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NASA NTRS2006

Polarimeter Arrays for Cosmic Microwave Background Measurements

We discuss general system architectures and specific work towards precision measurements of Cosmic Microwave Background (CMB) polarization. The CMB and its polarization carry fundamental information on the origin, structure, and evolution of the universe. Detecting the imprint of primordial gravitational radiation on the faint polarization of the CMB will be difficult. The two primary challenges will be achieving both the required sensitivity and precise control over systematic errors. At anisotropy levels possibly as small as a few nanokelvin, the gravity-wave signal is faint compared to the fundamental sensitivity limit imposed by photon arrival statistics, and one must make simultaneous measurements with large numbers, hundreds to thousands, of independent background-limited direct detectors. Highly integrated focal plane architectures, and multiplexing of detector outputs, will be essential. Because the detectors, optics, and even the CMB itself are brighter than the faint gravity-wave signal by six to nine orders of magnitude, even a tiny leakage of polarized light reflected or diffracted from warm objects could overwhelm the primordial signal. Advanced methods of modulating only the polarized component of the incident radiation will play an essential role in measurements of CMB polarization. One promising general polarimeter concept that is under investigation by a number of institutions is to first use planar antennas to separate millimeter-wave radiation collected by a lens or horn into two polarization channels. Then the signals can be fed to a pair of direct detectors through a planar circuit consisting of superconducting niobium microstrip transmission lines, hybrid couplers, band-pass filters, and phase modulators to measure the Stokes parameters of the incoming radiation.

Stevenson, Thomas↗
NASA NTRS2006

Determination of the Cosmic Distance Scale from Sunyaev-Zel'dovich Effect and Chandra X-ray Measurements of High Redshift Galaxy Clusters

We determine the distance to 38 clusters of galaxies in the redshift range 0.14 less than or equal to z less than or equal to 0.89 using X-ray data from Chandra and Sunyaev-Zeldovich Effect data from the Owens Valley Radio Observatory and the Berkeley-Illinois-Maryland Association interferometric arrays. The cluster plasma and dark matter distributions are analyzed using a hydrostatic equilibrium model that accounts for radial variations in density, temperature and abundance, and, the statistical and systematic errors of this method are quantified. The analysis is performed via a Markov chain Monte Carlo technique that provides simultaneous estimation of all model parameters. W

Bonamente, Massimiliano↗
NASA NTRS1995

Direct Comparison of GPS and VLBI Velocity Estimates

Considerable effort has been made to collocate permanent GPS and VLBI sites for comparison. The global GPS solution is derived from daily measurements spanning four years while the VLBI solution is based on monthly measurements spanning more than 10 years. Current WRMS agreement of velocities is 3-5 mm/yr for horizontal rates and 6-10 mm/yr for vertical rates. Comparison of velocities is limited by the time span of GPS data. Positions agree at the level of 1-2 cm and their comparison is limited by the quality of the site ties. Best and worst agreement will be discussed along with possible sources of systematic error.

GPS VLBI↗
NASA NTRS1995

Innovative Imaging Spectrometer Calibration Techniques

A laboratory calibration of the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) allowed experimentation with several innovative calibration techniques that would improve calibration accuracy, provide independent checks for systematic errors, and reduce the time required to collect a calibration data set.

remote sensing AVIRIS Airborne Visible Infrared Im↗
NASA NTRS1993

Sub-Daily Northern Hemisphere Ionospheric Maps Using the IGS GPS Network

Ionospheric total electron content (TEC) data derived from dual-frequency GPS signals from 30 globally distributed IGS network sites are fit to a simple ionospheric shell model, yielding, simultaneously, values for the satellite and receiver biases, and a map of the ionosphere in the northern hemisphere every 12 hours during the period of Jan. 1-15, 1993. RMS residuals of 2-3 TEC units are observed over the 20-80 degree latitude band. Various systematic errors affecting the TEC estimates are discussed. The capability of using these global maps to produce ionosphere calibrations for sites at which no GPS data are available is investigated.

