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At least 37 records · Page 2

Airborne Validation of Spatial Properties Measured by the CALIPSO Lidar

The primary payload onboard the Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) satellite is a dual-wavelength backscatter lidar designed to provide vertical profiling of clouds and aerosols. Launched in April 2006, the first data from this new satellite was obtained in June 2006. As with any new satellite measurement capability, an immediate post-launch requirement is to verify that the data being acquired is correct lest scientific conclusions begin to be drawn based on flawed data. A standard approach to verifying satellite data is to take a similar, or validation, instrument and fly it onboard a research aircraft. Using an aircraft allows the validation instrument to get directly under the satellite so that both the satellite instrument and the aircraft instrument are sensing the same region of the atmosphere. Although there are almost always some differences in the sampling capabilities of the two instruments, it is nevertheless possible to directly compare the measurements. To validate the measurements from the CALIPSO lidar, a similar instrument, the Cloud Physics Lidar, was flown onboard the NASA high-altitude ER-2 aircraft during July- August 2006. This paper presents results to demonstrate that the CALIPSO lidar is properly calibrated and the CALIPSO Level 1 data products are correct. The importance of the results is to demonstrate to the research community that CALIPSO Level 1 data can be confidently used for scientific research.

McGill, Matthew J.↗

A-Train Mission Operations Working Group: CALIPSO Mission Status

This series of viewgraphs presents an introduction to the status of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO),lessons learned during CALIPSO inclination maneuvers, the planning for CALIPSO's inclination maneuver to take place in 2009, examines a decision whether to precess or not, the plans to change CALIPSO's pitch, and the plans to change CALIPSO's pitch from the viewpoint of the payload.

Cisewski, Michael S.↗

Approximating the Lidar Ratio of Modeled Aerosol Species to Help Inform Lidar Ratio Selection for Marine Aerosols in the Forthcoming Version 5 CALIPSO Data Products

- After 16+ years, the NASA Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission will soon retire. - Narrow window of opportunity exists to improve quality of CALIPSO aerosol retrievals by advancing knowledge of aerosol lidar ratios for different aerosol types; - For CALIOP, the elastic backscatter lidar aboard CALIPSO, an aerosol lidar ratio (i.e., extinction-to-backscatter ratio) is generally assumed to retrieve vertical profiles of aerosol extinction and subsequently column-integrated aerosol optical depth (AOD). - Current CALIPSO lidar ratio selection process uses a single lidar ratio for each of the 7 CALIPSO tropospheric aerosol types, with large uncertainties for most aerosol types. Goal of this study: creation of regional and seasonal climatological lidar ratio maps for marine aerosols by leveraging passive aerosol retrievals (MODIS) and global model simulations (GEOS/GOGART).

Travis D Toth↗

25 Years of CALIPSO

Selected for development in 1998 and launched together with CloudSat in 2006, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations(CALIPSO) mission terminated science operations in the summer of 2023 aftercompleting17 years of on-orbit observations. As one of NASA’s Earth System Science Pathfinder missions, CALIPSO was truly a pathfinder. CALIPSO observations have provided a new perspective on clouds and aerosol and have not only met but far exceeded the original objectives of the mission. Many unanticipated findings and data applications have been discovered along the way. Fly-ing with many other remote sensing instruments, as part of the A-train constellation, stimulated the discovery of numerous retrieval synergies between lidar and other sensors. This paper describes how the CALIPSO mission came to be, discusses some of the early choices made by the CALIPSO team that shaped the mission, and some of the challenges facing the team in developing the first-ever global climatologies of aerosol and cloud based on lidar observations.

Space lidar↗

Variable Lidar Ratios for Marine and Dusty Marine Using MODIS AOD Constrained Retrievals and GOCART Model Simulations and their Impact on Level 2 CALIPSO Data Products in Version 5

