; Guissard, A.

2002-08-01

Spaceborne microwave remote sensing allows the determination of oceanic and atmospheric parameters. Operational payloads such as ERS-1 and ERS-2 and TOPEX/Poseidon as well as missions such as Jason (from NASA-Centre National d'Etudes) or Envisat (from the European Space Agency), have contained or contain paired microwave instruments looking at the nadir direction. This combination consists of microwave radiometers and a radar-altimeter. For the frequencies chosen in oceanographic satellite payloads, the active mode signal is mostly dependent on the surface state through its reflectivity and thus used for the near-surface wind speed retrieval. The active mode can also be attenuated by the atmosphere. On the other hand, the passive mode is related to the surface emissivity and the atmospheric radiation through the radiative transfer equation. Until now, the oceanic and atmospheric parameters have been retrieved separately, the latter being used to correct radar measurements. However, the reflectivity and the emissivity of a target are not independent quantities; hence the synergistic use of these two kinds of microwave measurements should allow one to improve the retrieval quality of the sea and atmosphere parameters. For this purpose, a unified model has been developed for the simulation of both the microwave backscattering coefficient σ° (active measurement) and the microwave emissivity, an important factor for the brightness temperature TB simulation, for every configuration (incidence angles, frequency, polarizations), taking into account the fact that the reflectivity and the emissivity are complementary to unity. The atmospheric absorption is computed following a widely used model from the literature. This paper gives a description and a first attempt of validation of this approach through a comparison with real data. The performance of the model is assessed by comparing the simulations to both brightness temperatures and backscattering coefficients from ERS-1 and TOPEX/Poseidon's instruments during the SEMAPHORE experiment, over a two-month period.

Improvements to the swath-level near-surface atmospheric state parameter retrievals within the NRL Ocean Surface Flux System (NFLUX)

NASA Astrophysics Data System (ADS)

May, J. C.; Rowley, C. D.; Meyer, H.

2017-12-01

The Naval Research Laboratory (NRL) Ocean Surface Flux System (NFLUX) is an end-to-end data processing and assimilation system used to provide near-real-time satellite-based surface heat flux fields over the global ocean. The first component of NFLUX produces near-real-time swath-level estimates of surface state parameters and downwelling radiative fluxes. The focus here will be on the satellite swath-level state parameter retrievals, namely surface air temperature, surface specific humidity, and surface scalar wind speed over the ocean. Swath-level state parameter retrievals are produced from satellite sensor data records (SDRs) from four passive microwave sensors onboard 10 platforms: the Special Sensor Microwave Imager/Sounder (SSMIS) sensor onboard the DMSP F16, F17, and F18 platforms; the Advanced Microwave Sounding Unit-A (AMSU-A) sensor onboard the NOAA-15, NOAA-18, NOAA-19, Metop-A, and Metop-B platforms; the Advanced Technology Microwave Sounder (ATMS) sensor onboard the S-NPP platform; and the Advanced Microwave Scannin Radiometer 2 (AMSR2) sensor onboard the GCOM-W1 platform. The satellite SDRs are translated into state parameter estimates using multiple polynomial regression algorithms. The coefficients to the algorithms are obtained using a bootstrapping technique with all available brightness temperature channels for a given sensor, in addition to a SST field. For each retrieved parameter for each sensor-platform combination, unique algorithms are developed for ascending and descending orbits, as well as clear vs cloudy conditions. Each of the sensors produces surface air temperature and surface specific humidity retrievals. The SSMIS and AMSR2 sensors also produce surface scalar wind speed retrievals. Improvement is seen in the SSMIS retrievals when separate algorithms are used for the even and odd scans, with the odd scans performing better than the even scans. Currently, NFLUX treats all SSMIS scans as even scans. Additional improvement in all of the surface retrievals comes from using a 3-hourly SST field, as opposed to a daily SST field.

Advances in simultaneous atmospheric profile and cloud parameter regression based retrieval from high-spectral resolution radiance measurements

NASA Astrophysics Data System (ADS)

Weisz, Elisabeth; Smith, William L.; Smith, Nadia

2013-06-01

The dual-regression (DR) method retrieves information about the Earth surface and vertical atmospheric conditions from measurements made by any high-spectral resolution infrared sounder in space. The retrieved information includes temperature and atmospheric gases (such as water vapor, ozone, and carbon species) as well as surface and cloud top parameters. The algorithm was designed to produce a high-quality product with low latency and has been demonstrated to yield accurate results in real-time environments. The speed of the retrieval is achieved through linear regression, while accuracy is achieved through a series of classification schemes and decision-making steps. These steps are necessary to account for the nonlinearity of hyperspectral retrievals. In this work, we detail the key steps that have been developed in the DR method to advance accuracy in the retrieval of nonlinear parameters, specifically cloud top pressure. The steps and their impact on retrieval results are discussed in-depth and illustrated through relevant case studies. In addition to discussing and demonstrating advances made in addressing nonlinearity in a linear geophysical retrieval method, advances toward multi-instrument geophysical analysis by applying the DR to three different operational sounders in polar orbit are also noted. For any area on the globe, the DR method achieves consistent accuracy and precision, making it potentially very valuable to both the meteorological and environmental user communities.

Synergy of the SimSphere land surface process model with ASTER imagery for the retrieval of spatially distributed estimates of surface turbulent heat fluxes and soil moisture content

NASA Astrophysics Data System (ADS)

Petropoulos, George; Wooster, Martin J.; Carlson, Toby N.; Drake, Nick

2010-05-01

Accurate information on spatially explicit distributed estimates of key land-atmosphere fluxes and related land surface parameters is of key importance in a range of disciplines including hydrology, meteorology, agriculture and ecology. Estimation of those parameters from remote sensing frequently employs the integration of such data with mathematical representations of the transfers of energy, mass and radiation between soil, vegetation and atmosphere continuum, known as Soil Vegetation Atmosphere Transfer (SVAT) models. The ability of one such inversion modelling scheme to resolve for key surface energy fluxes and of soil surface moisture content is examined here using data from a multispectral high spatial resolution imaging instrument, the Advanced Spaceborne Thermal Emission and Reflection Scanning Radiometer (ASTER) and SimSphere one-dimensional SVAT model. Accuracy of the investigated methodology, so-called as the "triangle" method, is verified using validated ground observations obtained from selected days collected from nine CARBOEUROPE IP sites representing a variety of climatic, topographic and environmental conditions. Subsequently, a new framework is suggested for the retrieval of two additional parameters by the investigated method, namely the Evaporative (EF) and the Non-Evaporative (NEF) Fractions. Results indicated a close agreement between the inverted surface fluxes and surface moisture availability maps as well as of the EF and NEF parameters with the observations both spatially and temporally with accuracies comparable to those obtained in similar experiments with high spatial resolution data. Inspection of the inverted surface fluxes maps regionally, showed an explainable distribution in the range of the inverted parameters in relation with the surface heterogeneity. Overall performance of the "triangle" inversion methodology was found to be affected predominantly by the SVAT model "correct" initialisation representative of the test site environment, most importantly the atmospheric conditions required in the SVAT model initial conditions. This study represents the first comprehensive evaluation of the performance of this particular methodological implementation at a European setting using the SimSphere SVAT with the ASTER data. The present work is also very timely in that, a variation of this specific inversion methodology has been proposed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2012. KEYWORDS: micrometeorology, surface heat fluxes, soil moisture content, ASTER, triangle method, SimSphere, CarboEurope IP

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A.; Gupta, P.; Bhartia, P. K.; Veefkind, P.; Sneep, M.; de Haan, J.; Polonsky, I.; Spurr, R.

2012-01-01

The cloud Optical Centroid Pressure (OCP), also known as the effective cloud pressure, is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosol. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals from the Ozone Monitoring Instrument (OMI) with estimates based on collocated cloud extinction profiles from a combination of CloudS at radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, low altitude clouds missed by CloudSat, and the fact that CloudSat only observes a relatively small fraction of an OMI field-of-view.

Modeling and mining term association for improving biomedical information retrieval performance.

PubMed

Hu, Qinmin; Huang, Jimmy Xiangji; Hu, Xiaohua

2012-06-11

The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind term associations. These latent factors are decided by the proposed model and their term appearances in the first round retrieved passages.

Modeling and mining term association for improving biomedical information retrieval performance

PubMed Central

2012-01-01

Background The growth of the biomedical information requires most information retrieval systems to provide short and specific answers in response to complex user queries. Semantic information in the form of free text that is structured in a way makes it straightforward for humans to read but more difficult for computers to interpret automatically and search efficiently. One of the reasons is that most traditional information retrieval models assume terms are conditionally independent given a document/passage. Therefore, we are motivated to consider term associations within different contexts to help the models understand semantic information and use it for improving biomedical information retrieval performance. Results We propose a term association approach to discover term associations among the keywords from a query. The experiments are conducted on the TREC 2004-2007 Genomics data sets and the TREC 2004 HARD data set. The proposed approach is promising and achieves superiority over the baselines and the GSP results. The parameter settings and different indices are investigated that the sentence-based index produces the best results in terms of the document-level, the word-based index for the best results in terms of the passage-level and the paragraph-based index for the best results in terms of the passage2-level. Furthermore, the best term association results always come from the best baseline. The tuning number k in the proposed recursive re-ranking algorithm is discussed and locally optimized to be 10. Conclusions First, modelling term association for improving biomedical information retrieval using factor analysis, is one of the major contributions in our work. Second, the experiments confirm that term association considering co-occurrence and dependency among the keywords can produce better results than the baselines treating the keywords independently. Third, the baselines are re-ranked according to the importance and reliance of latent factors behind term associations. These latent factors are decided by the proposed model and their term appearances in the first round retrieved passages. PMID:22901087

Sensitivity study of the inverse problem on retrieval of the altitude profile of ozone from emission intensities of the molecular oxygen in the MLT

NASA Astrophysics Data System (ADS)

Martyshenko, Kseniia; Yankovsky, Valentine

2015-04-01

Retrieval of the ozone density altitude profile is important problem for energetics of the upper atmosphere. For comparison of methods of retrieval of altitude profiles of ozone concentration from emissions of excited oxygen molecule and atom was used a modern model of electronic-vibrational kinetics of the products of O3 and O2 photolysis YM-2011 [1]. This study uses only a part of the complete model YM-2011 related to population of levels O2(b1Σ+g, v=0-2), O2(a1Δg, v=0-5) and metastable atom O(1D). Thereby, we obtained solutions of the inverse problem of [O3] retrieval from five proxies O2(a1Δg, v = 0), O2(b1Σ+g, v = 0, 1, 2) and O (1D). Theoretically, every proposed emission of excited component could be promising sources of information about [O3], because it depends on [O3] both in production and in quenching. Detailed analysis of the solutions of the inverse problem of [O3] retrieval were conducted by the sensitivity study of these levels for variations of all model parameters at altitudes of z=40-105 km. The maximum values of sensitivity coefficient to [O3] variations have the following components: O2(b1Σ+g, v = 1), O2(a1Δg, v = 0) and O(1D). The sensitivity of all excited component to variations of ozone decreases sharply above 105 km due to a drastic fall of ozone concentration. [O2(b1Σ+g, v=2)] does not depend on ozone completely at the proposed altitudes, and [O2(b1Σ+g, v=0)] has the lowest sensitivity to variations of [O3] among rest components. Based on the results of the sensitivity study authors investigated the ozone altitude profiles retrieval accuracy taking into account uncertainties of all input parameters (solar excitation and photodissociation rates, quantum yields of products and rate constants of aeronomical reactions). Uncertainties of retrieval of altitude profiles of [O3] from [O(1D)] don't exceed 10% in the interval 40-85 km were obtained. Profile of [O2(b1Σ+g, v=1] allows us to retrieval of [O3] with 21% uncertainty at z =40-95 km, and [O2(b1Σ+g, v=0] - 29% at altitudes up to 97 km. Uncertainties of retrieval of altitude profiles of ozone from [O2(a1Δg, v=0)] achieved 21% at altitudes of z=40-89 km, but it's not uniform in height and in the 77-85 km don't exceed 10%. Overall, optimal methods of retrieval of altitude profiles of ozone concentration is the observation volume emission rate of the molecule O2(b1Σ+g, v=1) in the MLT region. 1. Yankovsky V. A., Manuilova R. O., Babaev A. S., Feofilov A. G., Kutepov A. A. 2011. Model of electronic-vibrational kinetics of the O3 and O2 photolysis products in the middle atmosphere: applications to water vapor retrievals from SABER/TIMED 6.3 µm radiance measurements. International Journal of Remote Sensing, V. 33, N. 12, P. 3065-3078.

Obtaining the Grobner Initialization for the Ground Flash Fraction Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Solakiewicz, R.; Attele, R.; Koshak, W.

2011-01-01

At optical wavelengths and from the vantage point of space, the multiple scattering cloud medium obscures one's view and prevents one from easily determining what flashes strike the ground. However, recent investigations have made some progress examining the (easier, but still difficult) problem of estimating the ground flash fraction in a set of N flashes observed from space In the study by Koshak, a Bayesian inversion method was introduced for retrieving the fraction of ground flashes in a set of flashes observed from a (low earth orbiting or geostationary) satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters, a scalar function of three variables (one of which is the ground flash fraction) was minimized by a numerical method. This method has formed the basis of a Ground Flash Fraction Retrieval Algorithm (GoFFRA) that is being tested as part of GOES-R GLM risk reduction.

Muiti-Sensor Historical Climatology of Satellite-Derived Global Land Surface Moisture

NASA Technical Reports Server (NTRS)

Owe, Manfred; deJeu, Richard; Holmes, Thomas

2007-01-01

A historical climatology of continuous satellite derived global land surface soil moisture is being developed. The data set consists of surface soil moisture retrievals from observations of both historical and currently active satellite microwave sensors, including Nimbus-7 SMMR, DMSP SSM/I, TRMM TMI, and AQUA AMSR-E. The data sets span the period from November 1978 through the end of 2006. The soil moisture retrievals are made with the Land Parameter Retrieval Model, a physically-based model which was developed jointly by researchers from the above institutions. These data are significant in that they are the longest continuous data record of observational surface soil moisture at a global scale. Furthermore, while previous reports have intimated that higher frequency sensors such as on SSM/I are unable to provide meaningful information on soil moisture, our results indicate that these sensors do provide highly useful soil moisture data over significant parts of the globe, and especially in critical areas located within the Earth's many arid and semi-arid regions.

A New Methodology for Simultaneous Multi-layer Retrievals of Ice and Liquid Water Cloud Properties

NASA Astrophysics Data System (ADS)

Sourdeval, O.; Labonnote, L.; Baran, A. J.; Brogniez, G.

2014-12-01

It is widely recognized that the study of clouds has nowadays become one of the major concern of the climate research community. Consequently, a multitude of retrieval methodologies have been developed during the last decades in order to obtain accurate retrievals of cloud properties that can be supplied to climate models. Most of the current methodologies have proven to be satisfactory for separately retrieving ice or liquid cloud properties, but very few of them have attempted simultaneous retrievals of these two cloud types. Recent studies nevertheless show that the omission of one of these layers can have strong consequences on the retrievals and their accuracy. In this study, a new methodology that simultaneously retrieves the properties of ice and liquid clouds is presented. The optical thickness and the effective radius of up to two liquid cloud layers and the ice water path of one ice cloud layer are simultaneously retrieved, along with an accurate estimation of their uncertainties. Radiometric measurements ranging from the visible to the thermal infrared are used for performing the retrievals. In order to quantify the capabilities and limitations of our methodology, the results of a theoretical information content analysis are first presented. This analysis allows obtaining an a priori understanding of how much information should be expected on each of the retrieval parameters in different atmospheric conditions, and which set of channels is likely to provide this information. After such theoretical considerations, global retrievals corresponding to several months of A-Train data are presented. Comparisons of our retrievals with operational products from active and passive instruments are effectuated and show good global agreements. These comparisons are useful for validating our retrievals but also for testing how operational products can be influenced by multi-layer configurations.

Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC

NASA Astrophysics Data System (ADS)

Ebrahimi-Khusfi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-05-01

This study was carried out to evaluate possible improvements of the soil moisture (SM) retrievals from the SMAP observations, based on the synergy between SMAP and SMOS. We assessed the impacts of the vegetation and soil roughness parameters on SM retrievals from SMAP observations. To do so, the effects of three key input parameters including the vegetation optical depth (VOD), effective scattering albedo (ω) and soil roughness (HR) parameters were assessed with the emphasis on the synergy with the VOD product derived from SMOS-IC, a new and simpler version of the SMOS algorithm, over two years of data (April 2015 to April 2017). First, a comprehensive comparison of seven SM retrieval algorithms was made to find the best one for SM retrievals from the SMAP observations. All results were evaluated against in situ measurements over 548 stations from the International Soil Moisture Network (ISMN) in terms of four statistical metrics: correlation coefficient (R), root mean square error (RMSE), bias and unbiased RMSE (UbRMSE). The comparison of seven SM retrieval algorithms showed that the dual channel algorithm based on the additional use of the SMOS-IC VOD product (selected algorithm) led to the best results of SM retrievals over 378, 399, 330 and 271 stations (out of a total of 548 stations) in terms of R, RMSE, UbRMSE and both R & UbRMSE, respectively. Moreover, comparing the measured and retrieved SM values showed that this synergy approach led to an increase in median R value from 0.6 to 0.65 and a decrease in median UbRMSE from 0.09 m3/m3 to 0.06 m3/m3. Second, using the algorithm selected in a first step and defined above, the ω and HR parameters were calibrated over 218 rather homogenous ISMN stations. 72 combinations of various values of ω and HR were used for the calibration over different land cover classes. In this calibration process, the optimal values of ω and HR were found for the different land cover classes. The obtained results indicated that the impact of the VOD parameter on SM retrievals is more considerable than the effects of HR and ω. Overall, the inclusion of the VOD parameter in the SMAP SM retrieval algorithm was found to be a very interesting approach and showed the large potential benefit of the synergy between SMAP and SMOS.

High Vertically Resolved Atmospheric State Revealed with IASI Single FOV Retrievals under All-weather Conditions

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, William L.; Taylor, Jonathan P.; Schluessel, L. Peter; Strow, Larrybee; Mango, Stephen A.

2008-01-01

The Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite was launched on October 19, 2006. The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25 cm(exp -1) and a spectral coverage from 645 to 2760 cm(exp -1). Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated to benefit future NPOESS operation.

Retrieval of tropospheric carbon monoxide for the MOPITT experiment

NASA Astrophysics Data System (ADS)

Pan, Liwen; Gille, John C.; Edwards, David P.; Bailey, Paul L.; Rodgers, Clive D.

1998-12-01

A retrieval method for deriving the tropospheric carbon monoxide (CO) profile and column amount under clear sky conditions has been developed for the Measurements of Pollution In The Troposphere (MOPITT) instrument, scheduled for launch in 1998 onboard the EOS-AM1 satellite. This paper presents a description of the method along with analyses of retrieval information content. These analyses characterize the forward measurement sensitivity, the contribution of a priori information, and the retrieval vertical resolution. Ensembles of tropospheric CO profiles were compiled both from aircraft in situ measurements and from chemical model results and were used in retrieval experiments to characterize the method and to study the sensitivity to different parameters. Linear error analyses were carried out in parallel with the ensemble experiments. Results of these experiments and analyses indicate that MOPITT CO column measurements will have better than 10% precision, and CO profile measurement will have approximately three pieces of independent information that will resolve 3-5 tropospheric layers to approximately 10% precision. These analyses are important for understanding MOPITT data, both for application of data in tropospheric chemistry studies and for comparison with in situ measurements.

Surface roughness retrieval by inversion of the Hapke model: A multiscale approach

NASA Astrophysics Data System (ADS)

Labarre, S.; Ferrari, C.; Jacquemoud, S.

2017-07-01

Surface roughness is a key property of soils that controls many surface processes and influences the scattering of incident electromagnetic waves at a wide range of scales. Hapke (2012b) designed a photometric model providing an approximate analytical solution of the Bidirectional Reflectance Distribution Function (BRDF) of a particulate medium: he introduced the effect of surface roughness as a correction factor of the BRDF of a smooth surface. This photometric roughness is defined as the mean slope angle of the facets composing the surface, integrated over all scales from the grain size to the local topography. Yet its physical meaning is still a question at issue, as the scale at which it occurs is not clearly defined. This work aims at better understanding the relative influence of roughness scales on soil BRDF and to test the ability of the Hapke model to retrieve a roughness that depicts effectively the ground truth. We apply a wavelet transform on millimeter digital terrain models (DTM) acquired over volcanic terrains. This method allows splitting the frequency band of a signal in several sub-bands, each corresponding to a spatial scale. We demonstrate that sub-centimeter surface features dominate both the integrated roughness and the BRDF shape. We investigate the suitability of the Hapke model for surface roughness retrieval by inversion on optical data. A global sensitivity analysis of the model shows that soil BRDF is very sensitive to surface roughness, nearly as much as the single scattering albedo according to the phase angle, but also that these two parameters are strongly correlated. Based on these results, a simplified two-parameter model depending on surface albedo and roughness is proposed. Inversion of this model on BRDF data simulated by a ray-tracing code over natural targets shows a good estimation of surface roughness when the assumptions of the model are verified, with a priori knowledge on surface albedo.

Retrievals of atmospheric columnar carbon dioxide and methane from GOSAT observations with photon path-length probability density function (PPDF) method

NASA Astrophysics Data System (ADS)

Bril, A.; Oshchepkov, S.; Yokota, T.; Yoshida, Y.; Morino, I.; Uchino, O.; Belikov, D. A.; Maksyutov, S. S.

2014-12-01

We retrieved the column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO2) and methane (XCH4) from the radiance spectra measured by Greenhouse gases Observing SATellite (GOSAT) for 48 months of the satellite operation from June 2009. Recent version of the Photon path-length Probability Density Function (PPDF)-based algorithm was used to estimate XCO2 and optical path modifications in terms of PPDF parameters. We also present results of numerical simulations for over-land observations and "sharp edge" tests for sun-glint mode to discuss the algorithm accuracy under conditions of strong optical path modification. For the methane abundance retrieved from 1.67-µm-absorption band we applied optical path correction based on PPDF parameters from 1.6-µm carbon dioxide (CO2) absorption band. Similarly to CO2-proxy technique, this correction assumes identical light path modifications in 1.67-µm and 1.6-µm bands. However, proxy approach needs pre-defined XCO2 values to compute XCH4, whilst the PPDF-based approach does not use prior assumptions on CO2 concentrations.Post-processing data correction for XCO2 and XCH4 over land observations was performed using regression matrix based on multivariate analysis of variance (MANOVA). The MANOVA statistics was applied to the GOSAT retrievals using reference collocated measurements of Total Carbon Column Observing Network (TCCON). The regression matrix was constructed using the parameters that were found to correlate with GOSAT-TCCON discrepancies: PPDF parameters α and ρ, that are mainly responsible for shortening and lengthening of the optical path due to atmospheric light scattering; solar and satellite zenith angles; surface pressure; surface albedo in three GOSAT short wave infrared (SWIR) bands. Application of the post-correction generally improves statistical characteristics of the GOSAT-TCCON correlation diagrams for individual stations as well as for aggregated data.In addition to the analysis of the observations over 12 TCCON stations we estimated temporal and spatial trends (interannual XCO2 and XCH4 variations, seasonal cycles, latitudinal gradients) and compared them with modeled results as well as with similar estimates from other GOSAT retrievals.

Improved MODIS aerosol retrieval in urban areas using a land classification approach and empirical orthogonal functions

NASA Astrophysics Data System (ADS)

Levitan, Nathaniel; Gross, Barry

2016-10-01

New, high-resolution aerosol products are required in urban areas to improve the spatial coverage of the products, in terms of both resolution and retrieval frequency. These new products will improve our understanding of the spatial variability of aerosols in urban areas and will be useful in the detection of localized aerosol emissions. Urban aerosol retrieval is challenging for existing algorithms because of the high spatial variability of the surface reflectance, indicating the need for improved urban surface reflectance models. This problem can be stated in the language of novelty detection as the problem of selecting aerosol parameters whose effective surface reflectance spectrum is not an outlier in some space. In this paper, empirical orthogonal functions, a reconstruction-based novelty detection technique, is used to perform single-pixel aerosol retrieval using the single angular and temporal sample provided by the MODIS sensor. The empirical orthogonal basis functions are trained for different land classes using the MODIS BRDF MCD43 product. Existing land classification products are used in training and aerosol retrieval. The retrieval is compared against the existing operational MODIS 3 KM Dark Target (DT) aerosol product and co-located AERONET data. Based on the comparison, our method allows for a significant increase in retrieval frequency and a moderate decrease in the known biases of MODIS urban aerosol retrievals.

Assessing Surface BRDF-related Biases Using Target Mode Retrievals from the Orbiting Carbon Observatory-2 (OCO-2)

NASA Astrophysics Data System (ADS)

Natraj, V.; McDuffie, J. L.; O'Dell, C.; Eldering, A.; Fu, D.; Wunch, D.; Wennberg, P. O.

2015-12-01

The Orbiting Carbon Observatory-2 (OCO-2) is NASA's first dedicated Earth remote sensing satellite to study atmospheric carbon dioxide from space, and was launched successfully on July 2, 2014. In the target mode of observation, the Observatory will lock its view onto a specific surface location, and will scan back and forth over that target while flying overhead. A target track pass can last for up to 9 minutes. Over that time period, the Observatory can acquire as many as 12,960 samples at local zenith angles that vary between 0° and 85°. Here, we analyze target track measurements over several of the OCO-2 validation sites where ground-based solar-looking Fourier Transform Spectrometers are located. Preliminary analysis of target mode retrievals using the operational algorithm show biases that appear to be due to not accounting for bidirectional surface reflection (BRDF) effects, i.e., the non-isotropic nature of surface reflection. To address this issue, we implement a realistic BRDF model. The column averaged CO2 dry air mole fraction (XCO2) results using this new model show much less variation with scattering angle (or airmass). Further, the retrieved aerosol optical depth (AOD) is in much better agreement with coincident AERONET values. We also use information content analysis to evaluate the degrees of freedom with respect to BRDF parameters, and investigate cross-correlations between the parameters.

Retrieval of Aerosol Parameters from Continuous H24 Lidar-Ceilometer Measurements

NASA Astrophysics Data System (ADS)

Dionisi, D.; Barnaba, F.; Costabile, F.; Di Liberto, L.; Gobbi, G. P.; Wille, H.

2016-06-01

Ceilometer technology is increasingly applied to the monitoring and the characterization of tropospheric aerosols. In this work, a method to estimate some key aerosol parameters (extinction coefficient, surface area concentration and volume concentration) from ceilometer measurements is presented. A numerical model has been set up to derive a mean functional relationships between backscatter and the above mentioned parameters based on a large set of simulated aerosol optical properties. A good agreement was found between the modeled backscatter and extinction coefficients and the ones measured by the EARLINET Raman lidars. The developed methodology has then been applied to the measurements acquired by a prototype Polarization Lidar-Ceilometer (PLC). This PLC instrument was developed within the EC- LIFE+ project "DIAPASON" as an upgrade of the commercial, single-channel Jenoptik CHM15k system. The PLC run continuously (h24) close to Rome (Italy) for a whole year (2013-2014). Retrievals of the aerosol backscatter coefficient at 1064 nm and of the relevant aerosol properties were performed using the proposed methodology. This information, coupled to some key aerosol type identification made possible by the depolarization channel, allowed a year-round characterization of the aerosol field at this site. Examples are given to show how this technology coupled to appropriate data inversion methods is potentially useful in the operational monitoring of parameters of air quality and meteorological interest.

Studying the MLT by a Combined Analysis of SABER/TIMED and Lidar Measurements

NASA Technical Reports Server (NTRS)

Feofilov, A. G.; Kutepov, A. A.; Pesnell, W. D.; Goldberg, R. A.; Zecha, M.; Gerding, M.; Luebken, F. J.; Fiedler, J.; vonZhan, U.; Russell, J. M., III

2006-01-01

The SABER instrument on board the TIMED Satellite is a limb scanning infrared radiometer designed to measure temperature and minor constituent vertical profiles and energetics parameters in the mesosphere and lower thermosphere (MLT). The measurements have been performed continuously since January 25, 2002 to provide excellent coverage for both hemispheres. The Leibniz-Institute of Atmospheric Physics (LAP) at Kuehlungsborn, Germany (54N, 12E) operates two lidar instruments, using three different temperature measurement methods, optimized for three altitude ranges. The total altitude range of the lidar installation lies from 1 to 105 km. Another instrument used for intercomparison is the ALOMAR RMR lidar, located at Andoya, Norway (69N, 16E). We have searched the SABER and lidar datasets for coincidental common volume measurements within plus or minus 1 degree in latitude, plus or minus 2 degrees in longitude and approx. 1 hour in time for the sake of (a) comparison of measured temperatures; (b) validation of the models used in SABER data analysis; and (c) extracting new information about MLT parameters. In this work we applied the non-LTE ALI-ARMS code designed to calculate the nonequilibrium radiance in different viewing geometries to the analysis of measurements which satisfied these search criteria. The results of this analysis (a) support the application of higher value of CO2-O quenching rate (6e-12 cubic centimeters per second) by the non-LTE temperature retrievals from the SABER 15 micrometer limb radiance data, and (b) demonstrate the importance of accounting for the vibrational-vibrational energy exchange among the CO2 isotopes for accurate temperature retrievals. Using temperature profiles obtained in lidar measurements as inputs for the retrieval algorithm we also retrieved the nighttime CO2 densities from the SABER 15 micrometer limb radiances and compared them with the model and climatology CO2 data used in the SABER nighttime temperature retrievals.

Retrieval with Infrared Atmospheric Sounding Interferometer and Validation during JAIVEx

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, William L.; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

2008-01-01

A state-of-the-art IR-only retrieval algorithm has been developed with an all-season-global EOF Physical Regression and followed by 1-D Var. Physical Iterative Retrieval for IASI, AIRS, and NAST-I. The benefits of this retrieval are to produce atmospheric structure with a single FOV horizontal resolution (approx. 15 km for IASI and AIRS), accurate profiles above the cloud (at least) or down to the surface, surface parameters, and/or cloud microphysical parameters. Initial case study and validation indicates that surface, cloud, and atmospheric structure (include TBL) are well captured by IASI and AIRS measurements. Coincident dropsondes during the IASI and AIRS overpasses are used to validate atmospheric conditions, and accurate retrievals are obtained with an expected vertical resolution. JAIVEx has provided the data needed to validate the retrieval algorithm and its products which allows us to assess the instrument ability and/or performance. Retrievals with global coverage are under investigation for detailed retrieval assessment. It is greatly desired that these products be used for testing the impact on Atmospheric Data Assimilation and/or Numerical Weather Prediction.

Towards retrievals of aerosol chemical composition from satellite observations by POLDER/PARASOL polarimeter

NASA Astrophysics Data System (ADS)

Li, L.; Dubovik, O.; Derimian, Y.; Lapyonok, T.; Schuster, G. L.; Ducos, F.

2016-12-01

The information about composition of aerosols has a great importance for monitoring and understanding of climate and environment dynamics. Such information can be obtained using situ measurements or chemical transport models. However, in situ sampling has limited spatial and temporal coverage, while estimations have large uncertainties. The present work enables the monitoring of aerosol chemical species from space-borne observations, providing observationally-based results with spatial and temporal coverage. Following the ideas of Schuster et al.(2005, 2009, 2016), we retrieve chemical composition directly from remote sensing measurements without intermediate retrieval of the refractive index (in contrast with Schuster's approach). This approach is expected to reduce the influence of modeling uncertainties, and to provide additional constraints in situations where remote sensing observations do not have enough spectral sensitivity to refractive index. One of principal difficulties is the identification of an adequate model for linking refractive index to chemical composition. Therefore, the initial effort of this work has focused on identifying an optimal "chemical composition to refractive index" conversion model. With that purpose, we first tested the retrieval approach using a simplified volume-weighting model and updated by the Maxwell Garnett mixing model. This concept was incorporated into the GRASP algorithm designed to retrieve an extended set of atmospheric parameters from remote sensing observations. Then a series of sensitivity tests using synthetic data of POLDER/PARASOL were conducted, and followed by inversion of real PARASOL observations. The sensitivity tests showed that these two models allow the retrieval to distinguish amongst the assumed chemical species. Results obtained from real PARASOL data demonstrated good agreement with the optical characteristics provided by AERONET (e.g., r2 of AOT 0.9). The obtained patterns of chemical component distribution agreed with known physical expectations. For example, the mass concentration of black and brown carbon in the biomass burning region was found five times higher than in the region mainly affected by dust. The mass concentration of quartz in western Africa is up to seven times higher than in southern Africa.

Material Properties from Air Puff Corneal Deformation by Numerical Simulations on Model Corneas.

PubMed

Bekesi, Nandor; Dorronsoro, Carlos; de la Hoz, Andrés; Marcos, Susana

2016-01-01

To validate a new method for reconstructing corneal biomechanical properties from air puff corneal deformation images using hydrogel polymer model corneas and porcine corneas. Air puff deformation imaging was performed on model eyes with artificial corneas made out of three different hydrogel materials with three different thicknesses and on porcine eyes, at constant intraocular pressure of 15 mmHg. The cornea air puff deformation was modeled using finite elements, and hyperelastic material parameters were determined through inverse modeling, minimizing the difference between the simulated and the measured central deformation amplitude and central-peripheral deformation ratio parameters. Uniaxial tensile tests were performed on the model cornea materials as well as on corneal strips, and the results were compared to stress-strain simulations assuming the reconstructed material parameters. The measured and simulated spatial and temporal profiles of the air puff deformation tests were in good agreement (< 7% average discrepancy). The simulated stress-strain curves of the studied hydrogel corneal materials fitted well the experimental stress-strain curves from uniaxial extensiometry, particularly in the 0-0.4 range. Equivalent Young´s moduli of the reconstructed material properties from air-puff were 0.31, 0.58 and 0.48 MPa for the three polymer materials respectively which differed < 1% from those obtained from extensiometry. The simulations of the same material but different thickness resulted in similar reconstructed material properties. The air-puff reconstructed average equivalent Young´s modulus of the porcine corneas was 1.3 MPa, within 18% of that obtained from extensiometry. Air puff corneal deformation imaging with inverse finite element modeling can retrieve material properties of model hydrogel polymer corneas and real corneas, which are in good correspondence with those obtained from uniaxial extensiometry, suggesting that this is a promising technique to retrieve quantitative corneal biomechanical properties.

Moderate Imaging Resolution Spectroradiometer (MODIS) Aerosol Optical Depth Retrieval for Aerosol Radiative Forcing

NASA Astrophysics Data System (ADS)

Asmat, A.; Jalal, K. A.; Ahmad, N.

2018-02-01

The present study uses the Aerosol Optical Depth (AOD) retrieved from Moderate Imaging Resolution Spectroradiometer (MODIS) data for the period from January 2011 until December 2015 over an urban area in Kuching, Sarawak. The results show the minimum AOD value retrieved from MODIS is -0.06 and the maximum value is 6.0. High aerosol loading with high AOD value observed during dry seasons and low AOD monitored during wet seasons. Multi plane regression technique used to retrieve AOD from MODIS (AODMODIS) and different statistics parameter is proposed by using relative absolute error for accuracy assessment in spatial and temporal averaging approach. The AODMODIS then compared with AOD derived from Aerosol Robotic Network (AERONET) Sunphotometer (AODAERONET) and the results shows high correlation coefficient (R2) for AODMODIS and AODAERONET with 0.93. AODMODIS used as an input parameters into Santa Barbara Discrete Ordinate Radiative Transfer (SBDART) model to estimate urban radiative forcing at Kuching. The observed hourly averaged for urban radiative forcing is -0.12 Wm-2 for top of atmosphere (TOA), -2.13 Wm-2 at the surface and 2.00 Wm-2 in the atmosphere. There is a moderate relationship observed between urban radiative forcing calculated using SBDART and AERONET which are 0.75 at the surface, 0.65 at TOA and 0.56 in atmosphere. Overall, variation in AOD tends to cause large bias in the estimated urban radiative forcing.