ionospheric total electron content GPS global iono↗
NASA NTRS2004

Systems engingeering for the Kepler Mission : a search for terrestrial planets

The Kepler mission will launch in 2007 and determine the distribution of earth-size planets (0.5 to 10 earth masses) in the habitable zones (HZs) of solar-like stars. The mission will monitor > 100,000 dwarf stars simultaneously for at least 4 years. Precision differential photometry will be used to detect the periodic signals of transiting planets. Kepler will also support asteroseismology by measuring the pressure-mode (p-mode) oscillations of selected stars. Key mission elements include a spacecraft bus and 0.95 meter, wide-field, CCD-based photometer injected into an earth-trailing heliocentric orbit by a 3-stage Delta II launch vehicle as well as a distributed Ground Segment and Follow-up Observing Program. The project is currently preparing for Preliminary Design Review (October 2004) and is proceeding with detailed design and procurement of long-lead components. In order to meet the unprecedented photometric precision requirement and to ensure a statistically significant result, the Kepler mission involves technical challenges in the areas of photometric noise and systematic error reduction, stability, and false-positive rejection. Programmatic and logistical challenges include the collaborative design, modeling, integration, test, and operation of a geographically and functionally distributed project. A very rigorous systems engineering program has evolved to address these challenges. This paper provides an overview of the Kepler systems engineering program, including some examples of our processes and techniques in areas such as requirements synthesis, validation & verification, system robustness design, and end-to-end performance modeling.

systems engineering↗
NASA NTRS2006

Final Results from the BIMA CMB Anisotropy Survey and Search for Signature of the SZ Effect

We report the final results of our study of the cosmic microwave background (CMB) with the BIMA array. Over 1000 hours of observation were dedicated to this project exploring CMB anisotropy on scales between 1' and 2' in eighteen 6'.6 FWHM fields. In the analysis of the CMB power spectrum, the visibility data is divided into two bins corresponding to different angular scales. Modeling the observed excess power as a flat band of average multipole l(sub eff)= 5237, we find deltaT(sup 2)(sub 1) = 220(sup +140)(sub -120) mu K(sup 2) at 68% confidence and deltaT(sup 2)(sub 1) greater than 0 muK(sup 2) with 94.7% confidence. In a second band with average multipole of l(sub eff) = 8748, we find deltaT(sup 2)(sub 2) consistent with zero, and an upper limit 880 muK(sup 2) at 95% confidence. An extensive series of tests and supplemental observations with the VLA provide strong evidence against systematic errors or radio point sources being the source of the observed excess power. The dominant source of anisotropy on these scales is expected to arise from the Sunyaev-Zel'dovich (SZ) effect in a population of distant galaxy clusters. If the excess power is due to the SZ effect, we can place constraints on the normalization of the matter power spectrum sigma(sub 8) = 1.03(sup +0.20)(sub -0.29) at 68% confidence. The distribution of pixel fluxes in the BIMA images are found to be consistent with simulated observations of the expected SZ background and rule out instrumental noise or radio sources as the source of the observed excess power with similar confidence to the detection of excess power. Follow-up optical observations to search for galaxy over-densities anti-correlated with flux in the BIMA images, as might be expected from the SZ effect, proved to be inconclusive.

Dawson, K. S.↗
NASA NTRS2006

Nadir Measurements of Carbon Monoxide Distributions by the Tropospheric Emission Spectrometer Instrument Onboard the Aura Spacecraft: Overview of Analysis Approach and Examples of Initial Results

We provide an overview of the nadir measurements of carbon monoxide (CO) obtained thus far by the Tropospheric Emission Spectrometer (TES). The instrument is a high resolution array Fourier transform spectrometer designed to measure infrared spectral radiances from low Earth orbit. It is one of four instruments successfully launched onboard the Aura platform into a sun synchronous orbit at an altitude of 705 km on July 15, 2004 from Vandenberg Air Force Base, California. Nadir spectra are recorded at 0.06/cm spectral resolution with a nadir footprint of 5 x 8 km. We describe the TES retrieval approach for the analysis of the nadir measurements, report averaging kernels for typical tropical and polar ocean locations, characterize random and systematic errors for those locations, and describe instrument performance changes in the CO spectral region as a function of time. Sample maps of retrieved CO for the middle and upper troposphere from global surveys during December 2005 and April 2006 highlight the potential of the results for measurement and tracking of global pollution and determining air quality from space.

