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NASA NTRS1995

Conversion of sunflower multiband radiometer polarization measurements to polarization parameters

The data processing analysis and conversion of polarization measurements to polarization parameters from the Sunflower multiband radiometer is presented in this final report. Included is: (1) the actual data analysis; (2) the comparison of the averaging techniques and the percent polarization derived from the original and averaged I, Q, U parameters; (3) the polarizer angles used in conversion; (4) the Matlab files; (5) the relative ground size, field of view location, and view zenith angles, and (6) the summary of all the sky data for all dates.

Biehl, Larry L.↗
NASA NTRS1995

Millimeter-wave imaging radiometer data processing and development of water vapor retrieval algorithms

This document describes the current status of Millimeter-wave Imaging Radiometer (MIR) data processing and the technical development of the first version of a water vapor retrieval algorithm. The algorithm is being used by NASA/GSFC Microwave Sensors Branch, Laboratory for Hydrospheric Processes. It is capable of a three dimensional mapping of moisture fields using microwave data from airborne sensor of MIR and spaceborne instrument of Special Sensor Microwave/T-2 (SSM/T-2).

Chang, L. Aron↗
NASA NTRS1994

SeaWiFS technical report series. Volume 22: Prelaunch acceptance report for the SeaWFS radiometer

The final acceptance, or rejection, of the Sea-viewing Wide field-of-view Sensor (SeaWiFS) will be determined by the instrument's on-orbit operation. There is, however, an extensive set of laboratory measurements describing the operating characteristics of the radiometer. Many of the requirements in the Ocean Color Data Mission (OCDM) specifications can be checked only by laboratory measurements. Here, the calibration review panel (composed of the authors of this technical memorandum) examines the laboratory characterization and calibration of SeaWiFS in the light of the OCDM performance specification. Overall, the performance of the SeaWiFS instrument meets or exceeds the requirements of the OCDM contract in all but a few unimportant details. The detailed results of this examination are presented here by following the outline of the specifications, as found in the Contract. The results are presented in the form of requirements and compliance pairs. These results give conclusions on many, but not all, of the performance specifications. The acceptance of this panel of the performance of SeaWiFS must only be considered as an intermediate conclusion. The ultimate acceptance (or rejection) of the SeaWiFS data set will rely on the measurements made by the instrument on orbit.

Hooker, Stanford B.↗
NASA NTRS1995

SeaWiFS technical report series. Volume 31: Stray light in the SeaWiFS radiometer

Some of the measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) will not be useful as ocean measurements. For the ocean data set, there are procedures in place to mask the SeaWiFS measurements of clouds and ice. Land measurements will also be masked using a geographic technique based on each measurment's latitude and longitude. Each of these masks involves a source of light much brighter than the ocean. Because of stray light in the SeaWiFS radiometer, light from these bright sources can contaminate ocean measurements located a variable number of pixels away from a bright source. In this document, the sources of stray light in the sensor are examined, and a method is developed for masking measurements near bright targets for stray light effects. In addition, a procedure is proposed for reducing the effects of stray light in the flight data from SeaWiFS. This correction can also reduce the number of pixels masked for stray light. Without these corrections, local area scenes must be masked 10 pixels before and after bright targets in the along-scan direction. The addition of these corrections reduces the along-scan masks to four pixels before and after bright sources. In the along-track direction, the flight data are not corrected, and are masked two pixels before and after. Laboratory measurements have shown that stray light within the instrument changes in a direct ratio to the intensity of the bright source. The measurements have also shown that none of the bands show peculiarities in their stray light response. In other words, the instrument's response is uniform from band to band. The along-scan correction is based on each band's response to a 1 pixel wide bright sources. Since these results are based solely on preflight laboratory measurements, their successful implementation requires compliance with two additional criteria. First, since SeaWiFS has a large data volume, the correction and masking procedures must be such that they can be converted into computationally fast algorithms. Second, they must be shown to operate properly on flight data. The laboratory results, and the corrections and masking procedures that derive from them, should be considered as zeroeth order estimates of the effects that will be found on orbit.

