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NASA NTRS2022

Simultaneous Retrieval of Selected Optical Water Quality Indicators From Landsat-8, Sentinel-2, and Sentinel-3

Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (a cdom (440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and a cdom (440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and a cdom (440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and a cdom (440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model.

Machine learning↗

NASA NTRS2020

Snow Property Inversion from Remote Sensing (SPIReS): A Generalized Multispectral Unmixing Approach with Examples from MODIS and Landsat 8 OLI

Spectral mixture analysis has a history in mappingsnow, especially where mixed pixels prevail. Using multiplespectral bands rather than band ratios or band indices, retrievalsof snow properties that affect its albedo lead to more accu-rate estimates than widely used age-based models of albedoevolution. Nevertheless, there is substantial room for improve-ment. We present the Snow Property Inversion from RemoteSensing (SPIReS) approach, offering the following improve-ments: 1) Solutions for grain size and concentrations of lightabsorbing particles are computed simultaneously; 2) Only snowand snow-free endmembers are employed; 3) Cloud-maskingand smoothing are integrated; 4) Similar spectra are groupedtogether and interpolants are used to reduce computation time.The source codes are available in an open repository. Com-putation is fast enough that users can process imagery ondemand. Validation of retrievals from Landsat 8 operational landimager (OLI) and moderate-resolution imaging spectroradiome-ter (MODIS) against WorldView-2/3 and the Airborne SnowObservatory shows accurate detection of snow and estimatesof fractional snow cover. Validation of albedo shows low errorsusing terrain-correctedin situmeasurements. We conclude bydiscussing the applicability of this approach to any airborne orspaceborne multispectral sensor and options to further improve retrievals.

Edward H Blair↗

NASA NTRS1996

Two-stage model of radon-induced malignant lung tumors in rats: effects of cell killing

A two-stage stochastic model of carcinogenesis is used to analyze lung tumor incidence in 3750 rats exposed to varying regimens of radon carried on a constant-concentration uranium ore dust aerosol. New to this analysis is the parameterization of the model such that cell killing by the alpha particles could be included. The model contains parameters characterizing the rate of the first mutation, the net proliferation rate of initiated cells, the ratio of the rates of cell loss (cell killing plus differentiation) and cell division, and the lag time between the appearance of the first malignant cell and the tumor. Data analysis was by standard maximum likelihood estimation techniques. Results indicate that the rate of the first mutation is dependent on radon and consistent with in vitro rates measured experimentally, and that the rate of the second mutation is not dependent on radon. An initial sharp rise in the net proliferation rate of initiated cell was found with increasing exposure rate (denoted model I), which leads to an unrealistically high cell-killing coefficient. A second model (model II) was studied, in which the initial rise was attributed to promotion via a step function, implying that it is due not to radon but to the uranium ore dust. This model resulted in values for the cell-killing coefficient consistent with those found for in vitro cells. An "inverse dose-rate" effect is seen, i.e. an increase in the lifetime probability of tumor with a decrease in exposure rate. This is attributed in large part to promotion of intermediate lesions. Since model II is preferable on biological grounds (it yields a plausible cell-killing coefficient), such as uranium ore dust. This analysis presents evidence that a two-stage model describes the data adequately and generates hypotheses regarding the mechanism of radon-induced carcinogenesis.

NASA Program Radiation Health↗

NASA NTRS2018

Active and Passive Radiative Transfer Modeling of the Olympic Mountains Experiment

