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The design of an Earth Remote Sensing Sensor, such as the Multi-angle Imaging SpectroRadiometer (MISR), begins with a set of science requirements and is quickly followed by a set of instrument specifications.
Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.
The Multi-Angle Imaging SpectroRadiometer (MISR), to be launched in 1998, is one of five instruments on NASA's first Earth Observing System (EOS) platform. The 3% absolute radiometric calibration requirement is considered challenging, particularly since it must be maintained through the five-year mission life. The Instrument requirements have led to the development of an On-Board Calibrator (OBC) consisting of diffuse panels and photodiode-based radiometric standards.
The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the five Earth-observing instruments on-board the National Aeronautics and Space Administration (NASA) Earth-Observing System(EOS) Terra spacecraft, launched in December 1999. It has 36 spectral bands with wavelengths ranging from 0.41 to 14.4 mm and collects data at three nadir spatial resolutions: 0.25 km for 2 bands with 40 detectors each, 0.5 km for 5 bands with 20 detectors each and 1 km for the remaining 29 bands with 10 detectors each. MODIS bands are located on four separate focal plane assemblies (FPAs) according to their spectral wavelengths and aligned in the cross-track direction. Detectors of each spectral band are aligned in the along-track direction. MODIS makes observations using a two-sided paddle-wheel scan mirror. Its on-board calibrators (OBCs) for the reflective solar bands (RSBs) include a solar diffuser (SD), a solar diffuser stability monitor (SDSM) and a spectral-radiometric calibration assembly (SRCA). Calibration is performed for each band, detector, sub-sample (for sub-kilometer resolution bands) and mirror side. In this study, a ratio approach is applied to MODIS observed Earth scene reflectances to track the detector-to-detector and mirror side differences. Simultaneous observed reflectances from the Multi-angle Imaging Spectroradiometer (MISR), also onboard the Terra spacecraft, are used with MODIS observed reflectances in this ratio approach for four closely matched spectral bands. Results show that the detector-to-detector difference between two adjacent detectors within each spectral band is typically less than 0.2% and, depending on the wavelengths, the maximum difference among all detectors varies from 0.5% to 0.8%. The mirror side differences are found to be very small for all bands except for band 3 at 0.44 mm. This is the band with the shortest wavelength among the selected matching bands, showing a time-dependent increase for the mirror side difference. This study is part of the effort by the MODIS Characterization Support Team (MCST) in order to track the RSB on-orbit performance for MODIS collection 5 data products. To support MCST efforts for future data re-processing, this analysis will be extended to include more spectral bands and temporal coverage.
It is predicted by both theory and models that high-altitude clouds will occur higher in the atmosphere as a result of climate warming. This produces a positive longwave feedback and has a substantial impact on the Earth's response to warming. This effect is well established by theory, but is poorly constrained by observations, and there is large spread in the feedback strength between climate models. For this study, we use the NASA Multi-angle Imaging SpectroRadiometer (MISR) to examine changes in Cloud-Top-Height (CTH). MISR uses a stereo-imaging technique to determine CTH. This approach is geometric in nature and insensitive to instrument calibration and therefore is well suited for trend analysis and studies of variability on long time scales. In this article we show that the current MISR record does have an increase in CTH for high-altitude cloud over Southern Hemisphere (SH) oceans but not over Tropical or the Northern Hemisphere (NH) oceans. We use climate model simulations to estimate when MISR might be expected to detect trends in CTH, that include the NH. The analysis suggests that according to the models used in this study MISR should detect changes over the SH ocean earlier than the NH, and if the model predictions are correct should be capable of detecting a trend over the Tropics and NH very soon (3–10 years). This result highlights the potential value of a follow-on mission to MISR, which no longer maintains a fixed equator crossing time and is unlikely to be making observations for another 10 years.
