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College has been hailed as a “great equalizer” that can substantially reduce the influence of parents' socioeconomic status on their children's subsequent life chances. Do the equalizing effects of college extend beyond the well-studied economic outcomes to other dimensions, in particular, marriage? When and whom one marries have important implications for economic and family stability, with marriage acting as a social safety net, encouraging joint long-term investments, and potentially producing dual-earner families. I focus on the marriage timing and assortative mating patterns of first- and continuing-generation college graduates to test whether college acts as an equalizer for marriage against alternative hypotheses. Using discrete-time event-history methods and data from the National Longitudinal Survey of Youth 1997, I find small differences between first- and continuing-generation graduates in marriage timing, but larger differences in assortative mating, particularly for women. First-generation women have a substantially lower likelihood of marrying another college graduate than do continuing-generation women, and a higher likelihood of marrying a noncollege graduate. These findings highlight the importance of examining noneconomic outcomes when studying social mobility and offer insight into how inequality may persist across generations, especially for women, despite apparent upward mobility.

Cloud longwave scattering is generally neglected in general circulation models (GCMs), but it plays a significant and highly uncertain role in the atmospheric energy budget as demonstrated in recent studies. To reduce the errors caused by neglecting cloud longwave scattering, two new radiance adjustment methods are developed that retain the computational efficiency of broadband radiative transfer simulations. In particular, two existing scaling methods and the two new adjustment methods are implemented in the Rapid Radiative Transfer Model (RRTM). The results are then compared with those based on the Discrete Ordinate Radiative Transfer model (DISORT) that explicitly accounts for multiple scattering by clouds. The two scaling methods are shown to improve the accuracy of radiative transfer simulations for optically thin clouds but not effectively for optically thick clouds. However, the adjustment methods reduce computational errors over a wide range, from optically thin to thick clouds. With the adjustment methods, the errors resulting from neglecting cloud longwave scattering are reduced to less than 2 W m−2 for the upward irradiance at the top of the atmosphere and less than 0.5 W m−2 for the surface downward irradiance. The adjustment schemes prove to be more accurate and efficient than a four-stream approximation that explicitly accounts for multiple scattering. The neglect of cloud longwave scattering results in an underestimate of the surface downward irradiance (cooling effect), but the errors are almost eliminated by the adjustment methods (warming effect).

In our companion study, we show how cloud property products change from MODIS (Moderate Resolution Imaging Spectroradiometer) collection 5.1 (C51) to collection 6 (C6) for both ice and liquid water clouds through a pixel-to-pixel comparison. However, the question remains as to the full impacts of these cloud property differences between collections on the inference of cloud radiative effects (CREs). In this study, we address this question from a modeling perspective using one year (2012) of MODIS gridded annual-averaged ice/liquid water cloud properties at 0.5° × 0.5° spatial resolution. The rapid radiative transfer model for general circulation model applications is used to simulate the broadband radiative fluxes at the top of the atmosphere under clear-sky and cloudy-sky conditions. The shortwave, longwave, and net radiative effects of ice, liquid water, and total clouds are derived individually assuming different cloud optical property parameterization schemes. The results provide quantifications of ice and liquid water CRE contributions to the total CRE. We find significant differences in the simulated CREs between C6 and C51 for ice clouds (up to 23 W m−2 for the shortwave CRE) and liquid water clouds (approximately −4.5 W m−2 for the shortwave CRE). The C6 total CRE provides the closest match with the Clouds and the Earth's Radiant Energy System Energy Balanced And Filled product. Sensitivity studies are performed to estimate the impacts of different ice optical parameterization schemes and multilayer cloud overlap assumptions. Results show that the C6–C51 CRE differences are larger than the CRE variations caused by the other factors.

The Moderate-Resolution Imaging Spectroradiometer (MODIS) level-2 (L2) 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: 1) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach; 2) improvement in the skill of the shortwave-derived cloud thermodynamic phase; 3) separate cloud effective radius retrieval data sets for each spectral combination used in previous collections; 4) separate retrievals for partly cloudy pixels and those associated with cloud edges; 5) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space; and 6) enhanced pixel-level retrieval uncertainty calculations. The C6 algorithm changes can collectively result in significant changes relative to C5, though the magnitude depends on the data set and the pixel’s retrieval location in the cloud parameter space. Example L2 granule and level-3 gridded data set differences between the two collections are shown. While the emphasis is on the suite of cloud optical property data sets, other MODIS cloud data sets are discussed when relevant.

Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from space-borne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This entails the derivation of surface albedo from SSFR/BBR and camera imagery for heterogeneous surfaces in the marginal ice zone (MIZ), as well as subsequent measurement-model inter-comparisons in the presence of thin clouds. In addition to MODIS cloud retrievals and surface albedo from SSFR, we used temperature and humidity data from in-situ data and reanalysis (MERRA-2). The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based measurements, and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case studies, about 22 % of clouds remained undetected (cloud optical thickness less than 0.5). The radiative effect of clouds above the detection threshold was −40 W m−2 above cloud, and −39 W m−2 below the cloud layer, and the optical thickness from the MODIS "1621" cloud product was consistent with the reflected and transmitted irradiance observations. This study suggests that passive imagery cloud detection could be improved through a multi-pixel approach, that would make it more dependable in the Arctic. Regardless of the cloud retrieval method, there is a need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effect from space-borne remote sensing.

The degree of surface roughness of ice particles within thick, cold ice clouds is inferred from multi-directional, multi-spectral satellite polarimetric observations over oceans, assuming a column-aggregate particle habit. An improved roughness inference scheme is employed that provides a more noise-resilient roughness estimate than the conventional best-fit approach. The improvements include the introduction of a quantitative roughness parameter based on empirical orthogonal function analysis and proper treatment of polarization due to atmospheric scattering above clouds. A global 1-month data sample supports the use of a severely roughened ice habit to simulate the polarized reflectivity associated with ice clouds over ocean. The density distribution of the roughness parameter inferred from the global 1-month data sample and further analyses of a few case studies demonstrate the significant variability of ice cloud single-scattering properties. However, the present theoretical results do not agree with observations in the tropics. In the extratropics, the roughness parameter is inferred but 74 % of the sample is out of the expected parameter range. Potential improvements are discussed to enhance the depiction of the natural variability on a global scale.