carbon monoxide↗
NASA NTRS2006

TES Level 1 Algorithms: Interferogram Processing, Geolocation, Radiometric, and Spectral Calibration

The Tropospheric Emission Spectrometer (TES) on the Earth Observing System (EOS) Aura satellite measures the infrared radiance emitted by the Earth's surface and atmosphere using Fourier transform spectrometry. The measured interferograms are converted into geolocated, calibrated radiance spectra by the L1 (Level 1) processing, and are the inputs to L2 (Level 2) retrievals of atmospheric parameters, such as vertical profiles of trace gas abundance. We describe the algorithmic components of TES Level 1 processing, giving examples of the intermediate results and diagnostics that are necessary for creating TES L1 products. An assessment of noise-equivalent spectral radiance levels and current systematic errors is provided. As an initial validation of our spectral radiances, TES data are compared to the Atmospheric Infrared Sounder (AIRS) (on EOS Aqua), after accounting for spectral resolution differences by applying the AIRS spectral response function to the TES spectra. For the TES L1 nadir data products currently available, the agreement with AIRS is 1 K or better.

infrared remote sensing↗
NASA NTRS2007

Accuracy Analysis on Large Blocks of High Resolution Images

Although high altitude frequencies effects are removed at the time of basic image generation, low altitude (Yaw) effects are still present in form of affinity/angular affinity. They are effectively removed by additional parameters. Bundle block adjustment based on properly weighted ephemeris/altitude quaternions (BBABEQ) are not enough to remove the systematic effect. Moreover, due to the narrow FOV of the HRSI, position and altitude are highly correlated making it almost impossible to separate and remove their systematic effects without extending the geometric model (Self-Calib.) The systematic effects gets evident on the increase of accuracy (in terms of RMSE at GCPs) for looser and relaxed ground control at the expense of large and strong block deformation with large residuals at check points. Systematic errors are most freely distributed and their effects propagated all over the block.

Passini, Richardo M.↗
NASA NTRS2006

On the Quality of the Nimbus 7 LIMS Version 6 Ozone for Studies of the Middle Atmosphere

The Nimbus 7 Limb Infrared Monitor of the Stratosphere (LIMS) radiance profile dataset of 1978/79 was reconditioned and reprocessed to Version 6 (V6) profiles of temperature and species that are improved significantly over those from Version 5 (V5). The LIMS V6 dataset was archived for public use in 2002. Improvements for its ozone include: (1) a more accurate accounting for instrument and spacecraft motion effects in the radiances, (2) the use of better spectroscopic line parameters for its ozone forward model, (3) retrievals of all its scans, (4) more accurate and compatible temperature versus pressure profiles (or T(p)), which are needed for the registration of the ozone radiances and for the removal of temperature effects from them, and (5) a better accounting for interfering species in the lower stratosphere. The retrieved V6 ozone profiles extend from near cloud top altitudes to about 80 km and from 64S to 84N latitude with better sampling along the orbit than for the V5 dataset. Calculated estimates of the single-profile precision and accuracy are provided for the V6 ozone from this study. Precision estimates based on the data themselves are of order 3% or better from 1 to 30 hPa. Estimates of total systematic error for a single profile are hard to generalize because the separate sources of error may not all be of the same sign and they depend somewhat on the atmospheric state. It is estimated that the V6 zonal mean ozone distributions are accurate to within 9% to 7% from 50 hPa to 3 hPa, respectively. Effects of a temperature bias can be significant and may be present at 1 to 2 hPa though. There may be ozone biases of order 10% at those levels due to possible biases of up to +2 K, but there is no indication of a similar problem elsewhere in the stratosphere. Simulation studies show that the LIMS retrievals are also underestimating slightly the small amplitudes of the atmospheric temperature tides, which affect its retrieved day/night ozone differences. There are small biases in the middle to lower stratosphere for the ascending versus descending node LIMS ozone, due principally to not accounting for the asymmetric weighting of its radiances across the tangent layer. The estimates of total accuracy were assessed by comparing the daily zonal mean LIMS ozone distributions against those from the Nimbus 7 SBUV Version 8 (V8) dataset for the same period. Generally, the LIMS V6 ozone agrees well with SBUV, except perhaps in the tropical lower stratosphere where the LIMS ozone is less. Still, the accuracy for LIMS V6 ozone in the lower stratosphere is improved over that found for LIMS V5, as indicated by several LIMS comparisons with ECC ozonesonde profiles. The LIMS V6 ozone is considered especially suitable for detailed studies of large-scale stratospheric processes above the 100-hPa level. Comparison of diurnal, photochemical model calculations with the monthly-averaged, upper stratospheric ozone observed from LIMS V6 indicates only a slight ozone deficit for the model at about 2 hPa. However, that deficit exhibits little to no seasonal variation and is in good agreement with similar model comparisons for a seasonal time series of ozone obtained with ground-based microwave instruments. Because the LIMS V6 ozone in the lower stratosphere has improved accuracy and sampling versus that of V5, it should now be possible to conduct quantitative studies of ozone transport and chemistry for the northern hemisphere, polar stratospheric winter of 1978/79 a time period when the catalytic loss of ozone due to reactive chlorine should not have been a major factor for the Arctic region.