Measurement of dust optical depth using the solar irradiance sensor (SIS) onboard the ExoMars 2016 EDM

NASA Astrophysics Data System (ADS)

Toledo, D.; Arruego, I.; Apéstigue, V.; Jiménez, J. J.; Gómez, L.; Yela, M.; Rannou, P.; Pommereau, J.-P.

2017-04-01

The solar irradiance sensor (SIS) was included in the DREAMS package onboard the ExoMars 2016 Entry Descent and Landing Demonstrator Module, and has been selected in the METEO meteorological station onboard the ExoMars 2020 Lander. This instrument is designed to measure at different time intervals the scattered flux or the sum of direct flux and scattered flux in UVA (315-400 nm) and NIR (700-1100 nm) bands. For SIS'16, these measurements are performed by a total of 3 sensors per band placed at the faces of a truncated tetrahedron with face inclination angles of 60°. The principal goal of SIS'16 design is to perform measurements of the dust opacity in UVA and NIR wavelengths ranges, crucial parameters in the understanding of the Martian dust cycle. The retrieval procedure is based on the use of radiative transfer simulations to reproduce SIS observations acquired during daytime as a function of dust opacity. Based on different sensitivity analysis, the retrieval procedure also requires to include as free parameters (1) the dust effective radius; (2) the dust effective variance; and (3) the imaginary part of the refractive index of dust particles in UVA band. We found that the imaginary part of the refractive index of dust particles does not have a big impact on NIR signal, and hence we can kept constant this parameter in the retrieval of dust opacity at this channel. In addition to dust opacity measurements, this instrument is also capable to detect and characterize clouds by looking at the time variation of the color index (CI), defined as the ratio between the observations in NIR and UVA channels, during daytime or twilight. By simulating CI signals with a radiative transfer model, the cloud opacity and cloud altitude (only during twilight) can be retrieved. Here the different retrieval procedures that are used to analyze SIS measurements, as well as the results obtained in different sensitivity analysis, are presented and discussed.

Optimisation of sea surface current retrieval using a maximum cross correlation technique on modelled sea surface temperature

NASA Astrophysics Data System (ADS)

Heuzé, Céline; Eriksson, Leif; Carvajal, Gisela

2017-04-01

Using sea surface temperature from satellite images to retrieve sea surface currents is not a new idea, but so far its operational near-real time implementation has not been possible. Validation studies are too region-specific or uncertain, due to the errors induced by the images themselves. Moreover, the sensitivity of the most common retrieval method, the maximum cross correlation, to the three parameters that have to be set is unknown. Using model outputs instead of satellite images, biases induced by this method are assessed here, for four different seas of Western Europe, and the best of nine settings and eight temporal resolutions are determined. For all regions, tracking a small 5 km pattern from the first image over a large 30 km region around its original location on a second image, separated from the first image by 6 to 9 hours returned the most accurate results. Moreover, for all regions, the problem is not inaccurate results but missing results, where the velocity is too low to be picked by the retrieval. The results are consistent both with limitations caused by ocean surface current dynamics and with the available satellite technology, indicating that automated sea surface current retrieval from sea surface temperature images is feasible now, for search and rescue operations, pollution confinement or even for more energy efficient and comfortable ship navigation.

Calibration and Data Retrieval Algorithms for the NASA Langley/Ames Diode Laser Hygrometer for the NASA Trace-P Mission

NASA Technical Reports Server (NTRS)

Podolske, James R.; Sachse, Glen W.; Diskin, Glenn S.; Hipskino, R. Stephen (Technical Monitor)

2002-01-01

This paper describes the procedures and algorithms for the laboratory calibration and the field data retrieval of the NASA Langley / Ames Diode Laser Hygrometer as implemented during the NASA Trace-P mission during February to April 2000. The calibration is based on a NIST traceable dewpoint hygrometer using relatively high humidity and short pathlength. Two water lines of widely different strengths are used to increase the dynamic range of the instrument in the course of a flight. The laboratory results are incorporated into a numerical model of the second harmonic spectrum for each of the two spectral window regions using spectroscopic parameters from the HITRAN database and other sources, allowing water vapor retrieval at upper tropospheric and lower stratospheric temperatures and humidity levels. The data retrieval algorithm is simple, numerically stable, and accurate. A comparison with other water vapor instruments on board the NASA DC-8 and ER-2 aircraft is presented.

Analyse du potentiel de la radiometrie infrarouge thermique pour la caracterisation des nuages de glace en Arctique

NASA Astrophysics Data System (ADS)

Blanchard, Yann

An important goal, within the context of improving climate change modelling, is to enhance our understanding of aerosols and their radiative effects (notably their indirect impact as cloud condensation nuclei). The cloud optical depth (COD) and average ice particle size of thin ice clouds (TICs) are two key parameters whose variations could strongly influence radiative effects and climate in the Arctic environment. Our objective was to assess the potential of using multi-band thermal radiance measurements of zenith sky radiance for retrieving COD and effective particle diameter (Deff) of TICs in the Arctic. We analyzed and quantified the sensitivity of thermal radiance on many parameters, such as COD, Deff, water vapor content, cloud bottom altitude and thickness, size distribution and shape. Using the sensitivity of IRT to COD and Deff, the developed retrieval technique is validated in comparison with retrievals from LIDAR and RADAR. Retrievals were applied to ground-based thermal infrared data acquired for 100 TICs at the high-Arctic PEARL observatory in Eureka, Nunavut, Canada and were validated using AHSRL LIDAR and MMCR RADAR data. The results of the retrieval method were used to successfully extract COD up to values of 3 and to separate TICs into two types : TIC1 characterized by small crystals (Deff < 30 mum) and TIC2 by large ice crystals (Deff > 30 mum, up to 300 mum). Inversions were performed across two polar winters. At the end of this research, we proposed different alternatives to apply our methodology in the Arctic. Keywords : Remote sensing ; ice clouds ; thermal infrared multi-band radiometry ; Arctic.

Exploiting the MODIS albedos with the Two-stream Inversion Package (JRC-TIP): 2. Fractions of transmitted and absorbed fluxes in the vegetation and soil layers

NASA Astrophysics Data System (ADS)

Pinty, B.; Clerici, M.; Andredakis, I.; Kaminski, T.; Taberner, M.; Verstraete, M. M.; Gobron, N.; Plummer, S.; Widlowski, J.-L.

2011-05-01

The two-stream model parameters and associated uncertainties retrieved by inversion against MODIS broadband visible and near-infrared white sky surface albedos were discussed in a companion paper. The present paper concentrates on the partitioning of the solar radiation fluxes delivered by the Joint Research Centre Two-stream Inversion Package (JRC-TIP). The estimation of the various flux fractions related to the vegetation and the background layers separately capitalizes on the probability density functions of the model parameters discussed in the companion paper. The propagation of uncertainties from the observations to the model parameters is achieved via the Hessian of the cost function and yields a covariance matrix of posterior parameter uncertainties. This matrix is propagated to the radiation fluxes via the model's Jacobian matrix of first derivatives. Results exhibit a rather good spatiotemporal consistency given that the prior values on the model parameters are not specified as a function of land cover type and/or vegetation phenological states. A specific investigation based on a scenario imposing stringent conditions of leaf absorbing and scattering properties highlights the impact of such constraints that are, as a matter of fact, currently adopted in vegetation index approaches. Special attention is also given to snow-covered and snow-contaminated areas since these regions encompass significant reflectance changes that strongly affect land surface processes. A definite asset of the JRC-TIP lies in its capability to control and ultimately relax a number of assumptions that are often implicit in traditional approaches. These features greatly help us understand the discrepancies between the different data sets of land surface properties and fluxes that are currently available. Through a series of selected examples, the inverse procedure implemented in the JRC-TIP is shown to be robust, reliable, and compliant with large-scale processing requirements. Furthermore, this package ensures the physical consistency between the set of observations, the two-stream model parameters, and radiation fluxes. It also documents the retrieval of associated uncertainties.

Contextualization: Memory Formation and Retrieval in a Nested Environment

NASA Astrophysics Data System (ADS)

Piefke, Martina; Markowitsch, Hans J.

Episodic memory functions are highly context-dependent. This is true for both experimental and autobiographical episodic memory. We here review neuropsychological and neuroimaging evidence for effects of differential encoding and retrieval contexts on episodic memory performance as well as the underlying neurofunctional mechanisms. In studies of laboratory episodic memory, the influence of context parameters can be assessed by experimental manipulations. Such experiments suggest that contextual variables mainly affect prefrontal functions supporting executive processes involved in episodic learning and retrieval. Context parameters affecting episodic autobiographical memory are far more complex and cannot easily be controlled. Data support the view that not only prefrontal, but also further medial temporal and posterior parietal regions mediating the re-experience and emotional evaluation of personal memories are highly influenced by changing contextual variables of memory encoding and retrieval. Based on our review of available data, we thus suggest that experimental and autobiographical episodic memories are influenced by both overlapping and differential context parameters.

Calibration of sea ice dynamic parameters in an ocean-sea ice model using an ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Massonnet, F.; Goosse, H.; Fichefet, T.; Counillon, F.

2014-07-01

The choice of parameter values is crucial in the course of sea ice model development, since parameters largely affect the modeled mean sea ice state. Manual tuning of parameters will soon become impractical, as sea ice models will likely include more parameters to calibrate, leading to an exponential increase of the number of possible combinations to test. Objective and automatic methods for parameter calibration are thus progressively called on to replace the traditional heuristic, "trial-and-error" recipes. Here a method for calibration of parameters based on the ensemble Kalman filter is implemented, tested and validated in the ocean-sea ice model NEMO-LIM3. Three dynamic parameters are calibrated: the ice strength parameter P*, the ocean-sea ice drag parameter Cw, and the atmosphere-sea ice drag parameter Ca. In twin, perfect-model experiments, the default parameter values are retrieved within 1 year of simulation. Using 2007-2012 real sea ice drift data, the calibration of the ice strength parameter P* and the oceanic drag parameter Cw improves clearly the Arctic sea ice drift properties. It is found that the estimation of the atmospheric drag Ca is not necessary if P* and Cw are already estimated. The large reduction in the sea ice speed bias with calibrated parameters comes with a slight overestimation of the winter sea ice areal export through Fram Strait and a slight improvement in the sea ice thickness distribution. Overall, the estimation of parameters with the ensemble Kalman filter represents an encouraging alternative to manual tuning for ocean-sea ice models.

A statistical look at the retrieval of exoplanetary atmospheres of super Earths and giant planets

NASA Astrophysics Data System (ADS)

Rocchetto, Marco; Waldmann, Ingo Peter; Tinetti, Giovanna; Yurchenko, Sergey; Tennyson, Jonathan

2015-08-01

Over the past decades transit spectroscopy has become one of the pioneering methods to characterise exoplanetary atmospheres. With the increasing number of observations, and the advent of new ground and spaced based instruments, it is now crucial to find the most optimal and objective methodologies to interpret these data, and understand the information content they convey. This is particularly true for smaller and fainter super Earth type planets.In this conference we will present a new take on the spectral retrieval of transiting planets, with particular focus on super Earth atmospheres. TauREx (Waldmann et al. 2015a,b.) is a new line-by-line radiative transfer atmospheric retrieval framework for transmission and emission spectroscopy of exoplanetary atmospheres, optimised for hot Jupiters and super Earths. The code has been built from scratch with the ideas of scalability, flexibility and automation. This allows to run retrievals with minimum user input that can be scaled to large cluster computing. Priors on the number and types of molecules considered are automatically determined using a custom built pattern recognition algorithm able to identify the most likely absorbers/emitters in the exoplanetary spectra, minimising the human bias in selecting the major atmospheric constituents.Using these tools, we investigate the impact of signal to noise, spectral resolution and wavelength coverage on the retrievability of individual model parameters from transit spectra of super Earths, and put our models to test (Rocchetto et al. 2015). Characterisation of the atmospheres of super Earths through transit spectroscopy is paramount, as it can provide an indirect - and so far unique - way to probe the nature of these planets. For the first time we analyse in a systematic way large grids of spectra generated for different observing scenarios. We perform thousands of retrievals aimed to fully map the degeneracies and understand the statistics of current exoplanetary retrieval models, in the limiting signal-to-noise regime of super Earth observations.

Estimation of Snow Parameters from Dual-Wavelength Airborne Radar

NASA Technical Reports Server (NTRS)

Liao, Liang; Meneghini, Robert; Iguchi, Toshio; Detwiler, Andrew

1997-01-01

Estimation of snow characteristics from airborne radar measurements would complement In-situ measurements. While In-situ data provide more detailed information than radar, they are limited in their space-time sampling. In the absence of significant cloud water contents, dual-wavelength radar data can be used to estimate 2 parameters of a drop size distribution if the snow density is assumed. To estimate, rather than assume, a snow density is difficult, however, and represents a major limitation in the radar retrieval. There are a number of ways that this problem can be investigated: direct comparisons with in-situ measurements, examination of the large scale characteristics of the retrievals and their comparison to cloud model outputs, use of LDR measurements, and comparisons to the theoretical results of Passarelli(1978) and others. In this paper we address the first approach and, in part, the second.

On the possible use of radio occultation middle latitude electron density profiles to retrieve thermospheric parameters

NASA Astrophysics Data System (ADS)

Mikhailov, Andrei V.; Belehaki, Anna; Perrone, Loredanna; Zolesi, Bruno; Tsagouri, Ioanna

2014-04-01

This paper investigates possible use of middle latitude daytime COSMIC and CHAMP ionospheric radio occultation (IRO) electron density profiles (EDPs) to retrieve thermospheric parameters, based on the Mikhailov et al. (2012) method. The aim of this investigation is to assess the applicability of this type of observations for the routine implementation of the method. According to the results extracted from the analysis presented here, about half of COSMIC IRO EDP observed under solar minimum (2007-2008) conditions gave neutral gas density with an inaccuracy close to the declared absolute inaccuracy ±(10-15)% of CHAMP observations, with the results being better than the empirical models JB-2008 and MSISE-00 provide. For the other half of IRO EDP, either the solution provided by the method had to be rejected due to insufficient accuracy or no solution could be obtained. For these cases, the parameters foF2 and hmF2 extracted from the corresponding IRO profiles have been found to be inconsistent with the classic mid-latitude daytime F2-layer formalism that the method relies on, and they are incompatible with the general trend provided by the IRI model. For solar maximum conditions (2002) the method was tested with IRO EDP from CHAMP and it is indicated that its performance is quite stable in the sense that a solution could be obtained for all the cases analyzed here. However available CHAMP EDP are confined by ~ 400 km in altitude and this might be the reason for the 20% bias of the retrieved densities toward larger values in respect to the observed densities. IRO observations up to 600 km under solar maximum are required to confirm the exact performance of the method.

Improvement of Forest Height Retrieval By Integration of Dual-Baseline PolInSAR Data And External DEM Data

NASA Astrophysics Data System (ADS)

Xie, Q.; Wang, C.; Zhu, J.; Fu, H.; Wang, C.

2015-06-01

In recent years, a lot of studies have shown that polarimetric synthetic aperture radar interferometry (PolInSAR) is a powerful technique for forest height mapping and monitoring. However, few researches address the problem of terrain slope effect, which will be one of the major limitations for forest height inversion in mountain forest area. In this paper, we present a novel forest height retrieval algorithm by integration of dual-baseline PolInSAR data and external DEM data. For the first time, we successfully expand the S-RVoG (Sloped-Random Volume over Ground) model for forest parameters inversion into the case of dual-baseline PolInSAR configuration. In this case, the proposed method not only corrects terrain slope variation effect efficiently, but also involves more observations to improve the accuracy of parameters inversion. In order to demonstrate the performance of the inversion algorithm, a set of quad-pol images acquired at the P-band in interferometric repeat-pass mode by the German Aerospace Center (DLR) with the Experimental SAR (E-SAR) system, in the frame of the BioSAR2008 campaign, has been used for the retrieval of forest height over Krycklan boreal forest in northern Sweden. At the same time, a high accuracy external DEM in the experimental area has been collected for computing terrain slope information, which subsequently is used as an inputting parameter in the S-RVoG model. Finally, in-situ ground truth heights in stand-level have been collected to validate the inversion result. The preliminary results show that the proposed inversion algorithm promises to provide much more accurate estimation of forest height than traditional dualbaseline inversion algorithms.

Evaluating Machine Learning Regression Algorithms for Operational Retrieval of Biophysical Parameters: Opportunities for Sentinel

NASA Astrophysics Data System (ADS)

Verrelst, Jochem; Rivera, J. P.; Alonso, L.; Guanter, L.; Moreno, J.

2012-04-01

ESA’s upcoming satellites Sentinel-2 (S2) and Sentinel-3 (S3) aim to ensure continuity for Landsat 5/7, SPOT- 5, SPOT-Vegetation and Envisat MERIS observations by providing superspectral images of high spatial and temporal resolution. S2 and S3 will deliver near real-time operational products with a high accuracy for land monitoring. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods. Machine learning regression algorithms could be powerful candidates for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. By using data from the ESA-led field campaign SPARC (Barrax, Spain), it was recently found [1] that Gaussian processes regression (GPR) outperformed competitive machine learning algorithms such as neural networks, support vector regression) and kernel ridge regression both in terms of accuracy and computational speed. For various Sentinel configurations (S2-10m, S2- 20m, S2-60m and S3-300m) three important biophysical parameters were estimated: leaf chlorophyll content (Chl), leaf area index (LAI) and fractional vegetation cover (FVC). GPR was the only method that reached the 10% precision required by end users in the estimation of Chl. In view of implementing the regressor into operational monitoring applications, here the portability of locally trained GPR models to other images was evaluated. The associated confidence maps proved to be a good indicator for evaluating the robustness of the trained models. Consistent retrievals were obtained across the different images, particularly over agricultural sites. To make the method suitable for operational use, however, the poorer confidences over bare soil areas suggest that the training dataset should be expanded with inputs from various land cover types.

Statistical Evaluation of VIIRS Ocean Color Products

NASA Astrophysics Data System (ADS)

Mikelsons, K.; Wang, M.; Jiang, L.

2016-02-01

Evaluation and validation of satellite-derived ocean color products is a complicated task, which often relies on precise in-situ measurements for satellite data quality assessment. However, in-situ measurements are only available in comparatively few locations, expensive, and not for all times. In the open ocean, the variability in spatial and temporal scales is longer, and the water conditions are generally more stable. We use this fact to perform extensive statistical evaluations of consistency for ocean color retrievals based on comparison of retrieved data at different times, and corresponding to various retrieval parameters. We have used the NOAA Multi-Sensor Level-1 to Level-2 (MSL12) ocean color data processing system for ocean color product data derived from the Visible Infrared Imaging Radiometer Suite (VIIRS). We show the results for statistical dependence of normalized water-leaving radiance spectra with respect to various parameters of retrieval geometry, such as solar- and sensor-zenith angles, as well as physical variables, such as wind speed, air pressure, ozone amount, water vapor, etc. In most cases, the results show consistent retrievals within the relevant range of retrieval parameters, showing a good performance with the MSL12 in the open ocean. The results also yield the upper bounds of solar- and sensor-zenith angles for reliable ocean color retrievals, and also show a slight increase of VIIRS-derived normalized water-leaving radiances with wind speed and water vapor concentration.

Assessment of Wildfire Risk in Southern California with Live Fuel Moisture Measurement and Remotely Sensed Vegetation Water Content Proxies

NASA Astrophysics Data System (ADS)

Jia, S.; Kim, S. H.; Nghiem, S. V.; Kafatos, M.

2017-12-01

Live fuel moisture (LFM) is the water content of live herbaceous plants expressed as a percentage of the oven-dry weight of plant. It is a critical parameter in fire ignition in Mediterranean climate and routinely measured in sites selected by fire agencies across the U.S. Vegetation growing cycle, meteorological metrics, soil type, and topography all contribute to the seasonal and inter-annual variation of LFM, and therefore, the risk of wildfire. The optical remote sensing-based vegetation indices (VIs) have been used to estimate the LFM. Comparing to the VIs, microwave remote sensing products have advantages like less saturation effect in greenness and representing the water content of the vegetation cover. In this study, we established three models to evaluate the predictability of LFM in Southern California using MODIS NDVI, vegetation temperature condition index (VTCI) from downscaled Soil Moisture Active Passive (SMAP) products, and vegetation optical depth (VOD) derived by Land Parameter Retrieval Model. Other ancillary variables, such as topographic factors (aspects and slope) and meteorological metrics (air temperature, precipitation, and relative humidity), are also considered in the models. The model results revealed an improvement of LFM estimation from SMAP products and VOD, despite the uncertainties introduced in the downscaling and parameter retrieval. The estimation of LFM using remote sensing data can provide an assessment of wildfire danger better than current methods using NDVI-based growing seasonal index. Future study will test the VOD estimation from SMAP data using the multi-temporal dual channel algorithm (MT-DCA) and extend the LFM modeling to a regional scale.

The performance of Yonsei CArbon Retrieval (YCAR) algorithm with improved aerosol information using GOSAT measurements over East Asia

NASA Astrophysics Data System (ADS)

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

2016-12-01

The Greenhouse Gases Observing SATellite (GOSAT) is the first satellite dedicated to measure atmospheric CO2 concentrations from space that can able to improve our knowledge about carbon cycle. Several studies have performed to develop the CO2 retrieval algorithms using GOSAT measurements, but limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. In this study, we develop the Yonsei CArbon Retrieval (YCAR) algorithm based on optimal estimation method to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) and the aerosol top height used to cause significant errors in retrieved XCO2 up to 2.5 ppm. Since this bias comes from a rough assumption of aerosol information in the forward model used in CO2 retrieval process, the YCAR algorithm improves the process to take into account AOPs as well as aerosol vertical distribution; total AOD and the fine mode fraction (FMF) are obtained from the ground-based measurements closely located, and other parameters are obtained from a priori information. Comparing to ground-based XCO2 measurements, the YCAR XCO2 product has a bias of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, showing lower biases and higher correlations rather than the GOSAT standard products. 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.

Constraining Methane Abundance and Cloud Properties from the Reflected Light Spectra of Directly Imaged Exoplanets

NASA Astrophysics Data System (ADS)

Lupu, R.; Marley, M. S.; Lewis, N. K.

2015-12-01

We have assembled an atmospheric retrieval package for the reflected light spectra of gas- and ice- giants in order to inform the design and estimate the scientific return of future space-based coronagraph instruments. Such instruments will have a working bandpass of ~0.4-1 μm and a resolving power R~70, and will enable the characterization of tens of exoplanets in the Solar neighborhood. The targets will be chosen form known RV giants, with estimated effective temperatures of ~100-600 K and masses between 0.3 and 20 MJupiter. In this regime, both methane and clouds will have the largest effects on the observed spectra. Our retrieval code is the first to include cloud properties in the core set of parameters, along with methane abundance and surface gravity. We consider three possible cloud structure scenarios, with 0, 1 or 2 cloud layers, respectively. The best-fit parameters for a given model are determined using a Monte Carlo Markov Chain ensemble sampler, and the most favored cloud structure is chosen by calculating the Bayes factors between different models. We present the performance of our retrieval technique applied to a set of representative model spectra, covering a SNR range form 5 to 20 and including possible noise correlations over a 25 or 100 nanometer scale. Further, we apply the technique to more realistic cases, namely simulated observations of Jupiter, Saturn, Uranus, and the gas-giant HD99492c. In each case, we determine the confidence levels associated with the methane and cloud detections, as a function of SNR and noise properties.

Scaling Up High-Value Retrieval to Medium-Volume Data

NASA Astrophysics Data System (ADS)

Cunningham, Hamish; Hanbury, Allan; Rüger, Stefan

We summarise the scientific work presented at the first Information Retrieval Facility Conference [3] and argue that high-value retrieval with medium-volume data, exemplified by patent search, is a thriving topic in a multidisciplinary area that sits between Information Retrieval, Natural Language Processing and Semantic Web Technologies. We analyse the parameters that condition choices of retrieval technology for different sizes and values of document space, and we present the patent document space and some of its characteristics for retrieval work.

Capturing Revolute Motion and Revolute Joint Parameters with Optical Tracking

NASA Astrophysics Data System (ADS)

Antonya, C.

2017-12-01

Optical tracking of users and various technical systems are becoming more and more popular. It consists of analysing sequence of recorded images using video capturing devices and image processing algorithms. The returned data contains mainly point-clouds, coordinates of markers or coordinates of point of interest. These data can be used for retrieving information related to the geometry of the objects, but also to extract parameters for the analytical model of the system useful in a variety of computer aided engineering simulations. The parameter identification of joints deals with extraction of physical parameters (mainly geometric parameters) for the purpose of constructing accurate kinematic and dynamic models. The input data are the time-series of the marker’s position. The least square method was used for fitting the data into different geometrical shapes (ellipse, circle, plane) and for obtaining the position and orientation of revolute joins.

Neural Network-Based Retrieval of Surface and Root Zone Soil Moisture using Multi-Frequency Remotely-Sensed Observations

NASA Astrophysics Data System (ADS)

Hamed Alemohammad, Seyed; Kolassa, Jana; Prigent, Catherine; Aires, Filipe; Gentine, Pierre

2017-04-01

Knowledge of root zone soil moisture is essential in studying plant's response to different stress conditions since plant photosynthetic activity and transpiration rate are constrained by the water available through their roots. Current global root zone soil moisture estimates are based on either outputs from physical models constrained by observations, or assimilation of remotely-sensed microwave-based surface soil moisture estimates with physical model outputs. However, quality of these estimates are limited by the accuracy of the model representations of physical processes (such as radiative transfer, infiltration, percolation, and evapotranspiration) as well as errors in the estimates of the surface parameters. Additionally, statistical approaches provide an alternative efficient platform to develop root zone soil moisture retrieval algorithms from remotely-sensed observations. In this study, we present a new neural network based retrieval algorithm to estimate surface and root zone soil moisture from passive microwave observations of SMAP satellite (L-band) and AMSR2 instrument (X-band). SMAP early morning observations are ideal for surface soil moisture retrieval. AMSR2 mid-night observations are used here as an indicator of plant hydraulic properties that are related to root zone soil moisture. The combined observations from SMAP and AMSR2 together with other ancillary observations including the Solar-Induced Fluorescence (SIF) estimates from GOME-2 instrument provide necessary information to estimate surface and root zone soil moisture. The algorithm is applied to observations from the first 18 months of SMAP mission and retrievals are validated against in-situ observations and other global datasets.

AN INFORMATION-THEORETIC APPROACH TO OPTIMIZE JWST OBSERVATIONS AND RETRIEVALS OF TRANSITING EXOPLANET ATMOSPHERES

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

Howe, Alex R.; Burrows, Adam; Deming, Drake, E-mail: arhowe@umich.edu, E-mail: burrows@astro.princeton.edu, E-mail: ddeming@astro.umd.edu

We provide an example of an analysis to explore the optimization of observations of transiting hot Jupiters with the James Webb Space Telescope ( JWST ) to characterize their atmospheres based on a simple three-parameter forward model. We construct expansive forward model sets for 11 hot Jupiters, 10 of which are relatively well characterized, exploring a range of parameters such as equilibrium temperature and metallicity, as well as considering host stars over a wide range in brightness. We compute posterior distributions of our model parameters for each planet with all of the available JWST spectroscopic modes and several programs ofmore » combined observations and compute their effectiveness using the metric of estimated mutual information per degree of freedom. From these simulations, clear trends emerge that provide guidelines for designing a JWST observing program. We demonstrate that these guidelines apply over a wide range of planet parameters and target brightnesses for our simple forward model.« less

Comparison of SMOS and SMAP Soil Moisture Retrieval Approaches Using Tower-based Radiometer Data over a Vineyard Field

NASA Technical Reports Server (NTRS)

Miernecki, Maciej; Wigneron, Jean-Pierre; Lopez-Baeza, Ernesto; Kerr, Yann; DeJeu, Richard; DeLannoy, Gabielle J. M.; Jackson, Tom J.; O'Neill, Peggy E.; Shwank, Mike; Moran, Roberto Fernandez;

Optimized model tuning in medical systems.

PubMed

Kléma, Jirí; Kubalík, Jirí; Lhotská, Lenka

2005-12-01

In medical systems it is often advantageous to utilize specific problem situations (cases) in addition to or instead of a general model. Decisions are then based on relevant past cases retrieved from a case memory. The reliability of such decisions depends directly on the ability to identify cases of practical relevance to the current situation. This paper discusses issues of automated tuning in order to obtain a proper definition of mutual case similarity in a specific medical domain. The main focus is on a reasonably time-consuming optimization of the parameters that determine case retrieval and further utilization in decision making/ prediction. The two case studies - mortality prediction after cardiological intervention, and resource allocation at a spa - document that the optimization process is influenced by various characteristics of the problem domain.

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.

Global retrieval of soil moisture and vegetation properties using data-driven methods

NASA Astrophysics Data System (ADS)

Rodriguez-Fernandez, Nemesio; Richaume, Philippe; Kerr, Yann

2017-04-01

Data-driven methods such as neural networks (NNs) are a powerful tool to retrieve soil moisture from multi-wavelength remote sensing observations at global scale. In this presentation we will review a number of recent results regarding the retrieval of soil moisture with the Soil Moisture and Ocean Salinity (SMOS) satellite, either using SMOS brightness temperatures as input data for the retrieval or using SMOS soil moisture retrievals as reference dataset for the training. The presentation will discuss several possibilities for both the input datasets and the datasets to be used as reference for the supervised learning phase. Regarding the input datasets, it will be shown that NNs take advantage of the synergy of SMOS data and data from other sensors such as the Advanced Scatterometer (ASCAT, active microwaves) and MODIS (visible and infra red). NNs have also been successfully used to construct long time series of soil moisture from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and SMOS. A NN with input data from ASMR-E observations and SMOS soil moisture as reference for the training was used to construct a dataset sharing a similar climatology and without a significant bias with respect to SMOS soil moisture. Regarding the reference data to train the data-driven retrievals, we will show different possibilities depending on the application. Using actual in situ measurements is challenging at global scale due to the scarce distribution of sensors. In contrast, in situ measurements have been successfully used to retrieve SM at continental scale in North America, where the density of in situ measurement stations is high. Using global land surface models to train the NN constitute an interesting alternative to implement new remote sensing surface datasets. In addition, these datasets can be used to perform data assimilation into the model used as reference for the training. This approach has recently been tested at the European Centre for Medium-Range Weather Forecasts (ECMWF). Finally, retrievals using radiative transfer models can also be used as a reference SM dataset for the training phase. This approach was used to retrieve soil moisture from ASMR-E, as mentioned above, and also to implement the official European Space Agency (ESA) SMOS soil moisture product in Near-Real-Time. We will finish with a discussion of the retrieval of vegetation parameters from SMOS observations using data-driven methods.

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.

The Belgian repository of fundamental atomic data and stellar spectra (BRASS). I. Cross-matching atomic databases of astrophysical interest

NASA Astrophysics Data System (ADS)

Laverick, M.; Lobel, A.; Merle, T.; Royer, P.; Martayan, C.; David, M.; Hensberge, H.; Thienpont, E.

2018-04-01

Context. Fundamental atomic parameters, such as oscillator strengths, play a key role in modelling and understanding the chemical composition of stars in the Universe. Despite the significant work underway to produce these parameters for many astrophysically important ions, uncertainties in these parameters remain large and can propagate throughout the entire field of astronomy. Aims: The Belgian repository of fundamental atomic data and stellar spectra (BRASS) aims to provide the largest systematic and homogeneous quality assessment of atomic data to date in terms of wavelength, atomic and stellar parameter coverage. To prepare for it, we first compiled multiple literature occurrences of many individual atomic transitions, from several atomic databases of astrophysical interest, and assessed their agreement. In a second step synthetic spectra will be compared against extremely high-quality observed spectra, for a large number of BAFGK spectral type stars, in order to critically evaluate the atomic data of a large number of important stellar lines. Methods: Several atomic repositories were searched and their data retrieved and formatted in a consistent manner. Data entries from all repositories were cross-matched against our initial BRASS atomic line list to find multiple occurrences of the same transition. Where possible we used a new non-parametric cross-match depending only on electronic configurations and total angular momentum values. We also checked for duplicate entries of the same physical transition, within each retrieved repository, using the non-parametric cross-match. Results: We report on the number of cross-matched transitions for each repository and compare their fundamental atomic parameters. We find differences in log(gf) values of up to 2 dex or more. We also find and report that 2% of our line list and Vienna atomic line database retrievals are composed of duplicate transitions. Finally we provide a number of examples of atomic spectral lines with different retrieved literature log(gf) values, and discuss the impact of these uncertain log(gf) values on quantitative spectroscopy. All cross-matched atomic data and duplicate transition pairs are available to download at http://brass.sdf.org

Synergistic Utilization of Microwave Satellite Data and GRACE-Total Water Storage Anomaly for Improving Available Water Capacity Prediction in Lower Mekong Basin

NASA Astrophysics Data System (ADS)

Gupta, M.; Bolten, J. D.; Lakshmi, V.

2015-12-01

The Mekong River is the longest river in Southeast Asia and the world's eighth largest in discharge with draining an area of 795,000 km² from the eastern watershed of the Tibetan Plateau to the Mekong Delta including three provinces of China, Myanmar, Lao PDR, Thailand, Cambodia and Viet Nam. This makes the life of people highly vulnerable to availability of the water resources as soil moisture is one of the major fundamental variables in global hydrological cycles. The day-to-day variability in soil moisture on field to global scales is an important quantity for early warning systems for events like flooding and drought. In addition to the extreme situations the accurate soil moisture retrieval are important for agricultural irrigation scheduling and water resource management. The present study proposes a method to determine the effective soil hydraulic parameters directly from information available for the soil moisture state from the recently launched SMAP (L-band) microwave remote sensing observations. Since the optimized parameters are based on the near surface soil moisture information, further constraints are applied during the numerical simulation through the assimilation of GRACE Total Water Storage (TWS) within the physically based land surface model. This work addresses the improvement of available water capacity as the soil hydraulic parameters are optimized through the utilization of satellite-retrieved near surface soil moisture. The initial ranges of soil hydraulic parameters are taken in correspondence with the values available from the literature based on FAO. The optimization process is divided into two steps: the state variable are optimized and the optimal parameter values are then transferred for retrieving soil moisture and streamflow. A homogeneous soil system is considered as the soil moisture from sensors such as AMSR-E/SMAP can only be retrieved for the top few centimeters of soil. To evaluate the performance of the system in helping improve simulation accuracy and whether they can be used to obtain soil moisture profiles at poorly gauged catchments the root mean square error (RMSE) and Mean Bias error (MBE) are used to measure the performance of the simulations.

Application of Artificial Neural Networks to the Development of Improved Multi-Sensor Retrievals of Near-Surface Air Temperature and Humidity Over Ocean

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Clayson, Carol Anne

2012-01-01

Improved estimates of near-surface air temperature and air humidity are critical to the development of more accurate turbulent surface heat fluxes over the ocean. Recent progress in retrieving these parameters has been made through the application of artificial neural networks (ANN) and the use of multi-sensor passive microwave observations. Details are provided on the development of an improved retrieval algorithm that applies the nonlinear statistical ANN methodology to a set of observations from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A) that are currently available from the NASA AQUA satellite platform. Statistical inversion techniques require an adequate training dataset to properly capture embedded physical relationships. The development of multiple training datasets containing only in-situ observations, only synthetic observations produced using the Community Radiative Transfer Model (CRTM), or a mixture of each is discussed. An intercomparison of results using each training dataset is provided to highlight the relative advantages and disadvantages of each methodology. Particular emphasis will be placed on the development of retrievals in cloudy versus clear-sky conditions. Near-surface air temperature and humidity retrievals using the multi-sensor ANN algorithms are compared to previous linear and non-linear retrieval schemes.

