We study the Earth surface polarized reflectance using data collected by a space-based lidar. Accurate modelling of the surface reflectance supports retrieval algorithm development for the current and future Earth Science missions. Strong polarization of the laser light from Cloud-Aerosol Transport System (CATS) instrument, operated in 2015-2017, and nighttime measurements yield higher signal-to-noise ratio for polarization compared to the previous analysis of reflected, initially unpolarized, solar light.
Inhalation of airborne particulate matter (PM) is associated with a variety of adverse health outcomes. However, the relative toxicity of specific PM types—mixtures of particles of varying sizes, shapes, and chemical compositions—is not well understood. A major impediment has been the sparse distribution of surface sensors, especially those measuring speciated PM. Aerosol remote sensing from Earth orbit offers the opportunity to improve our understanding of the health risks associated with different particle types and sources. The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard NASA’s Terra satellite has demonstrated the value of near-simultaneous observations of backscattered sunlight from multiple view angles for remote sensing of aerosol abundances and particle properties over land. The Multi-Angle Imager for Aerosols (MAIA) instrument, currently in development, improves on MISR’s sensitivity to airborne particle composition by incorporating polarimetry and expanded spectral range. Spatiotemporal regression relationships generated using collocated surface monitor and chemical transport model data will be used to convert fractional aerosol optical depths retrieved from MAIA observations to near-surface PM10, PM2.5, and speciated PM2.5. Health scientists on the MAIA team will use the resulting exposure estimates over globally distributed target areas to investigate the association of particle species with population health effects.
We discuss accuracy of our recently developed RT code SORD using 2 benchmark scenarios published by the IPRT group in 2015. These scenarios define atmospheres with a complicate dependence of scattering and absorption properties over height (profile). Equal step, dh=1km, is assumed in the profiles. We developed subroutines that split such atmospheres into layers of the same optical thickness, dτ. We provide full text of the subroutines with comments in Appendix. The dτ is a step for vertical integration in the method of successive orders. Modification of the input profiles from “equal step over h” to “equal step over τ” changes input for RT simulations. This may cause errors at or above the acceptable level of the measurement uncertainty. We show errors of the RT code SORD for both intensity and polarization. In addition to that, using our discrete ordinates RT code IPOL, we discuss one more IPRT scenario, in which changes in height profile indeed cause unacceptable errors. Clear understanding of source and magnitude of these errors is important, e.g. for the AERONET retrieval algorithm.
The successive orders of scattering radiative transfer (RT) codes frequently call the scalar (dot) product function. In this paper, we study performance of some implementations of the dot product in the RT code SORD using 50 scenarios for light scattering in the atmosphere-surface system. In the dot product function, we use the unrolled loops technique with different unrolling factor. We also considered the intrinsic Fortran functions. We show results for two machines: ifort compiler under Windows, and pgf90 under Linux. Intrinsic DOT_PRODUCT function showed best performance for the ifort. For the pgf90, the dot product implemented with unrolling factor 4 was the fastest.
The RT code SORD together with the interface that runs all the mentioned tests are publicly available from ftp://maiac.gsfc.nasa.gov/pub/skorkin/SORD_IP_16B (current release) or by email request from the corresponding (first) author.
We report a new publicly available radiative transfer (RT) code for numerical simulation of polarized light scattering in
plane-parallel Earth atmosphere. Using 44 benchmark tests, we prove high accuracy of the new RT code, SORD
(Successive ORDers of scattering1, 2). We describe capabilities of SORD and show run time for each test on two
different machines. At present, SORD is supposed to work as part of the Aerosol Robotic NETwork3 (AERONET)
inversion algorithm. For natural integration with the AERONET software, SORD is coded in Fortran 90/95. The code is
available by email request from the corresponding (first) author or from ftp://climate1.gsfc.nasa.gov/skorkin/SORD/ or
ftp://maiac.gsfc.nasa.gov/pub/SORD.zip
The Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth (AOD) data retrieved at 0:55 μm with spatial resolutions of 10 km and 1 km AOD have been considered in this work. The 10 km resolution of MODIS AOD product is from the MODIS Collection 5:1 dark target retrieval and the 1 km resolution retrieval is from the new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm. We evaluate ability of these two products to characterize the spatial distribution of aerosols in urban areas through comparison with surface PM10 measurements. The Po Valley area (northern Italy) is considered in this study since urban air pollution is an important concern. Population and industrial activities are located in a large number of urban areas distributed within the valley. The 10 km spatial resolution of MODIS AOD product is considered too large for air quality studies at the urban scale. Using MAIAC data at 1 km, we examine the relationship between PM10 concentrations, AOD, and AOD normalized by Planetary Boundary Layer (PBL) depths obtained from NCEP global analysis, for year 2012 over the Po Valley. Results show that the MAIAC retrieval provides a high resolution depiction of the AOD within the Po Valley and performs nearly as well in a statistical sense as the standard MODIS retrieval during the time period considered. Results also show that normalization by the analyzed PBL depth to obtain an estimate of the mean boundary layer extinction is needed to capture the seasonal cycle of the observed PM10 over the Po Valley.