Remsberg, Ellis↗
NASA NTRS2007

An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

Zhou and Cess [2001] developed an algorithm for retrieving surface downwelling longwave radiation (SDLW) based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for scenes that were covered with ice clouds. An improved version of the algorithm prevents the large errors in the SDLW at low water vapor amounts by taking into account that under such conditions the SDLW and water vapor amount are nearly linear in their relationship. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths available from the Cloud and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) product to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing and will be incorporated as one of the CERES empirical surface radiation algorithms.

Zhou, Yaping↗
NASA NTRSDate not supplied

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=about 15 orbits/day].

NEAR IR IMAGERY↗
NASA NTRSDate not supplied

MISR Level 1B1 Radiance Data (MI1B1_V1)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Horizontal_Resolution_Range=250 meters - < 500 meters; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=Daily - < Weekly, about 15 orbits/day, Daily - < Weekly].

EOSDIS↗
NASA NTRSDate not supplied

MISR Level 1B1 Radiance Data (MI1B1_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1.1 km; Longitude_Resolution=1.1 km; Temporal_Resolution=about 15 orbits/day; Temporal_Resolution_Range=about 15 orbits/day].

AM-1↗
NASA NTRSDate not supplied

MISR Level 1B1 Local Mode Radiance Data (MIB1LM_V2)

The results of two types of processing are included in this product. First, the Radiance Scaling operation converts the camera's digital number output to a measure of energy incident on the front optical surface. The measurement is expressed in units called radiance (energy per unit area, wavelength, and solid angle) as defined by the International Standard (SI). Second, Radiance Conditioning modifies the radiances to remove instrument-dependent effects. Specifically, image sharpening is applied, and focal-plane scattering is removed. Additionally, all radiances are adjusted to remove slight spectral sensitivity differences among the 1504 detector elements of each spectral band and each camera. In addition to the Level 1B1 radiometric product for MISR's Global Mode imagery, there is a separate Level 1B1 product for each high-resolution Local Mode scene. The Radiometric Product contains spectral radiances for all MISR channels (four spectral bands and nine cameras). Each radiance value represents the incident radiance averaged over the sensor's total band response. Processing includes both radiance scaling and conditioning steps. Radiance scaling converts the Level 1A data from digital counts to radiances using coefficients derived in combination with the On-Board Calibrator (OBC) and vicarious calibrations. The OBC contains Spectralon calibration panels which are deployed monthly and reflect sunlight into the cameras. The OBC detector standards then measure this reflected light to provide the calibration. Vicarious field campaigns are conducted less frequently but provide an independent methodology useful for reducing systematic errors. Radiance conditioning removes undesirable instrument effects. Image enhancement is provided by deconvolving the scene with the sensor's point-spread-function. Additionally, in-band scaling adjusts the reported radiances to correspond to a nominal band response profile. This frees the Level 2 software from the need to correct for detector element non-uniformities. No out-of-band correction is done for this product, nor are the data geometrically corrected or resampled at this point. In summary, the Level 1B1 Product contains the Data Numbers (DNs) radiometrically-scaled to radiances with no geometric resampling. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=275 m for red band only; Longitude_Resolution=275 m for red band only; Temporal_Resolution=about 15 orbits/day].

