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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Excerpt from Oxygen Monitor Clean Testing Report Performed in 2010

The Rosemount X-STREAM Series X2GP is a paramagnetic oxygen analyzer with a 0-25% oxygen measurement range. It claims a drift less than 2% of span (0.10% volume oxygen) per week, and a response time of less than 5 seconds (for the analyzer to report 90% of a step change). Our test equipment was set-up such that the same gas was running through each oxygen analyzer at the same time. This allowed Calibration Error, Calibration Drift, and Loss of Power Testing to be run on all monitors at the same time, eliminating any variability between the analyzers from tolerances in the gas cylinder, ambient temperature, ambient pressure, test duration, etc. An APTech pressure regulator was placed on the gas cylinder manifold and a 23 psia Paroscientific pressure transducer measured the regulator’s outlet pressure. This did not give the inlet pressure on any one analyzer but outlet pressure from the manifold before the stream was split. The APTech pressure regulator was used to keep operating conditions consistent. A DWYER rotameter was installed on each oxygen monitor’s outlet piping. With the exception of Variation of Flow Rate Testing, the rotameter was left fully open for all testing. The flow rate through each oxygen monitor was controlled by a Swagelok needle valve that was installed on each analyzer’s inlet piping. Additionally, a filter was installed in the each monitor’s inlet piping to keep particles from the measurement cells and a Swagelok ball valve was installed on each monitor’s outlet piping to isolate each monitor between tests. No pumps were installed. Each of the cylinders used was at a pressure greater than ambient room barometric pressure. This pressure differential was used to move gas through the testing equipment. The flow rate through each analyzer was controlled by the Swagelok needle valve installed on each analyzer’s inlet piping. Finally, for all tests, a Paroscientific Digiquartz Barometer was used to measure ambient room barometric pressure and a Fluke Thermo-hygrometer was used to measure ambient room temperature.

47 OTHER INSTRUMENTATION↗
NASA NTRS2000

Comparison of On-Orbit Performance of Rate Sensing Gyroscopes

This work presents results from the study of a large volume of spacecraft flight data pertaining to gyroscope performance. We have examined long and short term trends of gyroscope biase of first, an exact solution for the time-dependence of the attitude part of the state error covariance, averaged over the three spacecraft axes, is given. This solution is more complete than the usual cubic polynomial for the variance in that it includes coupling among the three gyroscope axes and includes an important term arising from the initial correlations. Second, several continuous 24-hour spans of gyroscope data are examined to verify the short-term statistical model. This analysis demonstrates that in-flight data can be used to determine the strength of the white noise driving the random walk of the gyroscope bias. This may be useful for postlaunch improvement to the noise model and for diagnosing the health of the gyroscope. Third, the long-term trends in gyroscope biases show a nearly linear systematic variation over time scales of years. This has been found on three different missions. While the random walk model is adequate as a basis for onboard Kalman filters or for state estimation using relatively short time spans, these trends indicate that some applications could benefit by accounting for the secular changes in the biases. One example is a new gyroscope calibration method that is under development that allows for multi-epoch bias solutions.

Sedlak, Joseph↗
NASA NTRS1991

Pi/4-QPSK modems for satellite sound/data broadcast systems

The use of pi/4-quadrature phase-shift keying (QPSK) modems for satellite sound broadcast systems (SSBS) broadcasting to mobile or portable receivers is proposed. Three different differential detectors (including the FM-discriminator followed by integrate-sample-and-dump filter) and a novel coherent detector are discussed. The degradation caused by the frequency offset between the local oscillator (LO) and the unmodulated carrier (CR) in the baseband differential detector is studied. The performance of both coherently and differentially detected pi/4-QPSK in a Gaussian channel is also studied. It is shown that with a frequency offset of more than 3 percent of the symbol rate, the performance degradation is more than 1 dB at 0.0001. The out-of-band power of the nonlinearly amplified bandlimited pi/4-QPSK signals is reduced from -13 dB to -37 dB if a 2-dB output back-off amplifier is used instead of a hardlimiter. The performance of the pi/4-QPSK is equivalent to that of QPSK, although the pi/4-QPSK has the advantage of less spectrum restoration after nonlinear amplification. The coherent demodulator and differential decoder avoid the three-level detection and achieve the same bit-error-rate performance as DEQPSK with a simple circuit.