Geocoronal Balmer α line profile observations and forward-model analysis

NASA Astrophysics Data System (ADS)

Mierkiewicz, E. J.; Bishop, J.; Roesler, F. L.; Nossal, S. M.

2006-05-01

High spectral resolution geocoronal Balmer α line profile observations from Pine Bluff Observatory (PBO) are presented in the context of forward-model analysis. Because Balmer series column emissions depend significantly on multiple scattering, retrieval of hydrogen parameters of general aeronomic interest from these observations (e.g., the hydrogen column abundance) currently requires a forward modeling approach. This capability is provided by the resonance radiative transfer code LYAO_RT. We have recently developed a parametric data-model comparison search procedure employing an extensive grid of radiative transport model input parameters (defining a 6-dimensional parameter space) to map-out bounds for feasible forward model retrieved atomic hydrogen density distributions. We applied this technique to same-night (March, 2000) ground-based Balmer α data from PBO and geocoronal Lyman β measurements from the Espectrógrafo Ultravioleta extremo para la Radiación Difusa (EURD) instrument on the Spanish satellite MINISAT-1 (provided by J.F. Gómez and C. Morales of the Laboratorio de Astrofisica Espacial y Física Fundamental, INTA, Madrid, Spain) in order to investigate the modeling constraints imposed by two sets of independent geocoronal intensity measurements, both of which rely on astronomical calibration methods. In this poster we explore extending this analysis to the line profile information also contained in the March 2000 PBO Balmer α data set. In general, a decrease in the Doppler width of the Balmer α emission with shadow altitude is a persistent feature in every night of PBO observations in which a wide range of shadow altitudes are observed. Preliminary applications of the LYAO_RT code, which includes the ability to output Doppler line profiles for both the singly and multiply scattered contributions to the Balmer α emission line, displays good qualitative agreement with regard to geocoronal Doppler width trends observed from PBO. Model-data Balmer α Doppler width comparisons, using the best-fit model parameters obtained during the March 2000 PBO/EURD forward-model study, will be presented and discussed, including the feasibility of using Balmer α observed Doppler widths as an additional model constraint in our forward-model search procedure.

A Parameterized Inversion Model for Soil Moisture and Biomass from Polarimetric Backscattering Coefficients

NASA Technical Reports Server (NTRS)

Truong-Loi, My-Linh; Saatchi, Sassan; Jaruwatanadilok, Sermsak

2012-01-01

A semi-empirical algorithm for the retrieval of soil moisture, root mean square (RMS) height and biomass from polarimetric SAR data is explained and analyzed in this paper. The algorithm is a simplification of the distorted Born model. It takes into account the physical scattering phenomenon and has three major components: volume, double-bounce and surface. This simplified model uses the three backscattering coefficients ( sigma HH, sigma HV and sigma vv) at low-frequency (P-band). The inversion process uses the Levenberg-Marquardt non-linear least-squares method to estimate the structural parameters. The estimation process is entirely explained in this paper, from initialization of the unknowns to retrievals. A sensitivity analysis is also done where the initial values in the inversion process are varying randomly. The results show that the inversion process is not really sensitive to initial values and a major part of the retrievals has a root-mean-square error lower than 5% for soil moisture, 24 Mg/ha for biomass and 0.49 cm for roughness, considering a soil moisture of 40%, roughness equal to 3cm and biomass varying from 0 to 500 Mg/ha with a mean of 161 Mg/ha

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

Partitioning CloudSat Ice Water Content for Comparison with Upper-Tropospheric Ice in Global Atmospheric Models

NASA Astrophysics Data System (ADS)

Chen, W. A.; Woods, C. P.; Li, J. F.; Waliser, D. E.; Chern, J.; Tao, W.; Jiang, J. H.; Tompkins, A. M.

2010-12-01

CloudSat provides important estimates of vertically resolved ice water content (IWC) on a global scale based on radar reflectivity. These estimates of IWC have proven beneficial in evaluating the representations of ice clouds in global models. An issue when performing model-data comparisons of IWC particularly germane to this investigation, is the question of which component(s) of the frozen water mass are represented by retrieval estimates and how they relate to what is represented in models. The present study developed and applied a new technique to partition CloudSat total IWC into small and large ice hydrometeors, based on the CloudSat-retrieved ice particle size distribution (PSD) parameters. The new method allows one to make relevant model-data comparisons and provides new insights into the model’s representation of atmospheric IWC. The partitioned CloudSat IWC suggests that the small ice particles contribute to 20-30% of the total IWC in the upper troposphere when a threshold size of 100 μm is used. Sensitivity measures with respect to the threshold size, the PSD parameters, and the retrieval algorithms are presented. The new dataset is compared to model estimates, pointing to areas for model improvement. Cloud ice analyses from the European Centre for Medium-Range Weather Forecasts model agree well with the small IWC from CloudSat. The finite-volume multi-scale modeling framework model underestimates total IWC at 147 and 215 hPa, while overestimating the fractional contribution from the small ice species. These results are discussed in terms of their applications to, and implications for, the evaluation of global atmospheric models, providing constraints on the representations of cloud feedback and precipitation in global models, which in turn can help reduce uncertainties associated with climate change projections. Figure 1. A sample lognormal ice number distribution (red curve), and the corresponding mass distribution (black curve). The dotted line represents the cutoff size for IWC partitioning (Dc = 100 µm as an example). The partial integrals of the mass distribution for particles smaller and larger than Dc correspond to IWC<100 (green area) and IWC>100 (blue area), respectively.

Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) PARM tape user's guide

NASA Technical Reports Server (NTRS)

Han, D.; Gloersen, P.; Kim, S. T.; Fu, C. C.; Cebula, R. P.; Macmillan, D.

1992-01-01

The Scanning Multichannel Microwave Radiometer (SMMR) instrument, onboard the Nimbus-7 spacecraft, collected data from Oct. 1978 until Jun. 1986. The data were processed to physical parameter level products. Geophysical parameters retrieved include the following: sea-surface temperatures, sea-surface windspeed, total column water vapor, and sea-ice parameters. These products are stored on PARM-LO, PARM-SS, and PARM-30 tapes. The geophysical parameter retrieval algorithms and the quality of these products are described for the period between Nov. 1978 and Oct 1985. Additionally, data formats and data availability are included.

Using the Change Manager Model for the Hippocampal System to Predict Connectivity and Neurophysiological Parameters in the Perirhinal Cortex

PubMed Central

Coward, L. Andrew; Gedeon, Tamas D.

2016-01-01

Theoretical arguments demonstrate that practical considerations, including the needs to limit physiological resources and to learn without interference with prior learning, severely constrain the anatomical architecture of the brain. These arguments identify the hippocampal system as the change manager for the cortex, with the role of selecting the most appropriate locations for cortical receptive field changes at each point in time and driving those changes. This role results in the hippocampal system recording the identities of groups of cortical receptive fields that changed at the same time. These types of records can also be used to reactivate the receptive fields active during individual unique past events, providing mechanisms for episodic memory retrieval. Our theoretical arguments identify the perirhinal cortex as one important focal point both for driving changes and for recording and retrieving episodic memories. The retrieval of episodic memories must not drive unnecessary receptive field changes, and this consideration places strong constraints on neuron properties and connectivity within and between the perirhinal cortex and regular cortex. Hence the model predicts a number of such properties and connectivity. Experimental test of these falsifiable predictions would clarify how change is managed in the cortex and how episodic memories are retrieved. PMID:26819594

Non-LTE diagnositics of infrared radiation of Titan's atmosphere

NASA Astrophysics Data System (ADS)

Feofilov, Artem; Rezac, Ladislav; Kutepov, Alexander; Vinatier, Sandrine; Rey, Michael; Nikitin, Andrew; Tyuterev, Vladimir

2016-06-01

Yelle (1991) and Garcia-Comas et al, (2011) demonstrated the importance of accounting for the local thermodynamic equilibrium (LTE) breakdown in the middle and upper atmosphere of Titan for the interpretation of infrared radiances measured at these heights. In this work, we make further advance in this field by: • updating the non-LTE model of CH4 emissions in Titan's atmosphere and including a new extended database of CH4 spectroscopic parameters • studying the non-LTE CH4 vibrational level populations and the impact of non-LTE on limb infrared emissions of various CH4 ro-vibrational bands including those at 7.6 and 3.3 µm • implementing our non-LTE model into the LTE-based retrieval algorithm applied by Vinatier et al., (2015) for processing the Cassini/CIRS spectra. We demonstrate that accounting for non-LTE leads to an increase in temperatures retrieved from CIRS 7.6 µm limb emissions spectra (˜10 K at 600 km altitude) and estimate how this affects the trace gas density retrieval. Finally, we discuss the effects of including a large number of weak one-quantum and combinational bands on the calculated daytime limb 3.3 µm emissions and the impact they may have on the CH4 density retrievals from the Cassini VIMS 3.3 µm limb emission observations.

Estimation for sparse vegetation information in desertification region based on Tiangong-1 hyperspectral image.

PubMed

Wu, Jun-Jun; Gao, Zhi-Hai; Li, Zeng-Yuan; Wang, Hong-Yan; Pang, Yong; Sun, Bin; Li, Chang-Long; Li, Xu-Zhi; Zhang, Jiu-Xing

2014-03-01

In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.

Calculations of Aerosol Radiative Forcing in the SAFARI Region from MODIS Data

NASA Technical Reports Server (NTRS)

Remer, L. A.; Ichoku, C.; Kaufman, Y. J.; Chu, D. A.

2003-01-01

SAFARI 2000 provided the opportunity to validate MODIS aerosol retrievals and to correct any assumptions in the retrieval process. By comparing MODIS retrievals with ground-based sunphotometer data, we quantified the degree to which the MODIS algorithm underestimated the aerosol optical thickness. This discrepancy was attributed to underestimating the degree of light absorption by the southern African smoke aerosol. Correcting for this underestimation of absorption, produces more realistic aerosol retrievals that allow various applications of the MODIS aerosol products. One such application is the calculation of the aerosol radiative forcing at the top and bottom of the atmosphere. The combination of MODIS accuracy, coverage, resolution and the ability to separate fine and coarse mode make this calculation substantially advanced over previous attempts with other satellites. We focus on the oceans adjacent to southern Africa and use a solar radiative transfer model to perform the flux calculations. The forcing at the top of atmosphere is calculated to be 10 W/sq m, while the forcing at the surface is -26 W/sq m. These results resemble those calculated from INDOEX data, and are most sensitive to assumptions of aerosol absorption, the same parameter that initially interfered with our retrievals.

Impact of Lidar Wind Sounding on Mesoscale Forecast

NASA Technical Reports Server (NTRS)

Miller, Timothy L.; Chou, Shih-Hung; Goodman, H. Michael (Technical Monitor)

2001-01-01

An Observing System Simulation Experiment (OSSE) was conducted to study the impact of airborne lidar wind sounding on mesoscale weather forecast. A wind retrieval scheme, which interpolates wind data from a grid data system, simulates the retrieval of wind profile from a satellite lidar system. A mesoscale forecast system based on the PSU/NCAR MM5 model is developed and incorporated the assimilation of the retrieved line-of-sight wind. To avoid the "identical twin" problem, the NCEP reanalysis data is used as our reference "nature" atmosphere. The simulated space-based lidar wind observations were retrieved by interpolating the NCEP values to the observation locations. A modified dataset obtained by smoothing the NCEP dataset was used as the initial state whose forecast was sought to be improved by assimilating the retrieved lidar observations. Forecasts using wind profiles with various lidar instrument parameters has been conducted. The results show that to significantly improve the mesoscale forecast the satellite should fly near the storm center with large scanning radius. Increasing lidar firing rate also improves the forecast. Cloud cover and lack of aerosol degrade the quality of the lidar wind data and, subsequently, the forecast.

Do detailed simulations with size-resolved microphysics reproduce basic features of observed cirrus ice size distributions?

NASA Astrophysics Data System (ADS)

Fridlind, A. M.; Atlas, R.; van Diedenhoven, B.; Ackerman, A. S.; Rind, D. H.; Harrington, J. Y.; McFarquhar, G. M.; Um, J.; Jackson, R.; Lawson, P.

2017-12-01

It has recently been suggested that seeding synoptic cirrus could have desirable characteristics as a geoengineering approach, but surprisingly large uncertainties remain in the fundamental parameters that govern cirrus properties, such as mass accommodation coefficient, ice crystal physical properties, aggregation efficiency, and ice nucleation rate from typical upper tropospheric aerosol. Only one synoptic cirrus model intercomparison study has been published to date, and studies that compare the shapes of observed and simulated ice size distributions remain sparse. Here we amend a recent model intercomparison setup using observations during two 2010 SPARTICUS campaign flights. We take a quasi-Lagrangian column approach and introduce an ensemble of gravity wave scenarios derived from collocated Doppler cloud radar retrievals of vertical wind speed. We use ice crystal properties derived from in situ cloud particle images, for the first time allowing smoothly varying and internally consistent treatments of nonspherical ice capacitance, fall speed, gravitational collection, and optical properties over all particle sizes in our model. We test two new parameterizations for mass accommodation coefficient as a function of size, temperature and water vapor supersaturation, and several ice nucleation scenarios. Comparison of results with in situ ice particle size distribution data, corrected using state-of-the-art algorithms to remove shattering artifacts, indicate that poorly constrained uncertainties in the number concentration of crystals smaller than 100 µm in maximum dimension still prohibit distinguishing which parameter combinations are more realistic. When projected area is concentrated at such sizes, the only parameter combination that reproduces observed size distribution properties uses a fixed mass accommodation coefficient of 0.01, on the low end of recently reported values. No simulations reproduce the observed abundance of such small crystals when the projected area is concentrated at larger sizes. Simulations across the parameter space are also compared with MODIS collection 6 retrievals and forward simulations of cloud radar reflectivity and mean Doppler velocity. Results motivate further in situ and laboratory measurements to narrow parameter uncertainties in models.

Global Clear-Sky Surface Skin Temperature from Multiple Satellites Using a Single-Channel Algorithm with Angular Anisotropy Corrections

NASA Technical Reports Server (NTRS)

Scarino, Benjamin R.; Minnis, Patrick; Chee, Thad; Bedka, Kristopher M.; Yost, Christopher R.; Palikonda, Rabindra

2017-01-01

Surface skin temperature (T(sub s)) is an important parameter for characterizing the energy exchange at the ground/water-atmosphere interface. The Satellite ClOud and Radiation Property retrieval System (SatCORPS) employs a single-channel thermal-infrared (TIR) method to retrieve T(sub s) over clear-sky land and ocean surfaces from data taken by geostationary Earth orbit (GEO) and low Earth orbit (LEO) satellite imagers. GEO satellites can provide somewhat continuous estimates of T(sub s) over the diurnal cycle in non-polar regions, while polar T(sub s) retrievals from LEO imagers, such as the Advanced Very High Resolution Radiometer (AVHRR), can complement the GEO measurements. The combined global coverage of remotely sensed T(sub s), along with accompanying cloud and surface radiation parameters, produced in near-realtime and from historical satellite data, should be beneficial for both weather and climate applications. For example, near-realtime hourly T(sub s) observations can be assimilated in high-temporal-resolution numerical weather prediction models and historical observations can be used for validation or assimilation of climate models. Key drawbacks to the utility of TIR-derived T(sub s) data include the limitation to clear-sky conditions, the reliance on a particular set of analyses/reanalyses necessary for atmospheric corrections, and the dependence on viewing and illumination angles. Therefore, T(sub s) validation with established references is essential, as is proper evaluation of T(sub s) sensitivity to atmospheric correction source. This article presents improvements on the NASA Langley GEO satellite and AVHRR TIR-based T(sub s) product that is derived using a single-channel technique. The resulting clear-sky skin temperature values are validated with surface references and independent satellite products. Furthermore, an empirically adjusted theoretical model of satellite land surface temperature (LST) angular anisotropy is tested to improve satellite LST retrievals. Application of the anisotropic correction yields reduced mean bias and improved precision of GOES-13 LST relative to independent Moderate-resolution Imaging Spectroradiometer (MYD11_L2) LST and Atmospheric Radiation Measurement Program ground station measurements. It also significantly reduces inter-satellite differences between LSTs retrieved simultaneously from two different imagers. The implementation of these universal corrections into the SatCORPS product can yield significant improvement in near-global-scale, near-realtime, satellite-based LST measurements. The immediate availability and broad coverage of these skin temperature observations should prove valuable to modelers and climate researchers looking for improved forecasts and better understanding of the global climate model.

Information Retrieval: A Sequential Learning Process.

ERIC Educational Resources Information Center

Bookstein, Abraham

1983-01-01

Presents decision-theoretic models which intrinsically include retrieval of multiple documents whereby system responds to request by presenting documents to patron in sequence, gathering feedback, and using information to modify future retrievals. Document independence model, set retrieval model, sequential retrieval model, learning model,…

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.

Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

NASA Technical Reports Server (NTRS)

Hun, Eunjin; Crow, Wade T.; Holmes, Thomas; Bolten, John

2014-01-01

Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputoutput structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross-correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moistureNDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities andor complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system.

LibKiSAO: a Java library for Querying KiSAO.

PubMed

Zhukova, Anna; Adams, Richard; Laibe, Camille; Le Novère, Nicolas

2012-09-24

The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of Systems Biology models, their characteristics, parameters and inter-relationships. KiSAO enables the unambiguous identification of algorithms from simulation descriptions. Information about analogous methods having similar characteristics and about algorithm parameters incorporated into KiSAO is desirable for simulation tools. To retrieve this information programmatically an application programming interface (API) for KiSAO is needed. We developed libKiSAO, a Java library to enable querying of the KiSA Ontology. It implements methods to retrieve information about simulation algorithms stored in KiSAO, their characteristics and parameters, and methods to query the algorithm hierarchy and search for similar algorithms providing comparable results for the same simulation set-up. Using libKiSAO, simulation tools can make logical inferences based on this knowledge and choose the most appropriate algorithm to perform a simulation. LibKiSAO also enables simulation tools to handle a wider range of simulation descriptions by determining which of the available methods are similar and can be used instead of the one indicated in the simulation description if that one is not implemented. LibKiSAO enables Java applications to easily access information about simulation algorithms, their characteristics and parameters stored in the OWL-encoded Kinetic Simulation Algorithm Ontology. LibKiSAO can be used by simulation description editors and simulation tools to improve reproducibility of computational simulation tasks and facilitate model re-use.

Adjusted Levenberg-Marquardt method application to methene retrieval from IASI/METOP spectra

NASA Astrophysics Data System (ADS)

Khamatnurova, Marina; Gribanov, Konstantin

2016-04-01

Levenberg-Marquardt method [1] with iteratively adjusted parameter and simultaneous evaluation of averaging kernels together with technique of parameters selection are developed and applied to the retrieval of methane vertical profiles in the atmosphere from IASI/METOP spectra. Retrieved methane vertical profiles are then used for calculation of total atmospheric column amount. NCEP/NCAR reanalysis data provided by ESRL (NOAA, Boulder,USA) [2] are taken as initial guess for retrieval algorithm. Surface temperature, temperature and humidity vertical profiles are retrieved before methane vertical profile retrieval for each selected spectrum. Modified software package FIRE-ARMS [3] were used for numerical experiments. To adjust parameters and validate the method we used ECMWF MACC reanalysis data [4]. Methane columnar values retrieved from cloudless IASI spectra demonstrate good agreement with MACC columnar values. Comparison is performed for IASI spectra measured in May of 2012 over Western Siberia. Application of the method for current IASI/METOP measurements are discussed. 1.Ma C., Jiang L. Some Research on Levenberg-Marquardt Method for the Nonlinear Equations // Applied Mathematics and Computation. 2007. V.184. P. 1032-1040 2.http://www.esrl.noaa.gov/psdhttp://www.esrl.noaa.gov/psd 3.Gribanov K.G., Zakharov V.I., Tashkun S.A., Tyuterev Vl.G.. A New Software Tool for Radiative Transfer Calculations and its application to IMG/ADEOS data // JQSRT.2001.V.68.№ 4. P. 435-451. 4.http://www.ecmwf.int/http://www.ecmwf.int

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.

Advances in remote sensing of forest background reflectance with MODIS BRDF data across Europe

NASA Astrophysics Data System (ADS)

Pisek, Jan; Alikas, Krista; Lukeš, Petr; Lundin, Lars; Kobler, Johannes; Santos-Reis, Margarida; Chen, Jing

2017-04-01

Spatial and temporal patterns of forest background (understory) reflectance are crucial for retrieving biophysical parameters of forest canopies (overstory) and subsequently for ecosystem modeling. However, systematic reflectance data covering different site types are almost missing. This presentation will focus on the validation of background reflectance retrievals using MODIS bidirectional reflectance distribution function (BRDF) data against in-situ understory reflectance measurements covering a diverse set of long-term ecological research (LTER) sites distributed along a wide latitudinal and elevational gradient across Europe: protected coniferous blueberry forest in Sweden, karst forest system in Austria, floodplain broadleaf forest and coniferous forest in the Czech Republic, and Mediterranean agro-sylvo-pastoral woodlands in Portugal. The multi-angle remote sensing data-based methodology was originally developed for the forest background signal retrieval in a boreal region. Here its performance will be tested across diverse forest conditions and moments during the growing season, which is a necessary step before conducting extensive mapping over forested areas. The results can be also used as an input for improved modeling of local carbon and energy fluxes.

A better understanding of POLDER's cloud droplet size retrieval: impact of cloud horizontal inhomogeneity and directional sampling

NASA Astrophysics Data System (ADS)

Shang, H.; Chen, L.; Bréon, F.-M.; Letu, H.; Li, S.; Wang, Z.; Su, L.

2015-07-01

The principles of the Polarization and Directionality of the Earth's Reflectance (POLDER) cloud droplet size retrieval requires that clouds are horizontally homogeneous. Nevertheless, the retrieval is applied by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using the POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval, and then analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-scale variability in droplet effective radius (CDR) can mislead both the CDR and effective variance (EV) retrievals. Nevertheless, the sub-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval is accurate using limited observations and is largely independent of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, the measurements in the primary rainbow region (137-145°) are used to ensure accurate large droplet (> 15 μm) retrievals and reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data for June 2008, the new CDR results are compared with the operational CDRs. The comparison show that the operational CDRs tend to be underestimated for large droplets. The reason is that the cloudbow oscillations in the scattering angle region of 145-165° are weak for cloud fields with CDR > 15 μm. Lastly, a sub-scale retrieval case is analyzed, illustrating that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size parameters from POLDER measurements.

Variability in Surface BRDF at Different Spatial Scales (30m-500m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhuosen; King, Michael D.

2012-01-01

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Variability in Surface BRDF at Different Spatial Scales (30 m-500 m) Over a Mixed Agricultural Landscape as Retrieved from Airborne and Satellite Spectral Measurements

NASA Technical Reports Server (NTRS)

Roman, Miguel O.; Gatebe, Charles K.; Schaaf, Crystal B.; Poudyal, Rajesh; Wang, Zhousen; King, Michael D.

2011-01-01

Over the past decade, the role of multiangle remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75 off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertain ties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Observational Tests of the Surface Reflectance Boundary Condition for Aerosol Retrievals using Multiangle Spectropolarimetric Imagery

NASA Astrophysics Data System (ADS)

Diner, D. J.; Martonchik, J. V.; Sanghavi, S.; Xu, F.; Garay, M. J.; Bradley, C.; Chipman, R.; McClain, S.

2011-12-01

Passive retrievals of aerosol properties from aircraft or satellite must account for surface reflection at the lower boundary. Future missions such as Aerosol-Cloud-Ecosystem (ACE) will use multiangular, multispectral, and polarimetric imagery for aerosol remote sensing. Interpreting such multidimensional measurements requires representing the aerosols by a set of optical and microphysical parameters and modeling the surface bidirectional reflectance distribution function (BRDF). We are developing a surface model represented by a matrix BRDF that describes both intensity and polarization. The BRDF is the sum of a depolarizing volumetric (diffuse) scattering term represented by the modified Rahman-Pinty-Verstraete (mRPV) function, and a specular reflection term corresponding to a distribution of tilted microfacets, each of which reflects according to the Fresnel laws. In order to limit the number of parameters that need to be retrieved, empirical constraints are placed on the surface reflection model, e.g., that the volumetric component can be written as the product of a function only of wavelength and a function only of illumination and view geometry and that the polarized surface reflectance is spectrally neutral. Validation of these assumptions is required to establish a successful surface reflectance model that can be used as part of the aerosol retrievals. The Ground-based and Airborne Multiangle SpectroPolarimetric Imagers (GroundMSPI and AirMSPI) are pushbroom cameras that use a novel dual-photoelastic modulator (PEM) design to measure the Stokes vector components I, Q, and U, degree of linear polarization (DOLP), and angle of linear polarization (AOLP) with high accuracy. Intensity bands are centered at 355, 380, 445, 555, 660, 865, and 935 nm, and polarization channels are at 470, 660, and 865 nm. GroundMSPI and AirMSPI data collected on clear days are being used to further develop and validate the parametric surface model. For GroundMSPI, time sequences of intensity and polarization imagery are acquired throughout the day, and motion of the Sun through the sky provides variable scattering angle. AirMSPI acquires multiangular imagery from the NASA ER-2 aircraft by pointing the camera at different angles using a motorized gimbal. In this paper, we will present examples of GroundMSPI and AirMSPI imagery and explore how well the parametric surface model is able to represent the measured intensity and polarization data.

Global Aerosol Remote Sensing from MODIS

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram J.; Remer, Lorraine A.; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Martins, Jose V.; Lau, William K. M. (Technical Monitor)

2002-01-01

The physical characteristics, composition, abundance, spatial distribution and dynamics of global aerosols are still very poorly known, and new data from satellite sensors have long been awaited to improve current understanding and to give a boost to the effort in future climate predictions. The derivation of aerosol parameters from the MODerate resolution Imaging Spectro-radiometer (MODIS) sensors aboard the Earth Observing System (EOS) Terra and Aqua polar-orbiting satellites ushers in a new era in aerosol remote sensing from space. Terra and Aqua were launched on December 18, 1999 and May 4, 2002 respectively, with daytime equator crossing times of approximately 10:30 am and 1:30 pm respectively. Several aerosol parameters are retrieved at 10-km spatial resolution (level 2) from MODIS daytime data. The MODIS aerosol algorithm employs different approaches to retrieve parameters over land and ocean surfaces, because of the inherent differences in the solar spectral radiance interaction with these surfaces. The parameters retrieved include: aerosol optical thickness (AOT) at 0.47, 0.55 and 0.66 micron wavelengths over land, and at 0.47, 0.55, 0.66, 0.87, 1.2, 1.6, and 2.1 micron over ocean; Angstrom exponent over land and ocean; and effective radii, and the proportion of AOT contributed by the small mode aerosols over ocean. To ensure the quality of these parameters, a substantial part of the Terra-MODIS aerosol products were validated globally and regionally, based on cross correlation with corresponding parameters derived from ground-based measurements from AERONET (AErosol RObotic NETwork) sun photometers. Similar validation efforts are planned for the Aqua-MODIS aerosol products. The MODIS level 2 aerosol products are operationally aggregated to generate global daily, eight-day (weekly), and monthly products at one-degree spatial resolution (level 3). MODIS aerosol data are used for the detailed study of local, regional, and global aerosol concentration, distribution, and temporal dynamics, as well as for radiative forcing calculations. We show several examples of these results and comparisons with model output.

The Influence of Spatial Resolutions on the Retrieval Accuracy of Sea Surface Wind Speed with Cross-polarized C-band SAR images

NASA Astrophysics Data System (ADS)

Zhang, K.; Han, B.; Mansaray, L. R.; Xu, X.; Guo, Q.; Jingfeng, H.

2017-12-01

Synthetic aperture radar (SAR) instruments on board satellites are valuable for high-resolution wind field mapping, especially for coastal studies. Since the launch of Sentinel-1A on April 3, 2014, followed by Sentinel-1B on April 25, 2016, large amount of C-band SAR data have been added to a growing accumulation of SAR datasets (ERS-1/2, RADARSAT-1/2, ENVISAT). These new developments are of great significance for a wide range of applications in coastal sea areas, especially for high spatial resolution wind resource assessment, in which the accuracy of retrieved wind fields is extremely crucial. Recently, it is reported that wind speeds can also be retrieved from C-band cross-polarized SAR images, which is an important complement to wind speed retrieval from co-polarization. However, there is no consensus on the optimal resolution for wind speed retrieval from cross-polarized SAR images. This paper presents a comparison strategy for investigating the influence of spatial resolutions on sea surface wind speed retrieval accuracy with cross-polarized SAR images. Firstly, for wind speeds retrieved from VV-polarized images, the optimal geophysical C-band model (CMOD) function was selected among four CMOD functions. Secondly, the most suitable C-band cross-polarized ocean (C-2PO) model was selected between two C-2POs for the VH-polarized image dataset. Then, the VH-wind speeds retrieved by the selected C-2PO were compared with the VV-polarized sea surface wind speeds retrieved using the optimal CMOD, which served as reference, at different spatial resolutions. Results show that the VH-polarized wind speed retrieval accuracy increases rapidly with the decrease in spatial resolutions from 100 m to 1000 m, with a drop in RMSE of 42%. However, the improvement in wind speed retrieval accuracy levels off with spatial resolutions decreasing from 1000 m to 5000 m. This demonstrates that the pixel spacing of 1 km may be the compromising choice for the tradeoff between the spatial resolution and wind speed retrieval accuracy with cross-polarized images obtained from RADASAT-2 fine quad polarization mode. Figs. 1 illustrate the variation of the following statistical parameters: Bias, Corr, R2, RMSE and STD as a function of spatial resolution.

Retrieval of the Nitrous Oxide Profiles using the AIRS Data in China

NASA Astrophysics Data System (ADS)

Chen, L.; Ma, P.; Tao, J.; Li, X.; Zhang, Y.; Wang, Z.; Li, S.; Xiong, X.

2014-12-01

As an important greenhouse gas and ozone-depleting substance, the 100-year global warming potential of Nitrous Oxide (N2O) is almost 300 times higher than that of carbon dioxide. However, there are still large uncertainties about the quantitative N2O emission and its feedback to climate change due to the coarse ground-based network. This approach attempts to retrieve the N2O profiles from the Atmospheric InfraRed Sounder (AIRS) data. First, the sensitivity of atmospheric temperature and humidity profiles and surface parameters between two spectral absorption bands were simulated by using the radiative transfer model. Second, the eigenvector regression algorithm is used to construct a priori state. Third, an optimal estimate method was developed based on the band selection of N2O. Finally, we compared our retrieved AIRS profiles with HIPPO data, and analyzed the seasonal and annual N2O distribution in China from 2004 to 2013.

Separating vegetation and soil temperature using airborne multiangular remote sensing image data

NASA Astrophysics Data System (ADS)

Liu, Qiang; Yan, Chunyan; Xiao, Qing; Yan, Guangjian; Fang, Li

2012-07-01

Land surface temperature (LST) is a key parameter in land process research. Many research efforts have been devoted to increase the accuracy of LST retrieval from remote sensing. However, because natural land surface is non-isothermal, component temperature is also required in applications such as evapo-transpiration (ET) modeling. This paper proposes a new algorithm to separately retrieve vegetation temperature and soil background temperature from multiangular thermal infrared (TIR) remote sensing data. The algorithm is based on the localized correlation between the visible/near-infrared (VNIR) bands and the TIR band. This method was tested on the airborne image data acquired during the Watershed Allied Telemetry Experimental Research (WATER) campaign. Preliminary validation indicates that the remote sensing-retrieved results can reflect the spatial and temporal trend of component temperatures. The accuracy is within three degrees while the difference between vegetation and soil temperature can be as large as twenty degrees.

Investigation of hydrometeor classification uncertainties through the POLARRIS polarimetric radar simulator

NASA Astrophysics Data System (ADS)

Dolan, B.; Rutledge, S. A.; Barnum, J. I.; Matsui, T.; Tao, W. K.; Iguchi, T.

2017-12-01

POLarimetric Radar Retrieval and Instrument Simulator (POLARRIS) is a framework that has been developed to simulate radar observations from cloud resolving model (CRM) output and subject model data and observations to the same retrievals, analysis and visualization. This framework not only enables validation of bulk microphysical model simulated properties, but also offers an opportunity to study the uncertainties associated with retrievals such as hydrometeor classification (HID). For the CSU HID, membership beta functions (MBFs) are built using a set of simulations with realistic microphysical assumptions about axis ratio, density, canting angles, size distributions for each of ten hydrometeor species. These assumptions are tested using POLARRIS to understand their influence on the resulting simulated polarimetric data and final HID classification. Several of these parameters (density, size distributions) are set by the model microphysics, and therefore the specific assumptions of axis ratio and canting angle are carefully studied. Through these sensitivity studies, we hope to be able to provide uncertainties in retrieved polarimetric variables and HID as applied to CRM output. HID retrievals assign a classification to each point by determining the highest score, thereby identifying the dominant hydrometeor type within a volume. However, in nature, there is rarely just one a single hydrometeor type at a particular point. Models allow for mixing ratios of different hydrometeors within a grid point. We use the mixing ratios from CRM output in concert with the HID scores and classifications to understand how the HID algorithm can provide information about mixtures within a volume, as well as calculate a confidence in the classifications. We leverage the POLARRIS framework to additionally probe radar wavelength differences toward the possibility of a multi-wavelength HID which could utilize the strengths of different wavelengths to improve HID classifications. With these uncertainties and algorithm improvements, cases of convection are studied in a continental (Oklahoma) and maritime (Darwin, Australia) regime. Observations from C-band polarimetric data in both locations are compared to CRM simulations from NU-WRF using the POLARRIS framework.

Variational estimation of process parameters in a simplified atmospheric general circulation model

NASA Astrophysics Data System (ADS)

Lv, Guokun; Koehl, Armin; Stammer, Detlef

2016-04-01

Parameterizations are used to simulate effects of unresolved sub-grid-scale processes in current state-of-the-art climate model. The values of the process parameters, which determine the model's climatology, are usually manually adjusted to reduce the difference of model mean state to the observed climatology. This process requires detailed knowledge of the model and its parameterizations. In this work, a variational method was used to estimate process parameters in the Planet Simulator (PlaSim). The adjoint code was generated using automatic differentiation of the source code. Some hydrological processes were switched off to remove the influence of zero-order discontinuities. In addition, the nonlinearity of the model limits the feasible assimilation window to about 1day, which is too short to tune the model's climatology. To extend the feasible assimilation window, nudging terms for all state variables were added to the model's equations, which essentially suppress all unstable directions. In identical twin experiments, we found that the feasible assimilation window could be extended to over 1-year and accurate parameters could be retrieved. Although the nudging terms transform to a damping of the adjoint variables and therefore tend to erases the information of the data over time, assimilating climatological information is shown to provide sufficient information on the parameters. Moreover, the mechanism of this regularization is discussed.

