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We present an improved remote sensing technique to infer an optimal habit/shape model for ice particles in cirrus clouds using multi-angle polarimetric measurements at 865 nm made by the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI) instrument. The common method of ice model inference is based on intensity (total reflectivity) measurements, which is generally not applicable to optically thin ice clouds (i.e., cirrus clouds) where single scattering dominates. The new approach is able to infer an ice model in clouds with optical thicknesses smaller than 5. The improvement is made by first assuming the optical thickness retrieved using total reflectivity. Subsequently, the polarized reflectivity is calculated based on look-up tables generated from simulated polarized reflectances computed for cirrus clouds in conjunction with eight ice particle models. The ice particle model that leads to the closest fit to the measurements is regarded as the optimal ice particle model. Additionally, an alternative method is applied that does not consider polarized reflectivity. These two methods are applied to a data sample as a proof-of-concept study where AirMSPI observed a single cirrus layer. In this case study, the hexagonal column aggregate model works for most pixels both with and without considering polarized reflectivities. The retrieval cost function is high when the camera pairs with large zenith angles are included in the retrievals. This result suggests that further studies will be necessary to have a better understanding of all eight selected ice particle models at scattering angles smaller than 100°.

The Cloud Absorption Radiometer (CAR) Science Team, and the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) recently released a unique dataset of bidirectional reflectance-distribution function (BRDF) of different surface types including clouds, snow/ice, vegetation, ocean, lakes, desert, city scape, smoke and other mixed surface types. The data were acquired during numerous field campaigns around the world, with measurements spanning 1991 to 2017. This presentation will address several uses of these data including developing new methods that define important surface and atmosphere radiative transfer functions, improve remote sensing retrievals of multiple geophysical parameters such as aerosols, clouds and surface albedo, and support satellite remote sensing activities. CAR data are archived at GES DISC: https://disc.gsfc.nasa.gov/datasets?keywords=car.

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.

Ice particle morphology and microphysical properties of cirrus clouds are essential for assessing radiative forcing associated with these clouds. We develop an optimal estimation-based algorithm to infer cirrus cloud optical thickness (COT), cloud effective radius (CER), plate fraction including quasi-horizontally oriented plates (HOPs) and the degree of surface roughness from the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) and the Infrared Imaging Radiometer (IIR) on the CALIPSO platform. A simple but realistic ice particle model is used, and the relevant bulk optical properties are computed using state-of-the-art light-scattering computational capabilities. Rigorous estimation of uncertainties related to surface properties, atmospheric gases and cloud heterogeneity is performed. The results based on the present method show that COTs are quite consistent with other satellite products, and CERs essentially agree with the other counterparts. A one-month global analysis for April 2007, in which CALIPSO off-nadir angle is 0.3∘, shows that the HOP has significant temperature-dependence and is critical to the lidar ratio when cloud temperature is warmer than −40∘C. The lidar ratio is calculated from the bulk optical properties based on the inferred parameters, showing robust temperature dependence. The median lidar ratio of cirrus clouds is 27–31 sr over the globe.

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.

In this paper we describe measurements of the bidirectional reflectance-distribution function (BRDF) acquired over a 30-year period (1984-2014) by the National Aeronautics and Space Administration's (NASA's) Cloud Absorption Radiometer (CAR). Our BRDF database encompasses various natural surfaces that are representative of many land cover or ecosystem types found throughout the world. CAR's unique measurement geometry allows a comparison of measurements acquired from different satellite instruments with various geometrical configurations, none of which are capable of obtaining such a complete and nearly instantaneous BRDF. This database is therefore of great value in validating many satellite sensors and assessing corrections of reflectances for angular effects. These data can also be used to evaluate the ability of analytical models to reproduce the observed directional signatures, to develop BRDF models that are suitable for sub-kilometer-scale satellite observations over both homogeneous and heterogeneous landscape types, and to test future spaceborne sensors. All of these BRDF data are publicly available and accessible in hierarchical data format (http:car.gsfc.nasa.gov/).

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.

Ice clouds and dust aerosols are two important atmospheric constituents. To reliably assess the radiativeforcings and to accurately infer the microphysical and optical properties of these two atmospheric components, it is necessary to use appropriate optical properties of ice crystals and dust particles. In this talk we will discuss the use of remote sensing techniques based on observations by passive and active sensors to constrain the optical properties. Specifically, we will use the MODIS (Moderate Resolution Imaging Spectroradiometer), POLDER (POLarization and Directionality of the Earth's Reflectances), MISR (Multi-angle Imaging SpectroRadiometer), and CALIOP/CALIPSO (Cloud-Aerosol Lidar with Orthogonal Polarization on the Cloud-Aerosol Lidar with Orthogonal Polarization) measurements in combination of theoretical light scattering simulations to identify the optimal single-scattering properties (extinction coefficient, single-scattering albedo, and phase matrix) of nonspherical/inhomogeneous ice crystals and dust particles.