Liu, Chia-Liang↗
NASA NTRS1992

HST image restoration: A comparison of pre- and post-servicing mission results

A variety of image restoration techniques (e.g., Wiener filter, Lucy-Richardson, MEM) have been applied quite successfully to the aberrated HST images. The HST servicing mission (scheduled for late 1993 or early 1994) will install a corrective optics system (COSTAR) for the Faint Object Camera and spectrographs and replace the Wide Field/Planetary Camera with a second generation instrument (WF/PC-II) having its own corrective elements. The image quality is expected to be improved substantially with these new instruments. What then is the role of image restoration for the HST in the long term? Through a series of numerical experiments using model point-spread functions for both aberrated and unaberrated optics, we find that substantial improvements in image resolution can be obtained for post-servicing mission data using the same or similar algorithms as being employed now to correct aberrated images. Included in our investigations are studies of the photometric integrity of the restoration algorithms and explicit models for HST pointing errors (spacecraft jitter).

Hanisch, R. J.↗
NASA NTRS2019

GOES-17 Magnetometer On-Orbit Calibration Design and Results

The Geostationary Operational Environmental Satellite-R (GOES-R) is a series of four NOAA weather satellites. Each spacecraft flies a Magnetometer instrument which includes two boom mounted fluxgate sensors located 6.3 and 8.5 meters from the spacecraft. Sensor readings are corrupted by both internal (bias and scale factor) and external (spacecraft emitted fields and misalignments) error sources. In order to estimate the bias, an on-orbit calibration is performed, slewing the spacecraft about multiple axes and then performing a fit of the data to determine zero offset and misalignment terms. The first satellite in the series, GOES-16 was launched in November 2016. Its magnetometer calibration maneuver was found to be inadequate providing insufficient rotation about orthogonal axes. The uncertainty in the estimated biases was found to be in the 3-5 nanotesla range, exceeding the magnetometer accuracy requirement of 1.0 nanotesla. Based on lessons learned, the maneuver was redesigned to provide multiple 360 degree rotations about two orthogonal axes, providing optimal visibility into bias and misalignment. Varying ambient fields over the duration of the calibration maneuvers, corrupts the ability to accurately determine parameters of interest. To address this issue, rather than assuming a constant field for the duration of the maneuver, a non-linear least squares filter was employed that uses a series of spline functions to better fit the ambient field. The number of splines can be varied to minimize the least squares filter residuals. Simulations were performed using 360 days of GOES-16 data to bound the uncertainty in the biases for given residuals of the fit to the ambient field. Following the launch of the second satellite in the series, GOES-17 in March 2018, the new calibration maneuver and enhanced bias estimation algorithm were exercised twice. Based on the residuals of the fit, the uncertainty of the estimated zero offset was reduced by an order of magnitude from 3-5 nanotesla to approximately 0.4 nanotesla per axis. This paper provides details of the maneuver design and the innovative algorithm used to estimate the GOES-17 biases and misalignments.

GOES-17↗
DOE OSTI2026

Ensemble Kalman filter for data assimilation coupled with low-resolution computations techniques applied in fluid dynamics

This paper presents an innovative Reduced-order model (ROM) for merging experimental and simulation data using data assimilation (DA) to estimate the "True" state of a fluid dynamics system, leading to more accurate predictions. Our methodology introduces a novel approach by implementing the ensemble Kalman filter (EnKF) within a reduced-dimensional framework, grounded in a robust theoretical foundation and applied to fluid dynamics. To address the substantial computational demands of DA, the proposed ROM employs low-resolution (LR) techniques to drastically reduce computational costs. This innovative approach involves downsampling datasets for DA computations, followed by an advanced reconstruction technique based on low-cost singular value decomposition (lcSVD). The lcSVD method, a key innovation in this paper, has never been applied to DA before and offers a highly efficient way to enhance resolution with minimal computational resources. Our results demonstrate significant reductions in both computation time and RAM usage through these LR techniques without compromising the accuracy of the estimations. For instance, in a turbulent test case, for a data compression rate of 15.9, the LR approach can achieve a speed-up of 13.7 and a RAM compression of 90.9% while maintaining a low relative root mean square error (RRMSE) of 2.6%, compared to 0.8% in the high-resolution (HR) reference. Furthermore, we highlight the effectiveness of the EnKF in estimating and predicting the state of fluid flow systems based on limited observations and given low-fidelity numerical data. This paper highlights the potential of the proposed DA method in fluid dynamics applications, particularly for improving computational efficiency in CFD and related fields. Its ability to balance accuracy with low computational and memory costs makes it especially suitable for large-scale and real-time applications, such as environmental monitoring or engineering design. This method will be incorporated into ModelFLOWs-app.