Hooker, Stanford B.↗
NASA NTRS1994

Surface temperatures in the polar regions from Nimbus 7 temperature humidity infrared radiometer

Monthly surface temperatures in the Arctic and Antarctic regions have been derived from the 11.5 micrometer thermal infrared channel of the Nimbus 7 temperature humidity infrared radiometer (THIR) for a whole year in 1979 and for a winter and a summer month from 1980 through 1985. The data set shows interannual variability and provides spatial details that allow identification of temperature patterns over sea ice and ice sheet surfaces. For example, the coldest spot in the southern hemisphere is observed to be consistently in the Antarctic plateau in the southern hemisphere, while that in the northern hemisphere is usually located in Greenland, or one of three other general areas: Siberia, the central Arctic, or the Canadian Archipelago. Also, in the southern hemisphere, the amplitude of the seasonal fluctuation of ice sheet temperatures is about 3 times that of sea ice, while in the northern hemisphere, the corresponding fluctuations for the two surfaces are about the same. The main sources of error in the retrieval are cloud and other atmospheric effects. These were minimized by first choosing the highest radiance value from the set of measurements during the day taken within a 30 km by 30 km grid of each daily map. Then the difference of daily maps was taken and where the difference is greater than a certain threshold (which in this case is 12 C), the data element is deleted. Overall, the monthly maps derived from the resulting daily maps are spatially and temporally consistent, are coherent with the topograph y of the Antarctic continent and the location of the sea ice edge, and are in qualitative agreement with climatological data. Quantitatively, THIR data are in good agreement with Antarctic ice sheet surface air temperature station data with a correlation coefficient of 0.997 and a standard deviation of 2.0 C. The absolute values are not as good over the sea ice edges, but a comparison with Russian 2-m drift station temperatures shows very high correlation (with correlation coefficient at 0.998) and a standard deviation of 1.1 C. Overall, the rms error is estimated to be from 1 to 2 C, depending on the surface, while the average bias when compared with in situ data is less than 2 C.

Comiso, Josefino C.↗
NASA NTRS1994

Time scales of pattern evolution from cross-spectrum analysis of advanced very high resolution radiometer and coastal zone color scanner imagery

We have selected square subareas (110 km on a side) from coastal zone color scanner (CZCS) and advanced very high resolution radiometer (AVHRR) images for 1981 in the California Current region off northern California for which we could identify sequences of cloud-free data over periods of days to weeks. We applied a two-dimensional fast Fourier transformation to images after median filtering, (x, y) plane removal, and cosine tapering. We formed autospectra and coherence spectra as functions of a scalar wavenumber. Coherence estimates between pairs of images were plotted against time separation between images for several wide wavenumber bands to provide a temporal lagged coherence function. The temporal rate of loss of correlation (decorrelation time scale) in surface patterns provides a measure of the rate of pattern change or evolution as a function of spatial dimension. We found that patterns evolved (or lost correlation) approximately twice as rapidly in upwelling jets as in the 'quieter' regions between jets. The rapid evolution of pigment patterns (lifetime of about 1 week or less for scales of 50-100 km) ought to hinder biomass transfer to zooplankton predators compared with phytoplankton patches that persist for longer times. We found no significant differences between the statistics of CZCS and AVHRR images (spectral shape or rate of decorrelation). In addition, in two of the three areas studied, the peak correlation between AVHRR and CZCS images from the same area occurred at zero lag, indicating that the patterns evolved simutaneously. In the third area, maximum coherence between thermal and pigment patterns occurred when pigment images lagged thermal images by 1-2 days, mirroring the expected lag of high pigment behind low temperatures (and high nutrients) in recently upwelled water. We conclude that in dynamic areas such as coastal upwelling systems, the phytoplankton cells (identified by pigment color patterns) behave largely as passive scalars at the mesoscale and that growth, death, and sinking of phytoplankton collectively play at most a mariginal role in determining the spectral statistics of the pigment patterns.