Similarity relations applied to ice cloud radiance calculations are theoretically analyzed and numerically validated. If τ(1-ϖ) and τ(1-ϖg) are conserved where τ is optical thickness, ϖ the single-scattering albedo, and g the asymmetry factor, it is possible that substantially different phase functions may give rise to similar radiances in both conservative and non-conservative scattering cases, particularly in the case of large optical thicknesses. In addition to theoretical analysis, this study uses operational ice cloud optical thickness retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 Collection 5 (C5) and Collection 6 (C6) cloud property products to verify radiative similarity relations. It is found that, if the MODIS C5 and C6 ice cloud optical thickness values are multiplied by their respective (1-ϖg) factors, the resultant products referred to as the effective optical thicknesses become similar with their ratio values around unity. Furthermore, the ratios of the C5 and C6 ice cloud effective optical thicknesses display an angular variation pattern similar to that of the corresponding ice cloud phase function ratios. The MODIS C5 and C6 values of ice cloud similarity parameter, defined as [(1-ϖ)/(1-ϖg)](1/2), also tend to be similar.

Cloud properties have been retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) over 12 years of continuous observations from Terra and over nine years from Aqua. Results include the spatial and temporal distribution of cloud fraction, the cloud top pressure and cloud top temperature, and the cloud optical thickness and effective radius of both liquid water and ice clouds. Globally, the cloud fraction derived by the MODIS cloud mask is ~ 67%, with somewhat more clouds over land during the afternoon and less clouds over ocean in the afternoon, with very little difference in global cloud cover between Terra and Aqua. Overall, the cloud fraction over land is ~ 55%, with a distinctive seasonal cycle, whereas the ocean cloudiness is much higher, around 72%, with much reduced seasonal variation. Aqua and Terra have comparable zonal cloud top pressures, with Aqua having somewhat higher clouds (cloud top pressures lower by 100 hPa) over land due to afternoon deep convection. The coldest cloud tops (colder than 230 K) generally occur over Antarctica and the high clouds in the tropics. The cloud effective particle radius of liquid water clouds is significantly larger over ocean (mode 12-13 μm) than land (mode 10-11 μm), consistent with the variation in hygroscopic aerosol concentrations that provide cloud condensation nuclei necessary for cloud formation. We also find the effective radius to be 2-3 μm larger in the southern hemisphere than in the northern hemisphere, likely reflecting differences in sources of cloud condensation nuclei.

We found that cloud spatial structure manifests itself as spectral signature in shortwave irradiance fields – specifically in transmittance and net horizontal photon transport in the visible and near-ultraviolet wavelength range. In this paper, we demonstrate this through radiative transfer calculations with cloud imagery from a field experiment, and show that such three-dimensional effects may occur on scales up to 60 km. Neglecting net horizontal photon transport leads to a transmittance bias on the order of ±12–19 % even at the relatively coarse spatial resolution of 20 km, and of more than ±50 % for 1 km. This poses a problem for radiative energy budget estimates from space because the bias for any pixel depends on its spatial context in a non-trivial way. The key for solving this problem may lie in the spectral dimension, since we found a robust correlation between the magnitude of net horizontal photon transport (H) and its spectral dependence (slope). It is scale-invariant and holds for the entire pixel population of a domain. This was at first surprising given the large degree of spatial inhomogeneity, but seems to be valid for any cloud field. We prove that the underlying physical mechanism for this phenomenon is molecular scattering in conjunction with cloud inhomogeneity. On this basis, we developed a simple parameterization through a single parameter ε, which quantifies the characteristic spectral signature of spatial heterogeneities. In a companion paper, we will show that it is accompanied by spectral radiance perturbations, which can be detected from multi-spectral imagers and may be translated into bias reductions for cloud radiative effect estimates in the future.

Retrievals of ice cloud properties using infrared measurements at 3.7, 6.7, 7.3, 8.5, 10.8, and 12.0 mm can provide consistent results regardless of solar illumination, but are limited to cloud optical thicknesses t < ~6. This paper investigates the variations in radiances at these wavelengths over a deep convective cloud system for their potential to extend retrievals of t and ice particle size De to optically thick clouds. Measurements from an imager, an interferometer, the Cloud Physics Lidar (CPL), and the Cloud Radar System (CRS) aboard the NASA ER-2 aircraft during the NASA TC4 (Tropical Composition, Cloud and Climate Coupling) experiment flight during 5 August 2007, are used to examine the retrieval potential of infrared radiances over optically thick ice clouds. Simulations based on coincident in situ measurements and combined cloud t from CRS and CPL measurements are comparable to the observations. They reveal that brightness temperatures at these bands and their differences (BTD) are sensitive to t up to ~20 and that for ice clouds having t > 20, the 3.7–10.8 µm and 3.7–6.7 µm BTDs are the most sensitive to De. Satellite imagery appears to be consistent with these results suggesting that t and De could be retrieved for greater optical thicknesses than previously assumed. But, because of sensitivity of the BTDs to uncertainties in the atmospheric profiles of temperature, humidity, and ice water content, and sensor noise, exploiting the small BTD signals in retrieval algorithms will be very challenging.

Large forest fires are a known natural and dominant disturbance factor in high northern latitudes, and form pyrocumulus (pyroCu), and occasionally pyrocumulonimbus (pyroCb) clouds. These clouds can transport emissions into the upper troposphere/lower stratosphere (UT/LS) and produce significant regional and even global climate effects, as is the case with some volcanoes. However, the lack of observational data within pyroCu or pyroCb complicates our ability to investigate pyro-convection and to understand the vertical and cross-isentropic transport mechanisms responsible for UT/LS injection. Here, we report detailed airborne radiation measurements within strong pyroCu taken over boreal forest fires in Saskatchewan, Canada during the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) summer field campaign in 2008. We find a prominent smoke core within the pyroCu, which is defined by strong extinction in the UV, VIS and NIR, and high gas-particle concentrations. We also find that the angular distribution of radiance within the pyroCu is closely related to the diffusion domain in water clouds, which is dominated by multiple scattering processes. The radiation field of pyroCu can be described by diffusion approximations that are comprised of simple cosine functions, which can be used to calculate the spatial and temporal characteristics of the radiance field, and applied in cloud resolving models. We demonstrate with Monte Carlo simulations that radiation transport in pyroCu is inherently a 3D problem and must account for particle absorption.