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO provided global measurements of attenuated backscatter profiles of various tropospheric aerosol species from June 2006 through June 2023. Extinction profiles are retrieved from these backscatter measurements by assuming a value for the extinction-to-backscatter or lidar ratio (LR). Up until version V4.51 of the data products, only a constant global value for each of the species has been used, spatially and temporally. However, it has been well known from various ground-based measurements that LRs of each aerosol species can potentially vary spatially as well seasonally. For the forthcoming Version 5 of the CALIPSO products, the CALIPSO team will implement variable lidar ratios at 532 nm for the species classified as “marine” and “dusty marine”. Here we present the essential elements of this scheme, which involves estimating lidar ratios by constraining Fernald solutions for the CALIOP particulate backscatter profiles using aerosol optical depths (AOD) from collocated MODIS retrievals. To account for the lack of measurements in various regions and seasons (e.g., Arctic winters), we leverage collocated model sea-salt volume fractions (SSVF) simulated by the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and use an empirical relationship between the SSVF and LR to build hybrid climatological maps for the entire globe, i.e., using the modelled values when reliable values of the constrained LRs are not available. Initial evaluation of the resulting extinction profiles and corresponding AODs, both globally and in specific regions are presented using a limited amount of data. The primary improvement in AOD occurs in the coastal areas, like the Arabian Sea and Bay of Bengal. The estimated marine LR values in these regions are significantly higher than the constant value of 23 sr used in previous data releases, likely due to mixing with offshore pollution which results in higher AODs. Initial validation results using the CALIPSO Ocean Derived Column Optical Depth (ODCOD) retrievals and ground-based AERONET AOD measurements are presented.

CALIPSO↗

Aerosol Models for the CALIPSO Lidar Inversion Algorithms

We use measurements and models to develop aerosol models for use in the inversion algorithms for the Cloud Aerosol Lidar and Imager Pathfinder Spaceborne Observations (CALIPSO). Radiance measurements and inversions of the AErosol RObotic NETwork (AERONET1, 2) are used to group global atmospheric aerosols using optical and microphysical parameters. This study uses more than 105 records of radiance measurements, aerosol size distributions, and complex refractive indices to generate the optical properties of the aerosol at more 200 sites worldwide. These properties together with the radiance measurements are then classified using classical clustering methods to group the sites according to the type of aerosol with the greatest frequency of occurrence at each site. Six significant clusters are identified: desert dust, biomass burning, urban industrial pollution, rural background, marine, and dirty pollution. Three of these are used in the CALIPSO aerosol models to characterize desert dust, biomass burning, and polluted continental aerosols. The CALIPSO aerosol model also uses the coarse mode of desert dust and the fine mode of biomass burning to build a polluted dust model. For marine aerosol, the CALIPSO aerosol model uses measurements from the SEAS experiment 3. In addition to categorizing the aerosol types, the cluster analysis provides all the column optical and microphysical properties for each cluster.

Omar, Ali H.↗

Calipso's Mission Design: Sun-Glint Avoidance Strategies

CALIPSO will fly in formation with the Aqua spacecraft to obtain a coincident image of a portion of the Aqua/MODIS swath. Since MODIS pixels suffering sun-glint degradation are not processed, it is essential that CALIPSO only co- image the glint h e portion of the MODIS instrument swath. This paper presents sun-glint avoidance strategies for the CALIPSO mission. First, we introduce the Aqua sun-glint geometry and its relation to the CALIPSO-Aqua formation flying parameters. Then, we detail our implementation of the computation and perform a cross-track trade-space analysis. Finally, we analyze the impact of the sun-glint avoidance strategy on the spacecraft power and delta-V budget over the mission lifetime.

Mailhe, Laurie M.↗

Selection Algorithm for the CALIPSO Lidar Aerosol Extinction-to-Backscatter Ratio

The extinction-to-backscatter ratio (S(sub a)) is an important parameter used in the determination of the aerosol extinction and subsequently the optical depth from lidar backscatter measurements. We outline the algorithm used to determine Sa for the Cloud and Aerosol Lidar and Infrared Pathfinder Spaceborne Observations (CALIPSO) lidar. S(sub a) for the CALIPSO lidar will either be selected from a look-up table or calculated using the lidar measurements depending on the characteristics of aerosol layer. Whenever suitable lofted layers are encountered, S(sub a) is computed directly from the integrated backscatter and transmittance. In all other cases, the CALIPSO observables: the depolarization ratio, delta, the layer integrated attenuated backscatter, beta, and the mean layer total attenuated color ratio, gamma, together with the surface type, are used to aid in aerosol typing. Once the type is identified, a look-up-table developed primarily from worldwide observations, is used to determine the S(sub a) value. The CALIPSO aerosol models include desert dust, biomass burning, background, polluted continental, polluted dust, and marine aerosols.