Model Evaluation with Multi-wavelength Satellite Observations Using a Neural Network

NASA Astrophysics Data System (ADS)

Kolassa, Jana; Jimenez, Carlos; Aires, Filipe

2013-04-01

A methodology has been developed to evaluate fields of modelled parameters against a set of satellite observations. The method employs a Neural Network (NN) to construct a statistical model capturing the relationship between the satellite observations and the parameter from a land surface model, in this case the Soil Moisture (SM). This statistical model is then used to estimate the parameter of interest from the set of satellite observations. These estimates are compared to the modelled parameter in order to detect local deviations indicating a possible problem in the model or in the satellite observations. Several synthetic tests, during which an artificial error was added to the"true" soil moisture fields, showed that the methodology is able to correct the errors (Jimenez et al., submitted, 2012). This evaluation technique is very general and can be applied to any modelled parameter for which sensitive satellite observations are available. The use of NNs simplifies the evaluation of the model against satellite observations and is particularly well-suited to utilize the synergy from the observations at different wavelengths (Aires et al., 2005, 2012). In this study the proposed methodology has been applied to evaluate SM fields from a number of land surface models against a synergy of satellite observations from passive and active microwave, infrared and visible sensors. In an inter-comparison of the performance of several land surface models (ORCHIDEE (de Rosnay et al., 2002), HTESSEL (Balsamo et al., 2009), JULES (Best et al., 2011) ) it was found that the soil moisture fields from JULES, HTESSEL and ORCHIDEE are very consistent with the observations, but ORCHIDEE soil moisture shows larger local deviations close to some river basins (Kolassa et al., in press, 2012; Jimenez et al., submitted, 2012). Differences between all models and the observations could also be observed in the Eastern US and over mountainous regions, however, the errors here are more likely linked to the retrieved SM uncertainties. The proposed methodology can also be used to evaluate the quality of the model forcings: two soil moisture fields from ORCHIDEE using WATCH (Weedon et al., 2011) and ERA-interim (Balsamo et al., 2010) forcings were analysed. It was shown that the WATCH forcing data are more optimal, underlining the importance of forcing data for the accuracy of model predictions (Kolassa et al., in press, 2012). References Aires, F., Prigent, C., and Rossow, W.B. (2005), Sensitivity of satellite microwave and infrared observations to soil moisture at a global scale: 2. Global statistical relationships, J. Geophys. Res., 110, D11103, doi:10.1029/2004JD005094. Aires, F., O. Aznay, C. Prigent, M. Paul, F. Bernardo, Synergetic multi-wavelegnth remote sensing versus a posteriori combination of retrieved products: Application for the retrieval of atmospheric profiles using MetOp measurements, J. Geophys. Res., 2011 Balsamo, G., Viterbo, P., Beljaars, A., van den Hurk, B., Hirschi, M., Betts, A. and Scipa,l K. (2009) A Revised Hydrology for the ECMWF Model: Verification from Field Site to Terrestrial Water Storage and Impact in the Integrated Forecast System, J. Hydrol., 10, 623-643 Balsamo, G., Boussetta, S., Lopez, P., and Ferranti, L. (2010), Evaluation of ERA-Interim and ERA- Interim-GPCP-rescaled precipitation over the U.S.A., ERA-Report Series, 5, pp. 10. Best, M. J., M. Pryor, D. B. Clark, G. G. Rooney, R .L. H. Essery, C. B. Ménard, J. M. Edwards, M. A. Hendry, A. Porson, N. Gedney, L. M. Mercado, S. Sitch, E. Blyth, O. Boucher, P. M. Cox, C. S. B. Grimmond, and R. J. Harding (2011), The Joint UK Land Environment Simulator (JULES), model description - Part 1: Energy and water fluxes, Geosci. Model Dev., 4 Jimenez, C., Clark, D., Kolassa, J., Aires, F., Prigent, C., and Blyth, E. (2012), A joint analysis of modeled soil moisture fields and satellite observations (2012), J. Geophys. Res., Kolassa, J., Aires, F., Polcher, J., Prigent, C., and Pereira, J. (2012), Soil moisture Retrieval from Multi-instrument Observations: Information Content Analysis and Retrieval Methodology (2012), J. Geophys. Res., de Rosnay, P., Polcher, J., Bruen, M., Laval, K. (2002), Impact of a physically based soil water flow and soil-plant interaction representation for modeling large-scale land surface processes, J. Geophys. Res., 107, D11, 4118, 10.1029/2001JD000634 Weedon, G.P., Gomes, S., Viterbo, P., Shuttleworth, W.J., Blyth, E., O ̈sterle, H., Adam, J.C., Bellouin, N., Boucher, O., and Best, M. (2011), Creation of the WATCH Forcing Data and its use to assess global and regional reference crop evaporation over land during the twentieth century, J. Hydrometeorology,12, 5, pp. 823-848.

A multi-tiered architecture for content retrieval in mobile peer-to-peer networks.

DOT National Transportation Integrated Search

2012-01-01

In this paper, we address content retrieval in Mobile Peer-to-Peer (P2P) Networks. We design a multi-tiered architecture for content : retrieval, where at Tier 1, we design a protocol for content similarity governed by a parameter that trades accu...

Retrieving water productivity parameters by using Landsat images in the Nilo Coelho irrigation scheme, Brazil

NASA Astrophysics Data System (ADS)

de C. Teixeira, Antônio H.; Lopes, Hélio L.; Hernandez, Fernando B. T.; Scherer-Warren, Morris; Andrade, Ricardo G.; Neale, Christopher M. U.

2013-10-01

The Nilo Coelho irrigation scheme, located in the semi-arid region of Brazil, is highlighted as an important agricultural irrigated perimeter. Considering the scenario of this fast land use change, the development and application of suitable tools to quantify the trends of the water productivity parameters on a large scale is important. To analyse the effects of land use change within this perimeter, the large-scale values of biomass production (BIO) and actual evapotranspiration (ET) were quantified from 1992 to 2011, under the naturally driest conditions along the year. Monteith's radiation model was applied for estimating the absorbed photosynthetically active radiation (APAR), while the SAFER (Simple Algorithm For Evapotranspiration Retrieving) algorithm was used to retrieve ET. The highest incremental BIO values happened during the years of 1999 and 2005, as a result of the increased agricultural area under production inside the perimeter, when the average differences between irrigated crops and natural vegetation were more than 70 kg ha-1 d-1. Comparing the average ET rates of 1992 (1.6 mm d-1) with those for 2011 (3.1 mm d-1), it was verified that the extra water consumption doubled because of the increments of irrigated areas along the years. More uniformity along the years on both water productivity parameters occurred for natural vegetation, evidenced by the lower values of standard deviation when comparing to irrigated crops. The heterogeneity of ET values under irrigation conditions are due to the different species, crop stages, cultural and water managements.

PubMed related articles: a probabilistic topic-based model for content similarity

PubMed Central

Lin, Jimmy; Wilbur, W John

2007-01-01

Background We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document is about a particular topic is computed from term frequencies, modeled as Poisson distributions. Unlike previous probabilistic retrieval models, we do not attempt to estimate relevance–but rather our focus is "relatedness", the probability that a user would want to examine a particular document given known interest in another. We also describe a novel technique for estimating parameters that does not require human relevance judgments; instead, the process is based on the existence of MeSH ® in MEDLINE ®. Results The pmra retrieval model was compared against bm25, a competitive probabilistic model that shares theoretical similarities. Experiments using the test collection from the TREC 2005 genomics track shows a small but statistically significant improvement of pmra over bm25 in terms of precision. Conclusion Our experiments suggest that the pmra model provides an effective ranking algorithm for related article search. PMID:17971238

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.

MODIS volcanic ash retrievals vs FALL3D transport model: a quantitative comparison

NASA Astrophysics Data System (ADS)

Corradini, S.; Merucci, L.; Folch, A.

2010-12-01

Satellite retrievals and transport models represents the key tools to monitor the volcanic clouds evolution. Because of the harming effects of fine ash particles on aircrafts, the real-time tracking and forecasting of volcanic clouds is key for aviation safety. Together with the security reasons also the economical consequences of a disruption of airports must be taken into account. The airport closures due to the recent Icelandic Eyjafjöll eruption caused millions of passengers to be stranded not only in Europe, but across the world. IATA (the International Air Transport Association) estimates that the worldwide airline industry has lost a total of about 2.5 billion of Euro during the disruption. Both security and economical issues require reliable and robust ash cloud retrievals and trajectory forecasting. The intercomparison between remote sensing and modeling is required to assure precise and reliable volcanic ash products. In this work we perform a quantitative comparison between Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of volcanic ash cloud mass and Aerosol Optical Depth (AOD) with the FALL3D ash dispersal model. MODIS, aboard the NASA-Terra and NASA-Aqua polar satellites, is a multispectral instrument with 36 spectral bands operating in the VIS-TIR spectral range and spatial resolution varying between 250 and 1000 m at nadir. The MODIS channels centered around 11 and 12 micron have been used for the ash retrievals through the Brightness Temperature Difference algorithm and MODTRAN simulations. FALL3D is a 3-D time-dependent Eulerian model for the transport and deposition of volcanic particles that outputs, among other variables, cloud column mass and AOD. Three MODIS images collected the October 28, 29 and 30 on Mt. Etna volcano during the 2002 eruption have been considered as test cases. The results show a general good agreement between the retrieved and the modeled volcanic clouds in the first 300 km from the vents. Even if the modeled volcanic cloud area is systematically wider than the retrieved area, the ash total mass is comparable and varies between 35 and 60 kt and between 20 and 42 kt for FALL3D and MODIS respectively. The mean AOD values are in good agreement and approximately equal to 0.8. When the whole volcanic clouds are considered the ash areas and the total ash masses, computed by FALL3D model are significantly greater than the same parameters retrieved from the MODIS data, while the mean AOD values remain in a very good agreement and equal to about 0.6. The volcanic cloud direction in its distal part is not coincident for the 29 and 30 October 2002 images due to the difference between the real and the modeled local wind fields. Finally the MODIS maps show regions of high mass and AOD due to volcanic puffs not modeled by FALL3D.

Waveform inversion for orthorhombic anisotropy with P waves: feasibility and resolution

NASA Astrophysics Data System (ADS)

Kazei, Vladimir; Alkhalifah, Tariq

2018-05-01

Various parametrizations have been suggested to simplify inversions of first arrivals, or P waves, in orthorhombic anisotropic media, but the number and type of retrievable parameters have not been decisively determined. We show that only six parameters can be retrieved from the dynamic linearized inversion of P waves. These parameters are different from the six parameters needed to describe the kinematics of P waves. Reflection-based radiation patterns from the P-P scattered waves are remapped into the spectral domain to allow for our resolution analysis based on the effective angle of illumination concept. Singular value decomposition of the spectral sensitivities from various azimuths, offset coverage scenarios and data bandwidths allows us to quantify the resolution of different parametrizations, taking into account the signal-to-noise ratio in a given experiment. According to our singular value analysis, when the primary goal of inversion is determining the velocity of the P waves, gradually adding anisotropy of lower orders (isotropic, vertically transversally isotropic and orthorhombic) in hierarchical parametrization is the best choice. Hierarchical parametrization reduces the trade-off between the parameters and makes gradual introduction of lower anisotropy orders straightforward. When all the anisotropic parameters affecting P-wave propagation need to be retrieved simultaneously, the classic parametrization of orthorhombic medium with elastic stiffness matrix coefficients and density is a better choice for inversion. We provide estimates of the number and set of parameters that can be retrieved from surface seismic data in different acquisition scenarios. To set up an inversion process, the singular values determine the number of parameters that can be inverted and the resolution matrices from the parametrizations can be used to ascertain the set of parameters that can be resolved.

Remote sensing of mineral dust aerosol using AERI during the UAE2: A modeling and sensitivity study

NASA Astrophysics Data System (ADS)

Hansell, R. A.; Liou, K. N.; Ou, S. C.; Tsay, S. C.; Ji, Q.; Reid, J. S.

2008-09-01

Numerical simulations and sensitivity studies have been performed to assess the potential for using brightness temperature spectra from a ground-based Atmospheric Emitted Radiance Interferometer (AERI) during the United Arab Emirates Unified Aerosol Experiment (UAE2) for detecting/retrieving mineral dust aerosol. A methodology for separating dust from clouds and retrieving the dust IR optical depths was developed by exploiting differences between their spectral absorptive powers in prescribed thermal IR window subbands. Dust microphysical models were constructed using in situ data from the UAE2 and prior field studies while composition was modeled using refractive index data sets for minerals commonly observed around the UAE region including quartz, kaolinite, and calcium carbonate. The T-matrix, finite difference time domain (FDTD), and Lorenz-Mie light scattering programs were employed to calculate the single scattering properties for three dust shapes: oblate spheroids, hexagonal plates, and spheres. We used the Code for High-resolution Accelerated Radiative Transfer with Scattering (CHARTS) radiative transfer program to investigate sensitivity of the modeled AERI spectra to key dust and atmospheric parameters. Sensitivity studies show that characterization of the thermodynamic boundary layer is crucial for accurate AERI dust detection/retrieval. Furthermore, AERI sensitivity to dust optical depth is manifested in the strong subband slope dependence of the window region. Two daytime UAE2 cases were examined to demonstrate the present detection/retrieval technique, and we show that the results compare reasonably well to collocated AERONET Sun photometer/MPLNET micropulse lidar measurements. Finally, sensitivity of the developed methodology to the AERI's estimated MgCdTe detector nonlinearity was evaluated.

Foundations for statistical-physical precipitation retrieval from passive microwave satellite measurements. I - Brightness-temperature properties of a time-dependent cloud-radiation model

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Mugnai, Alberto; Cooper, Harry J.; Tripoli, Gregory J.; Xiang, Xuwu

1992-01-01

The relationship between emerging microwave brightness temperatures (T(B)s) and vertically distributed mixtures of liquid and frozen hydrometeors was investigated, using a cloud-radiation model, in order to establish the framework for a hybrid statistical-physical rainfall retrieval algorithm. Although strong relationships were found between the T(B) values and various rain parameters, these correlations are misleading in that the T(B)s are largely controlled by fluctuations in the ice-particle mixing ratios, which in turn are highly correlated to fluctuations in liquid-particle mixing ratios. However, the empirically based T(B)-rain-rate (T(B)-RR) algorithms can still be used as tools for estimating precipitation if the hydrometeor profiles used for T(B)-RR algorithms are not specified in an ad hoc fashion.

Tests of the Grobner Basis Solution for Lightning Ground Flash Fraction Retrieval

NASA Technical Reports Server (NTRS)

Koshak, William; Solakiewicz, Richard; Attele, Rohan

2011-01-01

Satellite lightning imagers such as the NASA Tropical Rainfall Measuring Mission Lightning Imaging Sensor (TRMM/LIS) and the future GOES-R Geostationary Lightning Mapper (GLM) are designed to detect total lightning (ground flashes + cloud flashes). However, there is a desire to discriminate ground flashes from cloud flashes from the vantage point of space since this would enhance the overall information content of the satellite lightning data and likely improve its operational and scientific applications (e.g., in severe weather warning, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method was previously introduced for retrieving the fraction of ground flashes in a set of flashes observed from a satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters (one of which is the ground flash fraction), a scalar function was minimized by a numerical method. In order to improve this optimization, a Grobner basis solution was introduced to obtain analytic representations of the model parameters that serve as a refined initialization scheme to the numerical optimization. In this study, we test the efficacy of the Grobner basis initialization using actual lightning imager measurements and ground flash truth derived from the national lightning network.

Estimating chlorophyll content of spartina alterniflora at leaf level using hyper-spectral data

NASA Astrophysics Data System (ADS)

Wang, Jiapeng; Shi, Runhe; Liu, Pudong; Zhang, Chao; Chen, Maosi

2017-09-01

Spartina alterniflora, one of most successful invasive species in the world, was firstly introduced to China in 1979 to accelerate sedimentation and land formation via so-called "ecological engineering", and it is now widely distributed in coastal saltmarshes in China. A key question is how to retrieve chlorophyll content to reflect growth status, which has important implication of potential invasiveness. In this work, an estimation model of chlorophyll content of S. alterniflora was developed based on hyper-spectral data in the Dongtan Wetland, Yangtze Estuary, China. The spectral reflectance of S. alterniflora leaves and their corresponding chlorophyll contents were measured, and then the correlation analysis and regression (i.e., linear, logarithmic, quadratic, power and exponential regression) method were established. The spectral reflectance was transformed and the feature parameters (i.e., "san bian", "lv feng" and "hong gu") were extracted to retrieve the chlorophyll content of S. alterniflora . The results showed that these parameters had a large correlation coefficient with chlorophyll content. On the basis of the correlation coefficient, mathematical models were established, and the models of power and exponential based on SDb had the least RMSE and larger R2 , which had a good performance regarding the inversion of chlorophyll content of S. alterniflora.

Impacts of Mass-dimension and Area-dimension relationships on retrieval ice particle effective radius from radar and lidar measurements

NASA Astrophysics Data System (ADS)

Ham, S. H.; Kato, S.; Rose, F. G.

2016-12-01

In the retrieval of ice clouds from Radar and Lidar Measurements, mass-Dimension (m-D) and Area-Dimension (A-D) relationships are often used to describe nonspherical ice particle shapes. This study analytically investigates how the assumption of m-D and A-D relationships affects retrieval of ice effective radius. We use gamma and lognormal particle distributions and integrate optical parameters over the size distribution. The effective radius is expressed as a function of radar reflectivity factor, visible extinction coefficient, and parameters describing m-D and A-D relationships. The analytic expressions are used for converting effective radius retrieved from one set of m-D and A-D relationships into that with another set of m-D and A-D, including plates, solid columns, bullets, and mixture of different habits. The conversion method can be used for consistent radiative transfer simulation with cloud retrieval algorithms. In addition, when we want to merge cloud effective radii retrieved from different m-D and A-D, the conversion method can be efficiently used to remove undesired biases caused by m-D and A-D assumptions. Furthermore, the sensitivity of the effective radius to m-D and A-D relationships can be quantified by taking the first derivative of the effective radius with respect to parameters expressing the m-D and A-D relationships.

Simultaneous Retrieval of Multiple Aerosol Parameters Using a Multi-Angular Approach

NASA Technical Reports Server (NTRS)

Kuo, K. S.; Weger, R. C.; Welch, R. M.

1997-01-01

Atmospheric aerosol particles, both natural and anthropogenic, are important to the earth's radiative balance through their direct and indirect effects. They scatter the incoming solar radiation (direct effect) and modify the shortwave reflective properties of clouds by acting as cloud condensation nuclei (indirect effect). Although it has been suggested that aerosols exert a net cooling influence on climate, this effect has received less attention than the radiative forcing due to clouds and greenhouse gases. In order to understand the role that aerosols play in a changing climate, detailed and accurate observations are a prerequisite. The retrieval of aerosol optical properties by satellite remote sensing has proven to be a difficult task. The difficulty results mainly from the tenuous nature and variable composition of aerosols. To date, with single-angle satellite observations, we can only retrieve reliably against dark backgrounds, such as over oceans and dense vegetation. Even then, assumptions must be made concerning the chemical composition of aerosols. The best hope we have for aerosol retrievals over bright backgrounds are observations from multiple angles, such as those provided by the MISR and POLDER instruments. In this investigation we examine the feasibility of simultaneous retrieval of multiple aerosol optical parameters using reflectances from a typical set of twelve angles observed by the French POLDER instrument. The retrieved aerosol optical parameters consist of asymmetry factor, single scattering albedo, surface albedo, and optical thickness.

A Comparison of Aerosol Measurements from OCO-2 and MODIS

NASA Astrophysics Data System (ADS)

Nelson, R. R.; O'Dell, C.

2016-12-01

The goal of OCO-2 is to use hyperspectral measurements of reflected near-infrared sunlight to retrieve carbon dioxide with high accuracy and precision. This is only possible, however, if the light-path modification effects caused by clouds and aerosols are properly quantified. Even tiny amounts of clouds or aerosols can induce sufficient light-path modifications to lead to large errors in the estimated CO2 column-mean (XCO2). Therefore, it is imperative to evaluate the accuracy of the OCO-2 retrieved aerosol parameters. In this study, we compare OCO-2 retrieved aerosol parameters to Aqua-MODIS observations co-located in time and space. We find that there are significant disagreements between the aerosol information derived from MODIS and the retrieved aerosol parameters from OCO-2. These results are unsurprising, as previous comparisons to AERONET have also been poor. However, the tight co-location between Aqua and OCO-2 in the Afternoon Constellation allows us to examine the potential synergistic use of OCO-2 and MODIS measurements to more accurately constrain aerosol properties, potentially leading to a more accurate CO2 measurement. Specifically, we used select MODIS aerosol properties as the a priori for the OCO-2 retrievals and present the results here. Future studies include investigating the possibility of ingesting the MODIS radiances directly into the OCO-2 retrieval algorithm to further improve OCO-2's aerosol scheme and the resulting measurements.

[Foliage clumping index of main vegetation types in Daxing'an Mountains, Northeast China].

PubMed

Huang, Ting; Fan, Wen Yi; Mao, Xue Gang; Yu, Ying

2017-03-18

The foliage clumping index quantifies the cluster degree of the leaf spatial distribution under random canopy. It is of comparable importance for establishment of ecological models. MODIS BRDF model parameter products (MCD43A1 data) and land cover types (MCD12Q1 data) were used in this study to simulate the reflectivity of the hot spots and dark spots, and calculate the normalized difference between hotspot and darkspot (NDHD) based on the Ross-Li semi-empirical model. Least square method was then used to simulate the relationship between NDHD and the foliage clumping index and foliage clumping index products of 500-m resolution in August 2014 were retrieved. Measurements of the foliage clumping index in Daxing'an Mountains were conducted by using the TRAC (Tracing Radiation and Architecture of Canopies) sampling instrument for mo-del validation and analysis. Results showed that it was a feasible algorithm to retrieve clumping index from MCD43A1 product with the correlation of simulated data and the measured data of significance (R 2 =0.8879). The MODIS near infrared wave band was more sensitive than that on red band to foliage clumping index change. With the increase of the solar zenith angle, the clumping index retrieved by Ross-Li model had a linear increase (R 2 =0.9699), which indicated that the foliage clumping index related to the solar zenith angle.

A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

NASA Technical Reports Server (NTRS)

Hodges, D. B.

1976-01-01

An iterative method is presented to retrieve single field of view (FOV) tropospheric temperature profiles directly from cloud-contaminated radiance data. A well-defined temperature profile may be calculated from the radiative transfer equation (RTE) for a partly cloudy atmosphere when the average fractional cloud amount and cloud-top height for the FOV are known. A cloud model is formulated to calculate the fractional cloud amount from an estimated cloud-top height. The method is then examined through use of simulated radiance data calculated through vertical integration of the RTE for a partly cloudy atmosphere using known values of cloud-top height(s) and fractional cloud amount(s). Temperature profiles are retrieved from the simulated data assuming various errors in the cloud parameters. Temperature profiles are retrieved from NOAA-4 satellite-measured radiance data obtained over an area dominated by an active cold front and with considerable cloud cover and compared with radiosonde data. The effects of using various guessed profiles and the number of iterations are considered.

Analysis of DIAL/HSRL aerosol backscatter and extinction profiles during the SEAC4RS campaign with an aerosol assimilation system

NASA Astrophysics Data System (ADS)

Weaver, C. J.; da Silva, A. M., Jr.; Colarco, P. R.; Randles, C. A.

2015-12-01

We retrieve aerosol concentrations and optical information from vertical profiles of airborne 532 nm extinction and 532 and 1064 nm backscatter measurements made during the SEAC4RS summer 2013 campaign. The observations are from the High Spectral Resolution Lidar (HSRL) Airborne Differential Absorption Lidar (DIAL) on board the NASA DC-8. Instead of retrieving information about aerosol microphysical properties such as indexes of refraction, we seek information more directly applicable to an aerosol transport model - in our case the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module used in the GEOS-5 Earth modeling system. A joint atmosphere/aerosol mini-reanalysis was performed for the SEAC4RS period using GEOS-5. The meteorological reanalysis followed the MERRA-2 atmospheric reanalysis protocol, and aerosol information from MODIS, MISR, and AERONET provided a constraint on the simulated aerosol optical depth (i.e., total column loading of aerosols). We focus on the simulated concentrations of 10 relevant aerosol species simulated by the GOCART module: dust, sulfate, and organic and black carbon. Our first retrieval algorithm starts with the SEAC4RS mini-reanalysis and adjusts the concentration of each GOCART aerosol species so that differences between the observed and simulated backscatter and extinction measurements are minimized. In this case, too often we are unable to simulate the observations by simple adjustment of the aerosol concentrations. A second retrieval approach adjusts both the aerosol concentrations and the optical parameters (i.e., assigned mass extinction efficiency) associated with each GOCART species. We present results from DC-8 flights over smoke from forest fires over the western US using both retrieval approaches. Finally, we compare our retrieved quantities with in-situ observations of aerosol absorption, scattering, and mass concentrations at flight altitude.

Evaluation of MODIS aerosol optical depth for semi­-arid environments in complex terrain

NASA Astrophysics Data System (ADS)

Holmes, H.; Loria Salazar, S. M.; Panorska, A. K.; Arnott, W. P.; Barnard, J.

2015-12-01

The use of satellite remote sensing to estimate spatially resolved ground level air pollutant concentrations is increasing due to advancements in remote sensing technology and the limited number of surface observations. Satellite retrievals provide global, spatiotemporal air quality information and are used to track plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Ground level PM2.5 concentrations can be estimated using columnar aerosol optical depth (AOD) from MODIS, where the satellite retrieval serves as a spatial surrogate to simulate surface PM2.5 gradients. The spatial statistical models and MODIS AOD retrieval algorithms have been evaluated for the dark, vegetated eastern US, while the semi-arid western US continues to be an understudied region with associated complexity due to heterogeneous emissions, smoke from wildfires, and complex terrain. The objective of this work is to evaluate the uncertainty of MODIS AOD retrievals by comparing with columnar AOD and surface PM2.5 measurements from AERONET and EPA networks. Data is analyzed from multiple stations in California and Nevada for three years where four major wildfires occurred. Results indicate that MODIS retrievals fail to estimate column-integrated aerosol pollution in the summer months. This is further investigated by quantifying the statistical relationships between MODIS AOD, AERONET AOD, and surface PM2.5 concentrations. Data analysis indicates that the distribution of MODIS AOD is significantly (p<0.05) different than AERONET AOD. Further, using the results of distributional and association analysis the impacts of MODIS AOD uncertainties on the spatial gradients are evaluated. Additionally, the relationships between these uncertainties and physical parameters in the retrieval algorithm (e.g., surface reflectance, Ångström Extinction Exponent) are discussed.

Richards-like two species population dynamics model.

PubMed

Ribeiro, Fabiano; Cabella, Brenno Caetano Troca; Martinez, Alexandre Souto

2014-12-01

The two-species population dynamics model is the simplest paradigm of inter- and intra-species interaction. Here, we present a generalized Lotka-Volterra model with intraspecific competition, which retrieves as particular cases, some well-known models. The generalization parameter is related to the species habitat dimensionality and their interaction range. Contrary to standard models, the species coupling parameters are general, not restricted to non-negative values. Therefore, they may represent different ecological regimes, which are derived from the asymptotic solution stability analysis and are represented in a phase diagram. In this diagram, we have identified a forbidden region in the mutualism regime, and a survival/extinction transition with dependence on initial conditions for the competition regime. Also, we shed light on two types of predation and competition: weak, if there are species coexistence, or strong, if at least one species is extinguished.

Determination of Structural and Morphological Parameters of Human Bulbar Conjunctiva from Optical Diffuse Reflectance Spectra

NASA Astrophysics Data System (ADS)

Lisenko, S. A.; Firago, V. A.; Kugeiko, M. M.; Kubarko, A. I.

2016-09-01

We have developed a method for on-the-fl y retrieval of the volume concentration of blood vessels, the average diameter of the blood vessels, the blood oxygenation level, and the molar concentrations of chromophores in the bulbar conjunctiva from its diffuse reflectance spectra, measured when the radiation delivery and detection channels are spatially separated. The relationship between the diffuse reflectance spectrum of the conjunctiva and its unknown parameters is described in terms of an analytical model, constructed on the basis of a highly accurate approximation analog of the Monte Carlo method. We have studied the effect of localization of hemoglobin in erythrocytes and localization of erythrocytes in the blood vessels on the power of the retrieval of structural and morphological parameters for the conjunctiva. We developed a device for obtaining video images of the conjunctiva and contactless measurements of its diffuse reflectance spectrum. By comparing simulated diffuse reflectance spectra of the conjunctiva with the experimental measurements, we established a set of chromophores which must be taken into account in the model for reproducing the experimental data within the measurement error. We observed absorption bands for neuroglobin in the experimental spectra, and provided a theoretical basis for the possibility of determining its absolute concentrations in the conjunctiva. We have shown that our method can detect low bilirubin concentrations in blood.

Evolving discriminators for querying video sequences

NASA Astrophysics Data System (ADS)

Iyengar, Giridharan; Lippman, Andrew B.

1997-01-01

In this paper we present a framework for content based query and retrieval of information from large video databases. This framework enables content based retrieval of video sequences by characterizing the sequences using motion, texture and colorimetry cues. This characterization is biologically inspired and results in a compact parameter space where every segment of video is represented by an 8 dimensional vector. Searching and retrieval is done in real- time with accuracy in this parameter space. Using this characterization, we then evolve a set of discriminators using Genetic Programming Experiments indicate that these discriminators are capable of analyzing and characterizing video. The VideoBook is able to search and retrieve video sequences with 92% accuracy in real-time. Experiments thus demonstrate that the characterization is capable of extracting higher level structure from raw pixel values.

Millstone Angle Calibration 1989

DTIC Science & Technology

1990-09-14

tiltmeter calibration models are examined, ("A A 1 GAccession For NTIS GP\\A&I o DTIC TAB 0] Unannounced 01 Justificatlo By Distribution/ Avnilitb lty...parameters. T. A. Cott kindly added the ability to retrieve tiltmeter data from SATCIT raw data tapes to his program SATSNR and provided the program for my...AZLCAL and Current Method 17 3. THE ELEVATION JUMP PHENOMENON 27 3.1 AZLCAL Modeling 27 3.2 Elevation Rate Dependence 27 4. TILTMETER CALIBRATION 29 5

Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities

DOE PAGES

Cadeddu, Maria P.; Marchand, Roger; Orlandi, Emiliano; ...

2017-08-11

Satellite and ground-based microwave radiometers are routinely used for the retrieval of liquid water path (LWP) under all atmospheric conditions. The retrieval of water vapor and LWP from ground-based radiometers during rain has proved to be a difficult challenge for two principal reasons: the inadequacy of the nonscattering approximation in precipitating clouds and the deposition of rain drops on the instrument's radome. In this paper, we combine model computations and real ground-based, zenith-viewing passive microwave radiometer brightness temperature measurements to investigate how total, cloud, and rain LWP retrievals are affected by assumptions on the cloud drop size distribution (DSD) andmore » under which conditions a nonscattering approximation can be considered reasonably accurate. Results show that until the drop effective diameter is larger than similar to 200 mu m, a nonscattering approximation yields results that are still accurate at frequencies less than 90 GHz. For larger drop sizes, it is shown that higher microwave frequencies contain useful information that can be used to separate cloud and rain LWP provided that the vertical distribution of hydrometeors, as well as the DSD, is reasonably known. The choice of the DSD parameters becomes important to ensure retrievals that are consistent with the measurements. A physical retrieval is tested on a synthetic data set and is then used to retrieve total, cloud, and rain LWP from radiometric measurements during two drizzling cases at the atmospheric radiation measurement Eastern North Atlantic site.« less

Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities

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

Cadeddu, Maria P.; Marchand, Roger; Orlandi, Emiliano

Satellite and ground-based microwave radiometers are routinely used for the retrieval of liquid water path (LWP) under all atmospheric conditions. The retrieval of water vapor and LWP from ground-based radiometers during rain has proved to be a difficult challenge for two principal reasons: the inadequacy of the nonscattering approximation in precipitating clouds and the deposition of rain drops on the instrument's radome. In this paper, we combine model computations and real ground-based, zenith-viewing passive microwave radiometer brightness temperature measurements to investigate how total, cloud, and rain LWP retrievals are affected by assumptions on the cloud drop size distribution (DSD) andmore » under which conditions a nonscattering approximation can be considered reasonably accurate. Results show that until the drop effective diameter is larger than similar to 200 mu m, a nonscattering approximation yields results that are still accurate at frequencies less than 90 GHz. For larger drop sizes, it is shown that higher microwave frequencies contain useful information that can be used to separate cloud and rain LWP provided that the vertical distribution of hydrometeors, as well as the DSD, is reasonably known. The choice of the DSD parameters becomes important to ensure retrievals that are consistent with the measurements. A physical retrieval is tested on a synthetic data set and is then used to retrieve total, cloud, and rain LWP from radiometric measurements during two drizzling cases at the atmospheric radiation measurement Eastern North Atlantic site.« less

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.

EXPLORING BIASES OF ATMOSPHERIC RETRIEVALS IN SIMULATED JWST TRANSMISSION SPECTRA OF HOT JUPITERS

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

Rocchetto, M.; Waldmann, I. P.; Tinetti, G.

2016-12-10

With a scheduled launch in 2018 October, the James Webb Space Telescope ( JWST ) is expected to revolutionize the field of atmospheric characterization of exoplanets. The broad wavelength coverage and high sensitivity of its instruments will allow us to extract far more information from exoplanet spectra than what has been possible with current observations. In this paper, we investigate whether current retrieval methods will still be valid in the era of JWST , exploring common approximations used when retrieving transmission spectra of hot Jupiters. To assess biases, we use 1D photochemical models to simulate typical hot Jupiter cloud-free atmospheresmore » and generate synthetic observations for a range of carbon-to-oxygen ratios. Then, we retrieve these spectra using TauREx, a Bayesian retrieval tool, using two methodologies: one assuming an isothermal atmosphere, and one assuming a parameterized temperature profile. Both methods assume constant-with-altitude abundances. We found that the isothermal approximation biases the retrieved parameters considerably, overestimating the abundances by about one order of magnitude. The retrieved abundances using the parameterized profile are usually within 1 σ of the true state, and we found the retrieved uncertainties to be generally larger compared to the isothermal approximation. Interestingly, we found that by using the parameterized temperature profile we could place tight constraints on the temperature structure. This opens the possibility of characterizing the temperature profile of the terminator region of hot Jupiters. Lastly, we found that assuming a constant-with-altitude mixing ratio profile is a good approximation for most of the atmospheres under study.« less

Estimation of the Reactive Flow Model Parameters for an Ammonium Nitrate-Based Emulsion Explosive Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Ribeiro, J. B.; Silva, C.; Mendes, R.

2010-10-01

A real coded genetic algorithm methodology that has been developed for the estimation of the parameters of the reaction rate equation of the Lee-Tarver reactive flow model is described in detail. This methodology allows, in a single optimization procedure, using only one experimental result and, without the need of any starting solution, to seek the 15 parameters of the reaction rate equation that fit the numerical to the experimental results. Mass averaging and the plate-gap model have been used for the determination of the shock data used in the unreacted explosive JWL equation of state (EOS) assessment and the thermochemical code THOR retrieved the data used in the detonation products' JWL EOS assessments. The developed methodology was applied for the estimation of the referred parameters for an ammonium nitrate-based emulsion explosive using poly(methyl methacrylate) (PMMA)-embedded manganin gauge pressure-time data. The obtained parameters allow a reasonably good description of the experimental data and show some peculiarities arising from the intrinsic nature of this kind of composite explosive.

Skin Parameter Map Retrieval from a Dedicated Multispectral Imaging System Applied to Dermatology/Cosmetology

PubMed Central

2013-01-01

In vivo quantitative assessment of skin lesions is an important step in the evaluation of skin condition. An objective measurement device can help as a valuable tool for skin analysis. We propose an explorative new multispectral camera specifically developed for dermatology/cosmetology applications. The multispectral imaging system provides images of skin reflectance at different wavebands covering visible and near-infrared domain. It is coupled with a neural network-based algorithm for the reconstruction of reflectance cube of cutaneous data. This cube contains only skin optical reflectance spectrum in each pixel of the bidimensional spatial information. The reflectance cube is analyzed by an algorithm based on a Kubelka-Munk model combined with evolutionary algorithm. The technique allows quantitative measure of cutaneous tissue and retrieves five skin parameter maps: melanin concentration, epidermis/dermis thickness, haemoglobin concentration, and the oxygenated hemoglobin. The results retrieved on healthy participants by the algorithm are in good accordance with the data from the literature. The usefulness of the developed technique was proved during two experiments: a clinical study based on vitiligo and melasma skin lesions and a skin oxygenation experiment (induced ischemia) with healthy participant where normal tissues are recorded at normal state and when temporary ischemia is induced. PMID:24159326

A data storage, retrieval and analysis system for endocrine research. [for Skylab

NASA Technical Reports Server (NTRS)

Newton, L. E.; Johnston, D. A.

