The Earth Polychromatic Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) spacecraft observes the sunlit face of the Earth from a distance of about one-and-a-half million kilometers. Several studies demonstrated that EPIC images often feature sun glint from water surfaces and from horizontally oriented ice crystals occurring inside clouds. This study presents a statistical analysis of a yearlong EPIC dataset to gain insights into sun glints and their impacts on satellite measurements of cloudiness and cloud properties. The first results discussed demonstrate that over land, the observed glints, indeed, come mainly from ice clouds and not from small water bodies. Subsequent results reveal that sun glints affecting EPIC observations (especially at 388 nm) greatly increase the likelihood and sensitivity of cloud detection, particularly of the elusive thin and small ice clouds. Finally, the results indicate that sun glints often cause spurious increases in the cloud optical thickness (COT) and altitude values in the operational EPIC cloud product. Insights into the frequency, magnitude, and causes of glint effects and suggestions for future work are also provided.

From a distance of about one-and-a-half million kilometers, the Earth Polychromatic Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) spacecraft takes roughly hourly images of the sunlit side of the Earth. Earlier studies showed that these images often feature sun glint from water surfaces and from ice crystals that are suspended inside clouds in a horizontal orientation. This letter draws a wider view of the earlier analyses of observed glints caused by clouds, focusing on how the appearance of these glints varies with wavelength and season. The statistical analysis of all EPIC images taken in 2017 reveals that the wavelength dependence of glints is mainly shaped by the Rayleigh scattering and gaseous absorption caused by the air above the cloud top. The analysis also reveals that the radiative impact of cloud glints displays seasonal variations that are consistent with seasonal changes in the prevalence of ice clouds that were observed independently by the Moderate Resolution Imaging Spectroradiometer (MODIS).

A new technique to retrieve precipitable water vapor (PWV) amount in the clear-cloud transition zone using ground-based zenith spectral radiance is developed. The method uses zenith radiances at the water vapor band at 720 nm and at the adjacent nonadsorbing band at 750 nm. Radiative transfer calculations show that the relative difference in zenith radiance between the two bands depends on PWV and the variations in cloud optical depth introduce a small change in the relative difference which is independent of PWV amount. This allows us to retrieve PWV variations in the clear-cloud transition zone for clouds over dark ocean surface. We applied this method to a Cu cloud case with zenith radiance observations by Shortwave Array Spectroradiometer-Zenith (SASZe) during the Marine ARM GPCI Investigation of Clouds (MAGIC) field campaign. We found that there is about 10% change in PWV amount from the known-cloudy region to known-clear sky in the cloud edges.

The Earth Polychromatic Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) spacecraft takes images of the sunlit face of the earth from a million miles away. Earlier work showed that EPIC detected the specular reflection of sunlight (i.e., sun glint) from ice crystals floating in cold clouds over land; here we show that this phenomenon can also be detected over oceans. Furthermore, the results show that - using its observations at oxygen A-band absorption bands - EPIC can distinguish glints off marine ice clouds from those off the ocean surface. The analysis of more than two years of EPIC data reveals that the two kinds of glints are detected with comparable frequency. Glints off clouds are shown to be generally brighter but smaller in spatial extent. It is also demonstrated that glints off ice clouds have a discernible effect on the regional mean reflectance and that EPIC observations can help constrain the radiative contribution of oriented ice crystals.

Cloud detection/screening is a fundamental step in satellite data analysis. For the Ice, Cloud, and land Elevation Satellite (ICESat) and its successor ICESat-2, clouds can significantly affect the accuracy of the surface elevation retrievals. This paper proposes a new method for cloud screening in support of the ICESat-2 mission with focus on the polar ice sheet regions. The method utilizes the apparent surface reflectance (ASR) at the backscattering direction as the cloud screening test. The basis of this method is that clouds produce a strong signal by significantly decreasing the ASR. We show that depending on the height and microphysics of the cloud, the ASR decreases 8%–17% for clouds with an optical depth of 0.1 and 57%–85% for clouds with an optical depth 1.0. Data from ICESat's 1064-nm channel is used to demonstrate the feasibility of the method. It is shown that cloud detectability is a function of surface reflectance variability. Generally, the smaller the surface reflectance variability, the more accurate is cloud detection. Unlike ICESat, which used a 1064-nm laser, ICESat-2 adopts a 532-nm photon counting system for its laser altimeter. With both modeling studies and results from the Moderate Resolution Imaging Spectroradiometer (MODIS), we demonstrate that the ASR variability is much smaller for the 532-nm channel than that for the 1064-nm channel. Hence, the 532-nm channel is better suited for cloud screening than the 1064-nm channel.