Omar, Ali H.↗

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

Welton, Ellsworth J.↗

CALIPSO Observations of Stratospheric Aerosols: A Preliminary Assessment

We have examined the 532-nm aerosol backscatter coefficient measurements by the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) for their use in the observation of stratospheric aerosol. CALIPSO makes observations that span from 82 S to 82 N each day and, for each profile, backscatter coefficient values reported up to approx. 40 km. The possibility of using CALIPSO for stratospheric aerosol observations is demonstrated by the clear observation of the 20 May 2006 eruption of Montserrat in the earliest CALIPSO data in early June as well as by observations showing the 7 October 2006 eruption of Tavurvur (Rabaul). However, the very low aerosol loading within the stratosphere makes routine observations of the stratospheric aerosol far more difficult than relatively dense volcanic plumes. Nonetheless, we found that averaging a complete days worth of nighttime only data into 5-deg latitude by 1-km vertical bins reveals a stratospheric aerosol data centered near an altitude of 20 km, the clean wintertime polar vortices, and a small maximum in the lower tropical stratosphere. However, the derived values are clearly too small and often negative in much of the stratosphere. The data can be significantly improved by increasing the measured backscatter (molecular and aerosol) by approximately 5% suggesting that the current method of calibrating to a pure molecular atmosphere at 30 km is most likely the source of the low values.

Thomason, Larry W.↗

Evaluation of Low Altitude Cloud Amount Using CALIPSO Observations

Clouds strongly modulate the transfer of solar and thermal radiation within the atmosphere. Changes in the distribution and properties of clouds in a changing climate represent climate feedbacks affecting climate sensitivity, but the predicted responses of clouds from current climate models are inconsistent. Of particular concern is the response of low clouds, and it is recognized that proper representation of low clouds in global models is in need of improvement. Accurate satellite cloud climatologies are necessary to evaluate model performance, but existing climatologies require validation and are inadequate in some respects for model evaluation. CALIPSO and CloudSat have been acquiring high vertical resolution cloud profiles since launch in 2006. These global cloud datasets represent a new tool for evaluation of both models and existing satellite climatologies. While a recently available merged CALIPSO-CloudSat cloud climatology provides the most comprehensive view of global 3-D cloud distribution, the CALIPSO dataset set on its own has several unique characteristics, including profiles of the atmospheric boundary layer with 30 meter vertical resolution. In this paper we investigate the use of CALIPSO data to characterize boundary layer clouds, looking toward the development of a reliable global dataset suitable for evaluation of model performance.

Winker, Dave↗

Clear-Sky Remote Sensing in the Vicinity of Clouds: What We Learned from MODIS and CALIPSO

Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds, Analyzing a large dataset of MODIS observations we examine the effect of three-dimensional (3D) radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. Comparing with CALIPSO clear-sky backscatterer measurements, we show that the cloud adjacency effect may be responsible for a large portion of the enhanced clear sky reflectance observed by MODIS. While aerosol particles are responsible for a large part of the near-cloud enhancements in CALIPSO observations, misidentified or undetected cloud particles are also likely to contribute. As a result, both the nature of these particles (cloud vs. aerosol) and the processes creating them need to be clarified using a quantitative assessment of remote sensing limitations in particle detection and identification. The width and ubiquity of the transition zone near clouds imply that studies of aerosol-cloud interactions and aerosol direct radiative effects need to account for aerosol changes near clouds. Not accounted, these changes can cause systematic biases toward smaller aerosol radiative forcing. On the other hand, including aerosol products near clouds despite their uncertainties may overestimate aerosol radiative forcing. Therefore, there is an urgent need for developing methods that can assess and account for remote sensing challenges and thus allow for including the transition zone into the study. We describe a simple model that estimates the cloud-induced enhanced reflectances of cloud-free areas in the vicinity of clouds. The model assumes that the enhancement is due entirely to Rayleigh scattering and is therefore bigger at shorter wavelengths, thus creating a so-called apparent "bluing" of aerosols in remote sensing retrievals.

Marshak, Alexander↗

CALIPSO at Four: Results and Progress

Aerosols and clouds play important roles in Earth?s climate system, but limitations in our ability to observe them globally limit our understanding of the climate system and our ability to model it. The CALIPSO satellite was developed to provide new capabilities to observe aerosol and cloud from space. CALIPSO carries the first polarization-sensitive lidar to fly in space, which has now provided a four-year record of global aerosol and cloud profiles. This paper briefly summarizes the status of the CALIPSO mission, describes some of the results from CALIPSO, and presents highlights of recent improvements in data products.

