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NASA NTRS1970

GEOS satellite tracking corrections for refraction in the ionosphere

The analytic formulations at different elevation angles and at a frequency of 2-GHz for the ionospheric refraction corrections used on the GEOS satellite tracking data are compared. The formulas and ray trace results for elevations greater than 10 deg, where most satellite tracking is done, differ in elevation, range, and range rate by less than 0.4 millidegrees (1.4 arc-seconds), 12 meters, and 12 cm/sec, respectively. In comparison to most operational requirements, this is insignificant. However, for the GEOS Observation Systems Intercomparison Investigation, these differences are equivalent in size to observed differences in system biases for some of the best electronic geodetic tracking systems and are probably contributing to the observed biases. The ray trace results and most of the more detailed analytic correction formulas show that the ionospheric refraction correction for range rate on an overhead pass is a maximum for elevation angles between 15 deg and 30 deg and falls off rapidly for both higher and lower elevation angles, contrary to the effect of the troposphere and to some reports in the literature.

Berbert, J. H.↗
NASA NTRS1990

Investigation of Particle Sampling Bias in the Shear Flow Field Downstream of a Backward Facing Step

The flow field about a backward facing step was investigated to determine the characteristics of particle sampling bias in the various flow phenomena. The investigation used the calculation of the velocity:data rate correlation coefficient as a measure of statistical dependence and thus the degree of velocity bias. While the investigation found negligible dependence within the free stream region, increased dependence was found within the boundary and shear layers. Full classic correction techniques over-compensated the data since the dependence was weak, even in the boundary layer and shear regions. The paper emphasizes the necessity to determine the degree of particle sampling bias for each measurement ensemble and not use generalized assumptions to correct the data. Further, it recommends the calculation of the velocity:data rate correlation coefficient become a standard statistical calculation in the analysis of all laser velocimeter data.

Meyers, James F.↗
NASA NTRS1981

Seasat altimeter height calibration

The Seasat altimeter was calibrated for height bias using four overflight passes of Bermuda which were supported by the Bermuda laser. The altimeter data was corrected for: tides, using recorded tide gauge data; propagation effects, using meteorological data taken around the time of each pass; acceleration lag; and sea state bias, including both surface effects and instrumental effects. Altimeter data for each of the four passes was smoothed and extrapolated across the island. Interpolation between passes then produced an equivalent altimeter measurement to the geoid at the laser site, so that the altimeter bias could be estimated without the use of a geoid model. The estimated height bias was 0.0 + or - 0.07.

Kolenkiewicz, R.↗
NASA NTRS1994

Correlated environmental corrections in TOPEX/POSEIDON, with a note on ionospheric accuracy

Estimates of the effectiveness of an altimetric correction, and interpretation of sea level variability as a response to atmospheric forcing, both depend upon assuming that residual errors in altimetric corrections are uncorrelated among themselves and with residual sea level, or knowing the correlations. Not surprisingly, many corrections are highly correlated since they involve atmospheric properties and the ocean surface's response to them. The full corrections (including their geographically varying time mean values), show correlations between electromagnetic bias (mostly the height of wind waves) and either atmospheric pressure or water vapor of -40%, and between atmospheric pressure and water vapor of 28%. In the more commonly used collinear differences (after removal of the geographically varying time mean), atmospheric pressure and wave height show a -30% correlation, atmospheric pressure and water vapor a -10% correlation, both pressure and water vapor a 7% correlation with residual sea level, and a bit surprisingly, ionospheric electron content and wave height a 15% correlation. Only the ocean tide is totally uncorrelated with other corrections or residual sea level. The effectiveness of three ionospheric corrections (TOPEX dual-frequency, a smoothed version of the TOPEX dual-frequency, and Doppler orbitography and radiopositioning integrated by satellite (DORIS) is also evaluated in terms of their reduction in variance of residual sea level. Smooth (90-200 km along-track) versions of the dual-frequency altimeter ionosphere perform best both globally and within 20 deg in latitude from the equator. The noise variance in the 1/s TOPEX inospheric samples is approximately (11 mm) squared, about the same as noise in the DORIS-based correction; however, the latter has its error over scales of order 10(exp 3) km. Within 20 deg of the equator, the DORIS-based correction adds (14 mm) squared to the residual sea level variance.