Over the past decade, the role of multiangle 1 remote sensing has been central to the development of algorithms for the retrieval of global land surface properties including models of the bidirectional reflectance distribution function (BRDF), albedo, land cover/dynamics, burned area extent, as well as other key surface biophysical quantities represented by the anisotropic reflectance characteristics of vegetation. In this study, a new retrieval strategy for fine-to-moderate resolution multiangle observations was developed, based on the operational sequence used to retrieve the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5 reflectance and BRDF/albedo products. The algorithm makes use of a semiempirical kernel-driven bidirectional reflectance model to provide estimates of intrinsic albedo (i.e., directional-hemispherical reflectance and bihemispherical reflectance), model parameters describing the BRDF, and extensive quality assurance information. The new retrieval strategy was applied to NASA's Cloud Absorption Radiometer (CAR) data acquired during the 2007 Cloud and Land Surface Interaction Campaign (CLASIC) over the well-instrumented Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site in Oklahoma, USA. For the case analyzed, we obtained approx.1.6 million individual surface bidirectional reflectance factor (BRF) retrievals, from nadir to 75deg off-nadir, and at spatial resolutions ranging from 3 m - 500 m. This unique dataset was used to examine the interaction of the spatial and angular 18 characteristics of a mixed agricultural landscape; and provided the basis for detailed assessments of: (1) the use of a priori knowledge in kernel-driven BRDF model inversions; (2) the interaction between surface reflectance anisotropy and instrument spatial resolution; and (3) the uncertainties that arise when sub-pixel differences in the BRDF are aggregated to a moderate resolution satellite pixel. Results offer empirical evidence concerning the influence of scale and spatial heterogeneity in kernel-driven BRDF models; providing potential new insights into the behavior and characteristics of different surface radiative properties related to land/use cover change and vegetation structure.

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Earth Observing System (EOS) Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that present difficulties for retrieving cloud effective radius using single-layer plane-parallel cloud models. The algorithm uses the MODIS 0.94-μm water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94-μm methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases.

The spring 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) experiment was one of the major intensive field campaigns of the International Polar Year, aimed at detailed characterization of atmospheric physical and chemical processes in the Arctic region. Part of this campaign was a unique snow bidirectional reflectance experiment on the NASA P-3B aircraft conducted on 7 and 15 April by the Cloud Absorption Radiometer (CAR) jointly with airborne Ames Airborne Tracking Sunphotometer (AATS) and ground-based Aerosol Robotic Network (AERONET) sunphotometers. The CAR data were atmospherically corrected to derive snow bidirectional reflectance at high 1° angular resolution in view zenith and azimuthal angles along with surface albedo. The derived albedo was generally in good agreement with ground albedo measurements collected on 15 April. The CAR snow bidirectional reflectance factor (BRF) was used to study the accuracy of analytical Ross-Thick Li-Sparse (RTLS), Modified Rahman-Pinty-Verstraete (MRPV) and Asymptotic Analytical Radiative Transfer (AART) BRF models. Except for the glint region (azimuthal angles φ

This paper presents a new method for simultaneously retrieving aerosol and surface reflectance properties from combined airborne and ground-based direct and diffuse radiometric measurements. The method is based on the standard Aerosol Robotic Network (AERONET) method for retrieving aerosol size distribution, complex index of refraction, and single scattering albedo, but modified to retrieve aerosol properties in two layers, below and above the aircraft, and parameters on surface optical properties from combined datasets (Cloud Absorption Radiometer (CAR) and AERONET data). A key advantage of this method is the inversion of all available spectral and angular data at the same time, while accounting for the influence of noise in the inversion procedure using statistical optimization. The wide spectral (0.34–2.30 μm) and angular range (180°) of the CAR instrument, combined with observations from an AERONET sunphotometer, provide sufficient measurement constraints for characterizing aerosol and surface properties with minimal assumptions. The robustness of the method was tested on observations made during four different field campaigns: (a) the Southern African Regional Science Initiative 2000 over Mongu, Zambia, (b) the Intercontinental Transport Experiment-Phase B over Mexico City, Mexico (c) Cloud and Land Surface Interaction Campaign over the Atmospheric Radiation Measurement (ARM) Central Facility, Oklahoma, USA, and (d) the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) over Elson Lagoon in Barrow, Alaska, USA. The four areas are dominated by different surface characteristics and aerosol types, and therefore provide good test cases for the new inversion method.

In this paper, laboratory-based bidirectional reflectance distribution function (BRDF) analysis of vegetation leaves, soil, and leaf-litter samples is presented. The leaf litter and soil samples, numbered 1 and 2, were obtained from a site located in the savanna biome of South Africa (Skukuza: 25.0deg S, 31.5deg E). A third soil sample, number 3, was obtained from Etosha Pan, Namibia (19.20deg S, 15.93deg E, altitude of 1100 m). In addition, BRDF of local fresh and dry leaves from tulip polar tree (Liriodendron tulipifera) and black locust tree (Robinia pseudoacacia) were studied. It is shown how the BRDF depends on the incident and scatter angles, sample size (i.e., crushed versus whole leaf), soil samples fraction size, sample status (i.e., fresh versus dry leaves), vegetation species (i.e., poplar versus locust), and the vegetation's biochemical composition. As a demonstration of the application of the results of this paper, airborne BRDF measurements acquired with NASA's Cloud Absorption Radiometer over the same general site where the soil and leaf-litter samples were obtained are compared to the laboratory results. Good agreement between laboratory and airborne-measured BRDF is reported.

Five years (2000–04) of spatially complete snow-free land surface albedo data have been produced using high-quality-flagged diffuse bihemispherical (white sky) and direct-beam directional hemispherical (black sky) land surface albedo data derived from observations taken by the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument aboard the NASA Terra satellite platform (MOD43B3, collection 4). In addition, a spatially complete snow-free aggregate albedo climatological product was generated. These spatially complete products were prepared using an ecosystem-dependent temporal interpolation technique that retrieves missing data within 3%–8% error. These datasets have already been integrated into research and operational projects that require snow-free land surface albedo. As such, this paper provides details regarding the spatial and temporal distribution of the filled versus the original MOD43B3 data. The paper also explores the intra- and interannual variation in the 5-yr data record and provides a qualitative comparison of zonal averages and annual cycles of the filled versus the original MOD43B3 data. The analyses emphasize the data’s inter- and intraannual variation and show that the filled data exhibit large- and small-scale phenological behavior that is qualitatively similar to that of the original MOD43B3. These analyses thereby serve to showcase the inherent spectral, spatial, and temporal variability in the MOD43B3 data as well as the ability of the fill technique to preserve these unique regional and pixel-level phenological characteristics.

This study surveys the optical and microphysical properties of high (ice) clouds over the Tropics (30°S–30°N) over a 3-yr period from September 2002 through August 2005. The analyses are based on the gridded level-3 cloud products derived from the measurements acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard both the NASA Earth Observing System Terra and Aqua platforms. The present analysis is based on the MODIS collection-4 data products. The cloud products provide daily, weekly, and monthly mean cloud fraction, cloud optical thickness, cloud effective radius, cloud-top temperature, cloud-top pressure, and cloud effective emissivity, which is defined as the product of cloud emittance and cloud fraction. This study is focused on high-level ice clouds. The MODIS-derived high clouds are classified as cirriform and deep convective clouds using the International Satellite Cloud Climatology Project (ISCCP) classification scheme. Cirriform clouds make up more than 80% of the total high clouds, whereas deep convective clouds account for less than 20% of the total high clouds. High clouds are prevalent over the intertropical convergence zone (ITCZ), the South Pacific convergence zone (SPCZ), tropical Africa, the Indian Ocean, tropical America, and South America. Moreover, land–ocean, morning–afternoon, and summer–winter variations of high cloud properties are also observed.