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.

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.

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.

In this paper, we present five-year (2000–2004) climatological statistics of Northern Hemisphere spectral white-sky albedo for the 16 International Geosphere–Biosphere Program (IGBP) ecosystem classes when accompanied by the presence of snow on the ground. These statistics are obtained using validated, high quality Moderate Resolution Imaging Spectroradiometer (MODIS) land surface albedo (MOD43B3) data flagged as snow in the associated Quality Assurance (QA) fields. Near Real-Time Ice and Snow Extent (NISE) data are used as an additional discriminator of snow extent. Statistics are provided for the first seven MODIS bands, ranging from 0.47 to 2.1 μm, and for three broadbands, 0.3–0.7, 0.3–5.0 and 0.7–5.0 μm. The statistics demonstrate that each ecosystem classification has a discernible spectral albedo signature when accompanied by snow on the ground. This indicates that winter canopy and the underlying surface radiative properties are impacted by the presence of snow overlying these surfaces. For example, the 0.47 μm albedo of winter snow-free evergreen needleleaf forests increases from 0.03 to 0.36 in the presence of snow, compared to an increase of 0.04 to 0.76 for croplands. In general, the albedo of snow-covered ecosystems with some winter canopy has lower albedos than ecosystems with little to no winter canopy; for example the 0.47 μm albedo of snow-covered mixed forests is 0.39 compared to 0.87 for barren/deserts and 0.95 for permanent snow. These statistics can be used within land surface models in a stand-alone mode, to prescribe albedo values in atmospheric General Circulation Models (GCMs), or be incorporated into research and operational projects. They are intended to provide researchers with representative spectral albedo values of IGBP ecosystems in the presence of snow that are derived from validated satellite data.

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.

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.

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.

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 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.

Methods to infer cloud thermodynamic phase (ice or water) are investigated using multispectral imagery. An infrared (IR) trispectral algorithm using the 8.52-, 11-, and 12-gm bands (Ackerman et al., 1990; Strabala et al., 1994) forms the basis of this work and will be applied to data from the Earth Observing System (EOS) Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. Since the algorithm uses IR bands, it can be applied to either daytime or nighttime data and is not sensitive to the presence of cloud shadows. A case study analysis is performed with a MODIS airborne simulator (MAS) scene collected during the Subsonic Aircraft Contrail and Cloud Effects Special Study (SUCCESS) on April 21, 1996, at 2000 UTC. The scene under scrutiny is quite complex, containing low-level broken water clouds, cirrus cells, cloud shadows, subvisual cirrus, and contrails. The IR trispectral algorithm is found to be less accurate in (1) regions where more than one cloud phase type occurs and (2) regions of thin cirrus overlying a lower-level cloud layer. To improve the phase retrieval accuracy in these areas of difficulty, additional bands located at 0.65, 1.63, and 1.90 gm are incorporated. Radiative transfer (RT) calculations are performed to simulate the MAS bands using the cirrus and water cloud models detailed by Baum et al. (this issue). The RT calculations are performed for single- layer cirrus- and water-phase clouds as well as for the case of thin cirrus overlying a lower-level water droplet cloud. Both modeled results and application of the theory to a case study suggest that the cloud thermodynamic phase retrieval accuracy can be improved by inclusion of the visible and near infrared bands.

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.

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.

The Clouds and the Earth's Radiant Energy System (CERES) is part of NASA's Earth Observing System (EOS), CERES objectives include the following. (1) For climate change analysis, provide a continuation of the Earth Radiation Budget Experiment (ERBE) record of radiative fluxes at the top-of-the-atmosphere (TOA), analyzed using the same techniques as the existing ERBE data. (2) Double the accuracy of estimates of radiative fluxes at TOA and the Earth's surface. (3) Provide the first long-term global estimates of the radiative fluxes within the Earth's atmosphere. (4) Provide cloud property estimates collocated in space and time that are consistent with the radiative fluxes from surface to TOA. In order to accomplish these goals, CERES uses data from a combination of spaceborne instruments: CERES scanners, which are an improved version of the ERBE broadband radiometers, and collocated cloud spectral imager data on the same spacecraft. The CERES cloud and radiative flux data products should prove extremely useful in advancing the understanding of cloud-radiation interactions, particularly cloud feedback effects on the Earth's radiation balance. For this reason, the CERES data should be fundamental to the ability to understand, detect, and predict global climate change. CERES results should also be very useful for studying regional climate changes associated with deforestation, desertification, anthropogenic aerosols, and ENSO events. This overview summarizes the Release 3 version of the planned CERES data products and data analysis algorithms. These algorithms are a prototype for the system that will produce the scientific data required for studying the role of clouds and radiation in the Earth's climate system.