Variations in the top-of-atmosphere reflected solar radiation flux, and in the factors that determine its value, are among the most important diagnostic indicators of changes in Earth's energy balance. Data from the MISR (Multi-angle Imaging SpectroRadiometer), MODIS (Moderate-resolution Imaging Spectroradiometer), SAGE-3 (Stratospheric Aerosol and Gas Experiment), and CERES (Clouds and Earth's Radiant Energy System), all of which are spacecraft instruments scheduled for launch in 1999, will each constrain pieces of the RSRF budget. Prior to launch, we are performing studies to determine the sensitivity of these instruments to key factors that influence the cloud-free RSRF: aerosol optical depth, aerosol scattering properties, and surface visible bidirectional reflectance distribution function (BRDF). We are also assessing the ability of the aggregate of instruments to constrain the overall RSRF budget under natural conditions over the globe. Consider the MISR retrieval of aerosols: according to simulations over cloud-free, calm ocean, for pure particles with natural ranges of optical depth, particle size, and indices of refraction, MISR can retrieve column aerosol optical depth for all but the darkest particles, to an uncertainty of at most 0.05 or 20%, whichever is larger, even if the particle properties are poorly known. For one common particle type, soot, constraints on the optical depth over dark ocean are very poor. The simulated measurements also allow us to distinguish spherical from non-spherical particles, to separate two to four compositional groups based on indices of refraction, and to identify three to four distinct size groups between 0. 1 and 2.0 microns characteristic radius at most latitudes. Based on these results, we expect to distinguish air masses containing different aerosol types, routinely and globally, with multiangle remote sensing data. Such results far exceed current satellite aerosol retrieval capabilities, which provide only total optical depth for assumed particle properties; the new information will complement in situ data, which give details about aerosol size and composition locally. In addition, our team is using climatologies that reflect the constraints each instrument is expected to provide, along with ERBE (Earth Radiation Budget Experiment) data and a radiative transfer code, to study overall sensitivity to RSRF, helping us prepare for similar studies with new data from the EOS-era instruments.
The Multiangle Imaging Spectroradiometer (MISR) and the Moderate Resolution Imaging Spectroradiometer (MODIS), launched on 18 December 1999 aboard the Terra spacecraft, are making global observations of top-of-atmosphere (TOA) radiances. Aerosol optical depths and particle properties are independently retrieved from these radiances using methodologies and algorithms that make use of the instruments corresponding designs. This paper compares instantaneous optical depths retrieved from simultaneous and collocated radiances measured by the two instruments at locations containing sites within the Aerosol Robotic Network (AERONET). A set of 318 MISR and MODIS images, obtained during the months of March, June, and September 2002 at 62 AERONET sites, were used in this study. The results show that over land, MODIS aerosol optical depths at 470 and 660 nm are larger than those retrieved from MISR by about 35% and 10% on average, respectively, when all land surface types are included in the regression. The differences decrease when coastal and desert areas are excluded. For optical depths retrieved over ocean, MISR is on average about 0.1 and 0.05 higher than MODIS in the 470 and 660 nm bands, respectively. Part of this difference is due to radiometric calibration and is reduced to about 0.01 and 0.03 when recently derived band-to-band adjustments in the MISR radiometry are incorporated. Comparisons with AERONET data show similar patterns.
The Multi-angle Imaging SpectroRadiometer (MISR) is an Earth-observing sensor which provides global retrievals of aerosols, clouds, and land surface parameters. Instrument specifications require an accurate absolute calibration, as well as accurate camera-to-camera, band-to-band, and pixel-to-pixel relative response determinations. In order to achieve these requirements, MISR makes use of an on-board calibrator (OBC), as well as vicarious calibration (VC) experiments.
This CD-ROM contains sample data in HDF-EOS format from the instruments on board the Earth Observing System (EOS) Terra satellite: (1) Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER); (2) Clouds and the Earth's Radiant Energy System (CERES); (3) Multi-angle Imaging Spectroradiometer (MISR); and (4) Moderate Resolution Imaging Spectroradiometer (MODIS). Data from the Measurements of Pollution in the Troposphere (MOPITT) instrument were not available for distribution (as of October 17, 2000). The remotely sensed, coincident data for the Western US wildfires were acquired August 30, 2000. This CD-ROM provides information about the Terra mission, instruments, data, and viewing tools. It also provides the Collage tool for viewing data, and links to Web sites containing other digital data processing software. Full granules of the data on this CD-ROM and other EOS Data and Information System (EOSDIS) data products are available from the NASA Distributed Active Archive Centers (DAACs).