Several recent studies have found that clouds are surrounded by a transition zone of rapidly changing aerosol optical properties and particle size. Characterizing this transition zone is important for better understanding aerosol-cloud interactions and aerosol radiative effects, and also for improving satellite retrievals of aerosol properties. This letter presents a statistical analysis of a monthlong global data set of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observations over oceans. The results show that the transition zone is ubiquitous over all oceans and extends up to 15 km away from clouds. They also show that near-cloud enhancements in backscatter and particle size are strongest at low altitudes, slightly below the top of the nearest clouds. Also, the enhancements are similar near illuminated and shadowy cloud sides, which confirms that the asymmetry of Moderate Resolution Imaging Spectroradiometer reflectances found in an earlier study comes from 3-D radiative processes and not from differences in aerosol properties. Finally, the effects of CALIPSO aerosol detection and cloud identification uncertainties are discussed. The findings underline the importance of accounting for the transition zone to avoid potential biases in studies of satellite aerosol products, aerosol-cloud interactions, and aerosol direct radiative effects.

This paper establishes a framework that simulates the behavior of a spaceborne 532-nm micropulse photon-counting lidar in cloudy and clear atmospheres in support of the ICESat-2 mission. Adopted by the current mission design, the photon-counting system will be used to obtain surface altimetry for ICESat-2. To investigate how clouds affect surface elevation retrievals, a 3-D Monte Carlo radiative transfer model is used to simulate the photon path distribution and the Poisson distribution is adopted for the number of photon returns. Since the photon-counting system only registers the time of the first arriving photon within the detector “dead time,” the retrieved average surface elevation tends to bias toward higher values. This is known as the first photon bias. With the scenarios simulated here, the first photon bias for clear sky is about 6.5 cm. Clouds affect surface altimetry in two ways: 1) Cloud attenuation lowers the average number of arriving photons and hence reduces the first photon bias, and 2) cloud forward scattering increases the photon path length and makes the surface appear further away from the satellite. Compared with that for clear skies, the average surface elevation detected by the photon-counting system for cloudy skies with optical depth of 1.0 is 4.0-6.0 cm lower for the simulations conducted. The effect of surface roughness on the accuracy of elevation retrievals is also discussed.

Satellite and aircraft observations have revealed that remarkable changes in the Earth's polar ice cover have occurred in the last decade. The impacts of these changes, which include dramatic ice loss from ice sheets and rapid declines in Arctic sea ice, could be quite large in terms of sea level rise and global climate. NASA's Ice, Cloud and Land Elevation Satellite-2 (ICESat-2), currently planned for launch in 2015, is specifically intended to quantify the amount of change in ice sheets and sea ice and provide key insights into their behavior. It will achieve these objectives through the use of precise laser measurements of surface elevation, building on the groundbreaking capabilities of its predecessor, the Ice Cloud and Land Elevation Satellite (ICESat). In particular, ICESat-2 will measure the temporal and spatial character of ice sheet elevation change to enable assessment of ice sheet mass balance and examination of the underlying mechanisms that control it. The precision of ICESat-2's elevation measurement will also allow for accurate measurements of sea ice freeboard height, from which sea ice thickness and its temporal changes can be estimated. ICESat-2 will provide important information on other components of the Earth System as well, most notably large-scale vegetation biomass estimates through the measurement of vegetation canopy height. When combined with the original ICESat observations, ICESat-2 will provide ice change measurements across more than a 15-year time span. Its significantly improved laser system will also provide observations with much greater spatial resolution, temporal resolution, and accuracy than has ever been possible before.

