This paper presents a systematic study on the role of particle size in pure and doped nanocrystalline TiO2 photocatalysts, which was made possible by a versatile wet-chemical process capable of generating near-agglomeration-free TiO2 with well-controlled particle sizes and dopant dispersion. It is shown that particle size is a crucial factor in the dynamics of the electron/hole recombination process. For TiO2 particles with 6 or 11 nm diameter, Fe3+ dopants were added to inhibit the charge carrier surface recombination. The optimal Fe3+ dopant concentration for different particle sizes was identified, and this concentration was found to decrease with increasing particle size. To assist electron and hole separation in TiO2 with 21 nm diameter, Nb5+ dopants were introduced in combination with minor surface Pt dispersion. These carefully engineered nanocrystalline TiO2 catalysts showed higher reactivities than Degussa P25 TiO2 material in photocatalytic decomposition of chloroform.

The MODIS Level-2 cloud product (Earth Science Data Set names MOD06 and MYD06 for Terra and Aqua MODIS, respectively) provides pixel-level retrievals of cloud-top properties (day and night pressure, temperature, and height) and cloud optical properties (optical thickness, effective particle radius, and water path for both liquid water and ice cloud thermodynamic phases-daytime only). Collection 6 (C6) reprocessing of the product was completed in May 2014 and March 2015 for MODIS Aqua and Terra, respectively. Here we provide an overview of major C6 optical property algorithm changes relative to the previous Collection 5 (C5) product. Notable C6 optical and microphysical algorithm changes include: (i) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach, (ii) improvement in the skill of the shortwave-derived cloud thermodynamic phase, (iii) separate cloud effective radius retrieval datasets for each spectral combination used in previous collections, (iv) separate retrievals for partly cloudy pixels and those associated with cloud edges, (v) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space, and (vi) enhanced pixel-level retrieval uncertainty calculations. The C6 algorithm changes collectively can result in significant changes relative to C5, though the magnitude depends on the dataset and the pixel's retrieval location in the cloud parameter space. Example Level-2 granule and Level-3 gridded dataset differences between the two collections are shown. While the emphasis is on the suite of cloud optical property datasets, other MODIS cloud datasets are discussed when relevant.

The cloud droplet number concentration (N d) is of central interest to improve the understanding of cloud physics and for quantifying the effective radiative forcing by aerosol‐cloud interactions. Current standard satellite retrievals do not operationally provide N d, but it can be inferred from retrievals of cloud optical depth (τ c) cloud droplet effective radius (r e) and cloud top temperature. This review summarizes issues with this approach and quantifies uncertainties. A total relative uncertainty of 78% is inferred for pixel‐level retrievals for relatively homogeneous, optically thick and unobscured stratiform clouds with favorable viewing geometry. The uncertainty is even greater if these conditions are not met. For averages over 1° ×1° regions the uncertainty is reduced to 54% assuming random errors for instrument uncertainties. In contrast, the few evaluation studies against reference in situ observations suggest much better accuracy with little variability in the bias. More such studies are required for a better error characterization. N d uncertainty is dominated by errors in r e, and therefore, improvements in r e retrievals would greatly improve the quality of the N d retrievals. Recommendations are made for how this might be achieved. Some existing N d data sets are compared and discussed, and best practices for the use of N d data from current passive instruments (e.g., filtering criteria) are recommended. Emerging alternative N d estimates are also considered. First, new ideas to use additional information from existing and upcoming spaceborne instruments are discussed, and second, approaches using high‐quality ground‐based observations are examined.

[1] The Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product provides three separate 1 km resolution retrievals of cloud particle effective radii (r e ), derived from 1.6, 2.1 and 3.7 mm band observations. In this study, differences among the three size retrievals for maritime water clouds (designated as r e,1.6 r e,2.1 and r e,3.7 ) were systematically investigated through a series of case studies and global analyses. Substantial differences are found between r e,3.7 and r e,2.1 retrievals (Dr e,3.7-2.1 ), with a strong dependence on cloud regime. The differences are typically small, within ±2 mm, over relatively spatially homogeneous costal stratocumulus cloud regions. However, for trade wind cumulus regimes, r e,3.7 was found to be substantially smaller than r e,2.1 , sometimes by more than 10 mm. The correlation of Dr e,3.7-2.1 with key cloud parameters, including the cloud optical thickness (t), r e and a cloud horizontal heterogeneity index (H s ) derived from 250m resolution MODIS 0.86 mm band observations, were investigated using one month of MODIS Terra data. It was found that differences among the three r e retrievals for optically thin clouds (t < 5) are highly variable, ranging from −15 mm to 10 mm, likely due to the large MODIS retrieval uncertainties when the cloud is thin. The Dr e,3.7-2.1 exhibited a threshold-like dependence on both r e,2.1 and H s . The r e,3.7 is found to agree reasonably well with r e,2.1 when r e,2.1 is smaller than about 15 mm, but becomes increasingly smaller than r e,2.1 once r e,2.1 exceeds this size. All three r e retrievals showed little dependence when cloud is relatively homogenous (H s < 0.3 defined as standard deviation divided by the mean for the 250 m pixels within a 1 km pixel retrieval). However, for inhomogeneous clouds (H s > 0.3), both r e,1.6 and r e,2.1 were seen to increase quickly with H s . On the other hand, r e,3.7 statistics showed little dependence on H s and remained relatively stable over the whole range of H s values. Potential contributing causes to the substantial r e,3.7 and r e,2.1 differences are discussed. In particular, based on both 1-D and 3-D radiative transfer simulations, we have elucidated mechanisms by which cloud heterogeneity and 3-D radiative effects can cause large differences between r e,3.7 and r e,2.1 retrievals for highly inhomogeneous clouds. Our results suggest that the contrast in observed Dr e,3.7-2.1 between cloud regimes is correlated with increases in both cloud r e and H s . We also speculate that in some highly inhomogeneous drizzling clouds, vertical structure induced by drizzle and 3-D radiative effects might operate together to cause dramatic differences between r e,3.7 and r e,2.1 retrievals.Citation: Zhang, Z., and S. Platnick (2011), An assessment of differences between cloud effective particle radius retrievals for marine water clouds from three MODIS spectral bands,