Denman, Kenneth L.↗
NASA NTRS1994

Limb-darkening models from along-track operation of the ERBE scanning radiometer

During January and August 1985, the scanning radiometers of the Earth Radiation Budget Experiment(ERBE) aboard the Earth Radiation Budget Satellite (ERBS) and the NOAA-9 satellite were operated in along-track scanning modes. Along-track scanning permits the study of many measurement problems. It provides the data for developing a limb-darkening model for a single site over a short period of time and also permits the indentification of the scene from data taken at smaller nadir angles. The earth-emitted radiation measured by the scanners has been analyzed to produce limb-darkening models for a variety of scene types. Limb-darkening models relate the radiance in any given direction to the radiant flux. The scene types were computed using measurements within 10 deg of zenith. The models have values near zenith of 1.02-1.09. The typical zenith values of the model are 1.06 for both day and night for ERBS, and for NOAA-9, 1.06 for day and 1.05 for night. Mean models are formed for the ERBS and NOAA-9 results and are found to differ less than 1%, the ERBS results being the higher. The models vary about 1% with latitude near zenith and agree with earlier models that were used to analyze ERBE data typically to 2%.

Smith, G. Louis↗
NASA NTRS1994

Comments on the statistical analysis of excess variance in the COBE differential microwave radiometer maps

Cosmic anisotrophy produces an excess variance sq sigma(sub sky) in the Delta maps produced by the Differential Microwave Radiometer (DMR) on cosmic background explorer (COBE) that is over and above the instrument noise. After smoothing to an effective resolution of 10 deg, this excess sigma(sub sky)(10 deg), provides an estimate for the amplitude of the primordial density perturbation power spectrum with a cosmic uncertainty of only 12%. We employ detailed Monte Carlo techniques to express the amplitude derived from this statistic in terms of the universal root mean square (rms) quadrupole amplitude, (Q sq/RMS)(exp 0.5). The effects of monopole and dipole subtraction and the non-Gaussian shape of the DMR beam cause the derived (Q sq/RMS)(exp 0.5) to be 5%-10% larger than would be derived using simplified analytic approximations. We also investigate the properties of two other map statistics: the actual quadrupole and the Boughn-Cottingham statistic. Both the sigma(sub sky)(10 deg) statistic and the Boughn-Cottingham statistic are consistent with the (Q sq/RMS)(exp 0.5) = 17 +/- 5 micro K reported by Smoot et al. (1992) and Wright et al. (1992).

Wright, E. L.↗
NASA NTRS1994

Cosmic temperature fluctuations from two years of COBE differential microwave radiometers observations

The first two years of Cosmic Background Explorer (COBE) Differential Microwave Radiometers (DMR) observations of the cosmic microwave background (CMB) anisotropy are analyzed and compared with our previously published first year results. The results are consistent, but the addition of the second year of data increases the precision and accuracy detected CMB temperature fluctuations. The 2 yr 53 GHz data are characterized by rms temperature fluctuations of (delta-T)(sub rms) (7 deg) = 44 +/- 7 micro-K and (delta-T)(sub rms) (10 deg) = 30.5 +/- 2.7 micro-K at 7 deg and 10 deg angular resolution, respectively. The 53 x 90 GHz cross-correlation amplitude at zero lag is C(0)(sup 1/2) = 36 +/- 5 micro-K (68% CL) for the unsmoothed (7 deg resolution) DMR data. We perform a likelihood analysis of the cross-correlation function, with Monte Carlo simulations to infer biases of the method, for a power-law model of initial density fluctuations, P(k) proportional to R(exp n). The Monte Carlo simulations indicate that derived estimates of n are biased by +0.11 +/- 0.01, while the subset of simulations with a low quadrupole (as observed) indicate a bias of +0.31+/- 0.04. Derived values for 68% confidence intervals are given corrected (and not corrected) for our estimated biases. Including the quadrupole anisotropy, the most likely quadrupole-normalized amplitude is Q(sub rms-PS) = 14.3(sup + 5.2 sub -3.3) micro-K (12.8(sup + 5.2 sub -3.3) micro-K0 with a spectral index n = 1.42(sup + 0.49 sub -0.55)(n = 1.53(sup + 0.49 sub -0.55). With n fixed to 1.0 the most likely amplitude is 18.2 +/- 11.5 micro-K (17.4 +/- 1.5 micro-K). The marginal likelihood of n is 1.42 +/- 0.37 (1.53 +/- 0.37). Excluding the quadrupole anisotropy, the most likely quadrupole-normalized amplitude is Q(sub rms-PS) = 17.4(sup + 7.5 sub -5.2) micro-K (15.8(sup + 7.5 sub -5.2) micro-K) with a spectral index n = 1.11(sup + 0.60 sub -0.55) (n = 1.22(sup + 0.60 sub -0.55). With n fixed to 1.0 the most likely amplitude is 18.6 +/- 1.6 micro-K (18.2 +/- 1.6 micro-K). The marginal likelihood of n is 1.11 +/- 0.40 (1.22 +/- 0.40). Our best estimate of the dipole from the 2 yr DMR data is 3.363 +/- 0.024 mK toward Galactic coordinates (l, b) = (264.4 deg +/- 0.2 deg, 48.1 deg +/- 0.4 deg), and our best estimate of the rms quadrupole amplitude in our sky is 6 +/- 3 micro-K (68% CL).