This paper reports on the comparison of two latest versions (collections 4 and 5) of ice cloud products derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) measurements. The differences between the bulk optical properties of ice clouds used in collections 4 and 5 and the relevant impact on simulating the correlation of the bidirectional reflection functions at two MODIS bands centered at 0.65 (or 0.86) and 2.13 mum are investigated. The level-3 MODIS ice cloud properties (specifically, ice cloud fraction, optical thickness, and effective particle size in this paper) from the collection 4 and 5 datasets are compared for a tropical belt of 30deg S-30deg N. Furthermore, the impact of the differences between the MODIS collection 4 and 5 ice cloud products on the simulation of the radiative forcing of these clouds is investigated. Over the tropics, the averaged ice cloud fraction from collection 5 is 1.1% more than the collection 4 counterpart, the averaged optical thickness from collection 5 is 1.2 larger than the collection 4 counterpart, and the averaged effective particle radius from collection 5 is 1.8 mum smaller than the collection 4 counterpart. Moreover, the magnitude of the differences between collection 5 and 4 ice cloud properties also depends on the surface characteristics, i.e., over land or over ocean. The differences of these two datasets (collections 4 and 5) of cloud properties can have a significant impact on the simulation of the radiative forcing of ice clouds. In terms of total (longwave plus shortwave) cloud radiative forcing, the differences between the collection 5 and 4 results are distributed primarily between -60 and 20 W ldr m-2 but peak at 0 W ldr m-2.

Objective— To assess effects over 12 weeks of bisection nephrotomy on renal function, size, and morphology in cats. Study Design— Controlled, randomized, blinded experiment. Sample Population— Ten adult female cats. Methods— Glomerular filtration rate (GFR), determined by quantitative renal scintigraphy using 99mTechnetium-diethylenetriamine-pentaacetic acid, urinalysis, urine culture, and ultrasonographic measurement of renal size were performed preoperatively. Left or right nephrotomy (5 cats/group) was performed. Total and individual kidney GFRs were determined at 2, 28, and 84 days, ultrasonographic measurements at 28 and 86 days, and ultrasound-guided biopsy at 86 days. Results— No significant differences in mean GFR and kidney size of operated versus unoperated kidneys were observed. Individual GFR and renal size of all except 1 cat remained within normal limits. Two cats had evidence of transient ureteral obstruction in the immediate postoperative period. No significant, generalized histologic abnormalities were observed. Conclusions— Bisection nephrotomy in normal cats does not adversely affect renal function or morphology during the initial 12 weeks. Clinical Relevance— Bisection nephrotomy can be safely performed in normal feline kidneys without causing a significant deleterious effect on renal function. Studies in cats with pre-existing renal insufficiency are needed to ensure adverse effects would not occur in clinical cases where this surgical procedure is warranted.

During the ACE-Asia field campaign, unprecedented amounts of aerosol property data in East Asia during springtime were collected from an array of aircraft, shipboard, and surface instruments. However, most of the observations were obtained in areas downwind of the source regions. In this paper, the newly developed satellite aerosol algorithm called "Deep Blue" was employed to characterize the properties of aerosols over source regions using radiance measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Based upon the Aringngstroumlm exponent derived from the Deep Blue algorithm, it was demonstrated that this new algorithm is able to distinguish dust plumes from fine-mode pollution particles even in complex aerosol environments such as the one over Beijing. Furthermore, these results were validated by comparing them with observations from AERONET sites in China and Mongolia during spring 2001. These comparisons show that the values of satellite-retrieved aerosol optical thickness from Deep Blue are generally within 20%-30% of those measured by sunphotometers. The analyses also indicate that the roles of mineral dust and anthropogenic particles are comparable in contributing to the overall aerosol distributions during spring in northern China, while fine-mode particles are dominant over southern China. The spring season in East Asia consists of one of the most complex environments in terms of frequent cloudiness and wide ranges of aerosol loadings and types. This paper will discuss how the factors contributing to this complexity influence the resulting aerosol monthly averages from various satellite sensors and, thus, the synergy among satellite aerosol products

This paper presents a validation case study of Multi-angle Imaging SpectroRadiometer (MISR) surface products where its bidirectional reflectance (BRF) measurements during the Southern Africa Regional Science Initiative (SAFARI 2000) campaign are compared with those coincidently evaluated on the ground and from the air, using the Portable Apparatus for Rapid Acquisition of Bidirectional Observations of Land and Atmosphere (PARABOLA) and Cloud Absorption Radiometer observations, respectively. The presence of haze and smoke during the campaign provided a case study to evaluate the effect of atmospheric correction on MISR surface products. Two surface types were considered in the analyses: the bright desert-like surface of the Pan and the dark grassland that surrounds it. The results show that for the dark surface the BRF values retrieved from MISR are in good agreement, within 5%, with those obtained from field data. For the bright desert-like pan surface, better agreement, within ~10%, was found in all channels on the clear day but only in the forward scattering on the hazy day. A comparison of MISR aerosol retrievals to those obtained from three independent ground measurements suggests that, in the presence of a highly reflective surface, small uncertainties in the MISR aerosol retrievals become magnified at larger optical depths, causing errors in the surface BRF retrievals

This study examines the development of bulk single-scattering properties of ice clouds, including single-scattering albedo, asymmetry factor, and phase function, for a set of 1117 particle size distributions obtained from analysis of the First International Satellite Cloud Climatology Project Regional Experiment (FIRE)-I, FIRE-II, Atmospheric Radiation Measurement Program intensive observation period, Tropical Rainfall Measuring Mission Kwajalein Experiment (KWAJEX), and the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) data. The primary focus is to develop band-averaged models appropriate for use by the Moderate Resolution Imaging Spectroradiometer (MODIS) imager on the Earth Observing System Terra and Aqua platforms, specifically for bands located at wavelengths of 0.65, 1.64, 2.13, and 3.75 μm. The results indicate that there are substantial differences in the bulk scattering properties of ice clouds formed in areas of deep convection and those that exist in areas of much lower updraft velocities. Band-averaged bulk scattering property results obtained from a particle-size-dependent mixture of ice crystal habits are compared with those obtained assuming only solid hexagonal columns. The single-scattering albedo is lower for hexagonal columns than for a habit mixture for the 1.64-, 2.13-, and 3.75-μm bands, with the differences increasing with wavelength. In contrast, the asymmetry factors obtained from the habit mixture and only the solid hexagonal column are most different at 0.65 μm, with the differences decreasing as wavelength increases. At 3.75 μm, the asymmetry factor results from the two habit assumptions are almost indistinguishable. The asymmetry factor, single-scattering albedo, and scattering phase functions are also compared with the MODIS version-1 (V1) models. Differences between the current and V1 models can be traced to the microphysical models and specifically to the number of both the smallest and the largest particles assumed in the size distributions.