1975-01-01

This retrieval system builds, updates, retrieves, and performs basic statistical analyses on blood, urine, and diet parameters for the M071 and M073 Skylab and Apollo experiments. This system permits data entry from cards to build an indexed sequential file. Programs are easily modified for specialized analyses.

Retrieval of Raindrop Size Distribution, Vertical Air Velocity and Water Vapor Attenuation Using Dual-Wavelength Doppler Radar Observations

NASA Technical Reports Server (NTRS)

Heymsfield, Gerald M.; Tian, Lin; Li, Lihua; Srivastava, C.

2005-01-01

Two techniques for retrieving the slope and intercept parameters of an assumed exponential raindrop size distribution (RSD), vertical air velocity, and attenuation by precipitation and water vapor in light stratiform rain using observations by airborne, nadir looking dual-wavelength (X-band, 3.2 cm and W-band, 3.2 mm) radars are presented. In both techniques, the slope parameter of the RSD and the vertical air velocity are retrieved using only the mean Doppler velocities at the two wavelengths. In the first method, the intercept of the RSD is estimated from the observed reflectivity at the longer wavelength assuming no attenuation at that wavelength. The attenuation of the shorter wavelength radiation by precipitation and water vapor are retrieved using the observed reflectivity at the shorter wavelength. In the second technique, it is assumed that the longer wavelength suffers attenuation only in the melting band. Then, assuming a distribution of water vapor, the melting band attenuation at both wavelengths and the rain attenuation at the shorter wavelength are retrieved. Results of the retrievals are discussed and several physically meaningful results are presented.

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.

Calibration of Noah soil hydraulic property parameters using surface soil moisture from SMOS and basin-wide in situ observations

USDA-ARS?s Scientific Manuscript database

Soil hydraulic properties can be retrieved from physical sampling of soil, via surveys, but this is time consuming and only as accurate as the scale of the sample. Remote sensing provides an opportunity to get pertinent soil properties at large scales, which is very useful for large scale modeling....

Coupled retrieval of water cloud and above-cloud aerosol properties using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, F.; van Harten, G.; Diner, D. J.; Rheingans, B. E.; Tosca, M.; Seidel, F. C.; Bull, M. A.; Tkatcheva, I. N.; McDuffie, J. L.; Garay, M. J.; Davis, A. B.; Jovanovic, V. M.; Brian, C.; Alexandrov, M. D.; Hostetler, C. A.; Ferrare, R. A.; Burton, S. P.

2017-12-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (*denotes polarimetric bands). In sweep mode, georectified images cover an area of 80-100 km (along track) by 10-25 km (across track) between ±66° off nadir, with a map-projected spatial resolution of 25 meters. An efficient and flexible retrieval algorithm has been developed using AirMSPI polarimetric bands for simultaneous retrieval of cloud and above-cloud aerosol microphysical properties. We design a three-step retrieval approach, namely 1) estimating effective droplet size distribution using polarimetric cloudbow observations and using it as initial guess for Step 2; 2) combining water cloud and aerosol above cloud retrieval by fitting polarimetric signals at all scattering angles (e.g. from 80° to 180°); and 3) constructing a lookup table of radiance for a set of cloud optical depth grids using aerosol and cloud information retrieved from Step 2 and then estimating pixel-scale cloud optical depth based on 1D radiative transfer (RT) theory by fitting the AirMSPI radiance. Retrieval uncertainty is formulated by accounting for instrumental errors and constraints imposed on spectral variations of aerosol and cloud droplet optical properties. As the forward RT model, a hybrid approach is developed to combine the computational strengths of Markov-chain and adding-doubling methods to model polarized RT in a coupled aerosol, Rayleigh and cloud system. Our retrieval approach is tested using 134 AirMSPI datasets acquired during NASA ORACLES field campaign in 09/2016, with low to high aerosol loadings. For validation, the retrieved aerosol optical depths and cloud-top heights are compared to coincident High Spectral Resolution Lidar-2 (HSRL-2) data, and the droplet size parameters including effective radius and effective variance and cloud optical thickness are compared to coincident Research Scanning Polarimeter (RSP) data.

Serial position curves in free recall.

PubMed

Laming, Donald

2010-01-01

The scenario for free recall set out in Laming (2009) is developed to provide models for the serial position curves from 5 selected sets of data, for final free recall, and for multitrial free recall. The 5 sets of data reflect the effects of rate of presentation, length of list, delay of recall, and suppression of rehearsal. Each model accommodates the serial position curve for first recalls (where those data are available) as well as that for total recalls. Both curves are fit with the same parameter values, as also (with 1 exception) are all of the conditions compared within each experiment. The distributions of numbers of recalls are also examined and shown to have variances increased above what would be expected if successive recalls were independent. This is taken to signify that, in those experiments in which rehearsals were not recorded, the retrieval of words for possible recall follows the same pattern that is observed following overt rehearsal, namely, that retrieval consists of runs of consecutive elements from memory. Finally, 2 sets of data are examined that the present approach cannot accommodate. It is argued that the problem with these data derives from an interaction between the patterns of (covert) rehearsal and the parameters of list presentation.

VizieR Online Data Catalog: WISE/NEOWISE Mars-crossing asteroids (Ali-Lagoa+, 2017)

NASA Astrophysics Data System (ADS)

Ali-Lagoa, V.; Delbo, M.

2017-07-01

We fitted the near-Earth asteroid thermal model of Harris (1998, Icarus, 131, 29) to WISE/NEOWISE thermal infrared data (see, e.g., Mainzer et al. 2011ApJ...736..100M, and Masiero et al. 2014, Cat. J/ApJ/791/121). The table contains the best-fitting values of size and beaming parameter. We note that the beaming parameter is a strictly positive quantity, but a negative sign is given to indicate whenever we could not fit it and had to assume a default value. We also provide the visible geometric albedos computed from the diameter and the tabulated absolute magnitudes. Minimum relative errors of 10, 15, and 20 percent should be considered for size, beaming parameter and albedo in those cases for which the beaming parameter could be fitted. Otherwise, the minimum relative errors in size and albedo increase to 20 and 40 percent (see, e.g., Mainzer et al. 2011ApJ...736..100M). The asteroid absolute magnitudes and slope parameters retrieved from the Minor Planet Center (MPC) are included, as well as the number of observations used in each WISE band (nW2, nW3, nW4) and the corresponding average values of heliocentric and geocentric distances and phase angle of the observations. The ephemerides were retrieved from the MIRIADE service (http://vo.imcce.fr/webservices/miriade/?ephemph). (1 data file).

Application of neural network to remote sensing of soil moisture using theoretical polarimetric backscattering coefficients

NASA Technical Reports Server (NTRS)

Wang, L.; Shin, R. T.; Kong, J. A.; Yueh, S. H.

1993-01-01

This paper investigates the potential application of neural network to inversion of soil moisture using polarimetric remote sensing data. The neural network used for the inversion of soil parameters is multi-layer perceptron trained with the back-propagation algorithm. The training data include the polarimetric backscattering coefficients obtained from theoretical surface scattering models together with an assumed nominal range of soil parameters which are comprised of the soil permittivity and surface roughness parameters. Soil permittivity is calculated from the soil moisture and the assumed soil texture based on an empirical formula at C-, L-, and P-bands. The rough surface parameters for the soil surface, which is described by the Gaussian random process, are the root-mean-square (rms) height and correlation length. For the rough surface scattering, small perturbation method is used for the L-band frequency, and Kirchhoff approximation is used for the C-band frequency to obtain the corresponding backscattering coefficients. During the training, the backscattering coefficients are the inputs to the neural net and the output from the net are compared with the desired soil parameters to adjust the interconnecting weights. The process is repeated for each input-output data entry and then for the entire training data until convergence is reached. After training, the backscattering coefficients are applied to the trained neural net to retrieve the soil parameters which are compared with the desired soil parameters to verify the effectiveness of this technique. Several cases are examined. First, for simplicity, the correlation length and rms height of the soil surface are fixed while soil moisture is varied. Soil moisture obtained using the neural networks with either L-band or C-band backscattering coefficients for the HH and VV polarizations as inputs is in good agreement with the desired soil moisture. The neural net output matches the desired output for the soil moisture range of 16 to 60 percent for the C-band case. The next case investigated is to vary both soil moisture and rms height while keeping the correlation length fixed. For this case, C-band backscattering coefficients are not sufficient for retrieving two parameters because the Kirchhoff approximation gives the same HH and VV backscattering coefficients. Therefore, the backscattering coefficients at two different frequency bands are necessary to find both the soil moisture and rms height. Finally, the neural nets are also applied to simultaneously invert soil moisture, rms height, and correlation length. Overall, the soil moisture retrieved from the neural network agrees very well with the desired soil moisture. This suggests that the neural network shows potential for retrieval of soil parameters from remote sensing data.

GOSAILT: A hybrid of GOMS and SAILT with topography consideration

NASA Astrophysics Data System (ADS)

Wu, S.; Wen, J.

2017-12-01

Heterogeneous terrain significantly complicated the energy, mass and momentum exchange between the atmosphere and terrestrial ecosystem. Understanding of topographic effect on the forest reflectance is critical for biophysical parameters retrieval over rugged area. In this paper, a new hybrid bidirectional reflectance distribution function (BRDF) model of geometric optical mutual shadowing and scattering-from-arbitrarily-inclined-leaves model coupled topography (GOSAILT) for sloping forest was proposed. The effects of slope, aspect, gravity field of tree crown, multiple scattering scheme, and diffuse skylight are considered. The area proportions of scene components estimated by the GOSAILT model were compared with the geometric optical model for sloping terrains (GOST) model. The 3-D discrete anisotropic radiative transfer (DART) simulations were used to evaluate the performance of GOSAILT. The results indicate that the canopy reflectance is distorted by the slopes with a maximum variation of 78.3% in the red band and 17.3% in the NIR band on a steep 60 º slope. Compared with the DART simulations, the proposed GOSAILT model can capture anisotropic reflectance well with a determine coefficient (R2) of 0.9720 and 0.6701, root-mean-square error (RMSE) of 0.0024 and 0.0393, mean absolute percentage error of 2.4% and 4.61% for the red and near-infrared (NIR) band. The comparison results indicate the GOSAIL model can accurately reproducing the angular feature of discrete canopy over rugged terrain conditions. The GOSAILT model is promising for the land surface biophysical parameters retrieval (e.g. albedo, leaf area index) over the heterogeneous terrain.

Mapping forest canopy fuels in Yellowstone National Park using lidar and hyperspectral data

NASA Astrophysics Data System (ADS)

Halligan, Kerry Quinn

The severity and size of wildland fires in the forested western U.S have increased in recent years despite improvements in fire suppression efficiency. This, along with increased density of homes in the wildland-urban interface, has resulted in high costs for fire management and increased risks to human health, safety and property. Crown fires, in comparison to surface fires, pose an especially high risk due to their intensity and high rate of spread. Crown fire models require a range of quantitative fuel parameters which can be difficult and costly to obtain, but advances in lidar and hyperspectral sensor technologies hold promise for delivering these inputs. Further research is needed, however, to assess the strengths and limitations of these technologies and the most appropriate analysis methodologies for estimating crown fuel parameters from these data. This dissertation focuses on retrieving critical crown fuel parameters, including canopy height, canopy bulk density and proportion of dead canopy fuel, from airborne lidar and hyperspectral data. Remote sensing data were used in conjunction with detailed field data on forest parameters and surface reflectance measurements. A new method was developed for retrieving Digital Surface Model (DSM) and Digital Canopy Models (DCM) from first return lidar data. Validation data on individual tree heights demonstrated the high accuracy (r2 0.95) of the DCMs developed via this new algorithm. Lidar-derived DCMs were used to estimate critical crown fire parameters including available canopy fuel, canopy height and canopy bulk density with linear regression model r2 values ranging from 0.75 to 0.85. Hyperspectral data were used in conjunction with Spectral Mixture Analysis (SMA) to assess fuel quality in the form of live versus dead canopy proportions. Severity and stage of insect-caused forest mortality were estimated using the fractional abundance of green vegetation, non-photosynthetic vegetation and shade obtained from SMA. Proportion of insect attack was estimated with a linear model producing an r2 of 0.6 using SMA and bark endmembers from image and reference libraries. Fraction of red attack, with a possible link to increased crown fire risk, was estimated with an r2 of 0.45.

Material Properties from Air Puff Corneal Deformation by Numerical Simulations on Model Corneas

PubMed Central

Dorronsoro, Carlos; de la Hoz, Andrés; Marcos, Susana

2016-01-01

Objective To validate a new method for reconstructing corneal biomechanical properties from air puff corneal deformation images using hydrogel polymer model corneas and porcine corneas. Methods Air puff deformation imaging was performed on model eyes with artificial corneas made out of three different hydrogel materials with three different thicknesses and on porcine eyes, at constant intraocular pressure of 15 mmHg. The cornea air puff deformation was modeled using finite elements, and hyperelastic material parameters were determined through inverse modeling, minimizing the difference between the simulated and the measured central deformation amplitude and central-peripheral deformation ratio parameters. Uniaxial tensile tests were performed on the model cornea materials as well as on corneal strips, and the results were compared to stress-strain simulations assuming the reconstructed material parameters. Results The measured and simulated spatial and temporal profiles of the air puff deformation tests were in good agreement (< 7% average discrepancy). The simulated stress-strain curves of the studied hydrogel corneal materials fitted well the experimental stress-strain curves from uniaxial extensiometry, particularly in the 0–0.4 range. Equivalent Young´s moduli of the reconstructed material properties from air-puff were 0.31, 0.58 and 0.48 MPa for the three polymer materials respectively which differed < 1% from those obtained from extensiometry. The simulations of the same material but different thickness resulted in similar reconstructed material properties. The air-puff reconstructed average equivalent Young´s modulus of the porcine corneas was 1.3 MPa, within 18% of that obtained from extensiometry. Conclusions Air puff corneal deformation imaging with inverse finite element modeling can retrieve material properties of model hydrogel polymer corneas and real corneas, which are in good correspondence with those obtained from uniaxial extensiometry, suggesting that this is a promising technique to retrieve quantitative corneal biomechanical properties. PMID:27792759

Techniques to Access Databases and Integrate Data for Hydrologic Modeling

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

Whelan, Gene; Tenney, Nathan D.; Pelton, Mitchell A.

2009-06-17

This document addresses techniques to access and integrate data for defining site-specific conditions and behaviors associated with ground-water and surface-water radionuclide transport applicable to U.S. Nuclear Regulatory Commission reviews. Environmental models typically require input data from multiple internal and external sources that may include, but are not limited to, stream and rainfall gage data, meteorological data, hydrogeological data, habitat data, and biological data. These data may be retrieved from a variety of organizations (e.g., federal, state, and regional) and source types (e.g., HTTP, FTP, and databases). Available data sources relevant to hydrologic analyses for reactor licensing are identified and reviewed.more » The data sources described can be useful to define model inputs and parameters, including site features (e.g., watershed boundaries, stream locations, reservoirs, site topography), site properties (e.g., surface conditions, subsurface hydraulic properties, water quality), and site boundary conditions, input forcings, and extreme events (e.g., stream discharge, lake levels, precipitation, recharge, flood and drought characteristics). Available software tools for accessing established databases, retrieving the data, and integrating it with models were identified and reviewed. The emphasis in this review was on existing software products with minimal required modifications to enable their use with the FRAMES modeling framework. The ability of four of these tools to access and retrieve the identified data sources was reviewed. These four software tools were the Hydrologic Data Acquisition and Processing System (HDAPS), Integrated Water Resources Modeling System (IWRMS) External Data Harvester, Data for Environmental Modeling Environmental Data Download Tool (D4EM EDDT), and the FRAMES Internet Database Tools. The IWRMS External Data Harvester and the D4EM EDDT were identified as the most promising tools based on their ability to access and retrieve the required data, and their ability to integrate the data into environmental models using the FRAMES environment.« less

Parameter identification of process simulation models as a means for knowledge acquisition and technology transfer

NASA Astrophysics Data System (ADS)

Batzias, Dimitris F.; Ifanti, Konstantina

2012-12-01

Process simulation models are usually empirical, therefore there is an inherent difficulty in serving as carriers for knowledge acquisition and technology transfer, since their parameters have no physical meaning to facilitate verification of the dependence on the production conditions; in such a case, a 'black box' regression model or a neural network might be used to simply connect input-output characteristics. In several cases, scientific/mechanismic models may be proved valid, in which case parameter identification is required to find out the independent/explanatory variables and parameters, which each parameter depends on. This is a difficult task, since the phenomenological level at which each parameter is defined is different. In this paper, we have developed a methodological framework under the form of an algorithmic procedure to solve this problem. The main parts of this procedure are: (i) stratification of relevant knowledge in discrete layers immediately adjacent to the layer that the initial model under investigation belongs to, (ii) design of the ontology corresponding to these layers, (iii) elimination of the less relevant parts of the ontology by thinning, (iv) retrieval of the stronger interrelations between the remaining nodes within the revised ontological network, and (v) parameter identification taking into account the most influential interrelations revealed in (iv). The functionality of this methodology is demonstrated by quoting two representative case examples on wastewater treatment.

The hippocampus, medial prefrontal cortex, and selective memory retrieval: evidence from a rodent model of the retrieval-induced forgetting effect.

PubMed

Wu, Jade Q; Peters, Greg J; Rittner, Pedro; Cleland, Thomas A; Smith, David M

2014-09-01

Inhibition is an important component of many cognitive functions, including memory. For example, the retrieval-induced forgetting (RIF) effect occurs when extra practice with some items from a study list inhibits the retrieval of the nonpracticed items relative to a baseline condition that does not involve extra practice. Although counterintuitive, the RIF phenomenon may be important for resolving interference by inhibiting potentially competing retrieval targets. Neuroimaging studies suggest that the hippocampus and prefrontal cortex are involved in the RIF effect, but controlled lesion studies have not yet been performed. We developed a rodent model of the RIF training procedure and trained control rats and rats with temporary inactivation of the hippocampus or medial prefrontal cortex (mPFC). Rats were trained on a list of odor cues, presented in cups of digging medium with a buried reward, followed by additional practice trials with a subset of the cues. We then tested the rats' memories for the cues and their association with reward by presenting them with unbaited cups containing the test odorants and measuring how long they persisted in digging. Control rats exhibited a robust RIF effect in which memory for the nonpracticed odors was significantly inhibited. Thus, extra practice with some odor cues inhibited memory for the others, relative to a baseline condition that involved an identical amount of training. Inactivation of either the hippocampus or the mPFC blocked the RIF effect. We also constructed a computational model of a representational learning circuit to simulate the RIF effect. We show in this model that "sideband suppression" of similar memory representations can reproduce the RIF effect and that alteration of the suppression parameters and learning rate can reproduce the lesion effects seen in our rats. Our results suggest that the RIF effect is widespread and that inhibitory processes are an important feature of memory function. © 2014 Wiley Periodicals, Inc.

Deciphering the Hot Giant Atmospheres Orbiting Nearby Extrasolar Systems with JWST

NASA Astrophysics Data System (ADS)

Afrin Badhan, Mahmuda; Batalha, Natasha; Deming, Drake; Domagal-Goldman, Shawn; HEBRARD, Eric; Kopparapu, Ravi Kumar; Irwin, Patrick Gerard Joseph

2016-10-01

Unique and exotic planets give us an opportunity to understand how planetary systems form and evolve over their lifetime, by placing our own planetary system in the context of the vastly different extrasolar systems that are being continually discovered by present space missions. With orbital separations that are less than one-tenth of the Mercury-Sun distance, these close-in planets provide us with valuable insights about the host stellar atmosphere and planetary atmospheres subjected to their enormous stellar insolation. Observed spectroscopic signatures reveal all spectrally active species in a planet, along with information about its thermal structure and dynamics, allowing us to characterize the planet's atmosphere. NASA's upcoming missions will give us the high-resolution spectra necessary to constrain the atmospheric properties with unprecedented accuracy. However, to interpret the observed signals from exoplanetary transit events with any certainty, we need reliable atmospheric retrieval tools that can model the expected observables adequately. In my work thus far, I have built a Markov Chain Monte Carlo (MCMC) convergence scheme, with an analytical radiative equilibrium formulation for the thermal structures, within the NEMESIS atmospheric modeling tool, to allow sufficient (and efficient) exploration of the parameter space. I also augmented the opacity tables to improve the speed and reliability of retrieval models. I then utilized this upgraded version to infer the pressure-temperature (P-T) structures and volume-mixing ratios (VMRs) of major gas species in hot Jupiter dayside atmospheres, from their emission spectra. I have employed a parameterized thermal structure to retrieve plausible P-T profiles, along with altitude-invariant VMRs. Here I show my retrieval results on published datasets of HD189733b, and compare them with both medium and high spectral resolution JWST/NIRSPEC simulations. In preparation for the upcoming JWST mission, my current work expands on these efforts by exploring the observable impacts of chemistry in the hot Jupiter models and retrievals.

The Aquarius Salinity Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Meissner, Thomas; Wentz, Frank; Hilburn, Kyle; Lagerloef, Gary; Le Vine, David

2012-01-01

The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration [2] converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section 3. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water [3], [4] and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step.

Application of Terrestrial Microwave Remote Sensing to Agricultural Drought Monitoring

NASA Astrophysics Data System (ADS)

Crow, W. T.; Bolten, J. D.

2014-12-01

Root-zone soil moisture information is a valuable diagnostic for detecting the onset and severity of agricultural drought. Current attempts to globally monitor root-zone soil moisture are generally based on the application of soil water balance models driven by observed meteorological variables. Such systems, however, are prone to random error associated with: incorrect process model physics, poor parameter choices and noisy meteorological inputs. The presentation will describe attempts to remediate these sources of error via the assimilation of remotely-sensed surface soil moisture retrievals from satellite-based passive microwave sensors into a global soil water balance model. Results demonstrate the ability of satellite-based soil moisture retrieval products to significantly improve the global characterization of root-zone soil moisture - particularly in data-poor regions lacking adequate ground-based rain gage instrumentation. This success has lead to an on-going effort to implement an operational land data assimilation system at the United States Department of Agriculture's Foreign Agricultural Service (USDA FAS) to globally monitor variations in root-zone soil moisture availability via the integration of satellite-based precipitation and soil moisture information. Prospects for improving the performance of the USDA FAS system via the simultaneous assimilation of both passive and active-based soil moisture retrievals derived from the upcoming NASA Soil Moisture Active/Passive mission will also be discussed.

Rain retrieval from dual-frequency radar Doppler spectra: validation and potential for a midlatitude precipitating case-study

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

Tridon, F.; Battaglia, A.; Luke, E.

A recently developed technique retrieving the binned raindrop size distributions (DSDs) and air state parameters from ground-based K a and W-band radars Doppler spectra profiles is improved and applied to a typical midlatitude rain event. The retrievals are thoroughly validated against DSD observations of a 2D video disdrometer and independent X-band observations. Here for this case-study, profiles of rain rate, R, mean volume diameter and concentration parameter are retrieved, with low bias and standard deviations. In light rain (0.1 < R < 1 mm h -1), the radar reflectivities must be calibrated with a collocated disdrometer which introduces random errorsmore » due to sampling mismatch between the two instruments. The best performances are obtained in moderate rain (1 < R < 20 mm h -1) where the retrieval is providing self-consistent estimates of the absolute calibration and of the attenuation caused by antenna or radome wetness for both radars.« less

Rain retrieval from dual-frequency radar Doppler spectra: validation and potential for a midlatitude precipitating case-study

DOE PAGES

Tridon, F.; Battaglia, A.; Luke, E.; ...

2017-01-27

A recently developed technique retrieving the binned raindrop size distributions (DSDs) and air state parameters from ground-based K a and W-band radars Doppler spectra profiles is improved and applied to a typical midlatitude rain event. The retrievals are thoroughly validated against DSD observations of a 2D video disdrometer and independent X-band observations. Here for this case-study, profiles of rain rate, R, mean volume diameter and concentration parameter are retrieved, with low bias and standard deviations. In light rain (0.1 < R < 1 mm h -1), the radar reflectivities must be calibrated with a collocated disdrometer which introduces random errorsmore » due to sampling mismatch between the two instruments. The best performances are obtained in moderate rain (1 < R < 20 mm h -1) where the retrieval is providing self-consistent estimates of the absolute calibration and of the attenuation caused by antenna or radome wetness for both radars.« less

Simultaneous Retrieval of Multiple Aerosol Parameters Using a Multi-Angular Approach

NASA Technical Reports Server (NTRS)

Kuo, K.-S.; Weger, R. C.; Welch, R. M.

1997-01-01

Atmospheric aerosol particles, both natural and anthropogenic, are important to the earth's radiative balance through their direct and indirect effects. They scatter the incoming solar radiation (direct effect) and modify the shortwave reflective properties of clouds by acting as cloud condensation nuclei (indirect effect). Although it has been suggested that aerosols exert a net cooling influence on climate, this effect has received less attention than the radiative forcing due to clouds and greenhouse gases. In order to understand the role that aerosols play in a changing climate, detailed and accurate observations are a prerequisite. The retrieval of aerosol optical properties by satellite remote sensing has proven to be a difficult task. The difficulty results mainly from the tenuous nature and variable composition of aerosols. To date, with single-angle satellite observations, we can only retrieve reliably against dark backgrounds, such as over oceans and dense vegetation. Even then, assumptions must be made concerning the chemical composition of aerosols. In this investigation we examine the feasibility of simultaneous retrieval of multiple aerosol optical parameters using reflectances from a typical set of twelve angles observed by the French POLDER instrument. The retrieved aerosol optical parameters consist of asymmetry factor, single scattering albedo, surface albedo, and optical thickness.

WFIRST: Retrieval Studies of Directly Imaged Extrasolar Giant Planets

NASA Astrophysics Data System (ADS)

Marley, Mark; Lupu, Roxana; Lewis, Nikole K.; WFIRST Coronagraph SITs

2018-01-01

The typical direct imaging and spectroscopy target for the WFIRST Coronagraph will be a mature Jupiter-mass giant planet at a few AU from an FGK star. The spectra of such planets is expected to be shaped primarily by scattering from H2O clouds and absorption by gaseous NH3 and CH4. We have computed forward model spectra of such typical planets and applied noise models to understand the quality of photometry and spectra we can expect. Using such simulated datasets we have conducted Markov Chain Monte Carlo and MultiNest retrievals to derive atmospheric abundance of CH4, cloud scattering properties, gravity, and other parameters for various planets and observing modes. Our focus has primarily been to understand which combinations of photometry and spectroscopy at what SNR allow retrievals of atmospheric methane mixing ratios to within a factor of ten of the true value. This is a challenging task for directly imaged planets as the planet mass and radius--and thus surface gravity--are not as well constrained as in the case of transiting planets. We find that for plausible planets and datasets of the quality expected to be obtained by WFIRST it should be possible to place such constraints, at least for some planets. We present some examples of our retrieval results and explain how they have been utilized to help set design requirements on the coronagraph camera and integrated field spectrometer.

Convenient models of the atmosphere: optics and solar radiation

NASA Astrophysics Data System (ADS)

Alexander, Ginsburg; Victor, Frolkis; Irina, Melnikova; Sergey, Novikov; Dmitriy, Samulenkov; Maxim, Sapunov

2017-11-01

Simple optical models of clear and cloudy atmosphere are proposed. Four versions of atmospheric aerosols content are considered: a complete lack of aerosols in the atmosphere, low background concentration (500 cm-3), high concentrations (2000 cm-3) and very high content of particles (5000 cm-3). In a cloud scenario, the model of external mixture is assumed. The values of optical thickness and single scattering albedo for 13 wavelengths are calculated in the short wavelength range of 0.28-0.90 µm, with regard to the molecular absorption bands, that is simulated with triangle function. A comparison of the proposed optical parameters with results of various measurements and retrieval (lidar measurement, sampling, processing radiation measurements) is presented. For a cloudy atmosphere models of single-layer and two-layer atmosphere are proposed. It is found that cloud optical parameters with assuming the "external mixture" agrees with retrieved values from airborne observations. The results of calculating hemispherical fluxes of the reflected and transmitted solar radiation and the radiative divergence are obtained with the Delta-Eddington approach. The calculation is done for surface albedo values of 0, 0.5, 0.9 and for spectral values of the sandy surface. Four values of solar zenith angle: 0°, 30°, 40° and 60° are taken. The obtained values are compared with data of radiative airborne observations. Estimating the local instantaneous radiative forcing of atmospheric aerosols and clouds for considered models is presented together with the heating rate.

A Pure Marine Aerosol Model, for Use in Remote Sensing Applications

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Smirnov, A.; Hsu, N. C.; Holben, B. N.

2011-01-01

Retrievals of aerosol optical depth (AOD) and related parameters from satellite measurements typically involve prescribed models of aerosol size and composition, and are therefore dependent on how well these models are able to represent the radiative behaviour of real aerosols, This study uses aerosol volume size distributions retrieved from Sun-photometer measurements at 11 Aerosol Robotic Network (AERONET) island sites, spread throughout the world's oceans, as a basis to define such a model for unpolluted maritime aerosols. Size distributions are observed to be bimodal and approximately lognormal, although the coarse mode is skewed with a long tail on the low-radius end, The relationship of AOD and size distribution parameters to meteorological conditions is also examined, As wind speed increases, so do coarse-mode volume and radius, The AOD and Angstrom exponent (alpha) show linear relationships with wind speed, although there is considerable scatter in all these relationships, limiting their predictive power. Links between aerosol properties and near-surface relative humidity, columnar water vapor, and sea surface temperature are also explored. A recommended bimodal maritime model, which is able to reconstruct the AERONET AOD with accuracy of order 0.01-0.02, is presented for use in aerosol remote sensing applications. This accuracy holds at most sites and for wavelengths between 340 nm and 1020 nm. Calculated lidar ratios are also provided, and differ significantly from those currently used in Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) processing.

Retrieval of pine forest biomass using JPL AIRSAR data

NASA Technical Reports Server (NTRS)

Beaudoin, A.; Letoan, T.; Zagolski, F.; Hsu, C. C.; Han, H. C.; Kong, J. A.

1992-01-01

The analysis of Jet Propulsion Laboratory (JPL) Airborne Synthetic Aperture Radar (AIRSAR) data over the Landes forest in South-West France revealed strong correlation between L- and especially P-band sigma degrees and the pine forest biomass. To explain the physical link of radar backscatter to biomass, a polarimetric backscattering model was developed and validated. Then the model was used in a simulation study to predict sigma degree sensitivity to undesired canopy and environmental parameters. Main results concerning the data analysis, modeling, and simulation at P-band are reported.

Estimation of Microphysical and Radiative Parameters of Precipitating Cloud Systems Using mm-Wavelength Radars

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.

2009-03-01

A remote sensing approach is described to retrieve cloud and rainfall parameters within the same precipitating system. This approach is based on mm-wavelength radar signal attenuation effects which are observed in a layer of liquid precipitation containing clouds and rainfall. The parameters of ice clouds in the upper part of startiform precipitating systems are then retrieved using the absolute measurements of radar reflectivity. In case of the ground-based radar location, these measurements are corrected for attenuation in the intervening layer of liquid hydrometers.

Estimating leaf functional traits by inversion of PROSPECT: Assessing leaf dry matter content and specific leaf area in mixed mountainous forest

NASA Astrophysics Data System (ADS)

Ali, Abebe Mohammed; Darvishzadeh, Roshanak; Skidmore, Andrew K.; Duren, Iris van; Heiden, Uta; Heurich, Marco

2016-03-01

Assessments of ecosystem functioning rely heavily on quantification of vegetation properties. The search is on for methods that produce reliable and accurate baseline information on plant functional traits. In this study, the inversion of the PROSPECT radiative transfer model was used to estimate two functional leaf traits: leaf dry matter content (LDMC) and specific leaf area (SLA). Inversion of PROSPECT usually aims at quantifying its direct input parameters. This is the first time the technique has been used to indirectly model LDMC and SLA. Biophysical parameters of 137 leaf samples were measured in July 2013 in the Bavarian Forest National Park, Germany. Spectra of the leaf samples were measured using an ASD FieldSpec3 equipped with an integrating sphere. PROSPECT was inverted using a look-up table (LUT) approach. The LUTs were generated with and without using prior information. The effect of incorporating prior information on the retrieval accuracy was studied before and after stratifying the samples into broadleaf and conifer categories. The estimated values were evaluated using R2 and normalized root mean square error (nRMSE). Among the retrieved variables the lowest nRMSE (0.0899) was observed for LDMC. For both traits higher R2 values (0.83 for LDMC and 0.89 for SLA) were discovered in the pooled samples. The use of prior information improved accuracy of the retrieved traits. The strong correlation between the estimated traits and the NIR/SWIR region of the electromagnetic spectrum suggests that these leaf traits could be assessed at canopy level by using remotely sensed data.

Performance factors in associative learning: assessment of the sometimes competing retrieval model.

PubMed

Witnauer, James E; Wojick, Brittany M; Polack, Cody W; Miller, Ralph R

2012-09-01

Previous simulations revealed that the sometimes competing retrieval model (SOCR; Stout & Miller, Psychological Review, 114, 759-783, 2007), which assumes local error reduction, can explain many cue interaction phenomena that elude traditional associative theories based on total error reduction. Here, we applied SOCR to a new set of Pavlovian phenomena. Simulations used a single set of fixed parameters to simulate each basic effect (e.g., blocking) and, for specific experiments using different procedures, used fitted parameters discovered through hill climbing. In simulation 1, SOCR was successfully applied to basic acquisition, including the overtraining effect, which is context dependent. In simulation 2, we applied SOCR to basic extinction and renewal. SOCR anticipated these effects with both fixed parameters and best-fitting parameters, although the renewal effects were weaker than those observed in some experiments. In simulation 3a, feature-negative training was simulated, including the often observed transition from second-order conditioning to conditioned inhibition. In simulation 3b, SOCR predicted the observation that conditioned inhibition after feature-negative and differential conditioning depends on intertrial interval. In simulation 3c, SOCR successfully predicted failure of conditioned inhibition to extinguish with presentations of the inhibitor alone under most circumstances. In simulation 4, cue competition, including blocking (4a), recovery from relative validity (4b), and unblocking (4c), was simulated. In simulation 5, SOCR correctly predicted that inhibitors gain more behavioral control than do excitors when they are trained in compound. Simulation 6 demonstrated that SOCR explains the slower acquisition observed following CS-weak shock pairings.

Simultaneous Retrieval of Aerosol and Cloud Properties During the MILAGRO Field Campaign

NASA Technical Reports Server (NTRS)

Knobelspiesse, K.; Cairns, B.; Redemann, J.; Bergstrom, R. W.; Stohl, A.

2011-01-01

Estimation of Direct Climate Forcing (DCF) due to aerosols in cloudy areas has historically been a difficult task, mainly because of a lack of appropriate measurements. Recently, passive remote sensing instruments have been developed that have the potential to retrieve both cloud and aerosol properties using polarimetric, multiple view angle, and multi spectral observations, and therefore determine DCF from aerosols above clouds. One such instrument is the Research Scanning Polarimeter (RSP), an airborne prototype of a sensor on the NASA Glory satellite, which unfortunately failed to reach orbit during its launch in March of 2011. In the spring of 2006, the RSP was deployed on an aircraft based in Veracruz, Mexico, as part of the Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign. On 13 March, the RSP over flew an aerosol layer lofted above a low altitude marine stratocumulus cloud close to shore in the Gulf of Mexico. We investigate the feasibility of retrieving aerosol properties over clouds using these data. Our approach is to first determine cloud droplet size distribution using the angular location of the cloud bow and other features in the polarized reflectance. The selected cloud was then used in a multiple scattering radiative transfer model optimization to determine the aerosol optical properties and fine tune the cloud size distribution. In this scene, we were able to retrieve aerosol optical depth, the fine mode aerosol size distribution parameters and the cloud droplet size distribution parameters to a degree of accuracy required for climate modeling. This required assumptions about the aerosol vertical distribution and the optical properties of the coarse aerosol size mode. A sensitivity study was also performed to place this study in the context of future systematic scanning polarimeter observations, which found that the aerosol complex refractive index can also be observed accurately if the aerosol optical depth is larger than roughly 0.8 at a wavelength of (0.555 m).