Bennett, C. L.↗
NASA NTRS1994

Angular power spectrum of the microwave background anisotropy seen by the COBE differential microwave radiometer

The angular power spectrum estimator developed by Peebles (1973) and Hauser & Peebles (1973) has been modified and applied to the 2 yr maps produced by the Cosmic Background Explorer Satellite Differential Microwave Radiometer (COBE DMR)). The power spectrum of the real sky has been compared to the power spectra of a large number of simulated random skies produced with noise equal to the observed noise and primordial density fluctuation power spectra of power-law form, with P(k) proportional to k(exp n). Within the limited range of spatial scales covered by the COBE DMR, corresponding to spherical harmonic indices 3 less than or = l is less than or approximately = 30, the best-fitting value of the spectral index is n = 1.25(sup +0.39 sub -0.44) with the Harrisson-Zel'dovich value n = 1 approximately 0.5 sigma below the best fit. For 3 less than or = l less than or approximately = 19, the best fit is n = 1.46(sup +0.39 sub -0.44). Comparing the COBE DMR delta-T/T at small l to the delta-T/T at l approximately = 50 from degree scale anisotropy experiments gives a smaller range of acceptable spectral indices which includes n = 1.

Wright, E. L.↗
NASA NTRS1994

Statistics and topology of the COBE differential microwave radiometer first-year sky maps

We use statistical and topological quantities to test the Cosmic Background Explorer (COBE) Differential Microwave Radiometer (DMR) first-year sky maps against the hypothesis that the observed temperature fluctuations reflect Gaussian initial density perturbations with random phases. Recent papers discuss specific quantities as discriminators between Gaussian and non-Gaussian behavior, but the treatment of instrumental noise on the data is largely ignored. The presence of noise in the data biases many statistical quantities in a manner dependent on both the noise properties and the unknown cosmic microwave background temperature field. Appropriate weighting schemes can minimize this effect, but it cannot be completely eliminated. Analytic expressions are presented for these biases, and Monte Carlo simulations are used to assess the best strategy for determining cosmologically interesting information from noisy data. The genus is a robust discriminator that can be used to estimate the power-law quadrupole-normalized amplitude, Q(sub rms-PS), independently of the two-point correlation function. The genus of the DMR data is consistent with Gaussian initial fluctuations with Q(sub rms-PS) = (15.7 +/- 2.2) - (6.6 +/- 0.3)(n - 1) micro-K, where n is the power-law index. Fitting the rms temperature variations at various smoothing angles gives Q(sub rms-PS) = 13.2 +/- 2.5 micro-K and n = 1.7(sup (+0.3) sub (-0.6)). While consistent with Gaussian fluctuations, the first year data are only sufficient to rule out strongly non-Gaussian distributions of fluctuations.

Smoot, G. F.↗
NASA NTRS1994

Wiener filtering of the COBE Differential Microwave Radiometer data

We derive an optimal linear filter to suppress the noise from the cosmic background explorer satellite (COBE) Differential Microwave Radiometer (DMR) sky maps for a given power spectrum. We then apply the filter to the first-year DMR data, after removing pixels within 20 deg of the Galactic plane from the data. We are able to identify particular hot and cold spots in the filtered maps at a level 2 to 3 times the noise level. We use the formalism of constrained realizations of Gaussian random fields to assess the uncertainty in the filtered sky maps. In addition to improving the signal-to-noise ratio of the map as a whole, these techniques allow us to recover some information about the cosmic microwave background anisotropy in the missing Galactic plane region. From these maps we are able to determine which hot and cold spots in the data are statistically significant, and which may have been produced by noise. In addition, the filtered maps can be used for comparison with other experiments on similar angular scales.