The launch of ADEOS in August 1996 with POLDER, TOMS, and OCTS instruments on board and the future launch of EOS-AM 1 in mid-1998 with MODIS and MISR instruments on board start a new era in remote sensing of aerosol as part of a new remote sensing of the whole Earth system (see a list of the acronyms in the Notation section of the paper). These platforms will be followed by other international platforms with unique aerosol sensing capability, some still in this century (e.g., ENVISAT in 1999). These international spaceborne multispectral, multiangular, and polarization measurements, combined for the first time with international automatic, routine monitoring of aerosol from the ground, are expected to form a quantum leap in our ability to observe the highly variable global aerosol. This new capability is contrasted with present single-channel techniques for AVHRR, Meteosat, and GOES that although poorly calibrated and poorly characterized already generated important aerosol global maps and regional transport assessments. The new data will improve significantly atmospheric corrections for the aerosol effect on remote sensing of the oceans and be used to generate first real-time atmospheric corrections over the land. This special issue summarizes the science behind this change in remote sensing, and the sensitivity studies and applications of the new algorithms to data from present satellite and aircraft instruments. Background information and a summary of a critical discussion that took place in a workshop devoted to this topic is given in this introductory paper. In the discussion it was concluded that the anticipated remote sensing of aerosol simultaneously from several space platforms with different observation strategies, together with continuous validations around the world, is expected to be of significant importance to test remote sensing approaches to characterize the complex and highly variable aerosol field. So far, we have only partial understanding of the information content and accuracy of the radiative transfer inversion of aerosol information from the satellite data, due to lack of sufficient theoretical analysis and applications to proper field data. This limitation will make the anticipated new data even more interesting and challenging. A main concern is the present inadequate ability to sense aerosol absorption, from space or from the ground. Absorption is a critical parameter for climate studies and atmospheric corrections. Over oceans, main concerns are the effects of white caps and dust on the correction scheme. Future improvement in aerosol retrieval and atmospheric corrections will require better climatology of the aerosol properties and understanding of the effects of mixed composition and shape of the particles. The main ingredient missing in the planned remote sensing of aerosol are spaceborne and ground-based lidar observations of the aerosol profiles.

One of the major sources of uncertainty in climate studies is the detection of cirrus clouds and characterization of their radiative properties. Combinations of water vapor absorption channels (e.g., 1.38 µm), ice-water absorption channels (e.g., 1.64 µm), and atmospheric window channels (e.g., 11 µm) in the imager, together with a lidar profiler on future EOS platforms, will contribute to enhancing our understanding of cirrus clouds. The aforementioned spectral channels are used in this study to explore the effects exerted by uncertainties in cloud microphysical properties (e.g., particle size distribution) and cloud morphology on the apparent radiative properties, such as spectral reflectance and heating and cooling rate profiles. As in Part I of our previous study, which establishes the foundations of the Fourier-Riccati method of radiative transfer in inhomogeneous media, cloud extinction and scattering functions are characterized by simple spatial variations with measured and hypothesized mi...

An airborne scanning spectrometer was developed for measuring reflected solar and emitted thermal radiation in 50 narrowband channels between 0.55 and 14.2mm. The instrument provides multispectral images of outgoing radiation for purposes of developing and validating algorithms for the remote sensing of cloud, aerosol, water vapor, and surface properties from space. The spectrometer scans a swath width of 37 km, perpendicular to the aircraft flight track, with a 2.5-mrad instantaneous field of view. Images are thereby produced with a spatial resolution of 50 m at nadir from a nominal aircraft altitude of 20 km. Nineteen of the spectral bands correspond closely to comparable bands on the Moderate Resolution Imaging Spectroradiometer ( MODIS ) , a facility in- strument being developed for the Earth Observing System to be launched in the late 1990s. This paper describes the optical, mechanical, electrical, and data acquisition system design of the MODIS Airborne Simulator and presents some early results obtained from measurements acquired aboard the National Aeronautics and Space Administration ER-2 aircraft that illustrate the performance and quality of the data produced by this instrument.