Although ground-level PM2.5 monitoring sites provide accurate measurements, their spatial coverage within a given region is limited and thus often insufficient for exposure and epidemiological studies. Satellite data expand spatial coverage, enhancing our ability to estimate location- and/or subject-specific exposures to PM2.5. Recently, a new Multi- Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM2.5 as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrieval (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R2=0.45 and 0.50, respectively, suggesting that AOD is a reasonably good proxy for PM2.5 ground concentrations. Finally, we studied the relationship between PM2.5 and AOD at the intra-urban scale (≤10km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale.
MODIS and MISR are two Earth Observing System instruments flown onboard Terra satellite. Their synergistic use could greatly benefit the broad user community by ensuring the global view of the Earth with high-quality products. A necessary condition for data fusion is radiometric calibration agreement between the two instruments. Earlier studies showed about 3% absolute radiometric difference between MISR and respective MODIS land bands in the visible and near-IR spectrum, which are also used in aerosol and cloud research. This study found a systematic bias of +(0.01-0.03) between two surface albedo products derived from MODIS and MISR L1B data using the AERONET-based Surface Reflectance Validation Network (ASRVN). The primary cause of the bias is inconsistencies in the cross-sensor calibration. To characterize MODIS-MISR calibration difference, top-of-atmosphere MODIS and MISR reflectances were regressed against each other over liquid water clouds. The empirical regression results have been adjusted for the differences in the respective MISR and MODIS spectral responses using radiative transfer simulations. The MISR-MODIS band gain differences estimated with this technique are +6.0% in the blue, +3.3% in the green, +2.7% in the red, and +0.8% in the NIR band. About 2.1%-3.6% of the difference in the blue band is due to the difference in the MODIS-MISR solar irradiance models.
The MODerate Resolution Imaging Spectroraiometer (MODIS) reflective solar bands (RSB) are calibrated on-orbit
using solar illuminations reflected from its onboard solar diffuser (SD) plate. The specified calibration uncertainty
requirements for MODIS RSB are ±2% in reflectance and ±5% in radiance at their typical top of atmosphere (TOA)
radiances. The onboard SD bi-directional reflectance factor (BRF) was characterized pre-launch by the instrument
vendor using reference samples traceable to NIST reflectance standard. The SD on-orbit degradation is monitored
using a solar diffuser stability monitor (SDSM). One of contributors to the RSB calibration uncertainty is the
earthshine (ES) illumination on the SD plate during SD calibration. This effect was estimated pre-launch by the
instrument vendor to be of 0.5% for all RSB bands. Analyses of on-orbit observations show that some of the SD
calibration data sets have indeed been contaminated due to extra ES illumination and the degree of ES impact on the
SD calibration is spectrally dependent and varies with geo-location and atmospheric conditions (ground surface type
and cloudiness). This paper illustrates the observed ES impacts on the MODIS RSB calibration quality and compare
them with the effects derived from an ES model based on the viewing geometry of MODIS SD aperture door and
likelihood atmospheric conditions. It also describes an approach developed to minimize the ES impact on MODIS
RSB calibration.
MODIS's solar diffuser is one of the key calibration sources for its reflective bands. Geometric optical modeling
shows that Earthshine illuminating the solar diffuser contaminates measurements of the direct solar irradiance.
Before launch, a simple model was used that did not consider the non-diffuse component and the atmospheric
transfer of the Earthshine contamination. Recently, a more detailed Earthshine model has been recently developed to
better determine the magnitude and characteristics of Earthshine contamination. The model includes a geometric
optical model of the instrument, a model of the Earth/Sun/instrument geometry during the calibration interval, an
atmospheric model, and various bi-directional models of Earth surface types. Several types of vegetation and open-ocean
with different wind speeds are modeled. Analysis was performed of the solar diffuser data with particular
emphasis on the surface type at the Earth locations where specular reflections (glint) might occur, i.e., where the
solar and view zenith angles are almost the same and the relative azimuth angle is near 180°. The new model
compares well with detailed analysis of the solar diffuser data, both over open-ocean with glint, and over vegetation.
Both the modeling and analysis show a spectral dependence in the non-diffuse radiation that increases with
wavelength. The modeling and analysis give lower and upper bounds on the Earthshine contamination and suggest
approaches for minimizing its impact on the MODIS calibration.
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