Zlotnicki, V.↗
NASA NTRS2016

Model Development for MODIS Thermal Band Electronic Crosstalk

MODerate-resolution Imaging Spectroradiometer (MODIS) has 36 bands. Among them, 16 thermal emissive bands covering a wavelength range from 3.8 to 14.4 m. After 16 years on-orbit operation, the electronic crosstalk of a few Terra MODIS thermal emissive bands developed substantial issues that cause biases in the EV brightness temperature measurements and surface feature contamination. The crosstalk effects on band 27 with center wavelength at 6.7 m and band 29 at 8.5 m increased significantly in recent years, affecting downstream products such as water vapor and cloud mask. The crosstalk effect is evident in the near-monthly scheduled lunar measurements, from which the crosstalk coefficients can be derived. The development of an alternative approach is very helpful for independent verification.In this work, a physical model was developed to assess the crosstalk impact on calibration as well as in Earth view brightness temperature retrieval. This model was applied to Terra MODIS band 29 empirically to correct the Earth brightness temperature measurements. In the model development, the detectors nonlinear response is considered. The impact of the electronic crosstalk is assessed in two steps. The first step consists of determining the impact on calibration using the on-board blackbody (BB). Due to the detectors nonlinear response and large background signal, both linear and nonlinear coefficients are affected by the crosstalk from sending bands. The second step is to calculate the effects on the Earth view brightness temperature retrieval. The effects include those from affected calibration coefficients and the contamination of Earth view measurements. This model links the measurement bias with crosstalk coefficients, detector non-linearity, and the ratio of Earth measurements between the sending and receiving bands. The correction of the electronic cross talk can be implemented empirically from the processed bias at different brightness temperature. The implementation can be done through two approaches. As routine calibration assessment for thermal infrared bands, the trending over select Earth scenes is processed for all the detectors in a band and the band averaged bias is derived at a certain time. In this case, the correction of an affected band can be made using the regression of the model with band averaged bias and then corrections of detector differences are applied. The second approach requires the trending for individual detectors and the bias for each detector is used for regression with the model. A test using the first approach was made for Terra MODIS band 29 with the biases derived from long-term trending of brightness temperature over ocean and Dome-C.

Chang, Tiejun↗
NASA NTRS2020

Very High Resolution, Altitude-Corrected, TMPA-Based Monthly Satellite Precipitation Product Over the CONUS

The Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) product provided over 17 years of gridded precipitation datasets. However, the accuracy and spatial resolution of TMPA limits the applicability in hydrometeorological applications. We present a dataset that enhances the accuracy and spatial resolution of the TMPA monthly product (3B43). We resample the TMPA data to a 1 km grid and apply a correction function derived from the Parameter-elevation Regressions on Independent Slopes Model (PRISM) to reduce bias in the data. We confirm a linear relationship between bias and elevation above 1,500 meters where TMPA underestimates measured precipitation, providing a proof-of-concept of how simple linear scaling can be used to augment existing satellite datasets. The result of the correction is the High-Resolution Altitude-Corrected Precipitation product (HRAC-Precip) for the CONUS. Using 9,200 precipitation stations from the Global Historical Climatology Network (GHCN), we compare the accuracy of TMPA 3B43 versus the new HRAC-Precip product. The results show an improvement of the mean absolute error of 12.98% on average.

Hossein Hashemi↗
NASA NTRS2001

Atmospheric Multiple Scattering Effects on GLAS Altimetry: Analysis of Expected Errors in Antarctic Altitude Measurements - Part 2

The altimetry bias in GLAS (Geoscience Laser Altimeter System) or other laser altimeters resulting from atmospheric multiple scattering is studied in relationship to current knowledge of cloud properties over the Antarctic Plateau. Estimates of seasonal and interannual changes in the bias are presented. Results show the bias in altitude from multiple scattering in clouds would be a significant error source without correction. The selective use of low optical depth clouds or cloudfree observations, as well as improved analysis of the return pulse such as by the Gaussian method used here, are necessary to minimize the surface altitude errors. The magnitude of the bias is affected by variations in cloud height, cloud effective particle size and optical depth. Interannual variations in these properties as well as in cloud cover fraction could lead to significant year-to-year variations in the altitude bias. Although cloud-free observations reduce biases in surface elevation measurements from space, over Antarctica these may often include near-surface blowing snow, also a source of scattering-induced delay. With careful selection and analysis of data, laser altimetry specifications can be met.