The U.S. upper Midwest was subjected to severe flooding during the summer of 1993. Heavy rainfall in the Mississippi River basin from April through July caused flooding on many Midwest rivers, including the Mississippi, Illinois, Missouri, and Kansas Rivers. The flood crest of 15.1 m at St. Louis, Missouri, on 1 August 1993 was the highest ever measured, surpassing the previous record of 13.2 m set on 28 April 1973. Damage estimates include at least 47 flood-related deaths and a total damage cost of $12 billion. Remotely sensed imagery of severe flooding in the U.S. Midwest was obtained under cloud-free skies on 29 July 1993 by the MODIS (Moderate Resolution Imaging Spectroradiometer) Airborne Simulator (MAS). The MAS is a newly developed scanning spectrometer with 50 spectral bands in the wavelength range 0.55-14.3 micrometers. Estimation of the total flooded area in the MAS scene acquired near St. Louis was accomplished by comparing the MAS scene to a Landsat-5 thematic mapper (TM) scene of the same area acquired on 14 April 1984 in nonflood conditions. For comparison, the MAS band centered at 0.94 micrometers and the TM band centered at 1.65 micrometers were selected because of the high contrast seen in these bands between land and water-covered surfaces. An estimate of the area covered by water in the MAS and TM scenes was obtained by developing land/water brightness thresholds from histograms of the MAS and TM digital image data. Afetr applying the thresholds, the difference between the area covered by water in the MAS and TM scenes, and hence the flooded area in the MAS scene, was found to be about 396 sq km, or about 153 square miles.

An invariant imbedding T-matrix (II-TM) method is used to calculate the single-scattering properties of 8-column aggregate ice crystals. The II-TM based backscatter values are compared with those calculated by the improved geometric-optics method (IGOM) to refine the backscattering properties of the ice cloud radiative model used in the MODIS Collection 6 cloud optical property product. The integrated attenuated backscatter-to-cloud optical depth (IAB-ICOD) relation is derived from simulations using a CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite) lidar simulator based on a Monte Carlo radiative transfer model. By comparing the simulation results and co-located CALIPSO and MODIS (Moderate Resolution Imaging Spectroradiometer) observations, the non-uniform zonal distribution of ice clouds over ocean is characterized in terms of a mixture of smooth and rough ice particles. The percentage of the smooth particles is approximately 6% and 9% for tropical and midlatitude ice clouds, respectively.

Assessment of the effect of multiangular polarized incident light on the bidirectional reflectance factor (BRF) of vegetation and soil samples is presented in this paper. The samples were evaluated with a reference to 99% white Spectralon calibration standard in the UV-VIS-NIR spectral range. The BRF of the samples was found to be strongly influenced by the polarization of the incident light at different multiangular geometries.

[1] The measurement of cloud absorption from aircraft has been a controversial subject largely because broadband measurements provide little insight into the physical mechanisms underlying the absorption. To partition and quantify the various mechanisms of cloud absorption, spectrally resolved measurements are required. Measurements of cloud solar spectral (400–2150 nm) absorption from airborne spectroradiometers are presented from two cases of extensive tropical marine stratus cloud fields. Radiative transfer modeling was used to retrieve the cloud optical thickness and cloud droplet effective radius from a best fit with the measured cloud spectral albedo. These values were used to estimate the cloud spectral absorptance. For the higher optical thickness case, the measurement-model agreement in absorptance across the spectrum is better than 0.05 and substantially better (within 0.01) at visible wavelengths unaffected by cloud absorption. For an optically thinner and more heterogeneous cloud field, the differences were higher, up to 0.07 in the near infrared. The standard deviations of cloud absorptance spectra show that the integrated absorbed irradiances, usually measured by broadband radiometers, are strongly affected by variations in the water vapor amount. Radiative transfer modeling is used to illustrate the spectral dependence of the absorption from radiatively important gases (e.g., water vapor), cloud liquid water, and absorbing aerosol particles. A novel sampling strategy, based on single aircraft measurements, is demonstrated, as is the value of spectrally resolved measurements in partitioning the various mechanisms of cloud absorption including the possible effects of absorbing aerosols embedded in clouds.

Clouds play a crucial role in the remote sensing of the troposphere as they frequently obscure the radiation reflected or emitted from the surface. However they can be used to advantage to obtain concentration profile information with techniques such as cloud slicing. Treating clouds correctly is therefore an essential part of any retrieval of tropospheric data. The retrieval of cloud parameters from solar back scatter and thermal infrared radiation provides particular information about clouds. Chapter 5 describes the retrieval of the major cloud parameters and their validation, as well as dealing with modern trends and likely developments.

The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 microns (12.9 microns for MASTER). These observations were obtained from the NASA ER-2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability Of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS Cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC(sup 4), is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS-based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness Of liquid water clouds from MISR. Results of this analysis are compared and contrasted.