Sensor forward models are an important tool for interpreting remote sensing observations of geophysical phenomena. By implementing a three-dimensional framework, we can simulate and analyze observations from various sensors on disparate platforms. To demonstrate our model framework, we simulate observations from the Olympic Mountains Experiment (OLYMPEX). The use of cloud model simulations allows us to understand sensor response to cloud ice, falling snow, and other processes and features, and the application of model tools to observations allows us to quantify precipitation.MIIST 3D Forward ModelThe Multi-Instrument Inverse Solver Testbed(MIIST) uses the Atmospheric Radiative TransferSimulator (ARTS) for solving the vector radiativetransfer (RT) equation in up to three spatialdimensions within a spherical geometry• Gas absorptiono Line-by-line calculationso Fast transmittance tables• Hydrometeor scattering solverso Discrete ordinateo RT4 (Evans, 1D)o Radar Single Scattering (1D or 3D)o Monte Carlo (3D)Scattering TablesHigh-fidelity hydrometeor scatteringtables are necessary for accurateand consistent forward modeling ofmulti-frequency observations• Requires full Stokes matriceso And absorption vector• Randomly oriented particleso Discrete Dipole Approximationo Characteristic Basis Function Method(coming soon)• Horizontally-oriented plateso Invariant Imbedding T-matrix MethodCloud Resolving SimulationsCloud resolving simulations (e.g.,NU-WRF) supply output consistentwith ARTS needs• Atmospheric Informationo Temperatureo Pressure / heighto Water vapor• Hydrometeor Profileso ARTS architecture ripe for explicit binmicrophysics• Examples use Morrison 2M schemeThe Olympic Mountains Experiment (OLYMPEX)Validation for GPM of mid-latitudefrontal systems approaching nearcoastalmountains from the ocean• Large collection of ground-based andairborne sensorso Radarso Radiometerso In situ• Contemporaneous with RADEXo Two sets of radar at same frequenciesRadiometer Simulation (3 km NUWRF, 20151203, 15:00)2018.12.14 7Simulate 166 GHz polarizationdifference• Corresponds to the presence of aligned icecrystals• Look at trends for both simulations andobservations• Simulations can tolerate lower resolutiono Larger domainSimulations from Observations: OLYMPEXSimulate sensor response usinggeophysical retrievals as input• Single frequency radar retrievals• Multiple scattering enhancementapparent at W band• Spatially dependent phenomenonModeling Application: 1D Retrievals03 December 2015• DC-8 and ER-2 flightso Focus on APR-3 (DC-8)• Citationo Stacked microphysics legso Qualitative comparisonso Range of frozen habitso Presence of supercooledliquid cloudsResults• Retrievals match probeso Good qualitative match• Bands of increasedreflectivity correspond tolarge Dm and highaggregate fraction• Significant amounts ofsupercooled liquid water

Adams, Ian S.↗

NASA NTRS1984

Reflectance spectroscopy - Quantitative analysis techniques for remote sensing applications

The empirical methods and scattering theories that are important for solving remote sensing problems are among the methods for remotely sensed reflectance data analysis presently compared. In the case of the photon mean optical path length concept's implications for reflectance spectra modeling, it is shown that the mean optical path length in a particulate surface is in roughly inverse proportion to the square root of the absorption coefficient. Absorption bands, which are Gaussian in shape when plotted as true absorptance vs photon energy, are also Gaussians in apparent absorptance, although they have a smaller intensity. An apparent continuum in a reflectance spectrum is modeled as a mathematical function that is used to isolate a particular absorption feature for analysis, and it is noted that this continuum should be removed by dividing it into the reflectance spectrum.

Clark, R. N.↗

NASA NTRS1974

Development of technology for fluid-structure interaction modeling of a 1/8-scale dynamic model of shuttle External Tank (ET). Volume i: Technical report

A NASTRAN analysis of the external tank (ET) substructure of the 1/8-scale space shuttle structural dynamics model is described. The NASTRAN hydroelastic procedures were used to form a model of the liquid oxygen portion of the ET. Large computer storage requirements and running times were required unless these procedures were modified. Several possibilities were demonstrated including the substitution of the real for the complex eigenvalue routine and the use of the OMIT capability to reduce the number of fluid coordinates. A NASTRAN model of the complete ET was formed and reduced to 252 degrees of freedom. A review of the eigenvector extracted, using the unsymmetrical inverse power method, indicated that the structural OMIT's resulted in unsatisfactory modal deflections. Modifications to the NASTRAN hydroelastic capability appeared necessary to generate a successful ET model. An approach is described which, by assuming incompressibility, reduces the fluid representation to a symmetric mass matrix which can be added to the structural mass. The problem is solved using faster and more efficient eigenvalue routines. Using this approach the ET NASTRAN model was analyzed for three separate weight conditions.

Bernstein, M.↗

NASA NTRS1981

Analyzing and modeling gravity and magnetic anomalies using the SPHERE program and Magsat data

Computer codes were completed, tested, and documented for analyzing magnetic anomaly vector components by equivalent point dipole inversion. The codes are intended for use in inverting the magnetic anomaly due to a spherical prism in a horizontal geomagnetic field and for recomputing the anomaly in a vertical geomagnetic field. Modeling of potential fields at satellite elevations that are derived from three dimensional sources by program SPHERE was made significantly more efficient by improving the input routines. A preliminary model of the Andean subduction zone was used to compute the anomaly at satellite elevations using both actual geomagnetic parameters and vertical polarization. Program SPHERE is also being used to calculate satellite level magnetic and gravity anomalies from the Amazon River Aulacogen.