Mahesh, Ashwin↗
NASA NTRS1981

Sixth Annual Flight Mechanics/Estimation Theory Symposium

Methods of orbital position estimation were reviewed. The problem of accuracy in orbital mechanics is discussed and various techniques in current use are presented along with suggested improvements. Of special interest is the compensation for bias in satelliteborne instruments due to attitude instabilities. Image processing and correctional techniques are reported for geodetic measurements and mapping.

Lefferts, E.↗
NASA NTRS1985

Topological aspects of age parameter

The well known NKG function is a very useful tool to describe the lateral extension of the electromagnetic component in Extensive Air Showers (EAS); however, in spite of non-negligible qualities (simplicity, normalization by beta function), it doesn't correspond exactly to the natural shape of the lateral electron distribution. Several bias may occur in size estimation if NKG is used without correction. It is shown that the longitudinal age parameter s sub t can be correlated with the information obtained from the lateral electron densities according to the conditions of use of the NKG function.

Capdevielle, J. N.↗
NASA NTRS1993

Investigation for improving Global Positioning System (GPS) orbits using a discrete sequential estimator and stochastic models of selected physical processes

GEODYNII is a conventional batch least-squares differential corrector computer program with deterministic models of the physical environment. Conventional algorithms were used to process differenced phase and pseudorange data to determine eight-day Global Positioning system (GPS) orbits with several meter accuracy. However, random physical processes drive the errors whose magnitudes prevent improving the GPS orbit accuracy. To improve the orbit accuracy, these random processes should be modeled stochastically. The conventional batch least-squares algorithm cannot accommodate stochastic models, only a stochastic estimation algorithm is suitable, such as a sequential filter/smoother. Also, GEODYNII cannot currently model the correlation among data values. Differenced pseudorange, and especially differenced phase, are precise data types that can be used to improve the GPS orbit precision. To overcome these limitations and improve the accuracy of GPS orbits computed using GEODYNII, we proposed to develop a sequential stochastic filter/smoother processor by using GEODYNII as a type of trajectory preprocessor. Our proposed processor is now completed. It contains a correlated double difference range processing capability, first order Gauss Markov models for the solar radiation pressure scale coefficient and y-bias acceleration, and a random walk model for the tropospheric refraction correction. The development approach was to interface the standard GEODYNII output files (measurement partials and variationals) with software modules containing the stochastic estimator, the stochastic models, and a double differenced phase range processing routine. Thus, no modifications to the original GEODYNII software were required. A schematic of the development is shown. The observational data are edited in the preprocessor and the data are passed to GEODYNII as one of its standard data types. A reference orbit is determined using GEODYNII as a batch least-squares processor and the GEODYNII measurement partial (FTN90) and variational (FTN80, V-matrix) files are generated. These two files along with a control statement file and a satellite identification and mass file are passed to the filter/smoother to estimate time-varying parameter states at each epoch, improved satellite initial elements, and improved estimates of constant parameters.