The Cloud Absorption Radiometer (CAR) was flown aboard the University of Washington Convair 580 (CV-580) research aircraft during the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) field campaign and obtained measurements of bidirectional reflectance distribution function (BRDF) of the ocean in July and August 2001 under different illumination conditions with solar zenith angles ranging from 15° to 46°. The BRDF measurements were accompanied by concurrent measurements of atmospheric aerosol optical thickness and column water vapor above the airplane. The method of spherical harmonics with Cox–Munk wave-slope distribution is used in a new algorithm developed for this study to solve the atmosphere–ocean radiative transfer problem and to remove the effects of the atmosphere from airborne measurements. The algorithm retrieves simultaneously the wind speed and full ocean BRDF (sun’s glitter and water-leaving radiance) from CAR measurements and evaluates total albedo and equivalent albedo for the water-leaving radiance outside the glitter. Results show good overall agreement with other measurements and theoretical simulations, with the anisotropy of the water-leaving radiance clearly seen. However, the water-leaving radiance does not show a strong dependence on solar zenith angle as suggested by some theoretical studies. The spectral albedo was found to vary from 4.1%–5.1% at λ = 0.472 μm to 2.4%–3.5% for λ ≥ 0.682 μm. The equivalent water-leaving albedo ranges from 1.0%–2.4% at λ = 0.472 μm to 0.1%–0.6% for λ = 0.682 μm and 0.1%–0.3% for λ = 0.870 μm. Results of the validation of the Cox–Munk model under the conditions measured show that although the model reproduces the shape of sun’s glitter on average with an accuracy of better than 30%, it underestimates the center of the sun’s glitter reflectance by about 30% for low wind speeds (

Recent production of land surface anisotropy, diffuse bihemispherical (white-sky) albedo, and direct-beam directional hemispherical (black-sky) albedo from observations acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the National Aeronautics and Space Administration's Terra and Aqua satellite platforms have provided researchers with unprecedented spatial, spectral, and temporal information on the land surface's radiative characteristics. Cloud cover, which curtails retrievals, and the presence of ephemeral and seasonal snow limit the snow-free data to approximately half the global land surfaces on an annual equal-angle basis. This precludes the MOD43B3 albedo products from being used in some remote sensing and ground-based applications, climate models, and global change research projects. An ecosystem-dependent temporal interpolation technique is described that has been developed to fill missing or seasonally snow-covered data in the official MOD43B3 albedo product. The method imposes pixel-level and local regional ecosystem-dependent phenological behavior onto retrieved pixel temporal data in such a way as to maintain pixel-level spatial and spectral detail and integrity. The phenological curves are derived from statistics based on the MODIS MOD12Q1 IGBP land cover classification product geolocated with the MOD43B3 data. The resulting snow-free value-added products provide the scientific community with spatially and temporally complete global white- and black-sky surface albedo maps and statistics. These products are stored on 1-min and coarser resolution equal-angle grids and are computed for the first seven MODIS wavelengths, ranging from 0.47-2.1 /spl mu/m and for three broadband wavelengths 0.3-0.7, 0.3-5.0, and 0.7-5.0 /spl mu/m.

A multispectral scanning spectrometer was used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds, sea ice, snow, and tundra surfaces at 50 discrete wavelengths between 0.47 and 14.0 mm. These observations were obtained from the NASA ER-2 aircraft as part of the First ISCCP (International Satellite Cloud Climatology Project) Regional Experiment (FIRE) Arctic Clouds Experiment, conducted over a 1600 km 3 500 km region of the north slope of Alaska and surrounding Beaufort and Chukchi Seas between 18 May and 6 June 1998. Multispectral images in eight distinct bands of the Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud) over five different ecosystems. Based on the results of individual tests run as part of this cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). Finally, the cloud optical thickness and effective radius were derived for both water and ice clouds that were detected during one flight line on 4 June. This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS data in Alaska, is quite capable of distinguishing clouds from bright sea ice surfaces during daytime conditions in the high Arctic. Results of individual tests, however, make it difficult to distinguish ice clouds over snow and sea ice surfaces, so additional tests were added to enhance the confidence in the thermodynamic phase of clouds over the Chukchi Sea. The cloud optical thickness and effective radius retrievals used three distinct bands of the MAS, with a recently developed 1.62- and 2.13-mm-band algorithm being used quite successfully over snow and sea ice surfaces. These results are contrasted with a MODIS-based algorithm that relies on spectral reflectance at 0.87 and 2.13 mm.

Retrieving aerosol properties from satellite remote sensing over a bright surface is a challenging problem in the research of atmospheric and land applications. In this paper we propose a new approach to retrieve aerosol properties over surfaces such as arid, semiarid, and urban areas, where the surface reflectance is usually very bright in the red part of visible spectrum and in the near infrared, but is much darker in the blue spectral region (i.e., wavelength

The Moderate Resolution Imaging Spectroradiometer (MODIS) is an Earth-viewing sensor that flies on the Earth Observing System Terra and Aqua satellites, launched in 1999 and 2002, respectively. MODIS scans a swath width of 2330 km that is sufficiently wide to provide nearly complete global coverage every two days from a polar-orbiting, Sun-synchronous, platform at an altitude of 705 km. MODIS provides images in 36 spectral bands between 0.415 and 14.235 /spl mu/m with spatial resolutions of 250 m (two bands), 500 m (five bands), and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric properties. Twenty-six bands are used to derive atmospheric properties such as cloud mask, atmospheric profiles, aerosol properties, total precipitable water, and cloud properties. We describe each of these atmospheric data products, including characteristics of each of these products such as file size, spatial resolution used in producing the product, and data availability.