Data Assimilation↗
NASA NTRS2001

An OFDM System Using Polyphase Filter and DFT Architecture for Very High Data Rate Applications

This paper presents a conceptual architectural design of a four-channel Orthogonal Frequency Division Multiplexing (OFDM) system with an aggregate information throughput of 622 megabits per second (Mbps). Primary emphasis is placed on the generation and detection of the composite waveform using polyphase filter and Discrete Fourier Transform (DFT) approaches to digitally stack and bandlimit the individual carriers. The four-channel approach enables the implementation of a system that can be both power and bandwidth efficient, yet enough parallelism exists to meet higher data rate goals. It also enables a DC power efficient transmitter that is suitable for on-board satellite systems, and a moderately complex receiver that is suitable for low-cost ground terminals. The major advantage of the system as compared to a single channel system is lower complexity and DC power consumption. This is because the highest sample rate is half that of the single channel system and synchronization can occur at most, depending on the synchronization technique, a quarter of the rate of a single channel system. The major disadvantage is the increased peak-to-average power ratio over the single channel system. Simulation results in a form of bit-error-rate (BER) curves are presented in this paper.

Kifle, Muli↗
NASA NTRS2011

Large Aperture "Photon Bucket" Optical Receiver Performance in High Background Environments

The potential development of large aperture groundbased "photon bucket" optical receivers for deep space communications, with acceptable performance even when pointing close to the sun, is receiving considerable attention. Sunlight scattered by the atmosphere becomes significant at micron wavelengths when pointing to a few degrees from the sun, even with the narrowest bandwidth optical filters. In addition, high quality optical apertures in the 10-30 meter range are costly and difficult to build with accurate surfaces to ensure narrow fields-of-view (FOV). One approach currently under consideration is to polish the aluminum reflector panels of large 34-meter microwave antennas to high reflectance, and accept the relatively large FOV generated by state-of-the-art polished aluminum panels with rms surface accuracies on the order of a few microns, corresponding to several-hundred micro-radian FOV, hence generating centimeter-diameter focused spots at the Cassegrain focus of 34-meter antennas. Assuming pulse-position modulation (PPM) and Poisson-distributed photon-counting detection, a "polished panel" photon-bucket receiver with large FOV will collect hundreds of background photons per PPM slot, along with comparable signal photons due to its large aperture. It is demonstrated that communications performance in terms of PPM symbol-error probability in high-background high-signal environments depends more strongly on signal than on background photons, implying that large increases in background energy can be compensated by a disproportionally small increase in signal energy. This surprising result suggests that large optical apertures with relatively poor surface quality may nevertheless provide acceptable performance for deep-space optical communications, potentially enabling the construction of cost-effective hybrid RF/optical receivers in the future.

photon bucket detection↗
NASA NTRS2025

Localization of Ad-Hoc Lunar Constellations in Communication Failure Modes for Distributed Spacecraft Autonomy

As Lunar missions increase in complexity, inspired by NASA’s Artemis Program, they will require reliable and sufficient Position, Navigation, and Timing (PNT) capability to support the upcoming Lunar users. The navigation service should also be compatible with the smaller platforms, like CubeSats, being sent by the public and private sectors. A non-dedicated, ad-hoc Lunar navigation constellation can provide PNT services on-demand using the non-dedicated swarm assets. Swarm members cooperatively and autonomously localize themselves with minimal interaction from Earth, freeing up valuable bandwidth and ground segment resources. The autonomous localization of Lunar constellations utilizes neighbor two-way intersatellite link (ISL) measurements in a distributed extended Kalman filter (DEKF) system to minimize operating costs. Because the decentralized Lunar PNT system relies on relay communication amongst the agents, network failures or loss of assets among ad-hoc Lunar constellations may impact localization performance. This study presents an evaluation of localization performance under increasing levels of network degradation. A simulation of an ad-hoc Lunar PNT swarm is augmented to include system faults and the impacts of intermittent and permanent failures on localization performance are evaluated. We investigate three potential causes of network degradation: single spacecraft loss, multiple spacecraft loss, and antenna failure. The numerical assessments from the simulation show that the LPNT system under study, based on an autonomous decentralized concept of operation, is highly robust and resilient to communication failures. Minor faults, such as single spacecraft loss, solar interference, technical malfunctions, message delays, and antenna outages, have minimal impact on state estimation, with only a 4.47% and 3.75% degradation in median position error for assets and a representative ground user, respectively, compared to an ideal communication scenario. However, major faults, such as hardware failures or meteor strikes leading to the loss of multiple spacecrafts, are more concerning. The permanent loss of three spacecraft results in a more severe performance degradation, with median position error increasing by 23.3% for assets and 11.7% for a representative ground user, despite the Lunar PNT system remaining functional.