Goad, Clyde C.↗
NASA NTRS1996

Combinations of Earth Orientation Measurements: SPACE94, COMB94, and POLE94

A Kalman filter has been used to combine independent measurements of the Earth's orientation taken by the space-geodetic observing techniques of lunar laser ranging, satellite laser ranging, very long baseline interferometry, and the Global Positioning System. Prior to their combination, the data series were adjusted to have the same bias and rate, the stated uncertainties of the measurements were adjusted, and data points considered to be outliers were deleted. The resulting combination, SPACE94, consists of smoothed, interpolated polar motion and UT1-UTC values spanning October 6, 1976, to January 27, 1995, at 1-day intervals. The Kalman filter was then used to combine the space-geodetic series comprising SPACE94 with two different, independent series of Earth orientation measurements taken by the technique of optical astrometry. Prior to their combination with SPACE94, the bias, rate and annual term of the optical astrometric series were corrected, the stated uncertainties of the measurements were adjusted, and data points considered to be outliers were deleted. The adjusted optical astrometric series were then combined with SPACE94 in two steps: (1) the Bureau International de l'Heure (BIH) optical astrometric series was combined with SPACE94 to form COMB94, a combined series of smoothed, interpolated polar motion and UT1-UTC values spanning January 20, 1962, to January 27, 1995, at 5-day intervals, and (2) the International Latitude Service (ILS) optical astrometric series was combined with COMB94 to form POLE94, a combined series of smoothed, interpolated polar motion values spanning January 20, 1900, to January 21, 1995, at 30.4375-day intervals.

Gross, Richard S.↗
NASA NTRS2000

Short-Term Retrospective Land Data Assimilation Schemes

Subsurface moisture and temperature and snow/ice stores exhibit persistence on various time scales that has important implications for the extended prediction of climatic and hydrologic extremes. Hence, to improve their specification of the land surface, many numerical weather prediction (NWP) centers have incorporated complex land surface schemes in their forecast models. However, because land storages are integrated states, errors in NWP forcing accumulates in these stores, which leads to incorrect surface water and energy partitioning. This has motivated the development of Land Data Assimilation Schemes (LDAS) that can be used to constrain NWP surface storages. An LDAS is an uncoupled land surface scheme that is forced primarily by observations, and is therefore less affected by NWP forcing biases. The implementation of an LDAS also provides the opportunity to correct the model's trajectory using remotely-sensed observations of soil temperature, soil moisture, and snow using data assimilation methods. The inclusion of data assimilation in LDAS will greatly increase its predictive capacity, as well as provide high-quality land surface assimilated data.

Houser, P. R.↗
NASA NTRS2012

Implications of Weak Link Effects on Thermal Characteristics of Transition-Edge Sensors

Weak link behavior in transition-edge sensor (TES) microcalorimeters creates the need for a more careful characterization of a device's thermal characteristics through its transition. This is particularly true for small TESs where a small change in the bias current results in large changes in effective transition temperature. To correctly interpret measurements, especially complex impedance, it is crucial to know the temperature-dependent thermal conductance, G(T), and heat capacity, C(T), at each point through the transition. We present data illustrating these effects and discuss how we overcome the challenges that are present in accurately determining G and T from I-V curves. We also show how these weak link effects vary wi.th TES size. Additionally, we use this improVed understanding of G(T) to determine that, for these TES microcalorimeters. Kaptiza boundary resistance dominates the G of devices with absorbers while the electron-phonon coupling also needs to be considered when determining G for devices without absorbers

Bailey, C. N.↗
NASA NTRS2016

A Correlation Between the Intrinsic Brightness and Average Decay Rate of Gamma-Ray Burst X-Ray Afterglow Light Curves

We present a correlation between the average temporal decay (alpha X,avg, greater than 200 s) and early-time luminosity (LX,200 s) of X-ray afterglows of gamma-ray bursts as observed by the Swift X-ray Telescope. Both quantities are measured relative to a rest-frame time of 200 s after the gamma-ray trigger. The luminosity â€" average decay correlation does not depend on specific temporal behavior and contains one scale-independent quantity minimizing the role of selection effects. This is a complementary correlation to that discovered by Oates et al. in the optical light curves observed by the Swift Ultraviolet Optical Telescope. The correlation indicates that, on average, more luminous X-ray afterglows decay faster than less luminous ones, indicating some relative mechanism for energy dissipation. The X-ray and optical correlations are entirely consistent once corrections are applied and contamination is removed. We explore the possible biases introduced by different light-curve morphologies and observational selection effects, and how either geometrical effects or intrinsic properties of the central engine and jet could explain the observed correlation.