International audience; The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System (EOS) platform launched in December 1999. After achieving final orbit, MODIS began Earth observations in late February 2000 and has been acquiring data since that time. The instrument is also being flown on the Aqua spacecraft, launched in May 2002. A comprehensive set of remote sensing algorithms for cloud detection and the retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere science team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud-top properties (temperature, pressure, effective emissivity), cloud thermodynamic phase, cloud optical and microphysical parameters (optical thickness, effective particle radius, water path), as well as derived statistics. We will describe the various algorithms being used for the remote sensing of cloud properties from MODIS data with an emphasis on the pixel-level retrievals (referred to as Level-2 products), with 1-km or 5-km spatial resolution at nadir. An example of each Level-2 cloud product from a common data granule (5 min of data) off the coast of South America will be discussed. Future efforts will also be mentioned. Relevant points related to the global gridded statistics products (Level-3) are highlighted though additional details are given in an accompanying paper in this issue.

Aerosol radiative forcing is a critical, though variable and uncertain, component of the global climate. Yet climate models rely on sparse information of the aerosol optical properties. In situ measurements, though important in many respects, seldom provide measurements of the undisturbed aerosol in the entire atmospheric column. Here, 8 yr of worldwide distributed data from the AERONET network of ground-based radiometers were used to remotely sense the aerosol absorption and other optical properties in several key locations. Established procedures for maintaining and calibrating the global network of radiometers, cloud screening, and inversion techniques allow for a consistent retrieval of the optical properties of aerosol in locations with varying emission sources and conditions. The multiyear, multi-instrument observations show robust differentiation in both the magnitude and spectral dependence of the absorption—a property driving aerosol climate forcing, for desert dust, biomass burning, urban‐industrial, and marine aerosols. Moreover, significant variability of the absorption for the same aerosol type appearing due to different meteorological and source characteristics as well as different emission characteristics are observed. It is expected that this aerosol characterization will help refine aerosol optical models and reduce uncertainties in satellite observations of the global aerosol and in modeling aerosol impacts on climate.

Angular distributions of spectral reflectance for four common arctic surfaces: snow-covered sea ice, melt-season sea ice, snow-covered tundra, and tundra shortly after snowmelt were measured using an aircraft based, high angular resolution (1-degree) multispectral radiometer. Results indicate bidirectional reflectance is higher for snow-covered sea ice than melt-season sea ice at all wavelengths between 0.47 and 2.3 pm, with the difference increasing with wavelength. Bidirectional reflectance of snow-covered tundra is higher than for snow-free tundra for measurements less than 1.64 pm, with the difference decreasing with wavelength. Bidirectional reflectance patterns of all measured surfaces show maximum reflectance in the forward scattering direction of the principal plane, with identifiable specular reflection for the melt-season sea ice and snow-free tundra cases. The snow-free tundra had the most significant backscatter, and the melt-season sea ice the least. For sea ice, bidirectional reflectance changes due to snowmelt were more significant than differences among the different types of melt-season sea ice. Also the spectral-hemispherical (plane) albedo of each measured arctic surface was computed. Comparing measured nadir reflectance to albedo for sea ice and snow-covered tundra shows albedo underestimated 5-40%, with the largest bias at wavelengths beyond 1 pm. For snow-free tundra, nadir reflectance underestimates plane albedo by about 30-50%.

Cloud optical thickness and droplet effective radius retrievals from solar reflectance measurements are traditionally implemented using a combination of spectral channels that are absorbing and nonabsorbing for water particles. Reflectances in nonabsorbing channels (e.g., 0.67, 0.86, 1.2 μm spectral window bands) are largely dependent on cloud optical thickness, while longer-wavelength absorbing channels (1.6, 2.1, and 3.7 μm window bands) provide cloud particle size information. Cloud retrievals over ice and snow surfaces present serious difficulties. At the shorter wavelengths, ice is bright and highly variable, both characteristics acting to significantly increase cloud retrieval uncertainty. In contrast, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. A modification to the traditional cloud retrieval technique is presented. The new algorithm uses only a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, retrievals have been made with the MODIS airborne simulator (MAS) imager flown aboard the high-altitude NASA ER-2 from May to June 1998 during the Arctic FIRE-ACE field deployment. Data from several coordinated ER-2 and in situ University of Washington Convair-580 aircraft observations of liquid water stratus clouds are examined. MAS retrievals of optical thickness, droplet effective radius, and liquid water path are shown to be in good agreement with in situ measurements. The initial success of the technique has implications for future operational satellite cloud retrieval algorithms in polar and wintertime regions.

In May and June 1998 the Airborne Multiangle Imaging Spectroradiometer (AirMISR) participated in the FIRE Arctic Cloud Experiment (ACE). AirMISR is an airborne instrument for obtaining multiangle imagery similar to that of the satellite-borne MISR instrument. This paper presents a detailed analysis of the data collected on June 3, 1998. In particular, AirMISR radiance measurements are compared with measurements made by two other instruments, the Cloud Absorption Radiometer (CAR) and the MODIS airborne simulator (MAS), as well as to plane-parallel radiative transfer simulations. It is found that the AirMISR radiance measurements and albedo estimates compare favorably both with the other instruments and with the radiative transfer simulations. In addition to radiance and albedo, the multiangle AirMISR data can be used to obtain estimates of cloud top height using stereoimaging techniques. Comparison of AirMISR retrieved cloud top height (using the complete MISR-based stereoimaging approach) shows excellent agreement with the measurements from the airborne Cloud Lidar System (CLS) and ground-based millimeter-wave cloud radar.

Cloud absorption radiometer (CAR) multispectral and multiangular data, collected during the Smoke, Clouds, and Radiation-Brazil (SCAR-B) Experiment, was used to examine the ratio technique, the official method for remote sensing of aerosols over land from the moderate resolution imaging spectroradiometer (MODIS) data, for view angles from nadir to 650 off-nadir. The strategy used is to first select a pristine, low aerosol optical thickness flight, and then to compute ratios of reflectance at 0.47 and 0.68 /spl mu/m to corresponding values at 2.20 /spl mu/m, separately for backward and forward scattering directions. Similarly, the authors analyzed data from high turbidity flights for comparison purposes. For both flights, they removed the effects of atmospheric absorption and scattering using 6S, a radiative transfer code, and then recomputed the ratios again for different values of aerosol optical thickness. Finally, they analyzed bidirectional reflection function (BRF) data to examine the dependence of the ratio technique on the relative azimuth angle. Results of this analysis show that a relationship between visible reflectance and near infrared (IR) reflectance exists for view angles from nadir to 400 off-nadir, and that simple parametric relationships can be derived.

The physical and radiative properties of a composite ship track are described from the analysis of 131 ship–ship track correlation pairs collected during the Monterey Area Ship Track experiment. The significant variability of ship tracks around their average characteristics is also described. The nominal environmental conditions for the ship track set are also described. The composite ship track is 296 ± 233 km long, 7.3 ± 6 h old, and averages 9 ± 5 km wide. The ship is, on the average, 16 ± 8 km from of the head of the ship track along the relative wind vector and corresponds to a time of 25 ± 15 min. The set of ship tracks examined in this study formed in marine boundary layers that were between 300 and 750 m deep, and no tracks formed in boundary layers above 800 m. The tracks form in regions of high relative humidity, small air–sea temperature differences, and moderate winds (average of 7.7 ± 3.1 m s−1). The ambient cloud reflectance in advanced very high resolution radiometer channel 3 (3.7...