Braile, L. W.↗

NASA NTRS2013

Real-Time Minimization of Tracking Error for Aircraft Systems

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

Garud, Sumedha↗

NASA NTRSDate not supplied

Transfer Function Models and Sensitivity Analysis

In many situations, real or induced flaws such as tight cracks with known morphology cannot be manufactured in part configuration specimens or in real parts. Typically, fatigue cracks are manufactured in simple geometry specimens such as flat plates, dog-bone shaped flat or round specimens. If a nondestructive evaluation (NDE) technique is required to provide a reliably detectable target flaw size denoted as α_(90/95) for induced flaws in real part, then the direct method for qualifying the NDE procedure is to use the appropriate induced flaw specimens and perform probability of detection analysis using these flaws. This can be described as direct POD demonstration testing, which may follow guidelines of MIL-HDBK-1823. This paper considers a case, where induced flaws are not available in part configuration specimens. Therefore, a direct POD demonstration study cannot be undertaken. In such situation, general practice for NDE procedure qualification is to use artificial flaws in simple geometry and part configuration specimens, and induced flaws in the chosen simple geometry specimens. Signal response data is taken on all sets of artificial and induced flaws. NDE procedure testing on induced flaw in simple geometry specimen is called NDE demonstration testing here. A transfer function NDE procedure qualification method for forward case calculates predicted induced flaw size for demonstration using a chosen target flaw size. Another transfer function method for inverse case, calculates the target flaw size using a given demonstration flaw size. The transfer function analysis assumes relationship of artificial flaw signal responses in real parts and simple geometry specimens; and induced flaw responses in simple geometry specimens to induced flaws in real parts. The signal response transfer relationships model should be defined before transfer function models can be devised. Assuming that the signal response transfer relationships model is valid, forward and inverse case transfer function methods have been devised. Because of lack of signal response data from induced flaws in real part, 90/95% POD/confidence (P/C) cannot be demonstrated directly. However, the transfer function method may be assessed using simulation to evaluate whether the resulting target flaw size or demonstration flaw size provides adequate confidence to the assumed signal response transfer relationships model. Therefore, the transfer function approach is a risk assessment approach. Both the signal response transfer relationships model and the transfer function model are important in managing risk in results provided by the transfer function NDE technique qualification or assessment. The signal response transfer relationships model needs to be validated with empirical data and then transfer function model needs to be validated for desired P/C on case-by-case basis.

Nondestructive evaluation↗

NASA NTRS1990

Recursive dynamics for geared robot manipulators

The authors consider the dynamical modeling of robot manipulators whose joint actuators consist of motors driving the joints through gears. The dynamical models for such manipulators are significantly more complex than those for direct drive manipulators. The authors develop recursive O(n) inverse and forward dynamics algorithms as well as recursive O(n2) algorithms for the computation of the mass matrix for geared manipulators. It is shown that, despite the added complexity of the dynamical models for geared manipulators, the algorithms closely resemble the corresponding algorithms for direct drive manipulators, and that the additional algorithmic or computational complexity is relatively insignificant. As a consequence, with little additional cost, existing direct drive algorithms can be easily extended to handle the effects of gearing at the joints.

Jain, A.↗

NASA NTRS2022

Re-Evaluation of Low Cloud Amount Relationships With Lower-Tropospheric Stability and Estimated Inversion Strength

Lower-tropospheric stability (LTS) and estimated inversion strength (EIS) have a widely accepted relationship with low cloud amount and are key observational foundations for understanding and modeling low-level stratiform clouds. Using the updated surface-based and satellite cloud data, we find that low cloud amount is not as strongly correlated with LTS, and not as sensitive to LTS, as established in the past. EIS does not provide a stronger correlation with low cloud amount than LTS over all eight regions (including the midlatitudes). Further analyzing the relationships between LTS and EIS with different types of low clouds, we find that there is a strong correlation of LTS and EIS with stratocumulus only. This explains the weaker correlation of low cloud fraction (including cumulus, stratocumulus, and stratus) to both LTS and EIS. These results also suggest the need to re-evaluate these relationships in Earth system models. Plain Language Summary: Low-level clouds play an important role in the global radiation budget. Low cloud amount has two established linear relationships with lower-tropospheric stability (LTS) and estimated inversion strength (ETS). These two relationships are re-evaluated here using three separate observational cloud and two reanalysis datasets for three distinct but overlapping time periods. The analysis shows that the strength of the LTS and ETS relationships with low cloud amount varies, depending on the cloud data used. They have a strong relationship with stratocumulus cloud amount only.