Yeji Kim↗
DOE OSTI2021

Efficient Precoding for Single Carrier Modulation in Multi-User Massive MIMO Networks

Abstract—Frequency domain (FD) multi-user detection (MUD) and precoding has been shown to be an effective means of approaching the theoretical per-user capacity for single carrier modulation (SCM) schemes in massive MIMO scenarios with highly dispersive channels. When a cyclic prefix is added to the SCM waveform, the circulant structures of the resulting convolutional channel matrix allows for relatively simple expressions for the FD detection and precoding. In this paper, we further refine the computationally efficient minimum mean squared error (MMSE) FD-MUD technique in a time-division duplexing (TDD) massive MIMO setup by pre-computing the scale factor needed to produce an unbiased estimate. The resulting scale factor and the matrix inverse that was calculated for the uplink is then reused for the downlink to form a computationally efficient precoding scheme with superior performance compared to zero-forcing (ZF) precoding. Performance analysis is provided and confirmed through simulation results.

5G and Beyond Communications↗
NASA NTRS2007

Performance of the Lidar Design and Data Algorithms for the GLAS Global Cloud and Aerosol Measurements

The Geoscience Laser Altimeter System (GLAS) launched in early 2003 is the first polar orbiting satellite lidar. The instrument design includes high performance observations of the distribution and optical scattering cross sections of atmospheric clouds and aerosol. The backscatter lidar operates at two wavelengths, 532 and 1064 nm. For the atmospheric cloud and aerosol measurements, the 532 nm channel was designed for ultra high efficiency with solid state photon counting detectors and etalon filtering. Data processing algorithms were developed to calibrate and normalize the signals and produce global scale data products of the height distribution of cloud and aerosol layers and their optical depths and particulate scattering cross sections up to the limit of optical attenuation. The paper will concentrate on the effectiveness and limitations of the lidar channel design and data product algorithms. Both atmospheric receiver channels meet and exceed their design goals. Geiger Mode Avalanche Photodiode modules are used for the 532 nm signal. The operational experience is that some signal artifacts and non-linearity require correction in data processing. As with all photon counting detectors, a pulse-pile-up calibration is an important aspect of the measurement. Additional signal corrections were found to be necessary relating to correction of a saturation signal-run-on effect and also for daytime data, a small range dependent variation in the responsivity. It was possible to correct for these signal errors in data processing and achieve the requirement to accurately profile aerosol and cloud cross section down to 10-7 llm-sr. The analysis procedure employs a precise calibration against molecular scattering in the mid-stratosphere. The 1064 nm channel detection employs a high-speed analog APD for surface and atmospheric measurements where the detection sensitivity is limited by detector noise and is over an order of magnitude less than at 532 nm. A unique feature of the GLAS is a full acquisition of the surface return pulse, which has important application to the atmospheric transmission retrieval.

Spinhirne, James D.↗
NASA NTRS2012

Simulation of Oxygen Disintegration and Mixing With Hydrogen or Helium at Supercritical Pressure

The simulation of high-pressure turbulent flows, where the pressure, p, is larger than the critical value, p(sub c), for the species under consideration, is relevant to a wide array of propulsion systems, e.g. gas turbine, diesel, and liquid rocket engines. Most turbulence models, however, have been developed for atmospheric-p turbulent flows. The difference between atmospheric-p and supercritical-p turbulence is that, in the former situation, the coupling between dynamics and thermodynamics is moderate to negligible, but for the latter it is very significant, and can dominate the flow characteristics. The reason for this stems from the mathematical form of the equation of state (EOS), which is the perfect-gas EOS in the former case, and the real-gas EOS in the latter case. For flows at supercritical pressure, p, the large eddy simulation (LES) equations consist of the differential conservation equations coupled with a real-gas EOS. The equations use transport properties that depend on the thermodynamic variables. Compared to previous LES models, the differential equations contain not only the subgrid scale (SGS) fluxes, but also new SGS terms, each denoted as a correction. These additional terms, typically assumed null for atmospheric pressure flows, stem from filtering the differential governing equations, and represent differences between a filtered term and the same term computed as a function of the filtered flow field. In particular, the energy equation contains a heat-flux correction (q-correction) that is the difference between the filtered divergence of the heat flux and the divergence of the heat flux computed as a function of the filtered flow field. In a previous study, there was only partial success in modeling the q-correction term, but in this innovation, success has been achieved by using a different modeling approach. This analysis, based on a temporal mixing layer Direct Numerical Simulation database, shows that the focus in modeling the q-correction should be on reconstructing the primitive variable gradients rather than their coefficients, and proposes the approximate deconvolution model (ADM) as an effective means of flow field reconstruction for LES heat flux calculation. Further, results for a study conducted for temporal mixing layers initially containing oxygen in the lower stream, and hydrogen or helium in the upper stream, show that, for any LES, including SGS-flux models (constant-coefficient Gradient or Scale-Similarity models, dynamic-coefficient Smagorinsky/Yoshizawa or mixed Smagorinsky/Yoshizawa/Gradient models), the inclusion of the q-correction in the LES leads to the theoretical maximum reduction of the SGS heat-flux difference. The remaining error in modeling this new subgrid term is thus irreducible.