AM-1↗
NASA NTRS2006

How Well do State-of-the-Art Techniques Measuring the Vertical Profile of Tropospheric Aerosol Extinction Compare?

The recent Department of Energy Atmospheric Radiation Measurement (ARM) Aerosol Intensive Operations Period (AIOP, May 2003) yielded one of the best measurement sets obtained to date to assess our ability to measure the vertical profile of ambient aerosol extinction sigma(ep)(lambda) in the lower troposphere. During one month, a heavily instrumented aircraft with well-characterized aerosol sampling ability carrying well-proven and new aerosol instrumentation devoted most of the 60 available flight hours to flying vertical profiles over the heavily instrumented ARM Southern Great Plains (SGP) Climate Research Facility (CRF). This allowed us to compare vertical extinction profiles obtained from six different instruments: airborne Sun photometer (AATS-14), airborne nephelometer/absorption photometer, airborne cavity ring-down system, groundbased Raman lidar, and two ground-based elastic backscatter lidars. We find the in situ measured sigma(ep)(lambda) to be lower than the AATS-14 derived values. Bias differences are 0.002-0.004 Km!1 equivalent to 13-17% in the visible, or 45% in the near-infrared. On the other hand, we find that with respect to AATS-14, the lidar sigma(ep)(lambda) are higher: Bias differences are 0.004 Km(-1) (13%) and 0.007 Km(-1) (24%) for the two elastic backscatter lidars (MPLNET and MPLARM, lambda = 523 nm) and 0.029 Km(-1) (54%) for the Raman lidar (lambda = 355 nm). An unnoticed loss of sensitivity of the Raman lidar had occurred leading up to AIOP, and we expect better agreement from the recently restored system. Looking at the collective results from six field campaigns conducted since 1996, airborne in situ measurements of sigma(ep)(lambda) tend to be biased slightly low (17% at visible wavelengths) when compared to airborne Sun photometer sigma(ep)(lambda). On the other hand, sigma(ep)(lambda) values derived from lidars tend to have no or positive biases. From the bias differences we conclude that the typical systematic error associated with measuring the tropospheric vertical profile of the ambient aerosol extinction with current state-of-the-art instrumentation is 15-20% at visible wavelengths and potentially larger in the UV and near-infrared.

Schmid, B.↗
NASA NTRS2006

Assessment of Satellite Surface Radiation Products in Highland Regions with Tibet Instrumental Data

This study presents results of comparisons between instrumental radiation data in the elevated Tibetan Plateau and two global satellite products: the Global Energy and Water Cycle Experiment - Surface Radiation Budget (GEWEX-SRB) and International Satellite Cloud Climatology Project - Flux Data (ISCCP-FD). In general, shortwave radiation (SW) is estimated better by ISCCP-FD while longwave radiation (LW) is estimated better by GEWEX-SRB, but all the radiation components in both products are under-estimated. Severe and systematic errors were found in monthly-mean SRB SW (on plateau-average, -48 W/sq m for downward SW and -18 W/sq m for upward SW) and FD LW (on plateau-average, -37 W/sq m for downward LW and -62 W/sq m for upward LW) for radiation. Errors in monthly-mean diurnal variations are even larger than the monthly mean errors. Though the LW errors can be reduced about 10 W/sq m after a correction for altitude difference between the site and SRB and FD grids, these errors are still higher than that for other regions. The large errors in SRB SW was mainly due to a processing mistake for elevation effect, but the errors in SRB LW was mainly due to significant errors in input data. We suggest reprocessing satellite surface radiation budget data, at least for highland areas like Tibet.

Yang, Kun↗