Due to their extensive spatial coverage, satellite Aerosol Optical Depth (AOD) observations have been widely used to estimate and predict surface PM2.5 concentrations. While most previous studies have focused on establishing relationships between collocated, hourly or daily AOD and PM2.5 measurements, in this study, we instead focus on the comparison of the large-scale spatial and temporal variability between satellite AOD and PM2.5 using monthly mean measurements. A newly developed spectral analysis technique e Combined Maximum Covariance Analysis (CMCA) is applied to Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Ozone Monitoring Instrument (OMI) AOD datasets and Environmental Protection Agency (EPA) PM2.5 data, in order to extract and compare the dominant modes of variability. Results indicate that AOD and PM2.5 agree well in terms of interannual variability. An overall decrease is found in both AOD and PM2.5 across the United States, with the strongest signal over the eastern US. With respect to seasonality, good agreement is found only for Eastern US, while for Central and Western US, AOD and PM2.5 seasonal cycles are largely different or even reversed. These results are verified using Aerosol Robotic Network (AERONET) AOD observations and differences between satellite and AERONET are also examined. MODIS and MISR appear to have the best agreement with AERONET. In order to explain the disagreement between AOD and PM2.5 seasonality, we further use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) extinction profile data to investigate the effect of two possible contributing factors, namely aerosol vertical distribution and cloud-free sampling. We find that seasonal changes in aerosol vertical distribution, due to the seasonally varying mixing height, is the primary cause for the AOD and PM2.5 seasonal discrepancy, in particular, the low AOD but high PM2.5 observed during the winter season for Central and Western US. In addition, cloud-free sampling by passive sensors also induces some bias in AOD seasonality, especially for the Western US, where the largest seasonal change in cloud fraction is found. The seasonal agreement between low level (below 500 m AGL), all sky CALIOP AOD and PM2.5 is significantly better than column AOD from MODIS, MISR, SeaWiFS and OMI. In particular, the correlation between low level, all sky AOD and PM2.5 seasonal cycles increases to above 0.7 for Central and Western US, as opposed to near zero or negative correlation for column, clear sky AOD. This result highlights the importance of accounting for the seasonally varying aerosol profiles and cloud-free sampling bias when using column AOD measurements to infer surface PM2.5 concentrations.
Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.
The Multi-angle Imaging SpectroRadiometer (MISR) is an Earth observing sensor which will provide global retrievals of aerosols, clouds, and land surface parameters. Instrument specifications require high accuracy absolute calibration, as well as accurate camera-to-camera, band-to-band and pixel-to-pixel relative response determinations.
This paper validates that radiometric accuracy is maintained throughout the dynamic range of the instrument. As part of this study, a new look has been taken on the band-relative scale, and a decrease in the radiance reported for the Red and NIR Bands has resulted.
Aerosol scattering coefficients (sigma(sub sp)) have been measured over the ocean at different relative humidities (RH) as a function of attitude in the region surrounding the Canary Islands during the Second Aerosol Characterization Experiment (ACE-2) in June and July 1997. The data were collected by the University of Washington passive humidigraph (UWPH) mounted on the Pelican research aircraft. Concurrently, particle size distributions absorption coefficients and aerosol optical depth were measured throughout 17 flights. A parameterization of sigma(sub sp) as a function of RH was utilized to assess the impact of aerosol hydration on the upwelling radiance (normalized to the solar constant and cosine of zenith angle). The top of the atmosphere radiance signal was simulated at wavelengths corresponding to visible and near-infrared bands or the EOS-AM ("Terra") detectors, MODIS and MISR. The UWPH measured (sigma(sub sp)) at 2 RHs, one below and the other above ambient conditions. Ambient (sigma(sub sp)) was obtained by interpolation of these 2 measurements. The data were stratified in terms of 3 types of aerosols: Saharan dust, clean marine (marine boundary layer background) and polluted marine aerosols (i.e., 2- or 1-day old polluted aerosols advected from Europe). An empirical relation for the dependence of (sigma(sub sp)) on RH, defined by (sigma(sub sp))(RH) = k. ((1 - RH/100)(exp -gamma), was used with the hygroscopic exponent gamma derived from the data. The following gamma values were obtained for the 3 aerosol types: gamma(dust) = 0.23 +/- 0.05, gamma(clean marine) = 0.69 +/- 0.06 and gamma(polluted marine) = 0.57 + 0.06. Based on the measured (gamma)(s), the above equation was utilized to derive aerosol models with different hygroscopicities. The satellite simulation signal code 6S was used to compute the upwelling radiance corresponding to each of those aerosol models at several ambient humidities. For the pre-launch estimated precision of the sensors and the assumed viewing geometry of the instrument, the simulations suggest that the spectral and angular dependence of the reflectance measured by MISR is not sufficient to distinguish aerosol models with various different combinations of values ror dry composition. y and ambient RH. A similar behavior is observed for MODIS at visible wavelengths. However, the 2100 nm band of MODIS appears to be able to differentiate between at least some aerosol models with different aerosol hygroscopicity given the MODIS calibration error requirements. This result suggests the possibility of retrieval of aerosol hygroscopicity by MODIS.