Winker, Dave↗

Nearly a Decade of CALIPSO Observations of Asian and Saharan Dust Properties Near Source and Transport Regions

The lidar on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission, makes robust measurements of dust and has generated a length of record that is significant both seasonally and inter-annually. We exploit this record to determine a multi-year climatology of the properties of Asian and Saharan dust, in particular seasonal optical depths, layer frequencies, and layer heights of dust gridded in accordance with the Level 3 data products protocol, between 2006-2015. The data are screened using standard CALIPSO quality assurance flags, cloud aerosol discrimination (CAD) scores, overlying features and layer properties. To evaluate the effects of transport on the morphology, vertical extent and size of the dust layers, we compare probability distribution functions of the layer integrated volume depolarization ratios, geometric depths and integrated attenuated color ratios near the source to the same distributions in the far field or transport region. CALIPSO is collaboration between NASA and Centre National D'études Spatiales (CNES), was launched in April 2006 to provide vertically resolved measurements of cloud and aerosol distributions. The primary instrument on the CALIPSO satellite is the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a near-nadir viewing two-wavelength polarization-sensitive instrument. The unique nature of CALIOP measurements make it quite challenging to validate backscatter profiles, aerosol type, and cloud phase, all of which are used to retrieve extinction and optical depth. To evaluate the uncertainty in the lidar ratios, we compare the values computed from dust layers overlying opaque water clouds, considered nominal, with the constant lidar ratio value used in the CALIOP algorithms for dust. We also explore the effects of noise on the CALIOP retrievals at daytime by comparing the distributions of the properties at daytime to the nighttime distributions.

Omar, Ali H.↗

Tropical and Arctic Cloud Observations From CALIPSO Between 2008-2014 and its Implications

There has been studies (e.g., Schweiger, 2004) suggest significant increase of Arctic clouds during the last three decades, especially in the western Arctic region. Such studies are based on passive remote sensing that are not highly reliable due to the lack of contrasts in temperature and reflectance between clouds and snow/ice surfaces. Changes in the Arctic clouds can be evaluated more accurately using the space-based lidar measurements from CALIPSO during the last nine years since CALIPSO can provide much more accurate detection and classification of both water and ice clouds in the Arctic. Time series of Arctic cloud properties (e.g., cloud fraction, cloud thermodynamic phase, water cloud depolarization ratio and droplet number concentration) from CALIPSO data are analyzed in this study. This study reveals the changes in both cloud fraction and cloud microphysical properties during the last nine years when CALIPSO data are available. We will evaluate the changes in Arctic cloud fraction and cloud microphysical properties, their seasonal and spatial characteristics and the potential impact on the energy budget and the climate of the Arctic.

Hu, Yongxiang↗

The Cumulus and Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD)

Low clouds continue to contribute greatly to the uncertainty in cloud feedback estimates. Depending on whether a region is dominated by cumulus (Cu) or stratocumulus (Sc) clouds, the interannual low-cloud feedback is somewhat different in both spaceborne and large-eddy simulation studies. Therefore, simulating the correct amount and variation of the Cu and Sc cloud distributions could be crucial to predict future cloud feedbacks. Here we document spatial distributions and profiles of Sc and Cu clouds derived from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat measurements. For this purpose, we create a new dataset called the Cumulus And Stratocumulus CloudSat-CALIPSO Dataset (CASCCAD), which identifies Sc, broken Sc, Cu under Sc, Cu with stratiform outflow and Cu. To separate the Cu from Sc, we design an original method based on the cloud height, horizontal extent, vertical variability and horizontal continuity, which is separately applied to both CALIPSO and combined CloudSat–CALIPSO observations. First, the choice of parameters used in the discrimination algorithm is investigated and validated in selected Cu, Sc and Sc–Cu transition case studies. Then, the global statistics are compared against those from existing passive- and active-sensor satellite observations. Our results indicate that the cloud optical thickness – as used in passive-sensor observations – is not a sufficient parameter to discriminate Cu from Sc clouds, in agreement with previous literature. Using clustering-derived datasets shows better results although one cannot completely separate cloud types with such an approach. On the contrary, classifying Cu and Sc clouds and the transition between them based on their geometrical shape and spatial heterogeneity leads to spatial distributions consistent with prior knowledge of these clouds, from ground-based, ship-based and field campaigns. Furthermore, we show that our method improves existing Sc–Cu classifications by using additional information on cloud height and vertical cloud fraction variation. Finally, the CASCCAD datasets provide a basis to evaluate shallow convection and stratocumulus clouds on a global scale in climate models and potentially improve our understanding of low-level cloud feedbacks. The CASCCAD dataset (Cesana, 2019, https://doi.org/10.5281/zenodo.2667637) is available on the Goddard Institute for Space Studies (GISS) website at https://data.giss.nasa.gov/clouds/casccad/ (last access: 5 November 2019) and on the zenodo website at https://zenodo.org/record/2667637 (last access: 5 November 2019).