Bellan, Josette↗
NASA NTRS1997

Accuracy Study of a 2-Component Point Doppler Velocimeter (PDV)

A two-component Point Doppler Velocimeter (PDV) which has recently been developed is described, and a series of velocity measurements which have been obtained to quantify the accuracy of the PDV system are summarized. This PDV system uses molecular iodine vapor cells as frequency discriminating filters to determine the Doppler shift of laser light which is scattered off of seed particles in a flow. The majority of results which have been obtained to date are for the mean velocity of a rotating wheel, although preliminary data are described for fully-developed turbulent pipe flow. Accuracy of the present wheel velocity data is approximately +/- 1 % of full scale, while linearity of a single channel is on the order of +/- 0.5 % (i.e., +/- 0.6 m/sec and +/- 0.3 m/sec, out of 57 m/sec, respectively). The observed linearity of these results is on the order of the accuracy to which the speed of the rotating wheel has been set for individual data readings. The absolute accuracy of the rotating wheel data is shown to be consistent with the level of repeatability of the cell calibrations. The preliminary turbulent pipe flow data show consistent turbulence intensity values, and mean axial velocity profiles generally agree with pitot probe data. However, there is at present an offset error in the radial velocity which is on the order of 5-10 % of the mean axial velocity.

Kuhlman, John↗
NASA NTRS2007

A Side by Side Comparison of Filter-Based PM(sub 2.5) Measurements at a Suburban Site: A Closure Study

Reliable determination of the effects of air quality on public health and the environment requires accurate measurement of PM(sub 2.5) mass and the individual chemical components of fine aerosols. This study seeks to evaluate PM(sub 2.5) measurements that are part of a newly established national network by comparing them with a more conventional sampling system. Experiments were carried out during 2002 at a suburban site in Maryland, United States, where two samplers from the U.S. Environmental Protection Agency (USEPA) Speciation Trends Network: Met One Speciation Air Sampling System STNS and Thermo Scientific Reference Ambient Air Sampler STNR, two Desert Research Institute Sequential Filter Samplers DRIF, and a continuous TEOM monitor (Thermo Scientific Tapered Element Oscillating Microbalance) were sampling air in parallel. These monitors differ not only in sampling configuration but also in protocol-specific sample analysis procedures. Measurements of PM(sub 2.5) mass and major contributing species were well correlated among the different methods with r-values > 0.8. Despite the good correlations, daily concentrations of PM(sub 2.5) mass and major contributing species were significantly different at the 95% confidence level from 5 to 100% of the time. Larger values of PM(sub 2.5) mass and individual species were generally reported from STNR and STNS. The January STNR average PM(sub 2.5) mass (8.8 (micro)g/per cubic meter) was 1.5 (micro)g/per cubic meter larger than the DRIF average mass. The July STNS average PM(sub 2.5) mass (27.8 (micro)g/per cubic meter) was 3.8 (micro)g/per cubic meter larger than the DRIF average mass. These differences can only be partially accounted for by known random errors. Variations in flow control, face velocity, and sampling artifacts likely influence the measurement of PM(sub 2.5) speciation and mass closure. Simple statistical tests indicate that the current uncertainty estimates used in the STN network may underestimate the actual uncertainty.