Lauren Cutler↗

NASA NTRS1992

Inversion of surface parameters using fast learning neural networks

A neural network approach to the inversion of surface scattering parameters is presented. Simulated data sets based on a surface scattering model are used so that the data may be viewed as taken from a completely known randomly rough surface. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) are tested on the simulated backscattering data. The RMS error of training the FL network is found to be less than one half the error of the BP network while requiring one to two orders of magnitude less CPU time. When applied to inversion of parameters from a statistically rough surface, the FL method is successful at recovering the surface permittivity, the surface correlation length, and the RMS surface height in less time and with less error than the BP network. Further applications of the FL neural network to the inversion of parameters from backscatter measurements of an inhomogeneous layer above a half space are shown.

Dawson, M. S.↗

NASA NTRS2017

Upper Blue Nile Basin Water Budget from a Multi-Model Perspective

Improved understanding of the water balance in the Blue Nile is of critical importance because of increasingly frequent hydroclimatic extremes under a changing climate. The intercomparison and evaluation of multiple land surface models (LSMs) associated with different meteorological forcing and precipitation datasets can offer a moderate range of water budget variable estimates. In this context, two LSMs, Noah version 3.3 (Noah3.3) and Catchment LSM version Fortuna 2.5 (CLSMF2.5) coupled with the Hydrological Modeling and Analysis Platform (HyMAP) river routing scheme are used to produce hydrological estimates over the region. The two LSMs were forced with different combinations of two reanalysis-based meteorological datasets from the Modern-Era Retrospective analysis for Research and Applications datasets (i.e., MERRA-Land and MERRA-2) and three observation-based precipitation datasets, generating a total of 16 experiments. Modeled evapotranspiration (ET), streamflow, and terrestrial water storage estimates were evaluated against the Atmosphere-Land Exchange Inverse (ALEXI) ET, in-situ streamflow observations, and NASA Gravity Recovery and Climate Experiment (GRACE) products, respectively. Results show that CLSMF2.5 provided better representation of the water budget variables than Noah3.3 in terms of Nash-Sutcliffe coefficient when considering all meteorological forcing datasets and precipitation datasets. The model experiments forced with observation-based products, the Climate Hazards group Infrared Precipitation with Stations (CHIRPS) and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA), outperform those run with MERRA-Land and MERRA-2 precipitation. The results presented in this paper would suggest that the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System incorporate CLSMF2.5 and HyMAP routing scheme to better represent the water balance in this region.

Rainfall↗

NASA NTRS1999

The Prospect for Remote Sensing of Cirrus Clouds with a Submillimeter-Wave Spectrometer

Given the substantial radiative effects of cirrus clouds and the need to validate cirrus cloud mass in climate models, it is important to measure the global distribution of cirrus properties with satellite remote sensing. Existing cirrus remote sensing techniques, such as solar reflectance methods, measure cirrus ice water path (IWP) rather indirectly and with limited accuracy. Submillimeter/wave radiometry is an independent method of cirrus remote sensing based on ice particles scattering the upwelling radiance emitted by the lower atmosphere. A new aircraft instrument, the Far Infrared Sensor for Cirrus (FIRSC), is described. The FIRSC employs a Fourier Transform Spectrometer (FTS). which measures the upwelling radiance across the whole submillimeter region (0.1 1.0-mm wavelength). This wide spectral coverage gives high sensitivity to most cirrus particle sizes and allows accurate determination of the characteristic particle size. Radiative transfer modeling is performed to analyze the capabilities of the submillimeter FTS technique. A linear inversion analysis is done to show that cirrus IWP, particle size, and upper-tropospheric temperature and water vapor may be accurately measured, A nonlinear statistical algorithm is developed using a database of 20000 spectra simulated by randomly varying most relevant cirrus and atmospheric parameters. An empirical orthogonal function analysis reduces the 500-point spectrum (20 - 70/cm) to 15 "pseudo-channels" that are then input to a neural network to retrieve cirrus IWP and median particle diameter. A Monte Carlo accuracy study is performed with simulated spectra having realistic noise. The retrieval errors are low for IWP (rms less than a factor of 1.5) and for particle sizes (rins less than 30%) for IWP greater than 5 g/sq m and a wide range of median particle sizes. This detailed modeling indicates that there is good potential to accurately measure cirrus properties with a submillimeter FTS.