In support of the Ice, Cloud, and land Elevation Satellite (ICESat)-II mission, this paper studies the bias in surface-elevation measurements caused by undetected thin clouds. The ICESat-II satellite may only have a 1064-nm single-channel lidar onboard. Less sensitive to clouds than the 532-nm channel, the 1064-nm channel tends to miss thin clouds. Previous studies have demonstrated that scattering by cloud particles increases the photon-path length, thus resulting in biases in ice-sheet-elevation measurements from spaceborne lidars. This effect is referred to as atmospheric path delay. This paper complements previous studies in the following ways: First, atmospheric path delay is estimated over the ice sheets based on cloud statistics from the Geoscience Laser Altimeter System onboard ICESat and the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua. Second, the effect of cloud particle size and shape is studied with the state-of-the-art phase functions developed for MODIS cirrus-cloud microphysical model. Third, the contribution of various orders of scattering events to the path delay is studied, and an analytical model of the first-order scattering contribution is developed. This paper focuses on the path delay as a function of telescope field of view (FOV). The results show that reducing telescope FOV can significantly reduce the expected path delay. As an example, the average path delays forFOV= 167 ¿rad (a 100-m-diameter circle on the surface) caused by thin undetected clouds by the 1064-nm channel over Greenland and East Antarctica are illustrated.

Pulsed lidars are commonly used to retrieve vertical distributions of cloud and aerosol layers. It is widely believed that lidar cloud retrievals (other than cloud base altitude) are limited to optically thin clouds. Here, we demonstrate that lidars can retrieve optical depths of thick clouds using solar background light as a signal, rather than (as now) merely a noise to be subtracted. Validations against other instruments show that retrieved cloud optical depths agree within 10%-15% for overcast stratus and broken clouds. In fact, for broken cloud situations, one can retrieve not only the aerosol properties in clear-sky periods using lidar signals, but also the optical depth of thick clouds in cloudy periods using solar background signals. This indicates that, in general, it may be possible to retrieve both aerosol and cloud properties using a single lidar. Thus, lidar observations have great untapped potential to study interactions between clouds and aerosols.

The effect of scattering angle on Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud drop effective radius is studied using ensembles of cumulus clouds with varying sun-satellite scattering geometries. The results are interpreted as shadowing and illumination effects. When 3-D clouds are viewed near the backscatter geometry, well-illuminated cloud surfaces are seen, and the retrievals based on plane-parallel geometry underestimate the effective radius. The reverse is true when the satellite is far from the backscatter position, and the shadowed portions of clouds are observed. The shadowing geometry produces a larger bias than the illuminated geometry. These differences between the shadowed and the illuminated ensembles decrease toward zero as the clouds become shallower. Removing the edge pixels based on 1-km-scale geometry partially reduces biases due to the 3-D effects and surface contamination. Recommendations are provided for reducing the 3-D cloud effects using current satellite retrieval algorithms

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 μm. 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.

Dense isolated (cumulus-type) clouds are not amenable to the standard plane-parallel slab geometry used in operational remote sensing. We show that their opacity can nonetheless be estimated using an alternate geometrical model - the spherical cloud - which is also analytically tractable for photon transport by diffusion. The new retrieval method is illustrated with a cloudy Multispectral Thermal Imager (MTI) scene but could be applied to ground-based sky imagers. The only requirement is to have both dark and bright sides of the cloud in the same scene. Future application to the development of correction schemes for cloud-adjacency effects is discussed.

The independent pixel approximation (IPA), which treats radiative properties of each pixel independently by using standard plane-parallel calculations preserves scale-invariance found in the analyses of the horizontal variability of liquid water in marine stratocumulus clouds. Several studies, however, report a violation of scale-invariance in LANDSAT cloud radiance fields that are much smoother than cloud structure on small scales. This shows a limitation of IPA on small scales: it is unable to simulate the smooth small-scale behavior that is due to the horizontal photon transport. This paper introduces a "nonlocal" independent pixel approximation (NIPA) that extends the IPA by incorporating empirically the smoothing effects of horizontal interpixel fluxes through a convolution product of the IPA and an approximate Green function for radiative transfer. The authors also address the inverse problem of cloud optical depth retrieval from satellite data, showing how NIPA can be used to overcome the limitations of current IPA-based methods at small scales.

Empirical studies report several plausible correlations between transforms of spectral reflectance, called vegetation indexes, and parameters descriptive of vegetation leaf area, biomass and physiological functioning. However, most indexes can be generalized to show a derivative of surface reflectance with respect to wavelength. This derivative is a function of the optical properties of leaves and soil particles. In the case of optically dense vegetation, the spectral derivative, and thus the indexes, can be rigorously shown to be indicative of the abundance and activity of the absorbers in the leaves. Therefore, the widely used broad-band &near-infrared vegetation indexes are a measure of chlorophyll abundance and energy absorption.