Bunn, Emory F.↗
NASA NTRS1994

Trends in South American biomass burning detected with the GOES visible infrared spin scan radiometer atmospheric sounder from 1983 to 1991

Previous work demonstrated the ability to manually detect subpixel fire activity in selected areas of the selva and cerrado regions in South America with shortwave and longwave infrared data available from the Geostationary Operational Environmental Satellite (GOES) visible infrared spin scan radiometer atmospheric sounder (VAS). This paper presents the GOES VAS automated biomass-burning algorithm (ABBA) which was developed to determine basin-wide trends in fire activity in South America utilizing the GOES VAS archive. Comparisons between the manual and automated techniques revealed that overall, the ABBA proved to be more consistent in identifying fires and better suited for trend analysis. The automated algorithm was applied daily to a study area extending from 5 deg S to 15 deg S and from 45 deg W to 70 deg W for 2 weeks at the peak of the burning seasons in South America in 1983, 1988, 1989, and 1991 in an effort to measure the areal extent of burning in South American during the past decade and to provide additional insight into the diurnal signature in satellite detection of biomass-burning activities. The expansion of the regions of burning are readily detected in a comparison of these 4 years. From 1983 to 1991 the amount of burning detected by the GOES VAS ABBA during these 2-week periods nearly doubled in the selva and mixed regions and tripled in the cerrado. Diurnal analyses confirmed earlier results indicating that the optimum time to monitor biomass burning is around 1530 UTC.

Prins, Elain M.↗
NASA NTRS1994

Arctic sea ice concentrations from special sensor microwave imager and advanced very high resolution radiometer satellite data

Nearly coincident data from the special sensor microwave imager (SSM/I) and the advanced very high resolution radiometer (AVHRR) are used to compute and compare Arctic sea ice concentrations for different regions and times of the year. To help determine overall accuracies and to highlight sources of differences between passive microwave, optical wavelength, and thermal wavelength data, ice concentrations are estimated using two operational SSM/I ice concentration algorithms and with visible- and thermal-infrared wavelength AVHRR data. All algorithms capture the seasonal patterns of ice growth and melt. The ranges of differences fall within the general levels of uncertainty expected for each method and are similar to previous accuracy estimates. The estimated ice concentrations are all highly correlated, with uniform biases, although differences between individual pairs of observations can be large. On average, the NASA Team algorithm yielded 5% higher ice concentrations than the Bootstrap algorithm, while during nonmelt periods the two SSM/I algorithms agree to within 0.5%. These seasonal differences are consistent with the ways that the 19-GHz and 37-GHz microwave channels are used in the algorithms. When compared to the AVHRR-derived ice concentrations, the Team-algorithm results are more similar on average in terms of correlation and mean differences. However, the Team algorithm underestimates concentrations relative to the AVHRR output by 6% during cold months and overestimates by 3% during summer. Little seasonal difference exists between the Bootstrap and AVHRR results, with a mean difference of about 5%. Although the mean differences are less between the SSM/I-derived concentrations and concentrations estimated using AVHRR channel 1, the correlations appear substantially better between the SSM/I data and concentrations derived from AVHRR channel 4, particularly for the Team algorithm output.

Emery, W. J.↗
NASA NTRS1995

Accuracy of sea ice temperature derived from the advanced very high resolution radiometer

The accuracy of Arctic sea ice surface temperatures T(sub s) dericed from advanced very high resolution radiometer (AVHRR) thermal channels is evaluated in the cold seasons by comparing them with surface air temperatures T(sub air) from drifting buoys and ice stations. We use three different estimates of satellite surface temperatures, a direct estimate from AVHRR channel 4 with only correction for the snow surface emissivity but not for the atmosphere, a single-channel regression of T(sub s) with T(sub air), and Key and Haefliger's (1992) polar multichannel algorithm. We find no measurable bias in any of these estimates and few differences in their statistics. The similar performance of all three methods indicates that an atmospheric water vapor correction is not important for the dry winter atmosphere in the central Arctic, given the other sources of error that remain in both the satellite and the comparison data. A record of drifting station data shows winter air temperature to be 1.4 C warmer than the snow surface temperature. `Correcting' air temperatures to skin temperature by subtracting this amount implies that satellite T(sub s) estimates are biased warm with respect to skin temperature by about this amount. A case study with low-flying aircraft data suggests that ice crystal precipitation can cause satellite estimates of T(sub s) to be several degrees warmer than radiometric measurements taken close to the surface, presumably below the ice crystal precipitation layer. An analysis in which errors are assumed to exist in all measurements, not just the satellite measurements, gives a standard deviation in the satellite estimates of 0.9 C, about half the standard deviation of 1.7 C estimated by assigning all the variation between T(sub s) and T(sub air) to errors in T(sub s).