Evans, K. Franklin↗

NASA NTRS2005

Aerosol properties computed from aircraft-based observations during the ACE- Asia campaign: A case study of lidar ratio closure and aerosol radiative effects - 2

For a vertical profile with three distinct layers (marine boundary, pollution and dust), observed during the ACE-Asia campaign, we carried out a comparison between the modeled lidar ratio vertical profile and that obtained from collocated airborne NASA AATS-14 sunphotometer and shipborne Micro-Pulse Lidar (MPL) measurements. Vertically resolved lidar ratio was calculated from two size distribution vertical profiles - one obtained by inversion of sunphotometer-derived extinction spectra, and one measured in-situ - combined with the same refractive index model based on aerosol chemical composition. The aerosol model implies single scattering albedos of 0.78 - 0.81 and 0.93 - 0.96 at 0.523 microns (the wavelength of the lidar measurements), in the pollution and dust layers, respectively. The lidar ratios calculated from the two size distribution profiles have close values in the dust layer; they are however, significantly lower than the lidar ratios derived from combined lidar and sunphotometer measurements, most probably due to the use of a simple nonspherical model with a single particle shape in our calculations. In the pollution layer, the two size distribution profiles yield generally different lidar ratios. The retrieved size distributions yield a lidar ratio which is in better agreement with that derived from lidar/sunphotometer measurements in this layer, with still large differences at certain altitudes (the largest relative difference was 46%). We explain these differences by non-uniqueness of the result of the size distribution retrieval and lack of information on vertical variability of particle refractive index. Radiative transfer calculations for this profile showed significant atmospheric radiative forcing, which occurred mainly in the pollution layer. We demonstrate that if the extinction profile is known then information on the vertical structure of absorption and asymmetry parameter is not significant for estimating forcing at TOA and the surface, while it is of importance for estimating vertical profiles of radiative forcing and heating rates.

Kuzmanoski, Maja↗

NASA NTRS1972

Investigation of bubbles in arterial heat pipes

The behavior of gas occlusions in arterial heat pipes has been studied experimentally and theoretically. Specifically, the gas-liquid system properties, solubility and diffusivity, have been measured from -50 to 100 C for helium and argon in ammonia, Freon-21 (CHC12F), and methanol. Properties values obtained were then used to experimentally test models for gas venting from a heat pipe artery under isothermal conditions (i.e., no-heat flow), although the models, as developed, are also applicable to heat pipes operated at power, with some minor modifications. Preliminary calculations indicated arterial bubbles in a stagnant pipe require from minutes to days to collapse and vent. It has been found experimentally that a gas bubble entrapped within an artery structure has a very long lifetime in many credible situations. This lifetime has an approximately inverse exponential dependence on temperature, and is generally considerably longer for helium than for argon. The models postulated for venting under static conditions were in general quantitative agreement with experimental data. Factors of primary importance in governing bubble stability are artery diameter, artery wall thickness, noncondensible gas partial pressure, and the property group (the Ostwald solubility coefficient multiplied by the gas/liquid diffusivity).

Saaski, E. W.↗

NASA NTRS1982

Radar properties of Europa, Ganymede, and Callisto

The radar properties of Europa, Ganymede, and Callisto are summarized and present understanding of these properties is documented. The radar techniques are described, observational results reviewed, and salient aspects of the radar data set discussed. Theoretical interpretation of the satellites' anomalous radar properties is addressed, including aspects such as external scattering and double reflection from hemispherical craters, the random-facet model, total internal reflection, multiple total internal reflection, the high radar geometric albedos, the tenous upper layer, the two-component regolith, and compositional effects. It is concluded that multiple total internal reflection from randomly oriented subsurface facets can explain the anomalous circular polarization inversion in the radar echoes from the three satellites. Several refinements of the Goldstein-Green (1980) scattering model are suggested.

Ostro, S. J.↗

NASA NTRS2018

Polarization Decomposition and Temperature Bias Resolution for SMAP Passive Soil Moisture Retrieval Using Time Series Brightness Temperature Observations

In passive microwave remote sensing of soil moisture, the tau-omega (τ-ω) model has often been used to provide soil moisture estimates at a spatial scale representative of the satellite footprint dimensions. For modeling simplicity, model parameters such as the single scattering albedo (ω) and vegetation opacity (τ) that go into the geophysical inversion process are often assumed to be independent of polarizations. Although this absence of polarization dependence can often be justified in special cases as in low-frequency remote sensing or under dense vegetation conditions, it is not a robust assumption in general. Additional model parameterization errors arising from this assumption are possible, leading to degradation in soil moisture estimation accuracy. In this paper, we propose a time series approach to try to resolve the polarization dependence of several τ-ω model parameters as well as the temperature bias arising from the ancillary temperature data. The Version 4 of the Soil Moisture Active Passive (SMAP) Level 1B brightness temperature time series observations were used to illustrate the mechanics of this approach, with an emphasis on a comparison between resulting satellite soil moisture retrievals and in situ data collected at several core validation sites. It was found that this time series approach resulted in significant reduction of the dry bias exhibited in the current SMAP passive soil moisture data products, while retaining the same performance in other metrics of the current baseline passive soil moisture retrieval algorithm.

time series↗