Retrieval of Aerosol Phase Function and Polarized Phase Function from Polarization of Skylight for Different Observation Geometries

NASA Astrophysics Data System (ADS)

Li, L.; Qie, L. L.; Xu, H.; Li, Z. Q.

2018-04-01

The phase function and polarized phase function are important optical parameters, which describe scattering properties of atmospheric aerosol particles. Polarization of skylight induced by the scattering processes is sensitive to the scattering properties of aerosols. The Stokes parameters I, Q, U and the polarized radiance Lp of skylight measured by the CIMEL dual-polar sun-sky radiometer CE318- DP can be use to retrieve the phase function and polarized phase function, respectively. Two different observation geometries (i.e., the principal plane and almucantar) are preformed by the CE318-DP to detect skylight polarization. Polarization of skylight depends on the illumination and observation geometries. For the same solar zenith angle, retrievals of the phase function and the polarized phase function are still affected by the observation geometry. The performance of the retrieval algorithm for the principal plane and almucantar observation geometries was assessed by the numerical experiments at two typical high and low sun's positions (i.e. solar zenith angles are equal to 45° and 65°). Comparing the results for the principal plane and almucantar geometries, it is recommended to utilize the principal plane observations to retrieve the phase function when the solar zenith angle is small. The Stokes parameter U and the polarized radiance Lp from the almucantar observations are suggested to retrieve the polarized phase function, especially for short wavelength channels (e.g., 440 and 500 nm).

Nature of size effects in compact models of field effect transistors

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

Torkhov, N. A., E-mail: trkf@mail.ru; Scientific-Research Institute of Semiconductor Devices, Tomsk 634050; Tomsk State University of Control Systems and Radioelectronics, Tomsk 634050

Investigations have shown that in the local approximation (for sizes L < 100 μm), AlGaN/GaN high electron mobility transistor (HEMT) structures satisfy to all properties of chaotic systems and can be described in the language of fractal geometry of fractional dimensions. For such objects, values of their electrophysical characteristics depend on the linear sizes of the examined regions, which explain the presence of the so-called size effects—dependences of the electrophysical and instrumental characteristics on the linear sizes of the active elements of semiconductor devices. In the present work, a relationship has been established for the linear model parameters of themore » equivalent circuit elements of internal transistors with fractal geometry of the heteroepitaxial structure manifested through a dependence of its relative electrophysical characteristics on the linear sizes of the examined surface areas. For the HEMTs, this implies dependences of their relative static (A/mm, mA/V/mm, Ω/mm, etc.) and microwave characteristics (W/mm) on the width d of the sink-source channel and on the number of sections n that leads to a nonlinear dependence of the retrieved parameter values of equivalent circuit elements of linear internal transistor models on n and d. Thus, it has been demonstrated that the size effects in semiconductors determined by the fractal geometry must be taken into account when investigating the properties of semiconductor objects on the levels less than the local approximation limit and designing and manufacturing field effect transistors. In general, the suggested approach allows a complex of problems to be solved on designing, optimizing, and retrieving the parameters of equivalent circuits of linear and nonlinear models of not only field effect transistors but also any arbitrary semiconductor devices with nonlinear instrumental characteristics.« less

Simulation Framework to Estimate the Performance of CO2 and O2 Sensing from Space and Airborne Platforms for the ASCENDS Mission Requirements Analysis

NASA Technical Reports Server (NTRS)

Plitau, Denis; Prasad, Narasimha S.

2012-01-01

The Active Sensing of CO2 Emissions over Nights Days and Seasons (ASCENDS) mission recommended by the NRC Decadal Survey has a desired accuracy of 0.3% in carbon dioxide mixing ratio (XCO2) retrievals requiring careful selection and optimization of the instrument parameters. NASA Langley Research Center (LaRC) is investigating 1.57 micron carbon dioxide as well as the 1.26-1.27 micron oxygen bands for our proposed ASCENDS mission requirements investigation. Simulation studies are underway for these bands to select optimum instrument parameters. The simulations are based on a multi-wavelength lidar modeling framework being developed at NASA LaRC to predict the performance of CO2 and O2 sensing from space and airborne platforms. The modeling framework consists of a lidar simulation module and a line-by-line calculation component with interchangeable lineshape routines to test the performance of alternative lineshape models in the simulations. As an option the line-by-line radiative transfer model (LBLRTM) program may also be used for line-by-line calculations. The modeling framework is being used to perform error analysis, establish optimum measurement wavelengths as well as to identify the best lineshape models to be used in CO2 and O2 retrievals. Several additional programs for HITRAN database management and related simulations are planned to be included in the framework. The description of the modeling framework with selected results of the simulation studies for CO2 and O2 sensing is presented in this paper.

Performance evaluation of four directional emissivity analytical models with thermal SAIL model and airborne images.

PubMed

Ren, Huazhong; Liu, Rongyuan; Yan, Guangjian; Li, Zhao-Liang; Qin, Qiming; Liu, Qiang; Nerry, Françoise

2015-04-06

Land surface emissivity is a crucial parameter in the surface status monitoring. This study aims at the evaluation of four directional emissivity models, including two bi-directional reflectance distribution function (BRDF) models and two gap-frequency-based models. Results showed that the kernel-driven BRDF model could well represent directional emissivity with an error less than 0.002, and was consequently used to retrieve emissivity with an accuracy of about 0.012 from an airborne multi-angular thermal infrared data set. Furthermore, we updated the cavity effect factor relating to multiple scattering inside canopy, which improved the performance of the gap-frequency-based models.

GPS: A New Tool for Ocean Science

NASA Technical Reports Server (NTRS)

Komjathy, Attila; Garrison, James L.; Zavorotny, Valery

2001-01-01

In this article, we demonstrate wind retrieval (estimate its speed) from reflected signals obtained by a GPS receiver on board an aircraft to illustrate the potential of using GPS for remote-sensing applications. Before showing those results, we provide some background on radar remote sensing and discuss the theoretical model we used to interpret reflection data. This model describes the power and correlation properties of the reflected GPS signals as a function of scattering geometry and environmental parameters related to the reflecting surface.

Improving Pixel Level Cloud Optical Property Retrieval using Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Marshak, Alexander; Cahalan, Robert F.

1999-01-01

The accurate pixel-by-pixel retrieval of cloud optical properties from space is influenced by radiative smoothing due to high order photon scattering and radiative roughening due to low order scattering events. Both are caused by cloud heterogeneity and the three-dimensional nature of radiative transfer and can be studied with the aid of computer simulations. We use Monte Carlo simulations on variable 1-D and 2-D model cloud fields to seek for dependencies of smoothing and roughening phenomena on single scattering albedo, solar zenith angle, and cloud characteristics. The results are discussed in the context of high resolution satellite (such as Landsat) retrieval applications. The current work extends the investigation on the inverse NIPA (Non-local Independent Pixel Approximation) as a tool for removing smoothing and improving retrievals of cloud optical depth. This is accomplished by: (1) Delineating the limits of NIPA applicability; (2) Exploring NIPA parameter dependences on cloud macrostructural features, such as mean cloud optical depth and geometrical thickness, degree of extinction and cloud top height variability. We also compare parameter values from empirical and theoretical considerations; (3) Examining the differences between applying NIPA on radiation quantities vs direct application on optical properties; (4) Studying the radiation budget importance of the NIPA corrections as a function of scale. Finally, we discuss fundamental adjustments that need to be considered for successful radiance inversion at non-conservative wavelengths and oblique Sun angles. These adjustments are necessary to remove roughening signatures which become more prominent with increasing absorption and solar zenith angle.

Effect of the influence function of deformable mirrors on laser beam shaping.

PubMed

González-Núñez, Héctor; Béchet, Clémentine; Ayancán, Boris; Neichel, Benoit; Guesalaga, Andrés

2017-02-20

The continuous membrane stiffness of a deformable mirror propagates the deformation of the actuators beyond their neighbors. When phase-retrieval algorithms are used to determine the desired shape of these mirrors, this cross-coupling-also known as influence function (IF)-is generally disregarded. We study this problem via simulations and bench tests for different target shapes to gain further insight into the phenomenon. Sound modeling of the IF effect is achieved as highlighted by the concurrence between the modeled and experimental results. In addition, we observe that the actuators IF is a key parameter that determines the accuracy of the output light pattern. Finally, it is shown that in some cases it is possible to achieve better shaping by modifying the input irradiance of the phase-retrieval algorithm. The results obtained from this analysis open the door to further improvements in this type of beam-shaping systems.

The retrieval of a buried cylindrical obstacle by a constrained modified gradient method in the H-polarization case and for Maxwellian materials

NASA Astrophysics Data System (ADS)

Lambert, M.; Lesselier, D.; Kooij, B. J.

1998-10-01

The retrieval of an unknown, possibly inhomogeneous, penetrable cylindrical obstacle buried entirely in a known homogeneous half-space - the constitutive material parameters of the obstacle and of its embedding obey a Maxwell model - is considered from single- or multiple-frequency aspect-limited data collected by ideal sensors located in air above the embedding half-space, when a small number of time-harmonic transverse electric (TE)-polarized line sources - the magnetic field H is directed along the axis of the cylinder - is also placed in air. The wavefield is modelled from a rigorous H-field domain integral-differential formulation which involves the dot product of the gradients of the single component of H and of the Green function of the stratified environment times a scalar-valued contrast function which contains the obstacle parameters (the frequency-independent, position-dependent relative permittivity and conductivity). A modified gradient method is developed in order to reconstruct the maps of such parameters within a prescribed search domain from the iterative minimization of a cost functional which incorporates both the error in reproducing the data and the error on the field built inside this domain. Non-physical values are excluded and convergence reached by incorporating in the solution algorithm, from a proper choice of unknowns, the condition that the relative permittivity be larger than or equal to 1, and the conductivity be non-negative. The efficiency of the constrained method is illustrated from noiseless and noisy synthetic data acquired independently. The importance of the choice of the initial values of the sought quantities, the need for a periodic refreshment of the constitutive parameters to avoid the algorithm providing inconsistent results, and the interest of a frequency-hopping strategy to obtain finer and finer features of the obstacle when the frequency is raised, are underlined. It is also shown that though either the permittivity map or the conductivity map can be obtained for a fair variety of cases, retrieving both of them may be difficult unless further information is made available.

Real time retrieval of volcanic cloud particles and SO2 by satellite using an improved simplified approach

NASA Astrophysics Data System (ADS)

Pugnaghi, Sergio; Guerrieri, Lorenzo; Corradini, Stefano; Merucci, Luca

2016-07-01

Volcanic plume removal (VPR) is a procedure developed to retrieve the ash optical depth, effective radius and mass, and sulfur dioxide mass contained in a volcanic cloud from the thermal radiance at 8.7, 11, and 12 µm. It is based on an estimation of a virtual image representing what the sensor would have seen in a multispectral thermal image if the volcanic cloud were not present. Ash and sulfur dioxide were retrieved by the first version of the VPR using a very simple atmospheric model that ignored the layer above the volcanic cloud. This new version takes into account the layer of atmosphere above the cloud as well as thermal radiance scattering along the line of sight of the sensor. In addition to improved results, the new version also offers an easier and faster preliminary preparation and includes other types of volcanic particles (andesite, obsidian, pumice, ice crystals, and water droplets). As in the previous version, a set of parameters regarding the volcanic area, particle types, and sensor is required to run the procedure. However, in the new version, only the mean plume temperature is required as input data. In this work, a set of parameters to compute the volcanic cloud transmittance in the three quoted bands, for all the aforementioned particles, for both Mt. Etna (Italy) and Eyjafjallajökull (Iceland) volcanoes, and for the Terra and Aqua MODIS instruments is presented. Three types of tests are carried out to verify the results of the improved VPR. The first uses all the radiative transfer simulations performed to estimate the above mentioned parameters. The second one makes use of two synthetic images, one for Mt. Etna and one for Eyjafjallajökull volcanoes. The third one compares VPR and Look-Up Table (LUT) retrievals analyzing the true image of Eyjafjallajökull volcano acquired by MODIS aboard the Aqua satellite on 11 May 2010 at 14:05 GMT.

Comparison of full-sky polarization and radiance observations to radiative transfer simulations which employ AERONET products.

PubMed

Pust, Nathan J; Dahlberg, Andrew R; Thomas, Michael J; Shaw, Joseph A

2011-09-12

Visible-band and near infrared polarization and radiance images measured with a ground-based full-sky polarimeter are compared against a successive orders of scattering (SOS) radiative transfer model for 2009 summer cloud-free days in Bozeman, Montana, USA. The polarimeter measures radiance and polarization in 10-nm bands centered at 450 nm, 490 nm, 530 nm, 630 nm, and 700 nm. AERONET products are used to represent aerosols in the SOS model, while MISR satellite BRF products are used for the surface reflectance. While model results generally agree well with observation, the simulated degree of polarization is typically higher than observed data. Potential sources of this difference may include cloud contamination and/or underestimation of the AERONET-retrieved aerosol real refractive index. Problems with the retrieved parameters are not unexpected given the low aerosol optical depth range (0.025 to 0.17 at 500 nm) during the study and the corresponding difficulties that these conditions pose to the AERONET inversion algorithm.

Completion of spectral rotating shadowband radiometers and analysis of ARM spectral short-wave data. Technical progress report, November 1, 1994--October 31, 1995

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

Michalsky, J.; Harrison, L.

1995-04-26

The authors goal in the ARM program is the improvement of radiation models used in GCMs, especially in the shortwave, (1) by providing improved shortwave radiometric measurements for the testing of models and (2) by developing methods for retrieving climatologically sensitive parameters that serve as input to shortwave and longwave models. They are acquiring downwelling direct and diffuse spectral irradiance, at six wavelengths, plus downwelling broadband longwave, and upwelling and downwelling broadband shortwave irradiances that they combined with surface and upper air data from the Albany airport as a test data set for ARM modelers. They have also developed algorithmsmore » to improve shortwave measurements made at the Southern Great Plains (SGP) ARM site by standard thermopile instruments and by the multifolter rotating shadowband radiometer (MFRSR). However, the major objective of the program has been the development of two spectral versions of the rotating shadowband radiometer. The MFRSR, has become a workhose at the CART site in Oklahoma and Kansas, and it is widely deployed in other climate programs. They have spent most of their effort this year developing techniques to retrieve column aerosol, water vapor, and ozone from direct beam spectral measurements of the MFRSR. Additionally, they have had success in calculating shortwave surface albedo and aerosol optical depth from the ratio of direct to diffuse spectral irradiance. Using the surface albedo and the global irradiance, they have calculated cloud optical depths. From cloud optical depth and liquid water measured with the microwave radiometer, they have calculated effective liquid cloud particle radii. In each case the authors have attempted to validate the approach using independent measurements or retrievals of the parameters under investigation. With the exception of the ozone intercomparison, the corroborative measurements have been made at the SGP CART site. This report highlights these results.« less

The role of cloud contamination, aerosol layer height and aerosol model in the assessment of the OMI near-UV retrievals over the ocean

NASA Astrophysics Data System (ADS)

Gassó, Santiago; Torres, Omar

2016-07-01

Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD < 0.3, 30 % for AOD > 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm ˜ < 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (< 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that the spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. In addition, it is demonstrated in an example how an incorrect assumption of the aerosol height can lead to an underestimate. Nevertheless, this is not as significant as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

Retrieval of ice thickness from polarimetric SAR data

NASA Technical Reports Server (NTRS)

Kwok, R.; Yueh, S. H.; Nghiem, S. V.; Huynh, D. D.

1993-01-01

We describe a potential procedure for retrieving ice thickness from multi-frequency polarimetric SAR data for thin ice. This procedure includes first masking out the thicker ice types with a simple classifier and then deriving the thickness of the remaining pixels using a model-inversion technique. The technique used to derive ice thickness from polarimetric observations is provided by a numerical estimator or neural network. A three-layer perceptron implemented with the backpropagation algorithm is used in this investigation with several improved aspects for a faster convergence rate and a better accuracy of the neural network. These improvements include weight initialization, normalization of the output range, the selection of offset constant, and a heuristic learning algorithm. The performance of the neural network is demonstrated by using training data generated by a theoretical scattering model for sea ice matched to the database of interest. The training data are comprised of the polarimetric backscattering coefficients of thin ice and the corresponding input ice parameters to the scattering model. The retrieved ice thickness from the theoretical backscattering coefficients is compare with the input ice thickness to the scattering model to illustrate the accuracy of the inversion method. Results indicate that the network convergence rate and accuracy are higher when multi-frequency training sets are presented. In addition, the dominant backscattering coefficients in retrieving ice thickness are found by comparing the behavior of the network trained backscattering data at various incidence angels. After the neural network is trained with the theoretical backscattering data at various incidence anges, the interconnection weights between nodes are saved and applied to the experimental data to be investigated. In this paper, we illustrate the effectiveness of this technique using polarimetric SAR data collected by the JPL DC-8 radar over a sea ice scene.

Comparative exoplanetology with consistent retrieval methods

NASA Astrophysics Data System (ADS)

Barstow, Joanna Katy; Aigrain, Suzanne; Irwin, Patrick Gerard Joseph; Sing, David

2016-10-01

The number of hot Jupiters with broad wavelength spectroscopic data has finally become large enough to make comparative planetology a reasonable proposition. New results presented by Sing et al. (2016) showcase ten hot Jupiters with spectra from the Hubble Space Telescope and photometry from Spitzer, providing insights into the presence of clouds and hazes.Spectral retrieval methods allow interpretation of exoplanet spectra using simple models, with minimal prior assumptions. This is particularly useful for exotic exoplanets, for which we may not yet fully understand the physical processes responsible for their atmospheric characteristics. Consistent spectral retrieval of a range of exoplanets can allow robust comparisons of their derived atmospheric properties.I will present a retrieval analysis using the NEMESIS code (Irwin et al. 2008) of the ten hot Jupiter spectra presented by Sing et al. (2016). The only distinctive aspects of the model for each planet are the mass and radius, and the temperature range explored. All other a priori model parameters are common to all ten objects. We test a range of cloud and haze scenarios, which include: Rayleigh-dominated and grey clouds; different cloud top pressures; and both vertically extended and vertically confined clouds.All ten planets, with the exception of WASP-39b, can be well represented by models with at least some haze or cloud. Our analysis of cloud properties has uncovered trends in cloud top pressure, vertical extent and particle size with planet equilibrium temperature. Taken together, we suggest that these trends indicate condensation and sedimentation of at least two different cloud species across planets of different temperatures, with condensates forming higher up in hotter atmospheres and moving progressively further down in cooler planets.Sing, D. et al. (2016), Nature, 529, 59Irwin, P. G. J. et al. (2008), JQSRT, 109, 1136

Radiative transfer models for retrieval of cloud parameters from EPIC/DSCOVR measurements

NASA Astrophysics Data System (ADS)

Molina García, Víctor; Sasi, Sruthy; Efremenko, Dmitry S.; Doicu, Adrian; Loyola, Diego

2018-07-01

In this paper we analyze the accuracy and efficiency of several radiative transfer models for inferring cloud parameters from radiances measured by the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR). The radiative transfer models are the exact discrete ordinate and matrix operator methods with matrix exponential, and the approximate asymptotic and equivalent Lambertian cloud models. To deal with the computationally expensive radiative transfer calculations, several acceleration techniques such as, for example, the telescoping technique, the method of false discrete ordinate, the correlated k-distribution method and the principal component analysis (PCA) are used. We found that, for the EPIC oxygen A-band absorption channel at 764 nm, the exact models using the correlated k-distribution in conjunction with PCA yield an accuracy better than 1.5% and a computation time of 18 s for radiance calculations at 5 viewing zenith angles.

exocartographer: Constraining surface maps orbital parameters of exoplanets

NASA Astrophysics Data System (ADS)

Farr, Ben; Farr, Will M.; Cowan, Nicolas B.; Haggard, Hal M.; Robinson, Tyler

2018-05-01

exocartographer solves the exo-cartography inverse problem. This flexible forward-modeling framework, written in Python, retrieves the albedo map and spin geometry of a planet based on time-resolved photometry; it uses a Markov chain Monte Carlo method to extract albedo maps and planet spin and their uncertainties. Gaussian Processes use the data to fit for the characteristic length scale of the map and enforce smooth maps.

A method for retrieving vertical ozone profiles from limb scattered measurements

NASA Astrophysics Data System (ADS)

Wang, Zijun; Chen, Shengbo; Yang, Chunyan; Jin, Lihua

2011-10-01

A two-step method is employed in this study to retrieve vertical ozone profiles using scattered measurements from the limb of the atmosphere. The combination of the Differential Optical Absorption Spectroscopy (DOAS) and the Multiplicative Algebraic Reconstruction Technique (MART) is proposed. First, the limb radiance, measured over a range of tangent heights, is processed using the DOAS technique to recover the effective column densities of atmospheric ozone. Second, these effective column densities along the lines of sight (LOSs) are inverted using the MART coupled with a forward model SCIATRAN (radiative transfer model for SCIAMACHY) to derive the ozone profiles. This method is applied to Optical Spectrograph and Infra Red Imager System (OSIRIS) radiance, using the wavelength windows 571-617 nm. Vertical ozone profiles between 10 and 48 km are derived with a vertical resolution of 1 km. The results illustrate a good agreement with the cloud-free coincident SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) ozone measurements, with deviations less than ±10% (±5% for altitudes from 17 to 47 km). Furthermore, sensitivities of retrieved ozone to aerosol, cloud parameters and NO2 concentration are also investigated.

Thermospheric density and wind retrieval from Swarm observations

NASA Astrophysics Data System (ADS)

Visser, Pieter; Doornbos, Eelco; van den IJssel, Jose; Teixeira da Encarnação, João

2013-11-01

The three-satellite ESA Swarm mission aims at mapping the Earth's global geomagnetic field at unprecedented spatial and temporal resolution and precision. Swarm also aims at observing thermospheric density and possibly horizontal winds. Precise orbit determination (POD) and Thermospheric Density and Wind (TDW) chains form part of the Swarm Constellation and Application Facility (SCARF), which will provide the so-called Level 2 products. The POD and TDW chains generate the orbit, accelerometer calibration, and thermospheric density and wind Level 2 products. The POD and TDW chains have been tested with data from the CHAMP and GRACE missions, indicating that a 3D orbit precision of about 10 cm can be reached. In addition, POD allows to determine daily accelerometer bias and scale factor values with a precision of around 10-15 nm/s2 and 0.01-0.02, respectively, for the flight direction. With these accelerometer calibration parameter values, derived thermospheric density is consistent at the 9-11% level (standard deviation) with values predicted by models (taking into account that model values are 20-30% higher). The retrieval of crosswinds forms part of the processing chain, but will be challenging. The Swarm observations will be used for further developing and improving density and wind retrieval algorithms.

Registration methods for nonblind watermark detection in digital cinema applications

NASA Astrophysics Data System (ADS)

Nguyen, Philippe; Balter, Raphaele; Montfort, Nicolas; Baudry, Severine

2003-06-01

Digital watermarking may be used to enforce copyright protection of digital cinema, by embedding in each projected movie an unique identifier (fingerprint). By identifying the source of illegal copies, watermarking will thus incite movie theatre managers to enforce copyright protection, in particular by preventing people from coming in with a handy cam. We propose here a non-blind watermark method to improve the watermark detection on very impaired sequences. We first present a study on the picture impairments caused by the projection on a screen, then acquisition with a handy cam. We show that images undergo geometric deformations, which are fully described by a projective geometry model. The sequence also undergoes spatial and temporal luminance variation. Based on this study and on the impairments models which follow, we propose a method to match the retrieved sequence to the original one. First, temporal registration is performed by comparing the average luminance variation on both sequences. To compensate for geometric transformations, we used paired points from both sequences, obtained by applying a feature points detector. The matching of the feature points then enables to retrieve the geometric transform parameters. Tests show that the watermark retrieval on rectified sequences is greatly improved.

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.

On averaging aspect ratios and distortion parameters over ice crystal population ensembles for estimating effective scattering asymmetry parameters

PubMed Central

van Diedenhoven, Bastiaan; Ackerman, Andrew S.; Fridlind, Ann M.; Cairns, Brian

2017-01-01

The use of ensemble-average values of aspect ratio and distortion parameter of hexagonal ice prisms for the estimation of ensemble-average scattering asymmetry parameters is evaluated. Using crystal aspect ratios greater than unity generally leads to ensemble-average values of aspect ratio that are inconsistent with the ensemble-average asymmetry parameters. When a definition of aspect ratio is used that limits the aspect ratio to below unity (α≤1) for both hexagonal plates and columns, the effective asymmetry parameters calculated using ensemble-average aspect ratios are generally consistent with ensemble-average asymmetry parameters, especially if aspect ratios are geometrically averaged. Ensemble-average distortion parameters generally also yield effective asymmetry parameters that are largely consistent with ensemble-average asymmetry parameters. In the case of mixtures of plates and columns, it is recommended to geometrically average the α≤1 aspect ratios and to subsequently calculate the effective asymmetry parameter using a column or plate geometry when the contribution by columns to a given mixture’s total projected area is greater or lower than 50%, respectively. In addition, we show that ensemble-average aspect ratios, distortion parameters and asymmetry parameters can generally be retrieved accurately from simulated multi-directional polarization measurements based on mixtures of varying columns and plates. However, such retrievals tend to be somewhat biased toward yielding column-like aspect ratios. Furthermore, generally large retrieval errors can occur for mixtures with approximately equal contributions of columns and plates and for ensembles with strong contributions of thin plates. PMID:28983127

Transparency of the 2 μm (5000 cm-1) methane window in Titan's atmosphere and impact on retrieved surface reflectivity

NASA Astrophysics Data System (ADS)

Rannou, Pascal; Seignovert, Benoit; Le Mouélic, Stéphane; Sotin, Christophe

2016-10-01

The study of Titan properties with remote sensing relies on a good knowledge of the atmosphere properties. The in-situ observations made by Huygens combined with recent advances in the definition of methane properties enable to model and interpret observations with a very good accuracy. Thanks to these progresses, we can analyze in this work the observations made at the limb of Titan in order to retrieve information on the haze properties as its vertical profiles and its spectral behaviour along the VIMS/Cassini range (from 0.88 to 5.1 μm). However, for applications to real atmospheres, one need to account for the widening of the spectroscopic lines (e.g., Voigt profile) and apply an empirical cut-off of the far wings. In general, this is a multiplying function of the wavenumber, f(ν), applied to the Voigt profile that allows a faster decay of the wing profile beyond a given distance from the center of the line ν0 : f(ν)=1 if |ν- ν0| ≤ Δν, and f(ν)=exp(-|ν- ν0|/ σ) if |ν- ν0| > Δν. Although the 2-μm window is apparently straitforward to model, it appears that the standard cut-off parameters (that is Δν ~ 26 cm-1 and σ ~ 120 cm-1) which is used for other windows in Titan's atmosphere is not adequat for this window. Other sets of parameter must be used to reproduce Titan spectrum at 2 μm. However, there is no convergence of the results between these works and a large variety of cut-off parameters are used. Alternatively, it was found that some gas absorptions (ethane and another unknown gas) leave a signature around 2-μm and also affect the transparency in this window. In our study we make an exhaustive investigation on the cut-off parameters to determine which are the best couples of parameters to fit the 2-μm window. We also evaluated how gaseous absorptions can allow to reach a satisfactory agreement and, especially, if it allows to match observations with the standard cut-off. Finally, we investigate the impact of the different solutions (different cut-off, with or without supplementary absorptions) on the retrieved surface albedo.

Towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations

NASA Astrophysics Data System (ADS)

Bircher, Simone; Richaume, Philippe; Mahmoodi, Ali; Mialon, Arnaud; Fernandez-Moran, Roberto; Wigneron, Jean-Pierre; Demontoux, François; Jonard, François; Weihermüller, Lutz; Andreasen, Mie; Rautiainen, Kimmo; Ikonen, Jaakko; Schwank, Mike; Drusch, Mattias; Kerr, Yann H.

2017-04-01

From the passive L-band microwave radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) space mission global surface soil moisture data is retrieved every 2 - 3 days. Thus far, the empirical L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model applied in the SMOS soil moisture retrieval algorithm is exclusively calibrated over test sites in dry and temperate climate zones. Furthermore, the included dielectric mixing model relating soil moisture to relative permittivity accounts only for mineral soils. However, soil moisture monitoring over the higher Northern latitudes is crucial since these regions are especially sensitive to climate change. A considerable positive feedback is expected if thawing of these extremely organic soils supports carbon decomposition and release to the atmosphere. Due to differing structural characteristics and thus varying bound water fractions, the relative permittivity of organic material is lower than that of the most mineral soils at a given water content. This assumption was verified by means of L-band relative permittivity laboratory measurements of organic and mineral substrates from various sites in Denmark, Finland, Scotland and Siberia using a resonant cavity. Based on these data, a simple empirical dielectric model for organic soils was derived and implemented in the SMOS Soil Moisture Level 2 Prototype Processor (SML2PP). Unfortunately, the current SMOS retrieved soil moisture product seems to show unrealistically low values compared to in situ soil moisture data collected from organic surface layers in North America, Europe and the Tibetan Plateau so that the impact of the dielectric model for organic soils cannot really be tested. A simplified SMOS processing scheme yielding higher soil moisture levels has recently been proposed and is presently under investigation. Furthermore, recalibration of the model parameters accounting for vegetation and roughness effects that were thus far only evaluated using the default dielectric model for mineral soils is ongoing for the "organic" L-MEB version. Additionally, in order to decide where a soil moisture retrieval using the "organic" dielectric model should be triggered, information on soil organic matter content in the soil surface layer has to be considered in the retrieval algorithm. For this purpose, SoilGrids (www.soilgrids.org) providing soil organic carbon content (SOCC) in g/kg is under study. A SOCC threshold based on the relation between the SoilGrids' SOCC and the presence of organic soil surface layers (relevant to alter the microwave L-band emissions from the land surface) in the SoilGrids' source soil profile information has to be established. In this communication, we present the current status of the above outlined studies with the objective to advance towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations.

A proposal of fuzzy connective with learning function and its application to fuzzy retrieval system

NASA Technical Reports Server (NTRS)

Hayashi, Isao; Naito, Eiichi; Ozawa, Jun; Wakami, Noboru

1993-01-01

A new fuzzy connective and a structure of network constructed by fuzzy connectives are proposed to overcome a drawback of conventional fuzzy retrieval systems. This network represents a retrieval query and the fuzzy connectives in networks have a learning function to adjust its parameters by data from a database and outputs of a user. The fuzzy retrieval systems employing this network are also constructed. Users can retrieve results even with a query whose attributes do not exist in a database schema and can get satisfactory results for variety of thinkings by learning function.

Improving Database Simulations for Bayesian Precipitation Retrieval using Non-Spherical Ice Particles

NASA Astrophysics Data System (ADS)

Ringerud, S.; Skofronick Jackson, G.; Kulie, M.; Randel, D.

2016-12-01

NASA's Global Precipitation Measurement Mission (GPM) provides a wealth of both active and passive microwave observations aimed at furthering understanding of global precipitation and the hydrologic cycle. Employing a constellation of passive microwave radiometers increases global coverage and sampling, while the core satellite acts as a transfer standard, enabling consistent retrievals across individual constellation members. The transfer standard is applied in the form of a physically based a priori database constructed for use in Bayesian retrieval algorithms for each radiometer. The database is constructed using hydrometeor profiles optimized for the best fit to simultaneous active/passive core satellite measurements via the GPM Combined Algorithm. Initial validation of GPM rainfall products using the combined database suggests high retrieval errors for convective precipitation over land and at high latitudes. In such regimes, the signal from ice scattering observed at the higher microwave frequencies becomes particularly important for detecting and retrieving precipitation. For cross-track sounders such as MHS and SAPHIR, this signal is crucial. It is therefore important that the scattering signals associated with precipitation are accurately represented and modeled in the retrieval database. In the current GPM combined retrieval and constellation databases, ice hydrometeors are represented as "fluffy spheres", with assumed density and scattering parameters calculated using Mie theory. Resulting simulated Tb agree reasonably well at frequencies up to 89 GHz, but show significant biases at higher frequencies. In this work the database is recreated using an ensemble of non-spherical ice particles with single scattering properties calculated using discrete dipole approximation. Simulated Tb agreement is significantly improved across the high frequencies, decreasing biases by an order of magnitude in several of the channels. The new database is applied for a sample of GPM constellation retrievals and the retrieved precipitation rates compared, to demonstrate areas where the use of more complex ice particles will have the greatest effect upon the final retrievals.

Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument

NASA Astrophysics Data System (ADS)

Shang, H.; Chen, L.; Bréon, F. M.; Letu, H.; Li, S.; Wang, Z.; Su, L.

2015-11-01

The principles of cloud droplet size retrieval via Polarization and Directionality of the Earth's Reflectance (POLDER) requires that clouds be horizontally homogeneous. The retrieval is performed by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval and analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-grid-scale variability in droplet effective radius (CDR) can significantly reduce valid retrievals and introduce small biases to the CDR (~ 1.5 μm) and effective variance (EV) estimates. Nevertheless, the sub-grid-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval using limited observations is accurate and is largely free of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, measurements in the primary rainbow region (137-145°) are used to ensure retrievals of large droplet (> 15 μm) and to reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data from June 2008, and the new CDR results are compared with the operational CDRs. The comparison shows that the operational CDRs tend to be underestimated for large droplets because the cloudbow oscillations in the scattering angle region of 145-165° are weak for cloud fields with CDR > 15 μm. Finally, a sub-grid-scale retrieval case demonstrates that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size distribution parameters from POLDER measurements.

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.

Modeling the dynamics of recognition memory testing with an integrated model of retrieval and decision making.

PubMed

Osth, Adam F; Jansson, Anna; Dennis, Simon; Heathcote, Andrew

2018-08-01

A robust finding in recognition memory is that performance declines monotonically across test trials. Despite the prevalence of this decline, there is a lack of consensus on the mechanism responsible. Three hypotheses have been put forward: (1) interference is caused by learning of test items (2) the test items cause a shift in the context representation used to cue memory and (3) participants change their speed-accuracy thresholds through the course of testing. We implemented all three possibilities in a combined model of recognition memory and decision making, which inherits the memory retrieval elements of the Osth and Dennis (2015) model and uses the diffusion decision model (DDM: Ratcliff, 1978) to generate choice and response times. We applied the model to four datasets that represent three challenges, the findings that: (1) the number of test items plays a larger role in determining performance than the number of studied items, (2) performance decreases less for strong items than weak items in pure lists but not in mixed lists, and (3) lexical decision trials interspersed between recognition test trials do not increase the rate at which performance declines. Analysis of the model's parameter estimates suggests that item interference plays a weak role in explaining the effects of recognition testing, while context drift plays a very large role. These results are consistent with prior work showing a weak role for item noise in recognition memory and that retrieval is a strong cause of context change in episodic memory. Copyright © 2018 Elsevier Inc. All rights reserved.

Investigation of antenna pattern constraints for passive geosynchronous microwave imaging radiometers

NASA Technical Reports Server (NTRS)

Gasiewski, A. J.; Skofronick, G. M.

1992-01-01

Progress by investigators at Georgia Tech in defining the requirements for large space antennas for passive microwave Earth imaging systems is reviewed. In order to determine antenna constraints (e.g., the aperture size, illumination taper, and gain uncertainty limits) necessary for the retrieval of geophysical parameters (e.g., rain rate) with adequate spatial resolution and accuracy, a numerical simulation of the passive microwave observation and retrieval process is being developed. Due to the small spatial scale of precipitation and the nonlinear relationships between precipitation parameters (e.g., rain rate, water density profile) and observed brightness temperatures, the retrieval of precipitation parameters are of primary interest in the simulation studies. Major components of the simulation are described as well as progress and plans for completion. The overall goal of providing quantitative assessments of the accuracy of candidate geosynchronous and low-Earth orbiting imaging systems will continue under a separate grant.