Yu, Y.↗
NASA NTRS1995

Arctic sea ice leads from advanced very high resolution radiometer images

A large number of advanced very high resolution radiometer (AVHRR) images from throughout 1989 are analyzed to determine lead characteristics. The units of analysis are square 200-km cells, and there are 270 such cells in the data set. Clouds are masked manually. Leads determine from images of the potential open water delta, a scaled version of the surface temperature or albedo that weights thin ice by its thermal or brightness impact. The lead fraction is determined as the mean delta, the monthly mean lead fraction ranges from 0.02 in winter to 0.06 in summer in the central Arctic and is near 0.08 in the winter in the peripheral seas. A method of accounting for lead width sampling errors due to the finite sample areas is introduced. In the central Arctic the observed mean lead width for a threshold of delta = 0.1 ranges from 2 or 3 km (near the resolution of the instrument) in the winter to 6 km in the summer. In the peripheral seas it is about 5 km in the winter. Width distributions are often more heavily weighted in the tail than exponential distributions and are well approximated by a power law. The along-track, number density power law N = aw(exp -6) has a mean exponent of b = 1.60 (standard deviation 0.18) and shows some seasonal variability. Mean floe widths in the central Arctic are 40 to 50 km in the winter, dropping to about 10 km in the summer. For floes the power law has a mean exponent of 0.93 and exhibits a clearer annual cycle. Lead orientation is determined with a method based on the direction of maximum extent.

Lindsay, R. W.↗
NASA NTRS1995

Millimeter-wave Imaging Radiometer (MIR) data processing and development of water vapor retrieval algorithms

This document describes the progress of the task of the Millimeter-wave Imaging Radiometer (MIR) data processing and the development of water vapor retrieval algorithms, for the second six-month performing period. Aircraft MIR data from two 1995 field experiments were collected and processed with a revised data processing software. Two revised versions of water vapor retrieval algorithm were developed, one for the execution of retrieval on a supercomputer platform, and one for using pressure as the vertical coordinate. Two implementations of incorporating products from other sensors into the water vapor retrieval system, one from the Special Sensor Microwave Imager (SSM/I), the other from the High-resolution Interferometer Sounder (HIS). Water vapor retrievals were performed for both airborne MIR data and spaceborne SSM/T-2 data, during field experiments of TOGA/COARE, CAMEX-1, and CAMEX-2. The climatology of water vapor during TOGA/COARE was examined by SSM/T-2 soundings and conventional rawinsonde.

Chang, L. Aron↗
NASA NTRS1995

Water vapor radiometer measurements of the tropospheric delay fluctuations at Goldstone over a full year

One year of near-continuous water vapor radiometer (WVR) measurements at DSS 13 has provided a database for characterizing the Goldstone tropospheric delay properties in a statistical sense. The results have been expressed in terms of the Allan standard deviation of delay and compared to a previous model for Goldstone fluctuations and the specifications of the Cassini Gravitational Wave Experiment (GWE). The new WVR data indicate that average fluctuation levels at hour time scales or less are approximately 30 percent lower than the earlier Goldstone model predictions. At greater than 1 h time scales, the WVR indicated fluctuation levels are in closer agreement with the model, although noise floor limitations may be artificially raising the average WVR-derived atmospheric fluctuation levels at the longer time scales. When scaled to two-way Doppler tracking at 20 deg elevation, as will occur for the GWE, these results indicate that Goldstone winter tropospheric delay fluctuations will typically be a factor of 10 larger than the GWE requirements at 1000 s and a factor of 4 larger at 10,000 s.

Keihm, S. J.↗