Haines, Jennifer C.↗
NASA NTRS1992

Advanced satellite communication system

The objective of this research program was to develop an innovative advanced satellite receiver/demodulator utilizing surface acoustic wave (SAW) chirp transform processor and coherent BPSK demodulation. The algorithm of this SAW chirp Fourier transformer is of the Convolve - Multiply - Convolve (CMC) type, utilizing off-the-shelf reflective array compressor (RAC) chirp filters. This satellite receiver, if fully developed, was intended to be used as an on-board multichannel communications repeater. The Advanced Communications Receiver consists of four units: (1) CMC processor, (2) single sideband modulator, (3) demodulator, and (4) chirp waveform generator and individual channel processors. The input signal is composed of multiple user transmission frequencies operating independently from remotely located ground terminals. This signal is Fourier transformed by the CMC Processor into a unique time slot for each user frequency. The CMC processor is driven by a waveform generator through a single sideband (SSB) modulator. The output of the coherent demodulator is composed of positive and negative pulses, which are the envelopes of the chirp transform processor output. These pulses correspond to the data symbols. Following the demodulator, a logic circuit reconstructs the pulses into data, which are subsequently differentially decoded to form the transmitted data. The coherent demodulation and detection of BPSK signals derived from a CMC chirp transform processor were experimentally demonstrated and bit error rate (BER) testing was performed. To assess the feasibility of such advanced receiver, the results were compared with the theoretical analysis and plotted for an average BER as a function of signal-to-noise ratio. Another goal of this SBIR program was the development of a commercial product. The commercial product developed was an arbitrary waveform generator. The successful sales have begun with the delivery of the first arbitrary waveform generator.

Staples, Edward J.↗
NASA NTRS2019

Application of Synoptic Magnetograms for Prediction of Solar Activity Using Ensemble Kalman Filter

Solar activity predictions using the data assimilation approach have demonstrated great potential to build reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to a non-linear dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. These developments assume an empirical relationship between the mean toroidal magnetic field flux and the sunspot number. Estimated from the sunspot number series, variations of the toroidal field have been used to assimilate the data into the Parker-Kleeorin-Ruzmakin (PKR) dynamo model by applying the EnKF method. The dynamo model describes the evolution of the toroidal and poloidal components of the magnetic field and the magnetic helicity. Full-disk magnetograms provide more accurate and complete input data by constraining both the toroidal and poloidal global field components, but these data are available only for the last four solar cycles. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of limited time series observations on the accuracy of solar activity predictions. We present EnKF predictions of the upcoming Solar Cycle 25 based on both the sunspot number series and observed magnetic fields and discuss the uncertainties and potential of the data assimilation approach.

Kitiashvili, Irina N.↗
NASA NTRS2018

Enhancements to the Open Access Spectral Band Adjustment Factor Online Calculation Tool for Visible Channels

With close to 40 years of satellite observations, from which, cloud, land-use, and aerosol parameters can be measured, inter-consistent calibrations are needed to normalize retrievals across satellite records. Various visible-sensor inter-calibration techniques have been developed that utilize radiometrically stable Earth targets, e.g., deep convective clouds and desert/polar ice pseudo-invariant calibration sites. Other equally effective, direct techniques for intercalibration between satellite imagers are simultaneous nadir overpass comparisons and ray-matched radiance pairs. Combining independent calibration results from such varied techniques yields robust calibration coefficients, and is a form of self-validation. One potential source of significant error when cross-calibrating satellite sensors, however, are the often small but substantial spectral discrepancies between comparable bands, which must be accounted for. As such, visible calibration methods rely on a Spectral Band Adjustment Factor (SBAF) to account for the spectral-response function- induced radiance differences between analogous imagers. The SBAF is unique to each calibration method as it is a function of the Earth-reflected spectra. In recent years, NASA Langley pioneered the use of SCIAMACHY-, GOME-2-, and Hyperion-retrieved Earth spectra to compute SBAFs. By carefully selecting hyperspectral footprints that best represent the conditions inherent to an inter-calibration technique, the uncertainty in the SBAF is greatly reduced. NASA Langley initially provided the Global Space-based Inter-calibration System processing and research centers with online SBAF tools, with which users select conditions to best match their calibration criteria. This article highlights expanded SBAF tool capabilities for visible wavelengths, with emphasis on the use of the spectral range filtering for the purpose of separating scene conditions for the channel that the SBAF is needed based on the reflectance values of other bands. In other words, spectral filtering will enable better scene-type selection for bands where scene determination is difficult without information from other channels, which should prove valuable to users in the calibration community.

Scarino, Benjamin↗
NASA NTRS2016

Assimilation of SMOS Brightness Temperatures or Soil Moisture Retrievals into a Land Surface Model

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.

SMOS↗