Cesana, Gregory V.↗

Comparison of the CALIPSO satellite and ground-based observations of cirrus clouds at the ARM TWP sites

Statistics of ice cloud macrophysical and optical properties from the Cloud-Aerosol LIdar with Orthogonal Polarization (CALIOP) instrument on board the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite are compared with those from ground-based lidar observations over a 31 month period. Ground-based lidar observations are taken from the micropulse lidars (MPL) at the three Department of Energy Atmospheric Radiation Measurement (ARM) tropical western pacific (TWP) sites: Manus, Nauru and Darwin. CALIPSO observations show a larger cloud fraction at high altitudes while the ground-based MPLs show a larger cloud fraction at low altitudes. The difference in mean ice cloud top and base heights at the Manus and Nauru sites are all within 0.51 km, although differences are statistically significant. Mean ice cloud geometrical thickness agree to within 0.05 km at the Manus and Nauru sites. Larger differences exist at Darwin due to excessive degradation of the MPL output power during our sampling period. Both sets of observations show thicker clouds during the nighttime which may be real but could also be partially an artifact of the decreased signal-to-noise ratio during the daytime. The number of ice cloud layers per profile are also shown to be consistent after accounting for the difference in spatial resolution. For cloud optical depths, four different retrieval methods are compared, two for each set of observations. All products show that the majority of ice cloud optical depths ({approx}60%) fall below an optical depth of 0.2. For most comparisons all four retrievals agree to within the uncertainty intervals. We find that both CALIPSO retrievals agree best to ground-based optical depths when the lidar ratio in the latter is retrieved instead of set to a fixed value. Also thoroughly compared is the cloud properties for the subset of ice clouds which reside in the tropical tropopause layer (TTL).

58 GEOSCIENCES↗

Accounting for 3D Radiative Effects in MODIS Aerosol Retrievals near Clouds using CALIPSO Observations

Retrievals of aerosol properties near clouds from passive remote sensing is challenging. Sunlight scattered by clouds into nearby clear regions can effectively enhance the clear area reflectance. These cloud 3D radiative effects may lead to large biases in aerosol retrievals if uncorrected, risking an incorrect interpretation of satellite observations for aerosol-cloud interaction in cloudy atmosphere. In earlier studies, we developed a simple two-layer model (2LM) to estimate the cloud-induced clear-sky radiance enhancements in cloud fields. In this study, we take advantage of CALIPSO lidar observations, which should not be affected by the 3D radiative effect, to study passive aerosol retrievals in cloud fields in the Amazon region, specifically those produced by the operational Dark Target algorithm applied to Aqua-MODIS. From two-years’ worth of co-located CALIPSO/MODIS aerosol retrievals, we find a larger increase in operationally retrieved MODIS AOD from clear to cloudy regions (~0.075 or ~40%) than for the CALIPSO AOD (~0.021 or ~20%). The much larger increase in MODIS AOD is mainly due to the 3D radiative effects. After using the 2LM model to account for cloud 3D radiative effects, the clear to cloudy increase in MODIS AOD was reduced to ~0.043 (~23%), much closer to CALIPSO observations. The 3D corrected average MODIS AOD for cloudy scenes is significantly larger than AOD for clear conditions, even for cloud fraction (CF) less than 0.1, suggesting aerosols in cloudy scenes are characteristically different from aerosols in clear conditions. Furthermore, the 3D correction of AOD (i.e., τ_1D-τ_3D) increases linearly with CF for a large range of CF. We have also examined the impact of the 3D effect on aerosol Ångström Exponent (AE) and fine model fraction (FMF) of AOD. We found that the uncorrected average AE and FMF depend strongly on CF, ~25% increase in AE (decrease in particle size) and ~60% increase in FMF as CF increases from 0.05 to 0.45. The 3D correction leads to smaller average AE (bigger particle size) and FMF that are almost independent of CF. Thus, the 3D corrected aerosol properties are expected to provide more accurate information for better understanding aerosol-cloud interactions.

MODIS↗