MODIS Airborne Simulator Data Research Articles

Combining visible and infrared radiometry and lidar data to test simulations in clear and ice cloud conditions

Abstract. Measurements taken during the 2003 Pacific THORPEX Observing System Test (P-TOST) by the MODIS Airborne Simulator (MAS), the Scanning High-resolution Interferometer Sounder (S-HIS) and the Cloud Physics Lidar (CPL) are compared to simulations performed with a line-by-line and multiple scattering modeling methodology (LBLMS). Formerly used for infrared hyper-spectral data analysis, LBLMS has been extended to the visible and near infrared with the inclusion of surface bi-directional reflectance properties. A number of scenes are evaluated: two clear scenes, one with nadir geometry and one cross-track encompassing sun glint, and three cloudy scenes, all with nadir geometry. CPL data is used to estimate the particulate optical depth at 532 nm for the clear and cloudy scenes and cloud upper and lower boundaries. Cloud optical depth is retrieved from S-HIS infrared window radiances, and it agrees with CPL values, to within natural variability. MAS data are simulated convolving high resolution radiances. The paper discusses the results of the comparisons for the clear and cloudy cases. LBLMS clear simulations agree with MAS data to within 20% in the shortwave (SW) and near infrared (NIR) spectrum and within 2 K in the infrared (IR) range. It is shown that cloudy sky simulations using cloud parameters retrieved from IR radiances systematically underestimate the measured radiance in the SW and NIR by nearly 50%, although the IR retrieved optical thickness agree with same measured by CPL. MODIS radiances measured from Terra are also compared to LBLMS simulations in cloudy conditions, using retrieved cloud optical depth and effective radius from MODIS, to understand the origin for the observed discrepancies. It is shown that the simulations agree, to within natural variability, with measurements in selected MODIS SW bands. The impact of the assumed particles size distribution and vertical profile of ice content on results is evaluated. Sensitivity is much smaller than differences between measured and simulated radiances in the SW and NIR. The paper dwells on a possible explanation of these contradictory results, involving the phase function of ice particles in the shortwave.

Simultaneous retrieval of aerosol and thin cirrus optical depths using MODIS airborne simulator data during CRYSTAL‐FACE and CLAMS

We have developed a new methodology to simultaneously retrieve the optical depths of aerosols and thin cirrus clouds over the oceans by using the Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) data. This methodology takes advantage of the fact that the visible (or a near‐infrared window) reflectance from cirrus can be characterized by its correlation to the reflectance from a near‐infrared band located in a strong water vapor absorption region. Once the reflectance due to cirrus has been removed, the residual reflectance in these bands is used to retrieve aerosol optical depth. Cirrus cloud properties are subsequently obtained by minimizing the difference between observed and calculated reflectance values stored in look‐up tables that are constructed a priori and correlated to the retrieved aerosol optical depth. Examination of the data gathered from the recent Cirrus Regional Study of Tropical Anvils and Cirrus Layers–Florida Area Cirrus Experiment (CRYSTAL‐FACE) and Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) field campaigns demonstrates that our retrievals are consistent with both in‐situ and ground based measurements.

Comparisons of LASE, aircraft, and satellite measurements of aerosol optical properties and water vapor during TARFOX

We examine aerosol extinction and optical thickness from the Lidar Atmospheric Sensing Experiment (LASE), the in situ nephelometer and absorption photometer on the University of Washington C‐131A aircraft, and the NASA Ames Airborne Tracking Sun Photometer (AATS‐6) on the C‐131 A measured during the Tropospheric Aerosol Radiative Forcing Observational Experiment (TARFOX) over the east coast of the United States in July 1996. On July 17 and 24 the LASE profiles of aerosol extinction and aerosol optical thickness (AOT) had a bias difference of 0.0055 km−1 (10%) and a root‐mean‐square difference of 0.026 km−1 (42%) when compared to corresponding profiles derived from the airborne in situ data when the nephelometer measurements are adjusted to ambient relative humidities. Larger differences for two other days were associated with much smaller aerosol optical thicknesses (July 20) and differences in the locations sampled by the two aircraft (July 26). LASE profiles of AOT are about 10% higher than those derived from the airborne Sun photometer, which in turn are about 10–15% higher than those derived from the airborne in situ measurements. These differences are generally within the error estimates of the various measurements. The LASE measurements of AOT generally agree with AOT derived from both the Along‐Track and Scanning Radiometer 2 (ATSR 2) sensor flown on the European Remote Sensing Satellite 2 (ERS‐2) and from the Moderate‐Resolution Imaging Spectroradiometer (MODIS) airborne simulator (MAS) which flew with LASE on the NASA ER‐2 aircraft. Effective particle sizes derived from the MAS data indicate that the LASE retrievals of AOT are valid for effective particle radii less than 0.4 μm. Variations in the relative humidity derived from the LASE water vapor measurements on July 26 are found to be highly correlated with variations in the effective particle size derived from the MAS.

Vicarious calibration of the Moderate-Resolution Imaging Spectroradiometer Airborne Simulator thermal-infrared channels

We made an experimental vicarious calibration of the Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) thermal infrared (TIR) channel data acquired in the field campaign near Mono Lake, Calif. on 10 March 1998 to demonstrate the advantage of using high-elevation sites in dry atmospheric conditions for vicarious calibration. With three lake-surface sites and one snow-field site, we estimated the MAS noise-equivalent temperature difference as 0.7-1.0 degrees C for bands 30-32 in the 3.68-4.13-microm region and 0.1-0.5 degrees C for bands 42, 45, 46, and 48 in the 8-13.5-microm region. This study shows that the MAS calibration error is within +/-0.4 degrees C in the split-window channels (at 11 and 12 microm) and larger in other TIR channels based on the MAS data over Mono Lake and in situ measurement data over the snow-field site.

Assessment of Snow-Cover Mapping Accuracy in a Variety of Vegetation-Cover Densities in Central Alaska

Field and aircraft measurements were acquired in April 1995 in central Alaska to map snow cover with MODIS Airborne Simulator (MAS) data, acquired from high-altitude aircraft. The Earth Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) is a 36-channel system that will be launched on the EOS-AM-1 platform in 1999. A vegetation-density map derived from integrated reflectances ( R i ), from MAS data, is compared with an independently-produced vegetation type and density map derived from Thematic Mapper (TM) and ancillary data. The maps agreed to within 13%, thus corroborating the effectiveness of using the reflectance technique for mapping vegetation density. Snow cover was mapped on a 13 April 1995 MAS image, using the original MODIS prototype algorithm and an enhanced MODIS prototype algorithm. Field measurements revealed that the area was completely snow covered. With the original algorithm, snow was mapped in 96% of the pixels having <50% vegetation-cover density according to the R i map, while in the areas having vegetation-cover densities ⩾50%, snow was mapped in only 71% of the pixels. When the enhanced MODIS snow-mapping algorithm was employed, 99% of the pixels having <50% vegetation-cover density were mapped, and 98% of the pixels with ⩾50% vegetation-cover density were mapped as snow covered. These results demonstrate that the enhanced algorithm represents a significant improvement over the original MODIS prototype algorithm especially in the mapping of snow in dense vegetation. The enhanced algorithm will thus be adopted as the MODIS at-launch snow-cover algorithm. Using this simple method for estimating vegetation density from pixel reflectance, it will be possible to analyze the accuracy of the MODIS snow-cover algorithm in a range of vegetation-cover in places where information on vegetation-cover density is not available from ground measurements.