G. Wen

Impact of 3-D clouds on clear-sky reflectance and aerosol retrieval in a biomass burning region of Brazil

Three-dimensional (3-D) cloud radiative effects on clear-sky reflectances and associated aerosol optical depth retrievals are quantified for a cumulus cloud field in a biomass burning region in Brazil through a Monte Carlo simulation. In this study the 1-km Moderate Resolution Imaging Spectroradiometer cloud optical depth and surface reflectance datasets are used to compute the 3-D radiation fields with ambient aerosol optical thickness of 0.1 at a wavelength of 0.66 /spl mu/m. The 3-D radiative effects range from -0.015 to 0.018 with an average of 0.004 and standard deviation of 0.006. The 3-D effects are most pronounced and variable for cloud neighboring pixels, where both large negative effects over shadows and positive effects near sunlit cloud edges are found. The clear next-to-cloud pixels, that contain /spl sim/83% of the clear pixel population, are affected in the most complex way and not reliable for aerosol retrieval. In the area 2 km away from clouds, the 3-D effects enhance the reflectance in clear patches. The average and variability of enhancements gradually decrease as a function of the cloud-free distance, resulting in a systematically higher aerosol optical depth estimates for pixels closer to clouds in one-dimensional (1-D) retrieval. At a distance of 3 km away from clouds, the 3-D effect is still appreciable with the average enhancement slightly less than 0.004. This enhancement will lead to an over estimate of aerosol optical thickness of /spl sim/0.04 in 1-D retrieval, which is significant for an ambient atmosphere with aerosol optical thickness of 0.1.

Cloud characterization and clear-sky correction from Landsat-7

Abstract Landsat, with its wide swath and high resolution, fills an important mesoscale gap between atmospheric variations seen on a few kilometer scale by local surface instrumentation and the global view of coarser resolution satellites such as MODIS. In this important scale range, Landsat reveals radiative effects on the few hundred-meter scale of common photon mean-free-paths, typical of scattering in clouds at conservative (visible) wavelengths, and even shorter mean-free-paths of absorptive (near-infrared) wavelengths. Landsat also reveals shadowing effects caused by both cloud and vegetation that impact both cloudy and clear-sky radiances. As a result, Landsat has been useful in development of new cloud retrieval methods and new aerosol and surface retrievals that account for photon diffusion and shadowing effects. This paper discusses two new cloud retrieval methods: the nonlocal independent pixel approximation (NIPA) and the normalized difference nadir radiance method (NDNR). We illustrate the improvements in cloud property retrieval enabled by the new low gain settings of Landsat-7 and difficulties found at high gains. Then, we review the recently developed “path radiance” method of aerosol retrieval and clear-sky correction using data from the Department of Energy Atmospheric Radiation Measurement (ARM) site in Oklahoma. Nearby clouds change the solar radiation incident on the surface and atmosphere due to indirect illumination from cloud sides. As a result, if clouds are nearby, this extra side-illumination causes clear pixels to appear brighter, which can be mistaken for extra aerosol or higher surface albedo. Thus, cloud properties must be known in order to derive accurate aerosol and surface properties. A three-dimensional (3D) Monte Carlo (MC) radiative transfer simulation illustrates this point and suggests a method to subtract the cloud effect from aerosol and surface retrievals. The main conclusion is that cloud, aerosol, and surface retrievals are linked and must be treated as a combined system. Landsat provides the range of scales necessary to observe the 3D cloud radiative effects that influence joint surface-atmospheric retrievals.

A New Normalized Difference Cloud Retrieval Technique Applied to Landsat Radiances Over the Oklahoma ARM Site

The authors propose a new cloud property retrieval technique that accounts for cloud side illumination and shadowing effects present at high solar zenith angles. The technique uses the normalized difference of nadir reflectivities (NDNR) at a conservative and an absorbing (with respect to liquid water) wavelength. It can be further combined with the inverse nonlocal independent pixel approximation (NIPA) of Marshak et al. that corrects for radiative smoothing, thus providing a retrieval framework where all 3D cloud effects can potentially be accounted for. The effectiveness of the new technique is demonstrated using Monte Carlo simulations. Realworld application is shown to be feasible using Thematic Mapper (TM) radiance observations from Landsat-5 over the Southern Great Plains (SGP) site of the Atmospheric Radiation Measurement (ARM) Program. For the moderately oblique (458) solar zenith angle of the available Landsat scene, NDNR gives similar regional statistics and histograms when compared with standard independent pixel approximation (IPA), but significant differences at the pixel level. Inverse NIPA is also applied for the first time on observed high-resolution radiances of overcast Landsat subscenes. The dependence of the NIPA-retrieved cloud fields on the parameters of the method is illustrated and practical issues related to the optimal choice of these parameters are discussed. It is natural to compare novel cloud retrieval techniques with standard IPA retrievals. IPA is useful in revealing the inadequacy of plane parallel theory in certain situations and in demonstrating sensitivities to parameter choices, parameterizations, and assumptions. For example, it is found that IPA has problems in matching modeled and observed band-7 (2.2 mm) reflectance values for ;6% of the pixels, most of which are at cloud edges. For simultaneous cloud optical depth‐droplet effective radius retrievals (where a conservative and an absorptive TM band are needed), it is found that the band-4 (0.83 mm)‐band-7 pair was the most well behaved, having less saturation, smaller changes in nominal calibration, and better overall consistency with modeled values than other bands. Mean values of optical depth, effective radius, and liquid water path (LWP) for typical IPA retrievals using this pair are t 5 22, re 5 11 mm, and LWP 5 157 gm 22, respectively. Inclusion of aerosol scattering above clouds results in ;8% decrease in mean cloud optical depth for an aerosol optical depth of 0.2. Degradation of instrument resolution up to ;2 km has small effects on the optical property means and histograms, suggesting small actual cloud variability at these scales and/or radiative smoothing. Comparisons with surface instruments (microwave radiometer, pyranometer, and pyrgeometer) verify the statisitical adequacy of the IPA retrievals. Last, cloud fractions derived with a simple threshold method are compared with those from an automated procedure called Automatic Cloud Cover Assessment now in operational use for Landsat-7. For the northernmost 2000 scanlines of the scene, the cloud fraction Ac is 0.585 from thresholding, as compared with Ac 5 0.563 for the automated procedure, and the full scene values are Ac 5 0.870 and Ac 5 0.865, respectively. This suggests that the Landsat-7 automated procedure will likely give reliable scene-averaged cloud fractions for moderately thick clouds over continental U.S. scenes similar to SGP.

Limitations of ground‐based solar irradiance estimates due to atmospheric variations

[1]xa0The uncertainty in ground-based estimates of solar irradiance is quantitatively related to the temporal variability of the atmospheres optical thickness. The upper and lower bounds of the accuracy of estimates using the Langley plot technique are proportional to the standard deviation of aerosol optical thickness (approximately ±13σ(δτ)). The estimates of spectral solar irradiance in two Cimel Sun photometer channels at 340 and 380 nm from the Mauna Loa site of the Aerosol Robotic Network are compared with satellite observations from the Solar Stellar Irradiance Comparison Experiment (SOLSTICE) on the Upper Atmospheric Research Satellite for almost 2 years of data. The true solar variations related to the 27-day solar rotation cycle observed from SOLSTICE are ∼0.15% at the two Sun photometer channels. The variability in ground-based estimates is statistically 1 order of magnitude larger. Even though ∼30% of these estimates from all Level 2.0 Cimel data fall within the 0.4–0.5% variation level, ground-based estimates are not able to capture the 27-day solar variation observed from SOLSTICE.