gamma-ray burst: general X-rays: burst↗
NASA NTRS2010

Pixel-Level Calibration in the Kepler Science Operations Center Pipeline

We present an overview of the pixel-level calibration of flight data from the Kepler Mission performed within the Kepler Science Operations Center Science Processing Pipeline. This article describes the calibration (CAL) module, which operates on original spacecraft data to remove instrument effects and other artifacts that pollute the data. Traditional CCD data reduction is performed (removal of instrument/detector effects such as bias and dark current), in addition to pixel-level calibration (correcting for cosmic rays and variations in pixel sensitivity), Kepler-specific corrections (removing smear signals which result from the lack of a shutter on the photometer and correcting for distortions induced by the readout electronics), and additional operations that are needed due to the complexity and large volume of flight data. CAL operates on long (~30 min) and short (~1 min) sampled data, as well as full-frame images, and produces calibrated pixel flux time series, uncertainties, and other metrics that are used in subsequent Pipeline modules. The raw and calibrated data are also archived in the Multi-mission Archive at Space Telescope at the Space Telescope Science Institute for use by the astronomical community.

Calibration↗
NASA NTRS2010

Changes in the TRMM Version-5 and Version-6 Precipitation Radar Products Due to Orbit Boost

The performance of the version-5 and version-6 Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) products before and after the satellite orbit boost is assessed through a series of comparisons with Weather Surveillance Radar (WSR)-88D ground-based radar in Melbourne, Florida. Analysis of the comparisons of radar reflectivity near the storm top from the ground radar and both versions of the PR indicates that the PR bias relative to the WSR radar at Melbourne is on the order of 1dB for both pre- and post-boost periods, indicating that the PR products maintain accurate calibration after the orbit boost. Comparisons with the WSR-88D near-surface reflectivity factors indicate that both versions of the PR products accurately correct for attenuation in stratiform rain. However, in convective rain, both versions exhibit negative biases in the near-surface radar reflectivity with version-6 products having larger negative biases than version-5. Rain rate comparisons between the ground and space radars show similar characteristics

Liao, Liang↗
NASA NTRS1990

On the length of the drift region in the Ramsey cavity

The interaction of atoms in a beam with the microwave field in a separated field geometry such as a Ramsey cavity is generally described in terms of the three regions traversed successively by the atoms, namely two interaction regions of length (l) separated by a drift, or free precession, region of length L. For a monokinetic beam of velocity v, the linewidth of the central fringe in the Ramsey resonance pattern is usually expressed as delta omega equals pi v/L. A more detailed calculation shows, however, that the linewidth is equal to pi v/L asterisk, where the equivalent drift L asterisk is larger than L by an amount of the order of l/L. The correction depends on the field distribution in the interaction regions. Its origin lies in the fact that atomic precession is not limited to the field-free regions but also occurs in the interaction regions, where atomic coherence builds up or decreases continuously. Although the correction to the equivalent length of the drift region is small, it may be relevant to the evaluation of the second-order Doppler effect bias in primary cesium-beam standards to the extent that the atomic velocity is deduced from the lineshape and from the geometrical parameters of the cavity. It is shown that in current and projected standards with atoms of average thermal velocity, use of corrected dimensions may lead to a change of the calculated bias of the order of 10(exp -14), which is significant at the levels of accuracy considered nowadays.

Thomann, Pierre↗
NASA NTRS1984

The SEASAT altimeter wet tropospheric range correction revisited

An expanded set of radiosonde observations was used to calculate the wet tropospheric range correction for the brightness temperature measurements of the SEASAT scanning multichannel microwave radiometer (SMMR). The accuracy of the conventional algorithm for wet tropospheric range correction was evaluated. On the basis of the expanded observational data set, the algorithm was found to have a bias of about 1.0 cm, and a standard deviation 2.8 cm. In order to improve the algorithm, the exact linear, quadratic and logarithmic relationships between brightness temperatures and range corrections were determined. Various combinations of measurement parameters were used to reduce the standard deviation between SEASAT SMMR and radiosonde observations to about 2.1 cm. The performance of various range correction formulas is compared in a table.

Tapley, D. B.↗