Atmospheric Retrievals from Exoplanet Observations and Simulations with BART

NASA Astrophysics Data System (ADS)

Harrington, Joseph

This project will determine the observing plans needed to retrieve exoplanet atmospheric composition and thermal profiles over a broad range of planets, stars, instruments, and observing modes. Characterizing exoplanets is hard. The dim planets orbit bright stars, giving orders of magnitude more relative noise than for solar-system planets. Advanced statistical techniques are needed to determine what the data can - and more importantly cannot - say. We therefore developed Bayesian Atmospheric Radiative Transfer (BART). BART explores the parameter space of atmospheric chemical abundances and thermal profiles using Differential-Evolution Markov-Chain Monte Carlo. It generates thousands of candidate spectra, integrates over observational bandpasses, and compares to data, generating a statistical model for an atmosphere's composition and thermal structure. At best, it gives abundances and thermal profiles with uncertainties. At worst, it shows what kinds of planets the data allow. It also gives parameter correlations. BART is open-source, designed for community use and extension (http://github.com/exosports/BART). Three arXived PhD theses (papers in publication) provide technical documentation, tests, and application to Spitzer and HST data. There are detailed user and programmer manuals and community support forums. Exoplanet analysis techniques must be tested against synthetic data, where the answer is known, and vetted by statisticians. Unfortunately, this has rarely been done, and never sufficiently. Several recent papers question the entire body of Spitzer exoplanet observations, because different analyses of the same data give different results. The latest method, pixel-level decorrelation, produces results that diverge from an emerging consensus. We do not know the retrieval problem's strengths and weaknesses relative to low SNR, red noise, low resolution, instrument systematics, or incomplete spectral line lists. In observing eclipses and transits, we assume the planet has uniform composition and the same temperature profile everywhere. We do not know this assumption's impact. While Spitzer and HST have few exoplanet observing modes, JWST will have over 20. Given the signal challenges and the complexity of retrieval, modeling the observations and data analysis is the best way to optimize an observing plan. Our project solves all of these problems. Using only open-source codes, with tools available to the community for their immediate application in JWST and HST proposals and analyses, we will produce a faithful simulator of 2D spectral and photometric frames from each JWST exoplanet mode (WFC3 spatial scan mode works already), including jitter and intrapixel effects. We will extract and calibrate data, analyzing them with BART. Given planetary input spectra for terrestrial, super-Earth, Neptune, and Jupiterclass planets, and a variety of stellar spectra, we will determine the best combination of observations to recover each atmosphere, and the limits where low SNR or spectral coverage produce deceptive results. To facilitate these analyses, we will adapt an existing cloud model to BART, add condensate code now being written to its thermochemical model, include scattering, add a 3D atmosphere module (for dayside occultation mapping and the 1D vs. 3D question), and improve performance and documentation, among other improvements. We will host a web site and community discussions online and at conferences about retrieval issues. We will develop validation tests for radiative-transfer and BART-style retrieval codes, and provide examples to validate others' codes. We will engage the retrieval community in data challenges. We will provide web-enabled tools to specify planets easily for modeling. We will make all of these tools, tests, and comparisons available online so everyone can use them to maximize NASA's investment in high-end observing capabilities to characterize exoplanets.

A framework for combining multiple soil moisture retrievals based on maximizing temporal correlation

NASA Astrophysics Data System (ADS)

Kim, Seokhyeon; Parinussa, Robert M.; Liu, Yi. Y.; Johnson, Fiona M.; Sharma, Ashish

2015-08-01

A method for combining two microwave satellite soil moisture products by maximizing the temporal correlation with a reference data set has been developed. The method was applied to two global soil moisture data sets, Japan Aerospace Exploration Agency (JAXA) and Land Parameter Retrieval Model (LPRM), retrieved from the Advanced Microwave Scanning Radiometer 2 observations for the period 2012-2014. A global comparison revealed superior results of the combined product compared to the individual products against the reference data set of ERA-Interim volumetric water content. The global mean temporal correlation coefficient of the combined product with this reference was 0.52 which outperforms the individual JAXA (0.35) as well as the LPRM (0.45) product. Additionally, the performance was evaluated against in situ observations from the International Soil Moisture Network. The combined data set showed a significant improvement in temporal correlation coefficients in the validation compared to JAXA and minor improvements for the LPRM product.

Accuracy Assessments of Cloud Droplet Size Retrievals from Polarized Reflectance Measurements by the Research Scanning Polarimeter

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Cairns, Brian; Emde, Claudia; Ackerman, Andrew S.; vanDiedenhove, Bastiaan

2012-01-01

We present an algorithm for the retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was on-board of the NASA Glory satellite. This instrument measures both polarized and total reflectance in 9 spectral channels with central wavelengths ranging from 410 to 2260 nm. The cloud droplet size retrievals use the polarized reflectance in the scattering angle range between 135deg and 165deg, where they exhibit the sharply defined structure known as the rain- or cloud-bow. The shape of the rainbow is determined mainly by the single scattering properties of cloud particles. This significantly simplifies both forward modeling and inversions, while also substantially reducing uncertainties caused by the aerosol loading and possible presence of undetected clouds nearby. In this study we present the accuracy evaluation of our algorithm based on the results of sensitivity tests performed using realistic simulated cloud radiation fields.

Current Status and Future Plan of Arctic Sea Ice monitoring in South Korea

NASA Astrophysics Data System (ADS)

Shin, J.; Park, J.

2016-12-01

Arctic sea ice is one of the most important parameters in climate. For monitoring of sea ice changes, the National Meteorological Satellite Center (NMSC) of Korea Metrological Administration has developed the "Arctic sea ice monitoring system" to retrieve the sea ice extent and surface roughness using microwave sensor data, and statistical prediction model for Arctic sea ice extent. This system has been implemented to the web site for real-time public service. The sea ice information can be retrieved using the spaceborne microwave sensor-Special Sensor Microwave Imager/Sounder (SSMI/S). The sea ice information like sea ice extent, sea ice surface roughness, and predictive sea ice extent are produced weekly base since 2007. We also publish the "Analysis report of the Arctic sea ice" twice a year. We are trying to add more sea ice information into this system. Details of current status and future plan of Arctic sea ice monitoring and the methodology of the sea ice information retrievals will be presented in the meeting.

Retrieval of nonprecipitating liquid water cloud parameters from microwave data - A simulation study

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Diak, George R.

1992-01-01

A new microwave algorithm, analogous to the IR 'radiance-ratioing' method of Eyre and Menzel (1989) is developed to retrieve the height and 'effective' fraction (defined as the product of the emissivity times the actual physical fractional coverage) of nonprecipitating water clouds using various pairs of the 20 microwave channels planned for the Advanced Microwave Sounding Unit (AMSU), an instrument slated to fly on polar-orbiting satellites beginning in 1994. The results of a simulation study are presented to provide some insights into the potentials of this technique using different AMSU channel combinations. This study suggests that the use of the oxygen channels 3 and 5 and water vapor channels 19 and 20 will produce the most accurate retrievals of liquid water cloud parameters and the highest percentage of good-quality retrievals over a range of meteorological and cloud conditions.

Combined application of Sentinel2A data and growth modelling for novel monitoring and prediction of pasture yields

NASA Astrophysics Data System (ADS)

Verhoef, A.; Punalekar, S.; Quaife, T. L.; Humphries, D.; Reynolds, C.

2017-12-01

Currently, 30% of the world's land area is covered by permanent pasture. Grazing ruminants convert forage materials into milk and meat for human consumption; ruminant production is a key agricultural enterprise. Management of pasture farms (nutrient and herbi-/pesticides application, grazing rotations) is often suboptimal. Furthermore, adverse weather can have negative effects on pasture growth and quality. Near real-time herbage monitoring and prediction could help improve farm profitability. While the use of remote sensing (RS) in the context of arable crop growth prediction is becoming more established, the same is not true for pasture. However, recently launched Sentinel satellites offer real opportunities to exploit high spatio-temporal resolution datasets for effective monitoring of pastures, as well as crops. A perennial grazed ryegrass field in the Southwest of the UK was monitored regularly using field hyperspectral spectro-radiometers. Simultaneously, leaf area index (LAI) was measured using a ceptometer, and yield was measured, indirectly using a `plate meter' and directly by destructive sampling. Two sets of spectral data were used to retrieve LAI with the PROSAIL radiative transfer model: (i) Sentinel-2A bands convolved from field spectral data, (ii) actual Sentinel-2A image pixels for the sampling plots. Retrieved LAI was compared against field observations. LAI estimates were assimilated in a bespoke growth model (including grazing and management), driven by weather data, for calibration of sensitive parameters using a 4D-Var scheme, to obtain pasture biomass. The developed approach was used to study a pasture farm in the South of the UK, for which a large number of Sentinel-2A images were available throughout 2016-17. Retrieved LAI compared well with in-situ LAI, and significantly improved yield estimates. The calibrated model parameters compared well with literature values. The model, guided by satellite data and general information on farm operations, was able to estimate pasture biomass reasonably well. Assimilation of RS information in grass growth models offers a potential tool to monitor pasture growth in response to weather and management and may be used effectively in pasture prediction tools for dairy farmers.

On the VHF Source Retrieval Errors Associated with Lightning Mapping Arrays (LMAs)

NASA Technical Reports Server (NTRS)

Koshak, W.

2016-01-01

This presentation examines in detail the standard retrieval method: that of retrieving the (x, y, z, t) parameters of a lightning VHF point source from multiple ground-based Lightning Mapping Array (LMA) time-of-arrival (TOA) observations. The solution is found by minimizing a chi-squared function via the Levenberg-Marquardt algorithm. The associated forward problem is examined to illustrate the importance of signal-to-noise ratio (SNR). Monte Carlo simulated retrievals are used to assess the benefits of changing various LMA network properties. A generalized retrieval method is also introduced that, in addition to TOA data, uses LMA electric field amplitude measurements to retrieve a transient VHF dipole moment source.

Parameter estimation for a cohesive sediment transport model by assimilating satellite observations in the Hangzhou Bay: Temporal variations and spatial distributions

NASA Astrophysics Data System (ADS)

Wang, Daosheng; Zhang, Jicai; He, Xianqiang; Chu, Dongdong; Lv, Xianqing; Wang, Ya Ping; Yang, Yang; Fan, Daidu; Gao, Shu

2018-01-01

Model parameters in the suspended cohesive sediment transport models are critical for the accurate simulation of suspended sediment concentrations (SSCs). Difficulties in estimating the model parameters still prevent numerical modeling of the sediment transport from achieving a high level of predictability. Based on a three-dimensional cohesive sediment transport model and its adjoint model, the satellite remote sensing data of SSCs during both spring tide and neap tide, retrieved from Geostationary Ocean Color Imager (GOCI), are assimilated to synchronously estimate four spatially and temporally varying parameters in the Hangzhou Bay in China, including settling velocity, resuspension rate, inflow open boundary conditions and initial conditions. After data assimilation, the model performance is significantly improved. Through several sensitivity experiments, the spatial and temporal variation tendencies of the estimated model parameters are verified to be robust and not affected by model settings. The pattern for the variations of the estimated parameters is analyzed and summarized. The temporal variations and spatial distributions of the estimated settling velocity are negatively correlated with current speed, which can be explained using the combination of flocculation process and Stokes' law. The temporal variations and spatial distributions of the estimated resuspension rate are also negatively correlated with current speed, which are related to the grain size of the seabed sediments under different current velocities. Besides, the estimated inflow open boundary conditions reach the local maximum values near the low water slack conditions and the estimated initial conditions are negatively correlated with water depth, which is consistent with the general understanding. The relationships between the estimated parameters and the hydrodynamic fields can be suggestive for improving the parameterization in cohesive sediment transport models.

Inversion of atmospheric optical parameters from elastic-backscatter lidar returns using a Kalman filter

NASA Astrophysics Data System (ADS)

Rocadenbosch, Francesc; Comeron, Adolfo; Vazquez, Gregori; Rodriguez-Gomez, Alejandro; Soriano, Cecilia; Baldasano, Jose M.

1998-12-01

Up to now, retrieval of the atmospheric extinction and backscatter has mainly relied on standard straightforward non-memory procedures such as slope-method, exponential- curve fitting and Klett's method. Yet, their performance becomes ultimately limited by the inherent lack of adaptability as they only work with present returns and neither past estimations, nor the statistics of the signals or a prior uncertainties are taken into account. In this work, a first inversion of the backscatter and extinction- to-backscatter ratio from pulsed elastic-backscatter lidar returns is tackled by means of an extended Kalman filter (EKF), which overcomes these limitations. Thus, as long as different return signals income,the filter updates itself weighted by the unbalance between the a priori estimates of the optical parameters and the new ones based on a minimum variance criterion. Calibration errors or initialization uncertainties can be assimilated also. The study begins with the formulation of the inversion problem and an appropriate stochastic model. Based on extensive simulation and realistic conditions, it is shown that the EKF approach enables to retrieve the sought-after optical parameters as time-range-dependent functions and hence, to track the atmospheric evolution, its performance being only limited by the quality and availability of the 'a priori' information and the accuracy of the atmospheric model assumed. The study ends with an encouraging practical inversion of a live-scene measured with the Nd:YAG elastic-backscatter lidar station at our premises in Barcelona.

Field-scale surface soil moisture retrieval using L-band synthetic aperture radar data: shrublands examples

NASA Astrophysics Data System (ADS)

Kim, S.; Arii, M.; Jackson, T. J.

2017-12-01

L-band airborne synthetic aperture radar (SAR) observations at 7-m spatial resolution were made over California shrublands to better understand the effects of soil and vegetation parameters on backscattering coefficient (σ0). Temporal changes in σ0 of up to 3 dB were highly correlated to surface soil moisture but not to vegetation, even though vegetation water content (VWC) varied seasonally by a factor of two. HH was always greater than VV, suggesting the importance of double-bounce scattering by the woody parts. However, the geometric and dielectric properties of the woody parts did not vary significantly over time. Instead the changes in VWC occurred primarily in thin leaves that may not meaningfully influence absorption and scattering. A physically-based model for single scattering by discrete elements of plants successfully simulated the magnitude of the temporal variations in HH, VV, and HH/VV with a difference of less than 0.9 dB. In order to simulate the observations, the VWC input of the plant to the model was formulated as a function of plant's dielectric property (water fraction) while the plant geometry remains static in time. In comparison, when the VWC input was characterized by the geometry of a growing plant, the model performed poorly in describing the observed patterns in the σ0 changes. The modeling results offer explanation of the observation that soil moisture correlated highly with σ0: the dominant mechanisms for HH and VV are double-bounce scattering by trunk, and soil surface scattering, respectively. The time-series inversion of the physical model was able to retrieve soil moisture with the difference of -0.037 m3/m3 (mean), 0.025 m3/m3 (standard deviation), and 0.89 (correlation). Together with the previous results over croplands using the SAR data offering 0.05 m3/m3 retrieval accuracy, we will demonstrate the efficacy of the model-based time-series soil moisture retrieval at field scales.

Remote sensing of PM2.5 from ground-based optical measurements

NASA Astrophysics Data System (ADS)

Li, S.; Joseph, E.; Min, Q.

2014-12-01

Remote sensing of particulate matter concentration with aerodynamic diameter smaller than 2.5 um(PM2.5) by using ground-based optical measurements of aerosols is investigated based on 6 years of hourly average measurements of aerosol optical properties, PM2.5, ceilometer backscatter coefficients and meteorological factors from Howard University Beltsville Campus facility (HUBC). The accuracy of quantitative retrieval of PM2.5 using aerosol optical depth (AOD) is limited due to changes in aerosol size distribution and vertical distribution. In this study, ceilometer backscatter coefficients are used to provide vertical information of aerosol. It is found that the PM2.5-AOD ratio can vary largely for different aerosol vertical distributions. The ratio is also sensitive to mode parameters of bimodal lognormal aerosol size distribution when the geometric mean radius for the fine mode is small. Using two Angstrom exponents calculated at three wavelengths of 415, 500, 860nm are found better representing aerosol size distributions than only using one Angstrom exponent. A regression model is proposed to assess the impacts of different factors on the retrieval of PM2.5. Compared to a simple linear regression model, the new model combining AOD and ceilometer backscatter can prominently improve the fitting of PM2.5. The contribution of further introducing Angstrom coefficients is apparent. Using combined measurements of AOD, ceilometer backscatter, Angstrom coefficients and meteorological parameters in the regression model can get a correlation coefficient of 0.79 between fitted and expected PM2.5.

Dynamics of Mount Somma-Vesuvius edifice: from stress field inversion to analogue and numerical modelling

NASA Astrophysics Data System (ADS)

De Matteo, Ada; Massa, Bruno; D'Auria, Luca; Castaldo, Raffaele

2017-04-01

Geological processes are generally very complex and too slow to be directly observed in their completeness; modelling procedures overcome this limit. The state of stress in the upper lithosphere is the main responsible for driving geodynamical processes; in order to retrieve the active stress field in a rock volume, stress inversion techniques can be applied on both seismological and structural datasets. This approach has been successfully applied to active tectonics as well as volcanic areas. In this context the best approach in managing heterogeneous datasets in volcanic environments consists in the analysis of spatial variations of the stress field by applying robust techniques of inversion. The study of volcanic seismicity is an efficient tool to retrieve spatial and temporal pattern of the pre-, syn- and inter-eruptive stress field: magma migration as well as dynamics of magma chamber and hydrothermal system are directly connected to the volcanic seismicity. Additionally, analysis of the temporal variations of stress field pattern in volcanoes could be a useful monitoring tool. Recently the stress field acting on several active volcanoes has been investigated by using stress inversion techniques on seismological datasets (Massa et al., 2016). The Bayesian Right Trihedra Method (BRTM; D'Auria and Massa, 2015) is able to successfully manage heterogeneous datasets allowing the identification of regional fields locally overcame by the stress field due to volcano specific dynamics. In particular, the analysis of seismicity and stress field inversion at the Somma-Vesuvius highlighted the presence of two superposed volumes characterized by different behaviour and stress field pattern: a top volume dominated by an extensional stress field, in accordance with a gravitational spreading-style of deformation, and a bottom volume related to a regional extensional stress field. In addition, in order to evaluate the dynamics of deformation, both analogue and numerical modelling are being performed. Scaled analogue models of the Somma-Vesuvius are being built accordingly with the actual geometrical asymmetry of the volcano, varying just few parameters connected to the uncertainty of the depth and thickness of a buried decoupling layer. Experiments are being monitored by an optical stereo image system, useful to build a 3D time-lapsed models used to retrieve the model deformations. Simultaneously, a time-dependent 3D Finite Element model is being carried out in a fluid-dynamic context by fixing the same parameters of the proposed analogue model. Finally, a comparative analysis is being made between the model deformations and the DInSAR measurements derived from satellite data in order to estimate the uncertain parameters (i.e., thickness and viscosity of ductile layer). Preliminary results of the analogue models fit with the hypothesis of a spreading deformation active at the Somma-Vesuvius.

Limb darkening and exoplanets - II. Choosing the best law for optimal retrieval of transit parameters

NASA Astrophysics Data System (ADS)

Espinoza, Néstor; Jordán, Andrés

2016-04-01

Very precise measurements of exoplanet transit light curves both from ground- and space-based observatories make it now possible to fit the limb-darkening coefficients in the transit-fitting procedure rather than fix them to theoretical values. This strategy has been shown to give better results, as fixing the coefficients to theoretical values can give rise to important systematic errors which directly impact the physical properties of the system derived from such light curves such as the planetary radius. However, studies of the effect of limb-darkening assumptions on the retrieved parameters have mostly focused on the widely used quadratic limb-darkening law, leaving out other proposed laws that are either simpler or better descriptions of model intensity profiles. In this work, we show that laws such as the logarithmic, square-root and three-parameter law do a better job that the quadratic and linear laws when deriving parameters from transit light curves, both in terms of bias and precision, for a wide range of situations. We therefore recommend to study which law to use on a case-by-case basis. We provide code to guide the decision of when to use each of these laws and select the optimal one in a mean-square error sense, which we note has a dependence on both stellar and transit parameters. Finally, we demonstrate that the so-called exponential law is non-physical as it typically produces negative intensities close to the limb and should therefore not be used.

Investigating the Use of a Simplified Aerosol Parameterization in Space-Based XCO2 Retrievals from OCO-2

NASA Astrophysics Data System (ADS)

Nelson, R. R.; O'Dell, C.

2017-12-01

The primary goal of OCO-2 is to use hyperspectral measurements of reflected near-infrared sunlight to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with high accuracy. This is only possible for measurements of scenes nearly free of optically thick clouds and aerosols. As some cloud or aerosol contamination will always be present, the OCO-2 retrieval algorithm includes clouds and aerosols as retrieved properties in its state vector. Information content analyses demonstrate that there are only 2-6 pieces of information about aerosols in the OCO-2 radiances. However, the upcoming OCO-2 algorithm (B8) attempts to retrieve 9 aerosol parameters; this over-fitting can hinder convergence and produce multiple solutions. In this work, we develop a simplified cloud and aerosol parameterization that intelligently reduces the number of retrieved parameters to 5 by only retrieving information about two aerosol layers: a lower tropospheric layer and an upper tropospheric / stratospheric layer. We retrieve the optical depth of each layer and the height of the lower tropospheric layer. Each of these layers contains a mixture of fine and coarse mode aerosol. In comparisons between OCO-2 XCO2 estimates and validation sources including TCCON, this scheme performs about as well as the more complicated OCO-2 retrieval algorithm, but has the potential benefits of more interpretable aerosol results, faster convergence, less nonlinearity, and greater throughput. We also investigate the dependence of our results on the optical properties of the fine and coarse mode aerosol types, such as their effective radii and the environmental relative humidity.

Regional trace gas monitoring simplified - A linear retrieval scheme for carbon monoxide from hyperspectral soundings

NASA Astrophysics Data System (ADS)

Smith, N.; Huang, A.; Weisz, E.; Annegarn, H. J.

2011-12-01

The Fast Linear Inversion Trace gas System (FLITS) is designed to retrieve tropospheric total column trace gas densities [molec.cm-2] from space-borne hyperspectral infrared soundings. The objective to develop a new retrieval scheme was motivated by the need for near real-time air quality monitoring at high spatial resolution. We present a case study of FLITS carbon monoxide (CO) retrievals from daytime (descending orbit) Infrared Atmospheric Sounding Interferometer (IASI) measurements that have a 0.5 cm-1 spectral resolution and 12 km footprint at nadir. The standard Level 2 IASI CO retrieval product (COL2) is available in near real-time but is spatially averaged over 2 x 2 pixels, or 50 x 50 km, and thus more suitable for global analysis. The study region is Southern Africa (south of the equator) for the period 28-31 August 2008. An atmospheric background estimate is obtained from a chemical transport model, emissivity from regional measurements and surface temperature (ST) from space-borne retrievals. The CO background error is set to 10%. FLITS retrieves CO by assuming a simple linear relationship between the IASI measurements and background estimate of the atmosphere and surface parameters. This differs from the COL2 algorithm that treats CO retrieval as a moderately non-linear problem. When compared to COL2, the FLITS retrievals display similar trends in distribution and transport of CO over time with the advantage of an improved spatial resolution (single-pixel). The value of the averaging kernel (A) is consistently above 0.5 and indicates that FLITS retrievals have a stable dependence on the measurement. This stability is achieved through careful channel selection in the strongest CO absorption lines (2050-2225 cm-1) and joint retrieval with skin temperature (IASI sensitivity to CO is highly correlated with ST), thus no spatial averaging is necessary. We conclude that the simplicity and stability of FLITS make it useful first as a research tool, i.e. the algorithm is easy to understand and computationally simple enough to run on most desktop computers, and second, as an operational tool that can calculate near real-time CO retrievals at instrument resolution for regional monitoring.

Improving information retrieval in functional analysis.

PubMed

Rodriguez, Juan C; González, Germán A; Fresno, Cristóbal; Llera, Andrea S; Fernández, Elmer A

2016-12-01

Transcriptome analysis is essential to understand the mechanisms regulating key biological processes and functions. The first step usually consists of identifying candidate genes; to find out which pathways are affected by those genes, however, functional analysis (FA) is mandatory. The most frequently used strategies for this purpose are Gene Set and Singular Enrichment Analysis (GSEA and SEA) over Gene Ontology. Several statistical methods have been developed and compared in terms of computational efficiency and/or statistical appropriateness. However, whether their results are similar or complementary, the sensitivity to parameter settings, or possible bias in the analyzed terms has not been addressed so far. Here, two GSEA and four SEA methods and their parameter combinations were evaluated in six datasets by comparing two breast cancer subtypes with well-known differences in genetic background and patient outcomes. We show that GSEA and SEA lead to different results depending on the chosen statistic, model and/or parameters. Both approaches provide complementary results from a biological perspective. Hence, an Integrative Functional Analysis (IFA) tool is proposed to improve information retrieval in FA. It provides a common gene expression analytic framework that grants a comprehensive and coherent analysis. Only a minimal user parameter setting is required, since the best SEA/GSEA alternatives are integrated. IFA utility was demonstrated by evaluating four prostate cancer and the TCGA breast cancer microarray datasets, which showed its biological generalization capabilities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Radiation Products based on a constellation of Geostationary Satellites

NASA Astrophysics Data System (ADS)

Trigo, I. F.; Freitas, S. C.; Barroso, C.; Macedo, J.; Perdigão, R.; Silva, R.; Viterbo, P.

2012-04-01

The various components of the surface radiation budget present high variability in time and space, particularly over land surfaces where spatial heterogeneity of the upward fluxes is high. Geostationary satellites are well-suited to describe the daily cycle of downward and upward radiation fluxes and present spatial resolutions of the order of 3-to-5 km at sub-satellite point, acceptable for many applications. The work presented here is being carried out within the framework of Geoland-2 project, and aims the use of data from geostationary platforms to generate, archive and distribute in near real time four component of the surface radiation budget: land surface albedo, land surface temperature (LST) and downward short- and long-wave fluxes at the surface. All four components are retrieved from the following satellites - GOES-W covering North and South America, Meteosat Second Generation (MSG) covering essentially Europe and Africa, and MTSAT covering part of Asia and Australia. The variables are retrieved independently from each satellite and then merged into a single field, with a 5 km spatial resolution. Data are generated hourly in the case of the downward fluxes and LST, and 10-daily in the case of albedo. In regions covered by both GOES and MSG disks, the interpolated field makes use of both retrievals, giving more weight to those with lower uncertainty. The four components of the surface radiation budget described above are assessed through comparisons with similar parameters retrieved from other sensors (e.g., MODIS, CERES) or from models (e.g., ECMWF forecasts), as well as with in situ observations when available. The presentation will be focused on a brief description of algorithms and auxiliary data used in product estimation. The results of inter-comparisons with other data sources, along with the identification of the retrieval conditions that allow optimal / sub-optimal estimation of these surface radiation parameters will also be analysed. The radiation products generated within the Geoland-2 project are freely available to the user community.

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.

Spatially detailed retrievals of spring phenology from single-season high-resolution image time series

NASA Astrophysics Data System (ADS)

Vrieling, Anton; Skidmore, Andrew K.; Wang, Tiejun; Meroni, Michele; Ens, Bruno J.; Oosterbeek, Kees; O'Connor, Brian; Darvishzadeh, Roshanak; Heurich, Marco; Shepherd, Anita; Paganini, Marc

2017-07-01

Vegetation indices derived from satellite image time series have been extensively used to estimate the timing of phenological events like season onset. Medium spatial resolution (≥250 m) satellite sensors with daily revisit capability are typically employed for this purpose. In recent years, phenology is being retrieved at higher resolution (≤30 m) in response to increasing availability of high-resolution satellite data. To overcome the reduced acquisition frequency of such data, previous attempts involved fusion between high- and medium-resolution data, or combinations of multi-year acquisitions in a single phenological reconstruction. The objectives of this study are to demonstrate that phenological parameters can now be retrieved from single-season high-resolution time series, and to compare these retrievals against those derived from multi-year high-resolution and single-season medium-resolution satellite data. The study focuses on the island of Schiermonnikoog, the Netherlands, which comprises a highly-dynamic saltmarsh, dune vegetation, and agricultural land. Combining NDVI series derived from atmospherically-corrected images from RapidEye (5 m-resolution) and the SPOT5 Take5 experiment (10m-resolution) acquired between March and August 2015, phenological parameters were estimated using a function fitting approach. We then compared results with phenology retrieved from four years of 30 m Landsat 8 OLI data, and single-year 100 m Proba-V and 250 m MODIS temporal composites of the same period. Retrieved phenological parameters from combined RapidEye/SPOT5 displayed spatially consistent results and a large spatial variability, providing complementary information to existing vegetation community maps. Retrievals that combined four years of Landsat observations into a single synthetic year were affected by the inclusion of years with warmer spring temperatures, whereas adjustment of the average phenology to 2015 observations was only feasible for a few pixels due to cloud cover around phenological transition dates. The Proba-V and MODIS phenology retrievals scaled poorly relative to their high-resolution equivalents, indicating that medium-resolution phenology retrievals need to be interpreted with care, particularly in landscapes with fine-scale land cover variability.

Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

NASA Astrophysics Data System (ADS)

Holz, R. E.; Platnick, S.; Meyer, K.; Vaughan, M.; Heidinger, A.; Yang, P.; Wind, G.; Dutcher, S.; Ackerman, S.; Amarasinghe, N.; Nagle, F.; Wang, C.

2015-10-01

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of two bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ~ 0.75 in the mid-visible spectrum, 5-15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Resolving Ice Cloud Optical Thickness Biases Between CALIOP and MODIS Using Infrared Retrievals

NASA Technical Reports Server (NTRS)

Holz, R. E.; Platnick, S.; Meyer, K.; Vaughan, M.; Heidinger, A.; Yang, P.; Wind, G.; Dutcher, S.; Ackerman, S.; Amarasinghe, N.;

Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

NASA Astrophysics Data System (ADS)

Holz, Robert E.; Platnick, Steven; Meyer, Kerry; Vaughan, Mark; Heidinger, Andrew; Yang, Ping; Wind, Gala; Dutcher, Steven; Ackerman, Steven; Amarasinghe, Nandana; Nagle, Fredrick; Wang, Chenxi

2016-04-01

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light-scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of 2 bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single-scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ≈ 0.75 in the mid-visible spectrum, 5-15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single-habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Attitude angle effects on Nimbus-7 Scanning Multichannel Microwave Radiometer radiances and geophysical parameter retrievals

NASA Technical Reports Server (NTRS)

Macmillan, Daniel S.; Han, Daesoo

1989-01-01

The attitude of the Nimbus-7 spacecraft has varied significantly over its lifetime. A summary of the orbital and long-term behavior of the attitude angles and the effects of attitude variations on Scanning Multichannel Microwave Radiometer (SMMR) brightness temperatures is presented. One of the principal effects of these variations is to change the incident angle at which the SMMR views the Earth's surface. The brightness temperatures depend upon the incident angle sensitivities of both the ocean surface emissivity and the atmospheric path length. Ocean surface emissivity is quite sensitive to incident angle variation near the SMMR incident angle, which is about 50 degrees. This sensitivity was estimated theoretically for a smooth ocean surface and no atmosphere. A 1-degree increase in the angle of incidence produces a 2.9 C increase in the retrieved sea surface temperature and a 5.7 m/sec decrease in retrieved sea surface wind speed. An incident angle correction is applied to the SMMR radiances before using them in the geophysical parameter retrieval algorithms. The corrected retrieval data is compared with data obtained without applying the correction.

Airborne Measurements of CO2 Column Concentration and Range Using a Pulsed Direct-Detection IPDA Lidar

NASA Technical Reports Server (NTRS)

Abshire, James B.; Ramanathan, Anand; Riris, Haris; Mao, Jianping; Allan, Graham R.; Hasselbrack, William E.; Weaver, Clark J.; Browell, Edward V.

2013-01-01

We have previously demonstrated a pulsed direct detection IPDA lidar to measure range and the column concentration of atmospheric CO2. The lidar measures the atmospheric backscatter profiles and samples the shape of the 1,572.33 nm CO2 absorption line. We participated in the ASCENDS science flights on the NASA DC-8 aircraft during August 2011 and report here lidar measurements made on four flights over a variety of surface and cloud conditions near the US. These included over a stratus cloud deck over the Pacific Ocean, to a dry lake bed surrounded by mountains in Nevada, to a desert area with a coal-fired power plant, and from the Rocky Mountains to Iowa, with segments with both cumulus and cirrus clouds. Most flights were to altitudes >12 km and had 5-6 altitude steps. Analyses show the retrievals of lidar range, CO2 column absorption, and CO2 mixing ratio worked well when measuring over topography with rapidly changing height and reflectivity, through thin clouds, between cumulus clouds, and to stratus cloud tops. The retrievals shows the decrease in column CO2 due to growing vegetation when flying over Iowa cropland as well as a sudden increase in CO2 concentration near a coal-fired power plant. For regions where the CO2 concentration was relatively constant, the measured CO2 absorption lineshape (averaged for 50 s) matched the predicted shapes to better than 1% RMS error. For 10 s averaging, the scatter in the retrievals was typically 2-3 ppm and was limited by the received signal photon count. Retrievals were made using atmospheric parameters from both an atmospheric model and from in situ temperature and pressure from the aircraft. The retrievals had no free parameters and did not use empirical adjustments, and >70% of the measurements passed screening and were used in analysis. The differences between the lidar-measured retrievals and in situ measured average CO2 column concentrations were <1.4 ppm for flight measurement altitudes >6 km.

Vertical profile of cloud optical parameters derived from airborne measurements above, inside and below clouds

NASA Astrophysics Data System (ADS)

Melnikova, Irina; Gatebe, Charles K.

2018-07-01

Past strategies for retrieving cloud optical properties from remote sensing assumed significant limits for desired parameters such as semi-infinite optical thickness, single scattering albedo equaling unity (non-absorbing scattering), absence of spectral dependence of the optical thickness, etc., and only one optical parameter could be retrieved (either optical thickness or single scattering albedo). Here, we demonstrate a new method based on asymptotic theory for thick atmospheres, and the presence of a diffusion domain within the clouds that does not put restrictions and makes it possible to get two or even three optical parameters (optical thickness, single scattering albedo and phase function asymmetry parameter) for every wavelength independently. We applied this method to measurements of angular distribution of solar radiation above, inside and below clouds, obtained with NASA's Cloud Absorption Radiometer (CAR) over two cases of marine stratocumulus clouds; first case, offshore of Namibia and the second case, offshore of California. The observational and retrieval errors are accounted for by regularization, which allows stable and smooth solutions. Results show good potential for parameterization of the shortwave radiative properties (reflection, transmission, radiative divergence and heating rate) of water clouds.

The Use of Meteosat Second Generation Satellite Data Within A New Type of Solar Irradiance Calculation Scheme

NASA Astrophysics Data System (ADS)

Mueller, R. W.; Beyer, H. G.; Cros, S.; Dagestad, K. F.; Dumortier, D.; Ineichen, P.; Hammer, A.; Heinemann, D.; Kuhlemann, R.; Olseth, J. A.; Piernavieja, G.; Reise, C.; Schroedter, M.; Skartveit, A.; Wald, L.