Aerosol scattering coefficients (sigma(sub sp)) have been measured over the ocean at different relative humidities (RH) as a function of altitude in the region surrounding the Canary Islands during the Second Aerosol Characterization Experiment (ACE-2) in June and July 1997. The data were collected by the University of Washington passive humidigraph (UWPH) mounted on the Pelican research aircraft. Concurrently, particle size distributions, absorption coefficients and aerosol optical depth were measured throughout 17 flights. A parameterization of sigma(sub sp) as a function of RH was utilized to assess the impact of aerosol hydration on the upwelling radiance (normalized to the solar constant and cosine of zenith angle). The top of the atmosphere radiance signal was simulated at wavelengths corresponding to visible and near-infrared bands of the EOS (Earth Observing System) AM-1 (Terra) detectors, MODIS (Moderate Resolution Imaging Spectroradiometer) and MISR (Multi-angle Imaging Spectroradiometer). The UWPH measured sigma(sub sp) at two RHs, one below and the other above ambient conditions. Ambient sigma(sub sp) was obtained by interpolation of these two measurements. The data were stratified in terms of three types of aerosols: Saharan dust, clean marine (marine boundary layer background) and polluted marine aerosols (i.e., two- or one-day old polluted aerosols advected from Europe). An empirical relation for the dependence of sigma(sub sp) on RH, defined by sigma(sub sp)(RH) = k.(1 - RH/100)(sup gamma), was used with the hygroscopic exponent gamma derived from the data. The following gamma values were obtained for the 3 aerosol types: gamma(dust) = 0.23 +/- 0.05, gamma(clean marine) = 0.69 +/- 0.06 and gamma(polluted marine) = 0.57 +/- 0.06. Based on the measured gammas, the above equation was utilized to derive aerosol models with different hygroscopicities. The satellite simulation signal code 6S was used to compute the upwelling radiance corresponding to each of those aerosol models at several ambient humidities. For the prelaunch estimated precision of the sensors and the assumed viewing geometry of the instrument, the simulations suggest that the spectral and angular dependence of the reflectance measured by MISR is not sufficient to distinguish aerosol models with various different combinations of values for dry composition, gamma and ambient RH. A similar behavior is observed for MODIS at visible wavelengths. However, the 2100 nm band of MODIS appears to be able to differentiate between at least same aerosol models with different aerosol hygroscopicity given the MODIS calibration error requirements. This result suggests the possibility of retrieval of aerosol hygroscopicity by MODIS.
New set of satellites, MODIS and MISR launched on EOS-Terra and POLDER launched on ADEOS-1, and scheduled for ADEOS-II and PARASOL in orbit with EOS-AQUA, open exciting opportunities to measure aerosol and their radiative forcing of climate. Each of these instruments has a different approach to invert remote sensing data to derive the aerosol properties. MODIS is using wide spectral range 0.47-2.1 micron. MISR is using narrower spectral range (0.44 to 0.87 micron) but observing the same spot from 9 different angles along the satellite track. POLDER using similar wavelengths, uses two dimensional view with a wide angle optics and adds polarization to the inversion process. Among these instruments, we expect to measure the global distribution of aerosol, to distinguish small pollution particles from large particles from deserts and ocean spray. We shall try to measure the aerosol absorption of solar radiation, and their refractive index that indicates the effect of liquid water on the aerosol size and interaction with sunlight. The radiation field measured by these instruments in variety of wavelengths and angles, is also used to derive the effect of the aerosol on reflection of sunlight spectral fluxes to space. When combined with flux measurements at the ground, it gives a complete characterization of the effect of aerosol on solar illumination, heating in the atmosphere and reflection to space.
An Airborne Multi-angle Imaging SpectroRadiometer (AirMISR) instrument has been developed to assist in validation of the Earth Observing System (EOS) MISR experiment.
An Airborne Multi-angle Imaging SpectroRadiometer (AirMISR) instrument has beed developed to assist in validation of the Earth Observing System (EOS) MISR experiment.