The productivity of the Amazon rainforest is constrained by the availability of nutrients, in particular phosphorus (P). Deposition of long‐range transported African dust is recognized as a potentially important but poorly quantified source of phosphorus. This study provides a first multiyear satellite‐based estimate of dust deposition into the Amazon Basin using three‐dimensional (3‐D) aerosol measurements over 2007–2013 from the Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP). The 7 year average of dust deposition into the Amazon Basin is estimated to be 28 (8–48) Tg a−1 or 29 (8–50) kg ha−1 a−1. The dust deposition shows significant interannual variation that is negatively correlated with the prior‐year rainfall in the Sahel. The CALIOP‐based multiyear mean estimate of dust deposition matches better with estimates from in situ measurements and model simulations than a previous satellite‐based estimate does. The closer agreement benefits from a more realistic geographic definition of the Amazon Basin and inclusion of meridional dust transport calculation in addition to the 3‐D nature of CALIOP aerosol measurements. The imported dust could provide about 0.022 (0.006–0.037) Tg P of phosphorus per year, equivalent to 23 (7–39) g P ha−1 a−1 to fertilize the Amazon rainforest. This out‐of‐basin phosphorus input is comparable to the hydrological loss of phosphorus from the basin, suggesting an important role of African dust in preventing phosphorus depletion on timescales of decades to centuries.

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[1] This study investigates effects of drizzle and cloud horizontal inhomogeneity on cloud effective radius (r e ) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS). In order to identify the relative importance of various factors, we developed a MODIS cloud property retrieval simulator based on the combination of large-eddy simulations (LES) and radiative transfer computations. The case studies based on synthetic LES cloud fields indicate that at high spatial resolution ($100 m) 3-D radiative transfer effects, such as illumination and shadowing, can induce significant differences between retrievals of r e based on reflectance at 2.1 mm (r e,2.1 ) and 3.7 mm (r e,3.7 ). It is also found that 3-D effects tend to have stronger impact on r e,2.1 than r e,3.7 , leading to positive difference between the two (Dr e,3.7À2.1 ) from illumination and negative Dr e,3.7À2.1 from shadowing. The cancellation of opposing 3-D effects leads to overall reasonable agreement between r e,2.1 and r e,3.7 at high spatial resolution as far as domain averages are concerned. At resolutions similar to MODIS, however, r e,2.1 is systematically larger than r e,3.7 when averaged over the LES domain, with the difference exhibiting a threshold-like dependence on both r e,2.1 and an index of the sub-pixel variability in reflectance (H s ), consistent with MODIS observations. In the LES cases studied, drizzle does not strongly impact r e retrievals at either wavelength. It is also found that opposing 3-D radiative transfer effects partly cancel each other when cloud reflectance is aggregated from high spatial resolution to MODIS resolution, resulting in a weaker net impact of 3-D radiative effects on r e retrievals. The large difference at MODIS resolution between r e,3.7 and r e,2.1 for highly inhomogeneous pixels with H s > 0.4 can be largely attributed to what we refer to as the "plane-parallel r e bias," which is attributable to the impact of sub-pixel level horizontal variability of cloud optical thickness on r e retrievals and is greater for r e,2.1 than r e,3.7 . These results suggest that there are substantial uncertainties attributable to 3-D radiative effects and plane-parallel r e bias in the MODIS r e,2.1 retrievals for pixels with strong sub-pixel scale variability, and the H s index can be used to identify these uncertainties.Citation: Zhang, Z., A. S. Ackerman, G. Feingold, S. Platnick, R. Pincus, and H. Xue (2012), Effects of cloud horizontal inhomogeneity and drizzle on remote sensing of cloud droplet effective radius: Case studies based on large-eddy simulations,

This study summarizes recent improvements in the development of bulk scattering/absorption models at solar wavelengths. The approach combines microphysical measurements from various field campaigns with single-scattering properties for nine habits including droxtals, plates, solid/hollow columns, solid/hollow bullet rosettes, and several types of aggregates. Microphysical measurements are incorporated from a number of recent field campaigns in both the Northern and Southern Hemisphere. A set of 12 815 particle size distributions is used for which T cld # 2408C. The ice water content in the microphysical data spans six orders of magnitude. For evaluation, a library of ice-particle single-scattering properties is employed for 101 wavelengths between 0.4 and 2.24 mm. The library includes the full phase matrix as well as properties for smooth, moderately roughened, and severely roughened particles. Habit mixtures are developed for generalized cirrus, midlatitude cirrus, and deep tropical convection. The single-scattering properties are integrated over particle size and wavelength using an assumed habit mixture to develop bulk scattering and absorption properties. In comparison with global Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) data, models built with severely roughened particles compare best for all habit mixtures. The assumption of smooth particles provided the largest departure from CALIOP measurements. The use of roughened rather than smooth particles to infer optical thickness and effective diameter from satellite imagery such as the Moderate Resolution Imaging Spectroradiometer (MODIS) will result in a decrease in optical thickness and an increase in particle size.