1-University of Oldenburg, 2-University of Appl. Sciences Magdeburg, 3-Ecole des Mines de Paris, 4-University of Bergen, 5-Ecole Nationale des Travaux Publics de l'Etat, 6-University of Geneva, 7-Instituto Tecnologico de Canarias, 8-Fraunhofer Institute for Solar Energy Systems, 9-German Aerospace Center Geostationary satellites such as Meteosat provide cloud information with a high spatial and temporal resolution. Such satellites are therefore not only useful for weather fore- casting, but also for the estimation of solar irradiance since the knowledge of the light reflected by clouds is the basis for the calculation of the transmitted light. Additionally an the knowledge of atmospheric parameters involved in scattering and absorption of the sunlight is necessary for an accurate calculation of the solar irradiance. An accurate estimation of the downward solar irradiance is not only of particular im- portance for the assessment of the radiative forcing of the climate system, but also necessary for an efficient planning and operation of solar energy systems. Currently, most of the operational calculation schemes for solar irradiance are semi- empirical. They use cloud information from the current Meteosat satellite and clima- tologies of atmospheric parameters e.g. turbidity (aerosols and water vapor). The Me- teosat Second Generation satellites (MSG, to be launched in 2002) will provide not only a higher spatial and temporal resolution, but also the potential for the retrieval of atmospheric parameters such as ozone, water vapor and with restrictions aerosols. With this more detailed knowledge about atmospheric parameters it is evident to set up a new calculation scheme based on radiative transfer models using the retrieved atmospheric parameters as input. Unfortunately the possibility of deriving aerosol in- formation from MSG data is limited. As a cosequence the use of data from additional satellite instruments ( e.g. GOME/ATSR-2) is neeeded. Within this presentation a new type of the solar irradiance calculation scheme is de- scribed. It is based on the integrated use of a radiative transfer model (RTM), whereas the information of the atmospheric parameters retrieved from satellites (MSG and GOME/ATSR-2) will be used as input for the RTM. First comparisons between calcu- lated and measured solar irradiance are presented. The improvements linked with the usage of the new calculation scheme are discussed, taking into account the benefits and limitations of the new method and the MSG satellite.

HARV ANSER Flight Test Data Retrieval and Processing Procedures

NASA Technical Reports Server (NTRS)

Yeager, Jessie C.

1997-01-01

Under the NASA High-Alpha Technology Program the High Alpha Research Vehicle (HARV) was used to conduct flight tests of advanced control effectors, advanced control laws, and high-alpha design guidelines for future super-maneuverable fighters. The High-Alpha Research Vehicle is a pre-production F/A-18 airplane modified with a multi-axis thrust-vectoring system for augmented pitch and yaw control power and Actuated Nose Strakes for Enhanced Rolling (ANSER) to augment body-axis yaw control power. Flight testing at the Dryden Flight Research Center (DFRC) began in July 1995 and continued until May 1996. Flight data will be utilized to evaluate control law performance and aircraft dynamics, determine aircraft control and stability derivatives using parameter identification techniques, and validate design guidelines. To accomplish these purposes, essential flight data parameters were retrieved from the DFRC data system and stored on the Dynamics and Control Branch (DCB) computer complex at Langley. This report describes the multi-step task used to retrieve and process this data and documents the results of these tasks. Documentation includes software listings, flight information, maneuver information, time intervals for which data were retrieved, lists of data parameters and definitions, and example data plots.

Remote sensing of cloud droplet size distributions in DC3 with the UMBC-LACO Rainbow Polarimetric Imager (RPI)

NASA Astrophysics Data System (ADS)

Buczkowski, S.; Martins, J.; Fernandez-Borda, R.; Cieslak, D.; Hall, J.

2013-12-01

The UMBC Rainbow Polarimetric Imager is a small form factor VIS imaging polarimeter suitable for use on a number of platforms. An optical system based on a Phillips prism with three Bayer filter color detectors, each detecting a separate polarization state, allows simultaneous detection of polarization and spectral information. A Mueller matrix-like calibration scheme corrects for polarization artifacts in the optical train and allows retrieval of the polarization state of incoming light to better than 0.5%. Coupled with wide field of view optics (~90°), RPI can capture images of cloudbows over a wide range of aircraft headings and solar zenith angles for retrieval of cloud droplet size distribution (DSD) parameters. In May-June 2012, RPI was flown in a nadir port on the NASA DC-8 during the DC3 field campaign. We will show examples of cloudbow DSD parameter retrievals from the campaign to demonstrate the efficacy of such a system to terrestrial atmospheric remote sensing. RPI image from DC3 06/15/2012 flight. Left panel is raw image from the RPI 90° camera. Middle panel is Stokes 'q' parameter retrieved from full three camera dataset. Right panel is a horizontal cut in 'q' through the glory. Both middle and right panels clearly show cloudbow features which can be fit to infer cloud DSD parameters.

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).

SMAP Soil Moisture Disaggregation using Land Surface Temperature and Vegetation Data

NASA Astrophysics Data System (ADS)

Fang, B.; Lakshmi, V.

2016-12-01

Soil moisture (SM) is a key parameter in agriculture, hydrology and ecology studies. The global SM retrievals have been providing by microwave remote sensing technology since late 1970s and many SM retrieval algorithms have been developed, calibrated and applied on satellite sensors such as AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System), AMSR-2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). Particularly, SMAP (Soil Moisture Active/Passive) satellite, which was developed by NASA, was launched in January 2015. SMAP provides soil moisture products of 9 km and 36 km spatial resolutions which are not capable for research and applications of finer scale. Toward this issue, this study applied a SM disaggregation algorithm to disaggregate SMAP passive microwave soil moisture 36 km product. This algorithm was developed based on the thermal inertial relationship between daily surface temperature variation and daily average soil moisture which is modulated by vegetation condition, by using remote sensing retrievals from AVHRR (Advanced Very High Resolution Radiometer, MODIS (Moderate Resolution Imaging Spectroradiometer), SPOT (Satellite Pour l'Observation de la Terre), as well as Land Surface Model (LSM) output from NLDAS (North American Land Data Assimilation System). The disaggregation model was built at 1/8o spatial resolution on monthly basis and was implemented to calculate and disaggregate SMAP 36 km SM retrievals to 1 km resolution in Oklahoma. The SM disaggregation results were also validated using MESONET (Mesoscale Network) and MICRONET (Microscale Network) ground SM measurements.

A Tropospheric Emission Spectrometer HDO/H2O Retrieval Simulator for Climate Models

NASA Technical Reports Server (NTRS)

Field, R. D.; Risi, C.; Schmidt, G. A.; Worden, J.; Voulgarakis, A.; LeGrande, A. N.; Sobel, A. H.; Healy, R. J.

2012-01-01

Retrievals of the isotopic composition of water vapor from the Aura Tropospheric Emission Spectrometer (TES) have unique value in constraining moist processes in climate models. Accurate comparison between simulated and retrieved values requires that model profiles that would be poorly retrieved are excluded, and that an instrument operator be applied to the remaining profiles. Typically, this is done by sampling model output at satellite measurement points and using the quality flags and averaging kernels from individual retrievals at specific places and times. This approach is not reliable when the model meteorological conditions influencing retrieval sensitivity are different from those observed by the instrument at short time scales, which will be the case for free-running climate simulations. In this study, we describe an alternative, categorical approach to applying the instrument operator, implemented within the NASA GISS ModelE general circulation model. Retrieval quality and averaging kernel structure are predicted empirically from model conditions, rather than obtained from collocated satellite observations. This approach can be used for arbitrary model configurations, and requires no agreement between satellite-retrieved and model meteorology at short time scales. To test this approach, nudged simUlations were conducted using both the retrieval-based and categorical operators. Cloud cover, surface temperature and free-tropospheric moisture content were the most important predictors of retrieval quality and averaging kernel structure. There was good agreement between the D fields after applying the retrieval-based and more detailed categorical operators, with increases of up to 30 over the ocean and decreases of up to 40 over land relative to the raw model fields. The categorical operator performed better over the ocean than over land, and requires further refinement for use outside of the tropics. After applying the TES operator, ModelE had D biases of 8 over ocean and 34 over land compared to TES D, which were less than the biases using raw model D fields.

Initial retrieval sequence and blending strategy

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

Pemwell, D.L.; Grenard, C.E.

1996-09-01

This report documents the initial retrieval sequence and the methodology used to select it. Waste retrieval, storage, pretreatment and vitrification were modeled for candidate single-shell tank retrieval sequences. Performance of the sequences was measured by a set of metrics (for example,high-level waste glass volume, relative risk and schedule).Computer models were used to evaluate estimated glass volumes,process rates, retrieval dates, and blending strategy effects.The models were based on estimates of component inventories and concentrations, sludge wash factors and timing, retrieval annex limitations, etc.

Material and shape optimization for multi-layered vocal fold models using transient loadings.

PubMed

Schmidt, Bastian; Leugering, Günter; Stingl, Michael; Hüttner, Björn; Agaimy, Abbas; Döllinger, Michael

2013-08-01

Commonly applied models to study vocal fold vibrations in combination with air flow distributions are self-sustained physical models of the larynx consisting of artificial silicone vocal folds. Choosing appropriate mechanical parameters and layer geometries for these vocal fold models while considering simplifications due to manufacturing restrictions is difficult but crucial for achieving realistic behavior. In earlier work by Schmidt et al. [J. Acoust. Soc. Am. 129, 2168-2180 (2011)], the authors presented an approach in which material parameters of a static numerical vocal fold model were optimized to achieve an agreement of the displacement field with data retrieved from hemilarynx experiments. This method is now generalized to a fully transient setting. Moreover in addition to the material parameters, the extended approach is capable of finding optimized layer geometries. Depending on chosen material restriction, significant modifications of the reference geometry are predicted. The additional flexibility in the design space leads to a significantly more realistic deformation behavior. At the same time, the predicted biomechanical and geometrical results are still feasible for manufacturing physical vocal fold models consisting of several silicone layers. As a consequence, the proposed combined experimental and numerical method is suited to guide the construction of physical vocal fold models.

Winter wheat yield estimation of remote sensing research based on WOFOST crop model and leaf area index assimilation

NASA Astrophysics Data System (ADS)

Chen, Yanling; Gong, Adu; Li, Jing; Wang, Jingmei

2017-04-01

Accurate crop growth monitoring and yield predictive information are significant to improve the sustainable development of agriculture and ensure the security of national food. Remote sensing observation and crop growth simulation models are two new technologies, which have highly potential applications in crop growth monitoring and yield forecasting in recent years. However, both of them have limitations in mechanism or regional application respectively. Remote sensing information can not reveal crop growth and development, inner mechanism of yield formation and the affection of environmental meteorological conditions. Crop growth simulation models have difficulties in obtaining data and parameterization from single-point to regional application. In order to make good use of the advantages of these two technologies, the coupling technique of remote sensing information and crop growth simulation models has been studied. Filtering and optimizing model parameters are key to yield estimation by remote sensing and crop model based on regional crop assimilation. Winter wheat of GaoCheng was selected as the experiment object in this paper. And then the essential data was collected, such as biochemical data and farmland environmental data and meteorological data about several critical growing periods. Meanwhile, the image of environmental mitigation small satellite HJ-CCD was obtained. In this paper, research work and major conclusions are as follows. (1) Seven vegetation indexes were selected to retrieve LAI, and then linear regression model was built up between each of these indexes and the measured LAI. The result shows that the accuracy of EVI model was the highest (R2=0.964 at anthesis stage and R2=0.920 at filling stage). Thus, EVI as the most optimal vegetation index to predict LAI in this paper. (2) EFAST method was adopted in this paper to conduct the sensitive analysis to the 26 initial parameters of the WOFOST model and then a sensitivity index was constructed to evaluate the influence of each parameter mentioned above on the winter wheat yield formation. Finally, six parameters that sensitivity index more than 0.1 as sensitivity factors were chose, which are TSUM1, SLATB1, SLATB2, SPAN, EFFTB3 and TMPF4. To other parameters, we confirmed them via practical measurement and calculation, available literature or WOFOST default. Eventually, we completed the regulation of WOFOST parameters. (3) Look-up table algorithm was used to realize single-point yield estimation through the assimilation of the WOFOST model and the retrieval LAI. This simulation achieved a high accuracy which perfectly meet the purpose of assimilation (R2=0.941 and RMSE=194.58kg/hm2). In this paper, the optimum value of sensitivity parameters were confirmed and the estimation of single-point yield were finished. Key words: yield estimation of winter wheat, LAI, WOFOST crop growth model, assimilation

The influence of sea fog inhomogeneity on its microphysical characteristics retrieval

NASA Astrophysics Data System (ADS)

Hao, Zengzhou; Pan, Delu; Gong, Fang; He, Xianqiang

2008-10-01

A study on the effect of sea fog inhomogeneity on its microphysical parameters retrieval is presented. On the condition that the average liquid water content is linear vertically and the power spectrum spectral index sets 2.0, we generate a 3D sea fog fields by controlling the total liquid water contents greater than 0.04g/m3 based on the iterative method for generating scaling log-normal random field with an energy spectrum and a fragmentized cloud algorithm. Based on the fog field, the radiance at the wavelengths of 0.67 and 1.64 μm are simulated with 3D radiative transfer model SHDOM, and then the fog optical thickness and effective particle radius are simultaneously retrieved using the generic look-up-table AVHRR cloud algorithm. By comparing those fog optical thickness and effective particle radius, the influence of sea fog inhomogeneity on its properties retrieval is discussed. It exhibits the system bias when inferring sea fog physical properties from satellite measurements based on the assumption of plane parallel homogeneous atmosphere. And the bias depends on the solar zenith angel. The optical thickness is overrated while the effective particle radius is under-estimated at two solar zenith angle 30° and 60°. Those results show that it is necessary for sea fog true characteristics retrieval to develop a new algorithm using the 3D radiative transfer.

Accounting for the water-leaving radiance in the simultaneous retrieval of atmosphere and ocean properties from collocated polarimeters and lidar measurements: results for the SABOR campaign

NASA Astrophysics Data System (ADS)

Chowdhary, J.; Brian, C.; Stamnes, S.; Hostetler, C. A.; Cetinic, I.; Slade, W. H.; Hu, Y.

2017-12-01

Ocean spectra typically contribute less than 10% to top-of-atmosphere (TOA) radiance observations in the visible (VIS). The remaining 90% of TOA radiance originates from scattering in the atmosphere which needs to be removed (i.e. corrected) but varies substantially with the aerosol present at the time of observation. The traditional approach for atmospheric correction (AC), used for ocean color sensors such as SeaWiFS, MODIS, and VIIRS, estimates aerosol scattering properties from TOA radiance observations in the near-infrared/short-wave infrared (NIR/SWIR) where the ocean becomes dark. The aerosol model is subsequently used to compute the atmospheric scattering contribution to the TOA radiance in the VIS. The final step is to subtract this computed scattering contribution from the real (i.e. observed) TOA radiance. As an alternative to the traditional approach for AC, we retrieve the atmosphere (i.e., aerosol) and ocean (i.e., color) properties simultaneously from measurements in the VIS. To separate the information content for the atmosphere and ocean, we use lidar measurements and multi-angle polarization measurements. Lidar and polarimeter measurements are powerful tools to enhance the ocean product retrievals from conventional ocean color sensors, and are under consideration to accompany future generation ocean color sensors. Here, we present results of simultaneous atmosphere-ocean retrievals using collocated airborne lidar and polarimeter data that were acquired during the Ship-Aircraft Bio-Optical Research (SABOR) campaign. We discuss 2 hydrosol models (which differ in number of free parameters) that were used for these inversions. We then compare our ocean retrievals with measurements obtained from the accompanying cruise ship. Finally, we touch upon a next generation of hydrosol models that accommodates the unique sensitivity of ocean lidar profiles to plankton morphology.

Titan's Surface Temperatures Maps from Cassini - CIRS Observations

NASA Astrophysics Data System (ADS)

Cottini, Valeria; Nixon, C. A.; Jennings, D. E.; Anderson, C. M.; Samuelson, R. E.; Irwin, P. G. J.; Flasar, F. M.

2009-09-01

The Cassini Composite Infrared Spectrometer (CIRS) observations of Saturn's largest moon, Titan, are providing us with the ability to detect the surface temperature of the planet by studying its outgoing radiance through a spectral window in the thermal infrared at 19 μm (530 cm-1) characterized by low opacity. Since the first acquisitions of CIRS Titan data the instrument has gathered a large amount of spectra covering a wide range of latitudes, longitudes and local times. We retrieve the surface temperature and the atmospheric temperature profile by modeling proper zonally averaged spectra of nadir observations with radiative transfer computations. Our forward model uses the correlated-k approximation for spectral opacity to calculate the emitted radiance, including contributions from collision induced pairs of CH4, N2 and H2, haze, and gaseous emission lines (Irwin et al. 2008). The retrieval method uses a non-linear least-squares optimal estimation technique to iteratively adjust the model parameters to achieve a spectral fit (Rodgers 2000). We show an accurate selection of the wide amount of data available in terms of footprint diameter on the planet and observational conditions, together with the retrieved results. Our results represent formal retrievals of surface brightness temperatures from the Cassini CIRS dataset using a full radiative transfer treatment, and we compare to the earlier findings of Jennings et al. (2009). In future, application of our methodology over wide areas should greatly increase the planet coverage and accuracy of our knowledge of Titan's surface brightness temperature. References: Irwin, P.G.J., et al.: "The NEMESIS planetary atmosphere radiative transfer and retrieval tool" (2008). JQSRT, Vol. 109, pp. 1136-1150, 2008. Rodgers, C. D.: "Inverse Methods For Atmospheric Sounding: Theory and Practice". World Scientific, Singapore, 2000. Jennings, D.E., et al.: "Titan's Surface Brightness Temperatures." Ap. J. L., Vol. 691, pp. L103-L105, 2009.

Item parameters dissociate between expectation formats: a regression analysis of time-frequency decomposed EEG data

PubMed Central

Monsalve, Irene F.; Pérez, Alejandro; Molinaro, Nicola

2014-01-01

During language comprehension, semantic contextual information is used to generate expectations about upcoming items. This has been commonly studied through the N400 event-related potential (ERP), as a measure of facilitated lexical retrieval. However, the associative relationships in multi-word expressions (MWE) may enable the generation of a categorical expectation, leading to lexical retrieval before target word onset. Processing of the target word would thus reflect a target-identification mechanism, possibly indexed by a P3 ERP component. However, given their time overlap (200–500 ms post-stimulus onset), differentiating between N400/P3 ERP responses (averaged over multiple linguistically variable trials) is problematic. In the present study, we analyzed EEG data from a previous experiment, which compared ERP responses to highly expected words that were placed either in a MWE or a regular non-fixed compositional context, and to low predictability controls. We focused on oscillatory dynamics and regression analyses, in order to dissociate between the two contexts by modeling the electrophysiological response as a function of item-level parameters. A significant interaction between word position and condition was found in the regression model for power in a theta range (~7–9 Hz), providing evidence for the presence of qualitative differences between conditions. Power levels within this band were lower for MWE than compositional contexts when the target word appeared later on in the sentence, confirming that in the former lexical retrieval would have taken place before word onset. On the other hand, gamma-power (~50–70 Hz) was also modulated by predictability of the item in all conditions, which is interpreted as an index of a similar “matching” sub-step for both types of contexts, binding an expected representation and the external input. PMID:25161630

False memory for orthographically versus semantically similar words in adolescents with dyslexia: a fuzzy-trace theory perspective.

PubMed

Obidziński, Michał; Nieznański, Marek

2017-10-01

The presented research was conducted in order to investigate the connections between developmental dyslexia and the functioning of verbatim and gist memory traces-assumed in the fuzzy-trace theory. The participants were 71 high school students (33 with dyslexia and 38 without learning difficulties). The modified procedure and multinomial model of Stahl and Klauer (simplified conjoint recognition model) was used to collect and analyze data. Results showed statistically significant differences in four of the model parameters: (a) the probability of verbatim trace recollection upon presentation of orthographically similar stimulus was higher in the control than dyslexia group, (b) the probability of verbatim trace recollection upon presentation of semantically similar stimulus was higher in the control than dyslexia group, (c) the probability of gist trace retrieval upon presentation of semantically similar stimulus was higher in the dyslexia than control group, and (d) the probability of gist trace retrieval upon target stimulus presentation (in the semantic condition) was higher in the control than dyslexia group. The obtained results suggest differences of memory functioning in terms of verbatim and gist trace retrieval between people with and without dyslexia on specific, elementary cognitive processes postulated by the fuzzy-trace theory. These can indicate new approaches in the education of persons with developmental dyslexia, focused on specific impairments and the strengths of their memory functioning.

Ethane in Planetary and Cometary Atmospheres: Transmittance and Fluorescence Models of the nu7 Band at 3.3 Micrometers

NASA Technical Reports Server (NTRS)

Villanueva, G. L.; Mumma, M. J.; Magee-Sauer, K.

2011-01-01

Ethane and other hydrocarbon gases have strong rovibrational transitions in the 3.3 micron spectral region owing to C-H, CH2, and CH3 vibrational modes, making this spectral region prime for searching possible biomarker gases in extraterrestrial atmospheres (e.g., Mars, exoplanets) and organic molecules in comets. However, removing ethane spectral signatures from high-resolution terrestrial transmittance spectra has been imperfect because existing quantum mechanical models have been unable to reproduce the observed spectra with sufficient accuracy. To redress this problem, we constructed a line-by-line model for the n7 band of ethane (C2H6) and applied it to compute telluric transmittances and cometary fluorescence efficiencies. Our model considers accurate spectral parameters, vibration-rotation interactions, and a functional characterization of the torsional hot band. We integrated the new band model into an advanced radiative transfer code for synthesizing the terrestrial atmosphere (LBLRTM), achieving excellent agreement with transmittance data recorded against Mars using three different instruments located in the Northern and Southern hemispheres. The retrieved ethane abundances demonstrate the strong hemispheric asymmetry noted in prior surveys of volatile hydrocarbons. We also retrieved sensitive limits for the abundance of ethane on Mars. The most critical validation of the model was obtained by comparing simulations of C2H6 fluorescent emission with spectra of three hydrocarbon-rich comets: C/2004 Q2 (Machholz), 8P/Tuttle, and C/2007 W1 (Boattini). The new model accurately describes the complex emission morphology of the nu7 band at low rotational temperatures and greatly increases the confidence of the retrieved production rates (and rotational temperatures) with respect to previously available fluorescence models.

A Re-Unification of Two Competing Models for Document Retrieval.

ERIC Educational Resources Information Center

Bodoff, David

1999-01-01

Examines query-oriented versus document-oriented information retrieval and feedback learning. Highlights include a reunification of the two approaches for probabilistic document retrieval and for vector space model (VSM) retrieval; learning in VSM and in probabilistic models; multi-dimensional scaling; and ongoing field studies. (LRW)

Effective Tree Scattering and Opacity at L-Band

NASA Technical Reports Server (NTRS)

Kurum, Mehmet; O'Neill, Peggy E.; Lang, Roger H.; Joseph, Alicia T.; Cosh, Michael H.; Jackson, Thomas J.

2011-01-01

This paper investigates vegetation effects at L-band by using a first-order radiative transfer (RT) model and truck-based microwave measurements over natural conifer stands to assess the applicability of the tau-omega) model over trees. The tau-omega model is a zero-order RT solution that accounts for vegetation effects with effective vegetation parameters (vegetation opacity and single-scattering albedo), which represent the canopy as a whole. This approach inherently ignores multiple-scattering effects and, therefore, has a limited validity depending on the level of scattering within the canopy. The fact that the scattering from large forest components such as branches and trunks is significant at L-band requires that zero-order vegetation parameters be evaluated (compared) along with their theoretical definitions to provide a better understanding of these parameters in the retrieval algorithms as applied to trees. This paper compares the effective vegetation opacities, computed from multi-angular pine tree brightness temperature data, against the results of two independent approaches that provide theoretical and measured optical depths. These two techniques are based on forward scattering theory and radar corner reflector measurements, respectively. The results indicate that the effective vegetation opacity values are smaller than but of similar magnitude to both radar and theoretical estimates. The effective opacity of the zero-order model is thus set equal to the theoretical opacity and an explicit expression for the effective albedo is then obtained from the zero- and first- order RT model comparison. The resultant albedo is found to have a similar magnitude as the effective albedo value obtained from brightness temperature measurements. However, it is less than half of that estimated using the theoretical calculations (0.5 - 0.6 for tree canopies at L-band). This lower observed albedo balances the scattering darkening effect of the large theoretical albedo with a first-order multiple-scattering contribution. The retrieved effective albedo is different from theoretical definitions and not the albedo of single forest elements anymore, but it becomes a global parameter, which depends on all the processes taking place within the canopy, including multiple-scattering.

Mesospheric H2O Concentrations Retrieved from SABER/TIMED Measurements

NASA Technical Reports Server (NTRS)

Feofilov, A. G.; Marshall, B. T.; Garcia-Comas, M.; Kutepov, A. A.; Lopez-Puertas, M.; Manuilova, R. O.; Yankovsky, V.A.; Goldberg, R. A.; Gordley, L. L.; Petelin, S.;

Investigation of ice particle habits to be used for ice cloud remote sensing for the GCOM-C satellite mission

NASA Astrophysics Data System (ADS)

Letu, Husi; Ishimoto, Hiroshi; Riedi, Jerome; Nakajima, Takashi Y.; -Labonnote, Laurent C.; Baran, Anthony J.; Nagao, Takashi M.; Sekiguchi, Miho

2016-09-01

In this study, various ice particle habits are investigated in conjunction with inferring the optical properties of ice clouds for use in the Global Change Observation Mission-Climate (GCOM-C) satellite programme. We develop a database of the single-scattering properties of five ice habit models: plates, columns, droxtals, bullet rosettes, and Voronoi. The database is based on the specification of the Second Generation Global Imager (SGLI) sensor on board the GCOM-C satellite, which is scheduled to be launched in 2017 by the Japan Aerospace Exploration Agency. A combination of the finite-difference time-domain method, the geometric optics integral equation technique, and the geometric optics method is applied to compute the single-scattering properties of the selected ice particle habits at 36 wavelengths, from the visible to the infrared spectral regions. This covers the SGLI channels for the size parameter, which is defined as a single-particle radius of an equivalent volume sphere, ranging between 6 and 9000 µm. The database includes the extinction efficiency, absorption efficiency, average geometrical cross section, single-scattering albedo, asymmetry factor, size parameter of a volume-equivalent sphere, maximum distance from the centre of mass, particle volume, and six nonzero elements of the scattering phase matrix. The characteristics of calculated extinction efficiency, single-scattering albedo, and asymmetry factor of the five ice particle habits are compared. Furthermore, size-integrated bulk scattering properties for the five ice particle habit models are calculated from the single-scattering database and microphysical data. Using the five ice particle habit models, the optical thickness and spherical albedo of ice clouds are retrieved from the Polarization and Directionality of the Earth's Reflectances-3 (POLDER-3) measurements, recorded on board the Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. The optimal ice particle habit for retrieving the SGLI ice cloud properties is investigated by adopting the spherical albedo difference (SAD) method. It is found that the SAD is distributed stably due to the scattering angle increases for bullet rosettes with an effective diameter (Deff) of 10 µm and Voronoi particles with Deff values of 10, 60, and 100 µm. It is confirmed that the SAD of small bullet-rosette particles and all sizes of Voronoi particles has a low angular dependence, indicating that a combination of the bullet-rosette and Voronoi models is sufficient for retrieval of the ice cloud's spherical albedo and optical thickness as effective habit models for the SGLI sensor. Finally, SAD analysis based on the Voronoi habit model with moderate particle size (Deff = 60 µm) is compared with the conventional general habit mixture model, inhomogeneous hexagonal monocrystal model, five-plate aggregate model, and ensemble ice particle model. The Voronoi habit model is found to have an effect similar to that found in some conventional models for the retrieval of ice cloud properties from space-borne radiometric observations.

Ice Cloud Optical Thickness and Extinction Estimates from Radar Measurements.

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.; Shupe, Matthew D.; Heymsfield, Andrew J.; Zuidema, Paquita

2003-11-01

A remote sensing method is proposed to derive vertical profiles of the visible extinction coefficients in ice clouds from measurements of the radar reflectivity and Doppler velocity taken by a vertically pointing 35-GHz cloud radar. The extinction coefficient and its vertical integral, optical thickness τ, are among the fundamental cloud optical parameters that, to a large extent, determine the radiative impact of clouds. The results obtained with this method could be used as input for different climate and radiation models and for comparisons with parameterizations that relate cloud microphysical parameters and optical properties. An important advantage of the proposed method is its potential applicability to multicloud situations and mixed-phase conditions. In the latter case, it might be able to provide the information on the ice component of mixed-phase clouds if the radar moments are dominated by this component. The uncertainties of radar-based retrievals of cloud visible optical thickness are estimated by comparing retrieval results with optical thicknesses obtained independently from radiometric measurements during the yearlong Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment. The radiometric measurements provide a robust way to estimate τ but are applicable only to optically thin ice clouds without intervening liquid layers. The comparisons of cloud optical thicknesses retrieved from radar and from radiometer measurements indicate an uncertainty of about 77% and a bias of about -14% in the radar estimates of τ relative to radiometric retrievals. One possible explanation of the negative bias is an inherently low sensitivity of radar measurements to smaller cloud particles that still contribute noticeably to the cloud extinction. This estimate of the uncertainty is in line with simple theoretical considerations, and the associated retrieval accuracy should be considered good for a nonoptical instrument, such as radar. This paper also presents relations between radar-derived characteristic cloud particle sizes and effective sizes used in models. An average relation among τ, cloud ice water path, and the layer mean value of cloud particle characteristic size is also given. This relation is found to be in good agreement with in situ measurements. Despite a high uncertainty of radar estimates of extinction, this method is useful for many clouds where optical measurements are not available because of cloud multilayering or opaqueness.

Efficient solution methodology for calibrating the hemodynamic model using functional Magnetic Resonance Imaging (fMRI) measurements.

PubMed

Zambri, Brian; Djellouli, Rabia; Laleg-Kirati, Taous-Meriem

2015-08-01

Our aim is to propose a numerical strategy for retrieving accurately and efficiently the biophysiological parameters as well as the external stimulus characteristics corresponding to the hemodynamic mathematical model that describes changes in blood flow and blood oxygenation during brain activation. The proposed method employs the TNM-CKF method developed in [1], but in a prediction/correction framework. We present numerical results using both real and synthetic functional Magnetic Resonance Imaging (fMRI) measurements to highlight the performance characteristics of this computational methodology.

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

NASA Technical Reports Server (NTRS)

Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

2011-01-01

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Simulation of the detonation process of an ammonium nitrate based emulsion explosive using the lee-tarver reactive flow model

NASA Astrophysics Data System (ADS)

Ribeiro, José B.; Silva, Cristóvão; Mendes, Ricardo; Plaksin, I.; Campos, Jose

2012-03-01

The use of emulsion explosives [EEx] for processing materials (compaction, welding and forming) requires the ability to perform detailed simulations of its detonation process [DP]. Detailed numerical simulations of the DP of this kind of explosives, characterized by having a finite reaction zone thickness, are thought to be suitably performed using the Lee-Tarver reactive flow model. In this work a real coded genetic algorithm methodology was used to estimate the 15 parameters of the reaction rate equation [RRE] of that model for a particular EEx. This methodology allows, in a single optimization procedure, using only one experimental result and without the need of any starting solution, to seek for the 15 parameters of the RRE that fit the numerical to the experimental results. Mass averaging and the Plate-Gap Model have been used for the determination of the shock data used in the unreacted explosive JWL EoS assessment, and the thermochemical code THOR retrieved the data used in the detonation products JWL EoS assessment. The obtained parameters allow a reasonable description of the experimental data.

Data Discretization for Novel Relationship Discovery in Information Retrieval.

ERIC Educational Resources Information Center

Benoit, G.

2002-01-01

Describes an information retrieval, visualization, and manipulation model which offers the user multiple ways to exploit the retrieval set, based on weighted query terms, via an interactive interface. Outlines the mathematical model and describes an information retrieval application built on the model to search structured and full-text files.…

Assessment of the improvements in accuracy of aerosol characterization resulted from additions of polarimetric measurements to intensity-only observations using GRASP algorithm (Invited)

NASA Astrophysics Data System (ADS)

Dubovik, O.; Litvinov, P.; Lapyonok, T.; Herman, M.; Fedorenko, A.; Lopatin, A.; Goloub, P.; Ducos, F.; Aspetsberger, M.; Planer, W.; Federspiel, C.

2013-12-01

During last few years we were developing GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm designed for the enhanced characterization of aerosol properties from spectral, multi-angular polarimetric remote sensing observations. The concept of GRASP essentially relies on the accumulated positive research heritage from previous remote sensing aerosol retrieval developments, in particular those from the AERONET and POLDER retrieval activities. The details of the algorithm are described by Dubovik et al. (Atmos. Meas. Tech., 4, 975-1018, 2011). The GRASP retrieves properties of both aerosol and land surface reflectance in cloud-free environments. It is based on highly advanced statistically optimized fitting and deduces nearly 50 unknowns for each observed site. The algorithm derives a similar set of aerosol parameters as AERONET including detailed particle size distribution, the spectrally dependent the complex index of refraction and the fraction of non-spherical particles. The algorithm uses detailed aerosol and surface models and fully accounts for all multiple interactions of scattered solar light with aerosol, gases and the underlying surface. All calculations are done on-line without using traditional look-up tables. In addition, the algorithm uses the new multi-pixel retrieval concept - a simultaneous fitting of a large group of pixels with additional constraints limiting the time variability of surface properties and spatial variability of aerosol properties. This principle is expected to result in higher consistency and accuracy of aerosol products compare to conventional approaches especially over bright surfaces where information content of satellite observations in respect to aerosol properties is limited. The GRASP is a highly versatile algorithm that allows input from both satellite and ground-based measurements. It also has essential flexibility in measurement processing. For example, if observation data set includes spectral measurements of both total intensity and polarization, the algorithm can be easily set to use either total intensity or polarization, as well as both of them in the same retrieval. Using this feature of the algorithm design we have studied the relative importance of total intensity and polarization measurements for retrieving different parameters of aerosol. In this presentation, we present the quantitative assessment of the improvements in aerosol retrievals associated with additions of polarimetric measurements to the intensity-only observations. The study has been performed using satellite measurements by POLDER/PARASOL polarimeter and ground-based measurements by new generation AERONET sun/sky-radiometers implementing measurements of polarization at each spectral channel.

ENVISAT Land Surface Processes. Phase 2

NASA Technical Reports Server (NTRS)

vandenHurk, B. J. J. M.; Su, Z.; Verhoef, W.; Menenti, M.; Li, Z.-L.; Wan, Z.; Moene, A. F.; Roerink, G.; Jia, I.

2002-01-01

This is a progress report of the 2nd phase of the project ENVISAT- Land Surface Processes, which has a 3-year scope. In this project, preparative research is carried out aiming at the retrieval of land surface characteristics from the ENVISAT sensors MERIS and AATSR, for assimilation into a system for Numerical Weather Prediction (NWP). Where in the 1st phase a number of first shot experiments were carried out (aiming at gaining experience with the retrievals and data assimilation procedures), the current 2nd phase has put more emphasis on the assessment and improvement of the quality of the retrieved products. The forthcoming phase will be devoted mainly to the data assimilation experiments and the assessment of the added value of the future ENVISAT products for NWP forecast skill. Referring to the retrieval of albedo, leaf area index and atmospheric corrections, preliminary radiative transfer calculations have been carried out that should enable the retrieval of these parameters once AATSR and MERIS data become available. However, much of this work is still to be carried out. An essential part of work in this area is the design and implementation of software that enables an efficient use of MODTRAN(sub 4) radiative transfer code, and during the current project phase familiarization with these new components has been achieved. Significant progress has been made with the retrieval of component temperatures from directional ATSR-images, and the calculation of surface turbulent heat fluxes from these data. The impact of vegetation cover on the retrieved component temperatures appears manageable, and preliminary comparison of foliage temperature to air temperatures were encouraging. The calculation of surface fluxes using the SEBI concept,which includes a detailed model of the surface roughness ratio, appeared to give results that were in reasonable agreement with local measurements with scintillometer devices. The specification of the atmospheric boundary conditions appears a crucial component, and the use of first guess estimates from the RACMO models partially explains the success. Earlier data assimilation experiments with directional surface temperatures have been analysed a bit further and were also compared to results obtained from directly modeling the surface roughness ratio. Results between these calculations and the data assimilation results appeared well comparable, but a full test in which the surface roughness model is allowed to play a free role during the data assimilation process has yet to be carried out. A considerable number of tasks that have yet to be carried out during Phase 3 has been formulated.