The problem of deriving a complete set of aerosol optical properties from Sun and sky radiance measurements is discussed. Algorithm development is focused on improving aerosol retrievals by means of including a detailed statistical optimization of the influence of noise in the inversion procedure. The methodological aspects of such an optimization are discussed in detail and revised according to both modern findings in inversion theory and practical experience in remote sensing. Accordingly, the proposed inversion algorithm is built on the principles of statistical estimation: the spectral radiances and various a priori constraints on aerosol characteristics are considered as multisource data that are known with predetermined accuracy. The inversion is designed as a search for the best fit of all input data by a theoretical model that takes into account the different levels of accuracy of the fitted data. The algorithm allows a choice of normal or lognormal noise assumptions. The multivariable fitting is implemented by a stable numerical procedure combining matrix inversion and univariant relaxation. The theoretical inversion scheme has been realized in the advanced algorithm retrieving aerosol size distribution together with complex refractive index from the spectral measurements of direct and diffuse radiation. The aerosol particles are modeled as homogeneous spheres. The atmospheric radiative transfer modeling is implemented with well-established publicly available radiative transfer codes. The retrieved refractive indices can be wavelength dependent; however, the extended smoothness constraints are applied to its spectral dependence (and indirectly through smoothness constraints on retrieved size distributions). The positive effects of statistical optimization on the retrieval results as well as the importance of applying a priori constraints are discussed in detail for the retrieval of both aerosol size distribution and complex refractive index. The developed algorithm is adapted for the retrieval of aerosol properties from measurements made by ground-based Sun-sky scanning radiometers used in the Aerosol Robotic Network (AERONET). The results of numerical tests together with examples of experimental data inversions are presented.

A methodology for the retrieval of cirrus cloud microphysical and optical properties based on observations of reflected sunlight is introduced. The retrieval method is based on correlation of the bidirectional reflectance of three channels, 0.65, 1.6, and 2.2 μm, that are available onboard Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS). Validation studies using microphysical measurements and MODIS airborne simulator (MAS) observations illustrate the nature of the potential errors associated with the retrieved optical depth and mean effective ice crystal size. The effects of the physical assumptions involving ice crystal size distribution and shape employed in the algorithm are subsequently assessed. In terms of the microphysical models used for radiation calculations the ice crystal shape assumption is found to have the most significant impact on the retrieved parameters. The effect of the background surface reflectance on the retrieval results is further examined, and we show that in order to reliably infer nonblack cirrus parameters from solar reflectance measurements it is essential to properly account for the background radiation over both land and ocean surfaces. Finally, we present the measured ice microphysical data for tropical cirrus as a function of cloud development and ambient temperature to illustrate the importance of vertical inhomogeneity for validation studies.

During the SCAR-A, Kuwait Oil Fire Smoke Experiment, and TARFOX deployments, angular distributions of spectral reflectance for various surfaces were measured using the scanning Cloud Absorption Radiometer (CAR) mounted on the nose of the University of Washington C-131A research aircraft. The CAR contains 13 narrowband spectral channels between 0.47 and 2.3 μm with a 190° scan aperture (5° before zenith to 5° past nadir) and 1° instantaneous field of view. The bidirectional reflectance is obtained by flying a clockwise circular orbit above the surface, resulting in a ground track approximately 3 km in diameter within about 2 min. Spectral bidirectional reflectances of four surfaces are presented: the Great Dismal Swamp in Virginia with overlying haze layer, the Saudi Arabian Desert and the Persian Gulf in the Middle East, and the Atlantic Ocean measured east of Richmond, Virginia. Although the CAR measurements are contaminated by atmospheric effects, results show distinct spectral characteristics for various types of surface-atmosphere systems, including hot spots, limb brightening and darkening, and Sun glint. In addition, the hemispherical albedo of each surface-atmosphere system is calculated directly by integrating over all high angular-resolution CAR measurements for each spectral channel. Comparing the nadir reflectance with the overall hemispherical albedo of each surface, we find that using nadir reflectances as a surrogate for hemispherical albedo can cause albedos to be underestimated by as much as 95% and overestimated by up to 160%, depending on the type of surface and solar zenith angle.

Aerosol particles originate from man-made sources such as urban/industrial activities,rurning associated with land use processes, wind-blown dust, and natural sources. Their interaction with sunlight and their effect on cloud microphysics forms a major uncertainty in predicting climate change. Furthermore, the lifetime of only a few days causes high spatial variability in aerosol optical and radiative properties that requires global observations from space. Remote sensing of aerosol properties from space is reviewed both for present and planned national and international satellite sensors. Techniques that are being used to enhance our ability to characterize the global distribution of aerosol properties include well-calibrated multispectral radiometers, multispectral polarimeters, and multi-angle spectroradiometers. Though most of these sensor systems rely primarily on visible to mid-infrared spectral channels, the availability of of thermal channels to aid in cloud screening is an important additional piece of information that is not always incorporated into the sensor design. In this paper we describe the various satellite sensor systems being developed by Europe, Japan, and the U.S., and highlight the advantages and disadvantages of each of these systems for aerosol applications. An important underlying theme is that the remote sensing of aerosol properties, especially aerosol size distribution and single scattering albedo, is exceedingly difficult. As a consequence, no one sensor system is capable of providing totally unambiguous information, and hence a careful intercomparison of derived products from different sensors, together with a comprehensive network of ground-based sun-photometer and sky radiometer systems, are required to advance our quantitative understanding of global aerosol characteristics.

Using the data gathered from the Advanced Very High Resolution Radiometer (AVHRR) 0.63 and 3.7 µm channels, an algorithm for the inference of cirrus cloud optical depth and mean effective size has been developed for the first time. This scheme is based on the correlation between the 3.7 µm (total) and 0.63 µm radiances that is constructed from radiative transfer calculations involving ice crystal clouds. Application of the algorithm to AVHRR channels has been performed by using data sets that were collected during the First ISCCP Regional Experiment, Phase II, Cirrus Intensive Field Observation (FIRE-II-IFO; November- December 1991) at Coffeyville, Kansas. For validation, the in-situ data collected by the balloon-borne replicator and airborne 2-D probes that were collocated with AVHRR pixels were carefully analyzed for five cases involving single and multiple cirrus cloud layers. We demonstrate that the retrieved cirrus cloud optical depths and mean effective sizes compare reasonably well with those determined from the in- situ analyses.

The Smoke, Clouds, and Radiation-Brazil (SCAR-B) field project took place in the Brazilian Amazon and cerrado regions in August-September 1995 as a collaboration between Brazilian and American scientists. SCAR-B, a comprehensive experiment to study biomass burning, emphasized measurements of surface biomass, fires, smoke aerosol and trace gases, clouds, and radiation. their climatic effects, and remote sensing from aircraft and satellites. It included aircraft and ground-based in situ measurements of smoke emission factors and the compositions, sizes, and optical properties of the smoke particles; studies of the formation of ozone; the transport and evolution of smoke; and smoke interactions with water vapor and clouds. This overview paper introduces SCAR-B and summarizes some of the main results obtained so far. (1) Fires: measurements of the size distribution of fires, using the 50 m resolution MODIS Airborne Simulator, show that most of the fires are small (e.g. 0.005 square km), but the satellite sensors (e.g., AVHRR and MODIS with I km resolution) can detect fires in Brazil which are responsible for 60-85% of the burned biomass: (2) Aerosol: smoke particles emitted from fires increase their radius by as much as 60%, during their first three days in the atmosphere due to condensation and coagulation, reaching a mass median radius of 0.13-0.17 microns: (3) Radiative forcing: estimates of the globally averaged direct radiative forcing due to smoke worldwide, based on the properties of smoke measured in SCAR-B (-O.l to -0.3 W m(exp -2)), are smaller than previously modeled due to a lower single-scattering albedo (0.8 to 0.9), smaller scattering efficiency (3 square meters g(exp -2) at 550 nm), and low humidification factor; and (4) Effect on clouds: a good relationship was found between cloud condensation nuclei and smoke volume concentrations, thus an increase in the smoke emission is expected to affect cloud properties. In SCAR-B, new techniques were developed for deriving the absorption and refractive index of smoke from ground-based remote sensing. Future spaceborne radiometers (e.g., MODIS on the Earth Observing System), simulated on aircraft, proved to be very useful for monitoring smoke properties, surface properties, and the impacts of smoke on radiation and climate.

A multispectral scanning spectrometer was used to obtain measurements of the reflection function and brightness temperature of smoke, clouds, and terrestrial surfaces at 50 discrete wavelengths between 0.55 and 14.2 μm. These observations were obtained from the NASA ER-2 aircraft as part of the Smoke, Clouds, and Radiation-Brazil (SCAR-B) campaign, conducted over a 1500 x 1500 km region of cerrado and rain forest throughout Brazil between August 16 and September 11, 1995. Multispectral images of the reflection function and brightness temperature in 10 distinct bands of the MODIS airborne simulator (MAS) were used to derive a confidence in clear sky (or alternatively the probability of cloud), shadow, fire, and heavy aerosol. In addition to multispectral imagery, monostatic lidar data were obtained along the nadir ground track of the aircraft and used to assess the accuracy of the cloud mask results. This analysis shows that the cloud and aerosol mask being developed for operational use on the moderate-resolution imaging spectroradiometer (MODIS), and tested using MAS data in Brazil, is quite capable of separating cloud, aerosol, shadow, and fires during daytime conditions over land.

During the Smoke, Clouds, and Radiation-Brazil (SCAR-B) deployment, angular distributions of spectral reflectance for vegetated surfaces and smoke layers were measured using the scanning cloud absorption radiometer (CAR) mounted on the Univcrsity of Washington C-131A research aircraft. The CAR contains 13 narrowband spectral channels between 0.3 and 2.3 μm with a 190° scan aperture (5° before zenith to 5° past nadir) and 1° instantaneous field of view. The bidirectional reflectance is obtained by flying a clockwise circular orbit above the surface, resulting in a ground track ∼3 km in diameter within about 2 min. Although the CAR measurements are contaminated by minor atmospheric effects, results show distinct spectral characteristics for various types of surfaces. Spectral bidirectional reflectances of three simple and well-defined surfaces are presented: cerrado (August 18, 1995) and dense forest (August 25, 1995), both measured in Brazil under nearly clear-sky conditions, and thick smoke layers over dense forest (September 6 and 11, 1995). The bidirectional reflectances of cerrado and dense forest revealed fairly symmetric patterns along the principal plane, with varying maximal strengths and widths spectrally in the backscattering direction. In the shortwave-infrared region the aerosol effect is very small due to low spectral optical depth. Also, these backscattering maxima can be seen on the bidirectional reflectance of smoke layer over dense forest. These detailed measurements of the angular distribution of spectral reflectance can be parameterized by a few independent variables and utilized to retrieve either surface characteristics or aerosol microphysical and optical properties (e.g., size distribution and single-scattering parameters), if proper physical and radiation models are used. The spcctral-hemispherical albedo of these surfaces is obtained directly by integrating all angular measurements and is compared with the measured nadir reflectance. Using CAR nadir reflectance as a surrogate for spectral-hemispherical albedo can cause albedos to be underestimated by 10-60%, depending on solar zenith angle.

Two moderate resolution imaging spectroradiometer (MODIS) instruments are planned for launch in 1999 and 2000 on the NASA Earth Observing System (EOS) AM-1 and EOS PM-1 satellites. The MODIS instrument will sense fires with designated 3.9 and 11 μm channels that saturate at high temperatures (450 and 400 K, respectively). MODIS data will be used to detect fires, to estimate the rate of emission of radiative energy from the fire, and to estimate the fraction of biomass burned in the smoldering phase. The rate of emission of radiative energy is a measure of the rate of combustion of biomass in the fires. In the Smoke, Clouds, and Radiation-Brazil (SCAR-B) experiment the NASA ER-2 aircraft flew the MODIS airborne simulator (MAS) to measure the fire thermal and mid-IR signature with a 50 m spatial resolution. These data are used to observe the thermal properties and sizes of fires in the cerrado grassland and Amazon forests of Brazil and to simulate the performance of the MODIS 1 km resolution fire observations. Although some fires saturated the MAS 3.9 μm channel, all the fires were well within the MODIS instrument saturation levels. Analysis of MAS data over different ecosystems, shows that the fire size varied from single MAS pixels (50×50 m) to over 1 km2. The 1×1 km resolution MODIS instrument can observe only 30–40% of these fires, but the observed fires are responsible for 80 to nearly 100% of the emitted radiative energy and therefore for 80 to 100% of the rate of biomass burning in the region. The rate of emission of radiative energy from the fires correlated very well with the formation of fire burn scars (correlation coefficient = 0.97). This new remotely sensed quantity should be useful in regional estimates of biomass consumption.